WP3-P09-100628- D3 2 Smart Wireless Sensor Network Platform

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Smart Monitoring of

Historic Structures

D3.2 Smart wireless sensor network platform

Grant Agreement number: 212939

Project acronym: SMooHS

Project Title: Smart Monitoring of Historic Structures

Funding Scheme: Collaborative Project

Date of latest version of Annex I againstwhich the assessment will be made:

2010-02-20

Report: D3.2 Smart wireless sensor network platform

Period covered by this report: From 2009-11-01 to 2010-03-31

Dissemination level: CO (project partners incl. Commission)

Authors Krüger (TTI); Bahr (TTI), Bachmaier (IWB), Lehmann (MPA), Willeke(TTI)

Project coordinator: Dr. Markus Krüger

Project coordinator organisation: MPA Universität Stuttgart, Germany

Tel: +49 711 6856 6789

Fax: +49 711 6856 6797

Email: [email protected]

Project web site address: http://www.smoohs.eu

Doc. Name: WP3-P09-100628- D3 2 Smart wireless sensor network platform.doc



SMooHS WP3-P09-100628- D3 2 Smart wireless sensor network platform.doc

Rev. 2010-07-07 2/52

Table of Contents

1

Summary ............................................................................................................................. 4

2 Introduction .......................................................................................................................... 5

3

Related work ....................................................................................................................... 6

4 Structural health monitoring system .................................................................................... 7

4.1

Environmental Influences and Damage Processes ................................................... 7

4.2

Benefits of SHM on Historic Structures ...................................................................... 7

4.3 Principle system layout .............................................................................................. 7

5 Aspects of flexible and reliable sensor node hardware ....................................................... 9

6

Realization of a robust sensor node hardware .................................................................. 10

6.1 Processor board with wireless communication ........................................................ 11

6.2 Power supply ........................................................................................................... 13

6.3

Multi-sensor board for strain gauges, vibration, temperature and humidity ............. 14

6.3.1 General description ...................................................................................... 14

6.3.2

Features ....................................................................................................... 15

6.3.3 Technical data .............................................................................................. 15

6.4

Acceleration sensor board for piezo- and PVDF-sensors ........................................ 16

6.5

Inclination and tilt sensor board ............................................................................... 17


6.5.2 Features ....................................................................................................... 18

6.5.3

Technical data .............................................................................................. 18

6.6 Air velocity sensor board .......................................................................................... 19


6.6.2

Features ....................................................................................................... 20

6.6.3 Technical data .............................................................................................. 20

6.7

Impedance converter board system for electrochemical analysis and impedancespectroscopy ..................................................................................................................... 21

6.7.1

General description ...................................................................................... 21

6.7.2

Features ....................................................................................................... 22

6.7.3 Technical data .............................................................................................. 22

6.8

Electrometer with multiplexer ................................................................................... 23


6.8.2

Features ....................................................................................................... 24

6.8.3

Technical data .............................................................................................. 25

7 Structural health monitoring software ................................................................................ 26

7.1

Principal structure of the SHM system software ...................................................... 26

7.2

Sensor network and data transfer software ............................................................. 27




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7.2.1 Sensor network protocol .............................................................................. 27

7.2.2 Wboot – Sensor node boot loader ............................................................... 27

7.2.3

Miranda – sensor node application software................................................ 27

7.2.4 Starcatcher – radio to serial forwarder ......................................................... 28

7.2.5

Uranus – forwarder ...................................................................................... 28

7.2.6

Jupiter – base station and forwarder ............................................................ 28

7.2.7 Callisto – on-site control ............................................................................... 28

7.3 Data storage ............................................................................................................ 28

7.3.1

Galaxy – SQL data base .............................................................................. 28

7.3.2 Data Base Overview .................................................................................... 28

7.3.3

Mars – SQL interpreter ................................................................................ 29

7.4 Data analysis ........................................................................................................... 29

7.4.1

In-mote data analysis ................................................................................... 29

7.4.2

Database analysis ........................................................................................ 30

7.5 User interfaces ......................................................................................................... 31

7.5.1 Administration software tools ....................................................................... 31

7.5.2

Data readout software tools ......................................................................... 32

7.5.3 Data export software tools ........................................................................... 33

7.6 Planemos – Application builder ................................................................................ 33

8

Status of work.................................................................................................................... 34

9

Conclusions and outlook ................................................................................................... 36

10

References ........................................................................................................................ 37

11 Appendix ........................................................................................................................... 38

11.1 Hardware Description............................................................................................... 38

11.1.1 Processor and Communication Board ......................................................... 38

11.1.2

Power module .............................................................................................. 40

11.1.3 Multi-sensor board ....................................................................................... 41

11.1.4

Tilt and inclination sensor ............................................................................ 43

11.1.5

Air sensor ..................................................................................................... 44

11.1.6 Impedance Sensor ....................................................................................... 46

11.1.7

Electrometer ................................................................................................. 47

11.2 Database Description ............................................................................................... 49




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1 Summary

Historic structures are often characterized by their extraordinary architecture, design or material.The conservation of such structures for future generations of the European population is one of the

main tasks of monument conservators. To conserve historic structures it is increasingly importantto understand the deterioration processes mainly caused by the environment. To obtain moredetailed information about the deterioration processes in certain cases continuous monitoringsystems have been installed. However, most of these monitoring systems were only weather or airpollution data acquisition systems and basic models for data analysis are used. The real influenceof the environment to the structure or the structural material is often neglected. That means thatthe structural resistance is calculated from the measurements and not determined by sufficientsensors. Another facet is that most monitoring systems require cabling, which is neitheraesthetically appealing nor in some cases applicable due to the needed fastening techniques. Thisis particularly significant for historical monuments and other cultural heritage.

This report shows the cutting edge of competitive and smart wireless sensor network hardware and

software for monitoring historic structures. A special focus is on the hardware including appropriatelow power signal conditioning with respect to reliable and event-based data acquisition. The reportis introduced by a chapter of the general setup of the WSN architecture.

In detail, the following system components are included: a main board, similar to the main board ina personal computer, as a central component. It offers processing capabilities and optional storagecapacity. It offers connectors where one or two signal conditioning boards can be attached to and itcarries a radio frequency module for the transmission of data. The main board is powered by apower supply circuit that is powered by either batteries or a solar power module. For details on thesolar power modules tested on the platform, refer to D3.4 "Power supply technologies".

When it comes to the supported sensor types, the system already supports sensor boards for sixsensors and further adaptation boards are under development. One of the central sensor boards

developed to date is the multi-sensor board, capable of measuring air temperature and airhumidity, three-dimensional vibrations and up to two channels of external resistive sensors, as forexample temperature sensor, strain sensors or displacement transducer.

The electrometer sensor board allows the detection of moisture and salt induced electrical potentialin walls. Together with a third type of sensor board, which allows complex impedancemeasurements; this covers the application area of damp walls and salinization effects, which isimportant for many historical buildings.

Moving walls is an issue in larger structures, which will be measurable by our inclination sensoradaptation board with high accuracy. Recording of airflow is supported with a hot-wire anemometersensor. Event-triggered evaluation of acoustic emission is going to be a main focus.

The software system that operates the wireless sensors is proprietary and adapted especially forlong-term, low-power operation. It consists of a bootloader function that is responsible for radiotransmission and for over-the-air software updates. On top of this bootloader resides the sensorboard specific application. It is responsible for the acquisition of raw data and for the properconversion and preprocessing of raw data before transmission.

The base station runs on the Linux operating system and an application handles the forwarding ofdata via a secure virtual connection, using a built-in mobile connection modem.

A database system is the final destination of acquired data, where it can be read-out directly fromthe database by using secured access accounts. Else, data is retrievable online in various formatsvia a web interface. It can also be downloaded in common spreadsheet software formats.




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2 Introduction

The use of wireless monitoring systems often are supposed to have several advantages comparedto wired monitoring systems, that is for example easy installation, cost-effectiveness and

autonomous operation over longer periods providing remote control and analysis features.Therefore, a lot of research and development activities are ongoing with regard to wirelessmonitoring systems to be applied on civil engineering structures like bridges [1, 2] as well as onhistoric structures [3]. At first glance, continuous monitoring with wireless sensor networks seemsto be a perfect solution to get more detailed information about structures than from visualinspection only. However, wireless monitoring is often not that simple if the monitoring task is morecomplex than simply acquiring and transferring relatively basic data like temperature or humidityevery hour. For such simple tasks, many competitive solutions with adequate reliability in the formof data loggers, partly also equipped with wireless communication, are now commercially available.

The situation becomes challenging if the desired monitoring is focused on acquiring and analyzingdata like stress, strain, inclination, salt and moisture content inside materials or even vibration or

acoustic emissions caused by fracture processes that require higher sampling rates. The mainproblem in this context is the power supply (primary batteries are most common) so that thewireless monitoring hard- and software is subject to several restrictions. To remain cost-effectiveand practicable, a balance between the monitoring task respective to the expected result from themonitoring and the time and effort to perform the continuous monitoring must be found. This is whywireless monitoring systems frequently have to be customized for the desired monitoring objective.Thus, structural health monitoring is also to be seen as an interdisciplinary engineering task.




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3 Related work

Most of the wireless sensor networks under development consist of several multi-sensor nodes,called motes, and a minimum of one base station, which also could have an integrated modem

(GPRS/UMTS etc.) for internet connection and remote control. With respect to power consumption,network robustness, and the possibility to build up big meshes multihop-networks are often thebest solution for monitoring large structures.

The motes are the main components of a wireless monitoring system. There are different tasks asensor mote has to perform, which are to collect and digitize data from different sensors, to storesensor data, to analyze data with simple algorithms, to send and receive selective and relevantdata to and from other nodes as well as the central unit and to work for an adequate time periodwithout a wired power supply. There are many different wireless sensors that have been developedby researchers all over the world to be used for structural health monitoring (SHM). Acomprehensive review of available wireless sensing units is given by Lynch and Loh [4] that showthe cutting edge at that time. However, a lot of shortcomings especially with respect to reliability

are obvious. The biggest problem is still the conflict between power consumption, storage capacityand system bandwidth. The system bandwidth is mainly restricted by the wireless communicationthroughput that is limited. That is why multihop network algorithms, mote clustering and in-motedata processing and reduction are considered in the recent research [4, 5, 6, 7]. Another drawbackis the lack of adequate sensors especially with respect to sensitivity, reliability and robustness aswell as their integration into a mote [8].

Although numerous commercialized smart sensors are also available together with someapplication software from different companies (Dust Networks, Microstrain, Millenial Net,Sensametrics, Sensicast, Testo etc.), most of these sensor networks are in a basic configuration just wireless data acquisition systems for evaluation purposes that only transmit measured rawdata to a central base station for further processing. Moreover, most of the systems do not fulfill therequirements with respect to robustness, long-term stability, long-term battery operation or sensorreliability.




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4 Structural health monitoring system

4.1 Environmental Influences and Damage ProcessesHistoric materials and historical structures have been under environmental influence for centuriesor even millenniums. These influences induce damage processes in the building materials thatlead to a degraded state of the structures eventually. The degradation effects can add up anddestroy the valuable object that monument authorities try to preserve for future generations.

Environmental influences are manifold and have their origin in physical and chemical effects. Thiscomprises decomposition by light, rain, salts, gases and others. To prevent the degradation or thedestruction of historic objects, restorers and conservators try to chemically and physically conserveand protect the object and in some cases have to reconstruct parts. For the restorers andconservators, it is of great importance to know and understand the main factors responsible for thedamage.

4.2 Benefits of SHM on Historic StructuresBy knowing the main causes for damaging effects, best countermeasures for preservation andconservation can be taken and the remedies are adapted to the specific structure. To this end,understanding environmental effects is necessary. To this effect, all relevant environmentalquantities have to be recorded and analyzed by relating the resulting effects to the physical andchemical values. Damage processes are usually slow and medium to long-term measurements arenecessary.

The knowledge resulting from the SHM measurements can be used for the discovery andconfirmation of general correlations but it can also be used to erect an object specific treatmentplan, if correlations are already known but influencing factor for the specific object are unknown.

4.3 Principle system layoutWire-based measurement systems for SHM consist of several sensors applied to the structure atrelevant locations. Sensors are available for a plethora of physical quantities, and have to bechosen according to the application demands. The sensor readings are analog-digital converted ina central unit, where the digital data is also stored. Many systems allow online-retrieval of recordeddata (compare Figure 1, left side).

In contrast to these aforementioned systems, wireless systems have no central data acquisitionunit but one or several sensors are connected to a (usually) small data acquisition unit, which iscalled a measurement node. The complete measurement system consists of several independentnodes, linked to each other by a radio communication link, hence building a wireless sensornetwork. Additional elements of the system are the gateway, which relays the measurement data

to a long-distance network for remote access, and a database to save data storage for laterretrieval and optional post-processing. The WSN is operated remotely from an operation andmaintenance terminal (O&M). See Figure 1, right side, for a general layout of a WSN.

Figure 2 gives a more detailed view on the general system layout. The autonomous wirelesssensor nodes are depicted deployed on a building, sending their information via Smartswitches ifnecessary, to a mandatory base station, called Smartgate. The Smartgate includes a wide areamobile connection, used for controlling the system and for sending data to the central databaseand web server (Smartserver) within the operator's premises. The customer can then access theinformation via a web access (refer to chapter 7 for details).

Please read on in chapter 6 for the technical realization of the system.




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Equipment bus

S

Measurement

Equipment

Database &

Webserver

Short-range

Wireless

Gateway

Operation Terminal

Wireless Sensor NodesWired Sensors

Operation Terminal

Cellular mobile network

IP IP

Database &

Webserver

Figure 1: Wired SHM schematic with central measurement unit where individual sensors areconnected to, versus the proposed wireless SHM with autonomous sensor nodes relaying

measured data via a short-range transmission and (optionally) long-range mobile networks

LAN/WLAN

Client

Mobile phone

(PDA)

Da ta trans fer & re

mo te ma in tenance

A l a r m - S

M S

WWW

Client Mobile

Smartserver WS

SmartmoteWS

LAN/WLAN

SmartgateWS

SmartswitchWS

Figure 2: General system layout




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5 Aspects of flexible and reliable sensor node hardware

System and data reliability with respect to the desired operation period and desired accuracy are ofutter importance in terms of structural health monitoring under harsh environments. In addition to

these fundamental aspects, wireless monitoring should be more than just acquiring diversemeasurands at different locations of a structure and then storing it in a database. If the monitoringtask and the expected result are well-considered, immediate data processing of the data isrecommended to avoid collecting large amounts of senseless data no one will look at afterwards. Ifsuch immediate data processing is considered, wireless monitoring becomes intelligent and ofdirect practical use. Therefore, distributed computing strategies, which include data acquisition,data analysis and data reduction are of utter importance.

With respect to the restrictions of a sensor node event based data acquisition may become ofinterest or rather becomes an obligatory task if a critical short event occurs during the time themonitoring system is in sleep mode, thus not capable to recognize this event. Event basedmonitoring is useful if temporary loads or other influences stress the structure, e.g. trains, trucks,

wind, snow or rain, earthquakes or structural failure itself. That means that an object specific eventtriggers the measurement progress.

Some examples of event based monitoring concepts supported by sufficient hardware are reportedby several researchers. A case study on which event based monitoring was successfully testedwas the detection of a train crossing the bridge [9]. The task was to measure dynamic strain ofsteel girders during a train crossing a bridge. The train detection was conducted by using a MEMSvibration sensor on each mote that could be configured by software to trigger the system. TheMEMS sensor provides a vibration detection mode while using only little power. If a train crossesthe bridge the vibration is recognized by the MEMS sensor that then wakes up the microcontrollerfrom sleep mode by interrupt. After that, the measurement procedure starts within a fewmilliseconds. The procedure was acquiring dynamic strain during train crossing with a sampling

rate of 100 samples/s using resistive strain gauges. The collected data was first stored temporarilyinside the mote and then transmitted to the base station consecutively after the train has passed.This procedure was necessary to reduce data loss rate.

One of the most challenging examples of event based monitoring is acoustic emission analysis,which is useful to detect and also to characterize or localize fracture processes. Qualitativeacoustic emission analysis techniques often require very sensitive sensors and high-speed dataacquisition systems, because the full waveforms are analyzed. Due to the hard- and softwarerestrictions it is obvious that only certain quantitative acoustic emission analysis techniques couldbe implemented into a wireless sensor network. In terms of acoustic emission analysis hit rate(relevant acoustic events per second) determination, beam forming techniques for localizingacoustic events as well as signal characterization and classification techniques have beeninvestigated and possible solutions for both hard- and software have been discussed [9, 10, 11, 12,13, 14]. Although not all mentioned concepts have fully been implemented into a mote and furtherinvestigations are necessary, the concepts of acoustic emission data analysis in wireless sensornetworks are promising.




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6 Realization of a robust sensor node hardware

Figure 3 shows an example of an actual development. It shows a wireless sensor mote equippedwith low-power microcontroller, wireless transceiver, primary batteries and several sensor boards

for multiple sensing. The hardware is optimized to work under harsh environmental conditions asthey occur in case of structural health monitoring and supports several ultra-low power modes.Therefore, the sensor node is water and dust protected (IP65) and could work in a temperaturerange of -20°C to 80°C. Different kinds of sensors could be attached to the wireless motesimultaneously that is various MEMS (Microelectromechanical systems) sensors with digital output,e.g. for the acquisition of acceleration, temperature, humidity, inclination, solar radiation etc. Additionally analog sensors like resistive strain gauges or piezo-based vibration sensors areconnectable by using especially developed electric circuits for the signal conditioning. This modularconcept allows for customization and optimization for specific monitoring objectives.

Multi-Sensor Board

Multi-Sensor Board

Acceleration Sensor Board

WirelessCommunication

Module(Backside of

Processor Board)

ProcessorBoard

Programming Adapter

(USB/JTAG)

PowerSupply

Wireless Sensor

Figure 3. Robust wireless sensor node (mote) for multiple sensing and modular node components(© www.smartmote.de ).

The basic functionality common to all sensor nodes, e.g. communication, data processing etc., isintegrated into the so-called processor board. This processor board allows also the interfacing ofdifferent sensors not requiring specific signal conditioning. In addition to this processor board,several sensor boards were developed for interfacing sensors requiring a specific signalconditioning functionality that is not provided by the processor board. These sensor boards areconnected to the processor board. Currently, two sensor boards are available: a signal conditioning

board for interfacing piezo- and PVDF- sensors for acoustic emission and dynamic analysis and amulti-sensor signal conditioning board for strain gauges, displacement transducers and pressure




Rev. 2010-07-07 11/52

cells in combination with temperature/humidity and vibration measurements. Sensor boards forhigh precision inclination measurements and for high-impedance potential measurements as wellas for high-impedance resistivity measurements in the field of electrochemical analysis are underdevelopment.

6.1 Processor board with wireless communicationThe main components of the processor board presented here are a microcontroller equipped withFRAM for data storage and a low power radio chip for the wireless communication (see Figure 4).

The low power operation of the processor board is due to the ultra low power microcontrollerMSP430 F1611 featuring 10kB of RAM and 48kB of program memory (flash). This 16-bit RISCprocessor features several power-down modes with extremely low sleep-current consumption thatpermits the sensor node to run for a long time period. The MSP430 has an internal digitallycontrolled oscillator (DCO) that may operate up to 8MHz. However, the jitter and accuracy of theinternal DCO shows a strong variation with respect to temperature and supply voltage. This aspectis supposed to be problematic especially with respect to the usage of the internal A/D-conversionat higher sampling rates as well as time synchronization accuracy. Therefore, the MSP430

operates either with an external ceramic oscillator at 6 MHz or with an external 32’768 Hz crystalwatch on our processor board.

Six of the eight external ADC ports of the MSP430 were split up to two separate connectors withthree ADC ports each to which different sensors or sensor boards could be attached. Themaximum reliable total sampling rate for all ports was tested to be approximately 100 kHz at 12 bitresolution. The two remaining ADC ports are used to monitor the actual power supply voltage aswell as actual current consumption of the sensor node. The I2C and SPI ports, which are alsointegrated into the microcontroller, are mainly used to control additional sensors and signalconditioning boards. The MSP430 also includes a 3-port DMA controller. For data storage FRAM(Ferroelectric random access memory) was supposed to be the best choice, because of its highaddressing speed, low power operation and non-volatile storage capability. Up to four FRAMmodules with 256 kB each could be attached to the processor board providing a maximum of 1MB

storage capacity.

The processor board is equipped with a Chipcon IC (CC2420) soldered separately on aninterchangeable module for the wireless communication. It permits power management to ensurelow power consumption. The CC2420 is controlled by the TI MSP430 microcontroller through aseparate SPI port and a series of digital I/O to avoid data collisions with the digital sensors. Theradio may be shut off by the microcontroller for reducing the power consumption. The theoreticallyachievable maximum data throughput rate of the system is 250 kbps.

Details can be found in appendix 11.1.1.




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Radio Transceiver

CC2420

F-RAM Memory

8Mbit

4 x FM25H20

Sensor-Board Connector 2

MCU

MSP430F1611

2.4 GHz ISM

Sensor-Board Connector 1

32 kHz

USB-Connector

Programming Board

JTAG-Connector

USB to UART

FT232R

MCU Board

USB

UART

UART

GIO

Power

I2C/SPI 0

GIO Power

IO

SPI

IO

6 MHz

Power Supply

Battery

Power

Management

Supercap

XIN

XOUT

XT2IN

XT2OUT

Ext. Keyboard

Solar

Modul

Power

Keyboard

Adaptation

JTAG

K e y b o a r d

C o n n e c t o r

Supply Connector GIOPower

3.3V

Reg.

Supply Connector

Misc.

Power GIOJTAGUART

Supply Connector UART JTAG

GIO

GIO Power

Serial ID

DS28CM00

VREF

VREF

Ext.

VREF

Mem Ctrl Mem Ctrl

SPISPI 1

optional

Power

Ext. Solarpanel

I2CI2C/SPI 0

ADC

ADC

ADC

ADC

ADC

Figure 4. Principle sketch of the processor board, power supply and programming board.

The processor board is mounted headfirst, opposite to the other modules, so that the radio board ison top.

Figure 5. Processor board front and back with mounted radio board.




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6.2 Power supplyThe sensor node is primary powered by one or two Li-SOCl 2 batteries with each 7.3 Ah @ 3.6 V.This type of battery has a very long lifetime with a small drop of voltage and capacity due to ageingor temperature changes. The battery operates in the temperature range from -55°C to +85°C;however the operation at temperatures different from ambient may lead to some capacity

reduction. The actual voltage of the battery and the current consumption can be monitored forestimating the remaining lifetime of the sensor node. As secondary power supply one or two solarcells (optimal voltage at MPP 5.2V to 6V) can be attached to the sensor node. The power providedby the solar cell is regulated and stabilized by an electronic circuit to avoid power fluctuation thatcould lead to miscellaneous behavior in terms of reliable data acquisition and analysis. The usageof additional supercaps (high energy density capacitors 1.5F, 5V) allows for temporary poweringthe sensor node only with the solar cell during daylight condition even if relatively high current isneeded, which might be the case of full operation of all node components. The power regulationcircuit provides a maximum power output of 150 mA at 3.3 V. As long as the capacitors and thesolar power module provide enough energy, the sensor node uses solar power. If the voltage levelfalls below 3.4V, power supply is automatically switched to battery operation until the solar cell hascharged the supercaps to approximately 4.4V again.

With the batteries mentioned, the lifetime of a sensor node is estimated to be at least severalmonths or years. Note that the lifetime strongly depends on the type of embedded sensors, thedata acquisition and measurement rate, the processing effort and data transmission rate. Forachieving a long lifetime for the system, it is essential to run the sensor nodes in power down modemost of the time.

It is possible to connect a plastic foil keyboard with low current LED’s to this board. All componentswhich are necessary to operate a keyboard (3 LED’s, RESET button and 2 function buttons) aremounted on the board.

Figure 6. Power supply board for battery power and solar power.





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6.3 Multi-sensor board for strain gauges, vibration, temperature andhumidity

6.3.1 General description

The multi-sensor board (see Figure 7) is primarily developed to support any type of sensorsrequiring a Wheatstone bridge-type signal conditioning for an accurate measurement of changes ofelectric resistance (e.g. piezo-resistive, ceramic-thick film or steel membrane based). Manydifferent sensors for the measurement of strain, stress, load, displacement, inclination, soilpressure etc. can be attached to this signal conditioning board. With small changes in thehardware setup also PT100 elements for temperature measurements could be used. The boardperforms the digitalization of the sensor signals. It communicates with the processor board usingthe I2C bus. The board is equipped with two ZMD31050 differential sensor signal conditionerdevices for operating two independent sensors simultaneously. The ZMD31050 is a CMOSintegrated circuit for highly accurate amplification and sensor-specific correction of bridge sensorsignals. The IC provides digital compensation of sensor offset, sensitivity, temperature drift andnon-linearity of an integrated 16-bit RISC micro controller running a correction algorithm with

coefficients stored in a non-volatile EEPROM (Electrically Erasable Programmable Read-OnlyMemory). These coefficients can be programmed from the processor board, for example during acalibration process. In addition, the IC can interface a separate temperature sensor.

Sensor-Connector 2

ZMD 31050

Multi-Sensor Board

ZMD 31050

Sensor-Board Connector GIOPower

I2CPW

Sensor-Connector 1

Power

Switch

Accelero

meter

IO

HUM.

TEMP.

PW I2CINT PW I2C

EN

optional

I2C/SPI 0

Figure 7. Principle sketch of Multi-Sensor Board.

Because measuring with a Wheatstone-bridge circuit needs considerable power (power mainlydepends on the impedance of the used strain gauge), the signal conditioning board can beswitched off and on by an electronic switch that is controlled by the processor board via the GIOinterface. The bi-directional digital interface (I2C) is also used for simple software controlled one-shot calibration procedure, in order to program a set of calibration coefficients into the on-chipEEPROM. Thus a specific sensor and the ZMD31050 are digitally connected.

For measuring air temperature and humidity, a MEMS sensor (SHT15 from Sensirion) that isequipped with a digital interface could be connected to the multi-sensor board. The SHT15 digitalhumidity and temperature sensor is a fully calibrated MEMS sensor that offers high precision andexcellent long-term stability. The digital technology integrates two sensors and readout circuitry onone single chip.

Measuring time series with high sampling rates is energy consuming and also limited by thesystem bandwidth and the storage capability. It is therefore advisable to sample a measurand only




Rev. 2010-07-07 15/52

when signals of interest are expected. This often means to sample signals only if a certainamplitude threshold is exceeded. Especially in case of dynamic strain measurements, such anevent driven data acquisition is indispensible. Hence, a vibration detection mechanism/device wasdeveloped, which enables power-consuming measurements only in case of vibration exceedcertain level.

The chosen solution is an acceleration sensor, SMB380 from Bosch Sensortec GmbH, Germany,which features energy saving modes. The functional principle of the chosen vibration detectionsolution is briefly described: The on-chip routines measure periodically the acceleration and detectif a given threshold is exceeded. Then the SMB380 generates an interrupt to wake up the MSP430µC and the ZMD chips and to start with predefined measurement routine.

For the setting of the SMB380's parameters, a software tools is available. Once an optimal settingis found, it can be stored to the SMB380's EEPROM and is then fixed even without power. In the“any motion” detection mode, which was tested and found to be suitable e.g. to detect trainscrossing a bridge, the sensor consumes just about 200µA, which guarantees long batteryoperation.

Figure 8. Multi-Sensor Sensor Board and Temperature/Humidity Add-on sensor.

6.3.2 Features

• Wheatstone bridge measurements (Pt-elements, strain gauges etc. using ¼-, ½- or full-Wheatstone bridge)

• Software programmable (offset, gain etc.)

• Event detection using optional MEMS acceleration sensor

• Optional Temperature/Humidity Measurements

6.3.3 Technical data

Table 1: Multi-sensor board specifications, Rev. 2.2 (Wheatstone bridge)

Item / Parameter Symbol Value

Supply voltage 3V to 3.6V

Supply current

• Sleep mode

• Operation mode (without sensor)

ASM

AOM

12µA

6mA (typ.)

Response time




Rev. 2010-07-07 16/52

• From sleep mode

• From operation mode

20ms

40ms

No. of input channels Ch1, Ch2 2

Input range 2mV/V to 280mV/V

Resolution ≤15 bit

Max. sampling rate ≤3.9 kHz

Ambient Temperature -40 to +85°C

Ambient Humidity Not specified

Add-ons (optional)

• Bosch SMB380 (Event detection)

• Sensirion SHT15

Vibration detection

Temp. /Hum. measurement

Red = preliminary, values have to be checked


6.4 Acceleration sensor board for piezo- and PVDF-sensorsDuring a former research project (www.sustainablebridges.net), different kinds of accelerationsensors were tested for evaluating their fitness for acoustic emission analysis. However, nocommercially available MEMS sensors fulfilled the requirement of acoustic emission analysis.Especially their performance with respect to bandwidth, sensitivity, signal to noise ratio and/orpower consumption did not meet the requirements. Therefore, other sensors (piezo and PVDF) areused for acoustic emission analysis or other higher frequency vibration analysis. For thosesensors, a signal conditioning board (acceleration sensor board) was designed and manufacturedthat allows for an event-based data acquisition (see Figure 9).

The signal conditioning board for piezo- and PVDF-sensors is equipped with two amplifiers thathave a programmable gain (gain factor: 100, 1000), low pass filters and an analog trigger(threshold) that is adjustable in 256 steps by the software running on the processor board. Eachacceleration sensor board has two independent analog channels for performing simultaneously thesignal conditioning of the two sensors. The analog trigger option, which could be used before orafter the analog filtering, allows for running the processor board in power down mode most of thetime. Only if relevant events occur and a certain threshold is exceeded, an interrupt is initiated thatcould switch the processor board into working mode for a predefined time that can be controlled bythe microcontroller. The acceleration board itself needs about 800 µW in working mode so alifetime of several months up to years could be reached just working with a battery. A low passanti-aliasing filter is also implemented to meet the requirements of the analog to digital conversion.

The cut off frequency of the low pass filter can be adjusted to fit the selected sampling rate.The acceleration sensor board is not designed only for acoustic emission analysis usage. It can beused as a signal conditioning board for vibration analysis, too. This can be achieved by just a fewchanges in the low pass filtering module.




Rev. 2010-07-07 17/52

S E

L

Figure 9. Principle sketch of Acceleration Sensor Board.

6.5 Inclination and tilt sensor board


The inclination and tilt sensor board (see Figure 10) is primarily developed to support an additionalexternal inclination sensor module, which is equipped with up to two VTI SCA830-D07 or similarsensors for 1- or 2-axis inclination measurements. The inclination module, which is mounted on the

monitored surface of the structure, is connected to the sensor board via two cables, supplying themodule with electrical power and with a digital SPI interface for communication with the processorboard. The SCA830-D07 is a MEMS sensor that primarily contains the sensing element, a 16-bitanalog to digital converter, a temperature sensor for temperature compensation purposes, a non-volatile memory, a SPI interface and some self diagnostic features. The sensor module is equippedwith up to two SCA830-D07 sensors that are mounted orthogonally in the module to ensure 2-axismeasurements.

Because the MEMS sensors need considerable power, the inclination and tilt sensor board can beswitched off and on by an electronic switch that is controlled by the processor board via the GIOinterface.

Additionally the sensor board is equipped with a Bosch SMB380 acceleration sensor for

acceleration measurements or motion detection. Furthermore for air temperature and humiditymeasurements a Sensirion SHT15 sensor can be connected. The SMB380 and the SHT15sensors are already explained in chapter 6.3.1.




Rev. 2010-07-07 18/52

Sensor-Connector 2

Inclination Interface Board


PW

Sensor-Connector 1

Power

Switch

Accelero

meter

IO

HUM.

TEMP.

PW I2CINT PW I2C

EN

optional

I2C/SPI 0

Sensor-Connector 2

Sensor-Connector 1

ZMD 31050VTI SCA830

SPIPW IO

SPI

External Inclination Sensor

Figure 10. Principle sketch and picture of inclination and tilt-sensor board.

6.5.2 Features

• 2-axis inclination measurements with high resolution

• Software programmable


• Optional Temperature /Humidity Measurements


Table 2: Inclination and tilt sensor board specification


Supply voltage 3 V to 3.6 V

Supply current

• Sleep mode

• Operation mode (with 2 SCA830-D07)

ASM

AOM

12 µA

10 mA (typ.)

Response time

• From sleep mode 95ms

No. of channels Ch1, Ch2 2 one axis inclinometersorthogonally installed

Input range -90° to +90° Resolution 0.00179° (range +/-3°)




Rev. 2010-07-07 19/52

Max. sampling rate 125 Hz

Amplitude response 6.25 Hz



Add-ons (optional)


• Sensirion SHT15

Vibration detection



Details can be found in appendix 11.1.4 .

6.6 Air velocity sensor board


Figure 11: Principle sketch of the air velocity sensor adaptation board

The air velocity sensor board (see Figure 11 and Figure 12) is primarily developed to support theOmrom D6F-V03A1 MEMS flow sensor but actually any sensor equipped with a DC output in the

range of 0 to 3.6 V, a supply voltage of about 2.7 to 3.6 V and a supply current of less than 150 mAmay be connected. The D6F-V03A1 is able to measure air flow in the range of 0 to 3 m/s with anaccuracy of +/-10%. The analog to digital conversion is done by the internal A/D-converter of themicroprocessor with a resolution of 12 bit.

The second channel of the board is used for external temperature measurement with a PT100 orother RTD sensor. It is equipped with the ZMD31050 differential sensor signal conditioner device,which is already explained in chapter 6.3.1. With small changes in the hardware it is also possibleto connect any sensor based on a Wheatstone-bridge.

Because the two channels need considerable power, the air velocity sensor board can be switchedoff and on by an electronic switch that is controlled by the processor board via the GIO interface.

Additionally, the sensor board is equipped with a Bosch SMB380 acceleration sensor foracceleration measurements or motion detection. For air temperature and humidity measurements,




Rev. 2010-07-07 20/52

a Sensirion SHT15 sensor can be connected. The SMB380 and the SHT15 sensors are alreadyexplained in chapter 6.3.1.

6.6.2 Features

• Measurement of the air velocity on channel 1 (or other sensors with DC output)

• Wheatstone bridge measurements on channel 2 (Pt-elements, strain gauges etc. using ¼-,½- or full- Wheatstone bridge)

• Channel 2 software programmable (offset, gain etc.)



Figure 12. Air velocity sensor board with flow sensor


Table 3: Air velocity sensor board specifications


Supply voltage 3.15 to 3.6 V

Supply current

• Sleep mode ASM

AOM

12µA

about 20 mA




Rev. 2010-07-07 21/52

• Operation mode (with sensors)

Response time

• From sleep mode


No. of channels Ch1

Ch2

Air velocity sensor

RTD Temperature Sensor

Input range channel 1 0 to 3 m/s

Accuracy channel 1 +/-10 %

Ambient Temperature channel 1 -10 to +60°C

Ambient Humidity channel 1 Max. 85% RH

Input range channel 2 2mV/V to 280mV/V

Resolution channel 2 ≤15 bit

Max. sampling rate channel 2 ≤3.9 kHz

Ambient Temperature channel 2 -40 to +85°C

Impedance converter Add-ons (optional)


• Sensirion SHT15

Vibration detection




6.7 Impedance converter board system for electrochemical analysisand impedance spectroscopy


Sensor-Connector 2

AD 5933

Impedance Converter Board


I2CPW

Sensor-Connector 1

Power

Switch

HUM.

TEMP.

IO

Freq.

Divider

PW I2C PW IO

EN

optional

I2C/SPI 0 ADC

Buffer

Figure 13: Principle sketch of the impedance converter board




Rev. 2010-07-07 22/52

The impedance converter board (see Figure 13 and Figure 14) is primarily developed forelectrochemical analysis and impedance spectroscopy at historical or modern structures. Theboard performs the excitation, measurement and digitalization of external impedance connected tothe board via two electrodes. It communicates with the processor board using the I2C bus. Themain item on the board is the Analog Devices AD5933 integrated circuit. The AD5933 is a highprecision impedance converter system, which combines a programmable frequency generator witha 12 bit 1 MSPS analog-to-digital converter and a DSP engine. For each output frequency, a realand an imaginary data word is calculated. Furthermore a temperature sensor for temperaturecompensation purposes and an I2C interface are integrated on the chip.

To measure impedance below 1 kOhm an external buffer is required and for output frequenciesbelow 1 kHz an external programmable clock generator can be used, both are alreadyimplemented on the board.

Because the integrated circuits need considerable power, the impedance converter board can beswitched off and on by an electronic switch that is controlled by the processor board via the GIOinterface.

For measuring air temperature and humidity, a MEMS sensor (SHT15 from Sensirion) that is

equipped with a digital interface can be connected to the multi-sensor board. The SHT15 sensor isalready explained in chapter 6.3.1.

6.7.2 Features

• 1 MSPS 12 bit impedance converter system

• Software programmable (frequency sweep, excitation, gain etc.)


Figure 14. Impedance converter board


Table 4: Impedance converter system board specifications





Rev. 2010-07-07 23/52

Supply voltage 3 to 3.6 V

Supply current

• Sleep mode

• Operation mode

ASM

AOM

12 µA

18 mA

No. of channels Ch1

Input range 100 Ω to 10 MΩ

Resolution 12 bit

Max. sampling rate 1 MHz

Max. frequency 100 kHz



Add-ons (optional)

• Sensirion SHT15 Temp. /Hum. measurement



6.8 Electrometer with multiplexer


The electrometer board (see Figure 15 and Figure 16) is primarily developed to measure potentialdifferences caused by electrochemical cells with very high internal resistance. Therefore theelectrometer board must have an extremely high input resistance. This is ensured by using at the

input circuit of the board an operational amplifier with a very low bias current. The LMP7721 madeby National Semiconductor that is used here has a typical bias current of only 3 fA at ambienttemperature.

The board acts as an impedance converter and level shifter with extremely high input impedanceand low output impedance. The signal at the output of the board is digitized by the 12 bit analog-to-digital converter of the microprocessor. There are three charge pumps on the board to supply theoperational amplifiers and the multiplexer with the required supply voltages.

An additional relay multiplexer extends the numbers of input channel from one to eight. The eightinputs of the multiplexer can be switched via the I2C bus sequentially to the input of theelectrometer board.

For measuring air temperature and humidity, a MEMS sensor (SHT15 from Sensirion) that isequipped with a digital interface can be connected to the multi-sensor board. The SHT15 sensor isalready explained in chapter 6.3.1.




Rev. 2010-07-07 24/52

Figure 15. Principle sketch of the Electrometer board

6.8.2 Features

• Extremely high input resistance of 100 GOhm (If required up to 100 TOhm may be possible)

• Eight software selectable input channels with additional multiplexer

• Optional Temperature/Humidity measurements




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Figure 16. Electrometer board and multiplexer

6.8.3 Technical dataTable 5: Specifications of the electrometer board with multiplexer


Supply voltage 3V to 3.6V

Supply current

• Sleep mode

• Operation mode (without sensor)

ASM

AOM

12µA

Response time

• From sleep mode


Not specified

Not specified

No. of channels

• Single use

• In combination with Multiplexer

Ch1

Ch1 - CH8

1

8

Input range -2V to +2V

Resolution 12 bit

Input resistance ~100 GΩ



Add-ons (optional)

•

Sensirion SHT15 Temp. /Hum. measurementRed = preliminary, values have to be checked





Rev. 2010-07-07 26/52

7 Structural health monitoring software

7.1 Principal structure of the SHM system softwareTo operate the WSN, a complex but flexible architecture of software components has been coded,which interact to form the WSN. To each of the hardware components, as described in chapter 6,belongs a software component that operates this component. A block diagram of the softwaresystem is shown in Figure 17. The measurement nodes (Smartmotes) are the core of the system.The Smartmotes run two components: the sensor node boot loader (Wboot) and the sensor nodeapplication software, called Miranda. For details on this software, refer to chapters 7.2.2 and 7.2.3.

The Smartswitch is an optional system unit, which is not necessary for small-scaled deployments.The software component Uranus, running on the Smartswitch, is therefore postponed.

The Smartgate is the central node in the WSN and offers base station functionality. It is composedof the Starcatcher application, which receives the radio messages from all the Smartmotes andforwards them to the Jupiter application. Starcatcher can be seen as the radio interface component

of the Jupiter application. Jupiter is a component that manages the WSN. Command messagescan be injected into the network and also data can be displayed. The Callisto application is optionaland is used for on-site-interaction with the object.

„miranda“

Application (Data

Acquisition, Data

analysis)

„wboot“

Bootloader

„uranus“

Forwarder

„jupiter“

Forwarder

„mars“

SQL interpreter

(PHP-Skript)

V I - S e r v e r ( L a b v i e w - V i s )

„galaxy“

MySQL Data Base

Data analysis

toolbox

2.4GHz

LAN/WLAN

GPRS/UMTS

LAN/WLAN

SQL interpreter

SmartmoteWS SmartswitchWS SmartgateWS Smartserver WS

„planemos“

Application builder

„callisto“

On-Site control

SmartgateWS

SmartswitchWS

Smartserver WS

SmartmoteWS

miranda:

mir_shtup, mir_DMS

„starcatcher“

Serial forwarder

„starcatcher“

Serial forwarder 2.4GHz

Figure 17: Principle sketch of the SHM system software components including name conventions.




Rev. 2010-07-07 27/52

The Smartserver is a hardware unit which is detached from the rest of the WSN. For details refer tothe system description in chapter 4. A software component called Mars receives the data from theWSN and inserts the data into a database (Galaxy). The VI-Server, running National InstrumentsLabVIEW, handles the requests for online visualization of the data. The requests to thesevisualization tools originate from a web server, which is not shown in this sketch. The applicationbuilder software (Planemos) handles the update process of the sensor nodes with Mirandaapplications.

7.2 Sensor network and data transfer software

7.2.1 Sensor network protocol

The individual nodes erect a wireless sensor network by exchanging radio messages with theirneighbors or with the base station. The protocol that regulates the interchange of messages is acustomized protocol, implemented by TTI. To simplify matters and moreover to make the protocolas power-saving as possible, a routing-free direct-path transmission, request-based protocol wasdevised which establishes a star topology. The routing-free direct-path transmission can be

substituted by a multi-hop subsystem for large-scale deployments, where the forwarding of datafrom several star networks by Smartswitches would be uneconomic and a tree topology isdesirable.

The protocol realizes a low payload overhead for common tasks (~ 50 % less than ZigBee) whichresults to minimum power consumption (again ~ 50 % less than ZigBee). This is realized by 1) anearly split between Wboot and Miranda data on a very low level, and 2) an acknowledge-request-based-only transmission. This means that requests for sending a command can be sent to thenetwork nodes only with the acknowledgement of another message that has been sent before.

7.2.2 Wboot – Sensor node boot loader

The sensor boot loader can be seen as the operating system of the sensor nodes. It provides a

common interface for basic radio transmission routines to the application software (refer to chapter7.2.3). Furthermore, it provides support functions like a sleep timer, enabling the application topower down to a low-power mode during inactive periods, and read/write accesses routines for themicrocontroller flash memory.

The operation of the boot loader (and of the application software) is supervised by a watchdog.The watchdog resets the software to an initial state, if it is not responding any more. This is afallback safety feature, avoiding the "loss", i.e. the non-responsiveness, of a sensor node. Thewatchdog is automatically configured and cleared periodically by the boot loader.

The boot loader is also capable of loading software updates into the node. In this mode, thesoftware update is transmitted wirelessly to the node and flashed into the internal memory. A CRCcheck is provided to guarantee the error-free transmission of the software package. It is even

possible to auto-start the application when the CRC check is valid. This update feature is usuallyused to load newer version of the Miranda software, however, it is even possible to install a newboot loader over the air.

7.2.3 Miranda – sensor node application software

The Miranda packages represent the application software, which is specific to the signal adaptationboard (refer to chapter 6), which is build into a specific node. In general, this software componenthandles the data acquisition, data format conversion and data analysis. It can also store data toadditional flash memory, if the node is equipped like that.

Data acquisition is done by either using the microcontroller's internal analog-to-digital converter or

specialized measurement hardware on the signal conditioning board. The software accomplishingthis task is therefore as diverse as the underlying hardware. The general program flow, however, is




Rev. 2010-07-07 28/52

common to all Miranda applications. Firstly, the data is acquired from the hardware, then data isconverted to a common format, post-processed (optional) and then sent to the SmartgateWS basestation, using the Wboot radio driver. Afterwards, the sensor node is set to a sleep mode, to saveenergy. After the measurement interval has expired, the whole measurement cycle starts over.

Be referred to Table 8 in chapter 8 for details on the status of availability of the Miranda application

software packages.

7.2.4 Starcatcher – radio to serial forwarder

The Starcatcher software is software running on a SmartmoteWS that is directly connected to USB-Port of a SmartswitchWS or a SmartgateWS. It is designed to provide a reliable connection betweenthe SmartmotesWS and the SmartswitchWS or SmartgateWS units. This application can be seen asthe radio interface of the Jupiter application. Its coupling with the Jupiter package is therefore tight.Its task is to forward data from the nodes to the Uranus or Jupiter application, and to forwardcommand is opposite direction from Uranus or Jupiter to the network. Additionally, the sending ofsoftware update to the nodes is done by this component.

7.2.5 Uranus – forwarder

The Uranus software is a stripped-down version of the Jupiter software. It is designed for use inmulti-star networks in large deployments. It communicates with the mars component to put datainto the Galaxy data base.

The Uranus component is running on a Linux system or an embedded Linux system.

7.2.6 Jupiter – base station and forwarder

The Jupiter software is basically similar to the Uranus software but has some advanced features. Itsupports UMTS/GPRS modem support for wide area mobile network connections and provides adata interface for the Callisto software.

The Uranus component is running on a Linux system or an embedded Linux system.

7.2.7 Callisto – on-site control

Callisto is the software package that provides direct on-site control. This can be used forimmediate interaction with the object under observation. For example in a church where the airhumidity is monitored, the on-site control component could provide an interface to a acclimatizationappliance, or even only a window-opening control system, to reduce the humidity by ventilation orheating under certain conditions. This software is still under evaluation and not finished yet.

7.3 Data storage

7.3.1 Galaxy – SQL data base

Galaxy is the link between the nodes and the user interface. Nodes and user interface never talk toeach other directly; moreover, they always use the Galaxy as a link. That guaranties a commoninterface and the possibility to use more than one user interface. It also cares for all thesynchronization and data storage.

7.3.2 Data Base Overview

The database layout is designed to allow both a quick insertion of new data items into the structureand a quick retrieval of information items for further processing, analysis and visualization. Galaxy

is a relational database with tables as shown in Figure 18.




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Figure 18: Data base structure: each square stands for one table

For more details on the database layout, refer to chapter 11.2.

7.3.3 Mars – SQL interpreter

The Mars software is written in PHP. On the one hand, it is used to load data into the galaxy data

base. For security reasons direct SQL access is not permitted. On the other hand, simple PHPscripts readout the database and print it in simple HTML sites for client access. The scripts aresimple and for debugging only.

7.4 Data analysis After raw data is gathered with the above described system, the data has to be analyzed regardingthe sought-after information and to reduce the amount of data. These goals are achieved by a two-step analysis procedure. First, some basic data filtering and reduction is done within the motesthemselves, e.g. by using hardware filter components to disregard noise or by averaging of data.Then, in a second step after the transmission and storage, the data can be post-processed andanalyzed in depth.

7.4.1 In-mote data analysis

In wireless sensor networks, low power consumption is of utmost importance. Of the factors thataccount for the most power consumption in wireless sensor nodes, radio transmission is on thefirst ranks. Current drain is linear with the time a sensor needs to transmit data. This is also true formote processing power; however, data processing of one byte is less costly – in the sense ofpower consumption – than the radio transmission of one byte. It is hence interesting to reducetransmission times as much as possible. Preprocessing of data – so called in-mote data analysis –can be used to reduce the acquired data to useable information. The principles used for this,comprise standard approaches from information theory, like compression by differencing(transmission of deltas only) but include also more complex analysis that are application specific.

An example for such an analysis is the analysis of vibration time series to retrieve the naturalfrequencies.




Rev. 2010-07-07 30/52

At present, no reduction routines are implemented in-mote. Transmission of deltas-only is a firststep, which will be implemented during the next timeframe.

7.4.2 Database analysis

The database analysis is controlled by the individual user, who requests a data analysis via a web

server user interface (cf. Figure 19). The web server does not handle the request on its own, butforwards it to the analysis server running National Instruments LabVIEW. This server retrieves thedata to analyze from the database server (which coincides with the web server in this architecture).The data is then accordingly analyzed and the analysis results are returned as Portable NetworkGraphics (png) via the web server to the client web browser.

Customers

1. Request analysis

via web interface

2. Request analysis

Web server

(public access)

Database server

(local access only)

LabVIEW analysis server

(local access only)

3. Retrieve data

4. Return analysis results

5. Send html

and graphics

Figure 19 - Database analysis architecture

The modular database analysis architecture was chosen to guarantee a stability of the entiresystem while maintaining a high flexibility and to ensure maximum data integrity on the databaseserver by limiting the required access from the analysis and web servers to read-only. The use of a

LabVIEW analysis server allows the easy implementation of a considerably large ready-to-use dataanalysis toolbox.




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Figure 20 - LabVIEW analysis server code

In an initial step, only the interfaces between the four members of the analysis server architecture,as well as the graphical display of the raw data were implemented. The LabVIEW analysis servermain code is shown in Figure 20. During the remaining time frame of the project, the various typesof analysis will be developed and implemented.

7.5 User interfaces

7.5.1 Administration software tools

For operation and maintenance (O&M) of the wireless sensor network, technical tools have beendeveloped that allow a technically adept administrator to configure the network with respect to

measurement tasks, networking parameters and general system settings.

S: 30 SM_TEMP id: 76 temp: 26.70S: 30 SM_TEMP id: 77 temp: 26.70S: 2c SHT15 5: 24.48 36.79S: 30 SHT15 22.33 26.28S: 2c SM_AIRFLOW id: 6: 0.00 m/s 0S: 31 SHT15 5: 22.36 24.35sn 98L: Set Cmd Node: 98S: 98 SM_VOLTAGE id: 34 Voltage: 1511.6 mV

S: 98 SM_VOLTAGE id: 56 Voltage: 1512.8 mVS: 98 SM_VOLTAGE id: 0 Voltage: 1512.8 mVS: 98 SM_VOLTAGE id: 12 Voltage: 1515.2 mVload emeterapp.bin.. ..loading .. ..

Figure 21: Example trace of administration tool

The administration is considered to be done via a web interface. Having in mind the complexity ofthe administration and allowing for the current development phase where progress is fast andsoftware still changes rapidly, the O&M is done with specialized tools.




Rev. 2010-07-07 32/52

7.5.2 Data readout software tools

Apart from the administrative tools that have been implemented to operate and maintain thewireless sensor network, the data readout software tools are designed to bring the customer aneasy-to-use and easy-to-understand graphical user interface for data readout and visualization.The data visualization and data retrieval have been decided to be implemented as a set of online-

tools.For each project, the customer gets a web page as a starting point. See Figure 22 for an example.Here, the user rights management is handled and links to the individual retrieval, visualization andanalysis tools are offered.

Figure 23 depicts exemplarily a data visualization tools for temperature and humidity values on amedieval church in southwest Germany. Temperature and humidity are shown at the exact placeswhere the sensors are installed in the church. By using this tool, a quick impression of themeasurement values can be obtained.

Figure 22 - Web-interface start page, with the offered retrieval and visualization tools circled in red




Rev. 2010-07-07 33/52

Figure 23 – Data visualization of temperature and humidity data of a church in Germany

7.5.3 Data export software tools As mentioned in chapter 7.5.2, data retrieval can be triggered by another online tool. This tooloffers the download of information stored in the data base. Parameters include the start and endtime, the desired sensors and measurement type.

Data can be obtained in Excel file format, Open Document file format or as comma separatedvalues.

It is also possible to access the database online via a query language. This way of extracting datafor post processing is favored, over file export, as data is more up-to-date then.

7.6 Planemos – Application builder

Planemos is the connection between the Galaxy SQL data base and the binary files of the Mirandaapplication software. After the compiler builds the Miranda software, Planemos loads it into thedatabase. From there it can be uploaded to the motes. Planemos also writes into the databasewhere configuration values are stored. This is needed to tell the user interface what possibleconfigurations are implemented in this Miranda application.




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8 Status of work

Table 6: Basic sensor node components

Progress

Processor board Available

Wireless transceiver unit Available

Power supply

• Dual power regulation

• Battery operation

• Solar cell operation

Available

Available

Available

Housing (casing) Available

Programming adapter (USB/JTAG) Available

Table 7: Sensor and signal conditioning

Progress

Air temperature & relative humidity Available

Material temperature Available

Local strain and deformation Available

Large distance and deformation Available (only wire transducer)

Acceleration sensors:

• Event detection

• Modal analysis

• Acoustic emission analysis

Available

Available (on request)

Almost finished

Inclination Available

Barometric pressure (on request)

Air velocity Available

Material moisture:

• potential mapping sensors

• resistive measurement

Under development

Under development

Solar irradiance (on request)

UV light (on request)

Ozone (on request)




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Table 8: Wireless Sensor Node Operating System and Application Software

Progress

Bootloader (Wboot) Available

Application Software Packages (Mirandas)

• Environmental temperature and humidity

• Body temperature (Pt100)

• Electrometer (potential measurements)

• Air flow sensing

• Strain measurements

• Impedance measurements

• Acoustic emission analysis

Available

Available

Available

Available

Almost finished

Almost finished

Under development

Web-Interface Almost finished

Online-Analysis (basic tools) Available

Analysis packages

• Time Series

• Dew point analysis

• further analysis

Available

Almost finished

(on request)

Forwarder (Uranus) (on request)

Base Station Software (Jupiter) Available

Radio to serial forwarder (Starcatcher) Available

On-site control (Callisto) (on request)

Database system (Galaxy) Available

Application builder (Planemos) (on request)




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9 Conclusions and outlook

Wireless sensor networks using intelligent data acquisition and processing could enormouslyreduce the costs for structural health monitoring to a small percentage of a conventional wiredmonitoring system. This will increase its application and thus more detailed information could beobtained from the structural behavior as well as the actual condition of the building structure. Thiswill enable engineers to use more precisely information for the structural analysis and repair aswell as lifetime prediction. For that reason, diverse wireless monitoring systems and promisingdistributed computing strategies were developed or are under investigation. Reliability, especiallywith respect to long-term monitoring, is still challenging and the high complexity in customizing andassembling monitoring systems is in contrast to easy handling and usability. For that purpose morepracticable modular concepts must be developed like it is described shortly in this report for thesensor node hardware. The detection of abnormal or critical events is one aspect, in whichhardware could play a decisive role. Solutions for that must be further investigated and developed.In combination with intelligent distributed computing strategies, structural health monitoring will

then be intrinsically efficient and will help reduce maintenance costs.




Rev. 2010-07-07 37/52

10 References

1 Meyer, J., R. Bischoff, G. Feltrin, M. Krüger, O. Saukh, S. Bachmaier. 2007. “Sustainable Bridges5.7 - Prototype Implementation of a Wireless Sensor Network”, Report of ´Sustainable Bridges´

project, http://www.sustainablebridges.net/main.php/SB5.7.pdf?fileitem=11681876.2 Kim, S., S. Pakzad, D. Culler, J. Demmel G. Fenves, S. Glaser, M. Turon. 2007. “Health Monitoring

of Civil Infrastructures Using Wireless Sensor Networks”, in Proc. of the 6th International Conf. onInformation Processing in Sensor Networks. ACM Press. 254-263.

3 Grosse, C.U., G. Pascale, S. Simon, M. Krüger, A. Troi, C. Colla, V. Rajcic, M. Lukomski. 2008.“Recent Advances in Smart Monitoring of Historic Structures”, Proc. 8th European Conference onResearch for Protection, Conservation and Enhancement of Cultural Heritage (CHRESP), Ljubljana,Slovenia, November 2008.

4 Lynch, J.P., K. Loh. 2006. “A summary review of wireless sensors and sensor networks for structuralhealth monitoring”, in Shock and Vibration Digest, 38:2, 91-128.

5 Gao, Y., B. Spencer. 2008. “Structural Health Monitoring Strategies for Smart Sensor Networks”,Newmark Structural Laboratory Report Series (NSEL Report Series ISSN 1940-9826) NewmarkStructural Engineering Laboratory, University of Illinois at Urbana-Champaign, 2008-05.

6 Ruiz-Sandoval, M. 2004. “Smart sensors for civil infrastructure systems”, Ph.D. Dissertation,University of Notre Dame, Indiana.

7 Wang, Y. 2007. “Wireless sensing and decentralized control for civil structures: theory andImplementation”, Ph.D. Thesis, Department of Civil and Environmental Engineering, StanfordUniversity, Stanford, CA.

8 Nagayama, T., B. Spencer. 2007. “Structural Health Monitoring Using Smart Sensors”, NewmarkStructural Laboratory Report Series (NSEL Report Series ISSN 1940-9826) Newmark StructuralEngineering Laboratory, University of Illinois at Urbana-Champaign, 2007-01.

9 Meyer, J., R. Bischoff, G. Feltrin, M. Krüger, P. Chatzichrisafis, C. Grosse. 2007. “SustainableBridges 5.8 - Data analysis and reduction methodologies for wireless sensor networks”, Report of´Sustainable Bridges´ project,http://www.sustainablebridges.net/main.php/SB5.8.pdf?fileitem=11681877.

10 Grosse, C.U., M. Krüger, P. Chatzichrisafis. 2007. “Acoustic emission techniques using wirelesssensor networks”, in International Conference ´Sustainable Bridges – Assessment for Future TrafficDemands and Longer Lives´, Wrocław, Poland, October 10-11, 2007, pp. 191-200.

11 Grosse, C.U., M. Krüger, S.D. Glaser, G.C. McLaskey. 2008. “Bridge monitoring using wirelesssensors and acoustic emission techniques”, in Proc. EM08, Inaugural International Conference ofthe Engineering Mechanics Institute, Department of Civil Engineering, University of Minnesota, USA.(Eds. R. Ballarini, B. Guzina, and S. Wojtkiewicz), paper m2303, Minneapolis 2008, on CD, 7 p.

12 Grosse, C.U., M. Krüger, S. Bachmaier. 2008. “Wireless monitoring of structures including acousticemission techniques”, in Proc. Int. Conf. on Conc. Repair, Rehabilitation and Retrofitting (ICCRRR),Cape Town, South Africa, Nov. 2008, Balkema Publ. Rotterdam (eds. M. Alexander et a.).

13 Krüger, M., C.U. Grosse, J. Kurz. 2006. “Acoustic emission analysis techniques for wireless sensornetworks used for structural health monitoring”, in IABMAS'06 - Third International Conference onBridge Maintenance, Safety and Management, Porto.

14 Krüger, M., C.U. Grosse, J. Kurz. 2007. “Sustainable Bridges 5.5 - Technical Report on WirelessSensor Networks Using MEMS for Acoustic Emission Analysis Including Other Monitoring Tasks”,Report of ´Sustainable Bridges´ project,http://www.sustainablebridges.net/main.php/SB5.5.pdf?fileitem=11681873.




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11 Appendix

11.1 Hardware Description

11.1.1 Processor and Communication Board

Pin definitions

Table 9: MCU Sensor board connector X1 and X2

Item / Parameter Pin MCU-X1 MCU-X2

General-purpose digital I/O pin/slave in/master out ofUSART0/SPI mode, I2C data − USART0/I2C mode

P1 I2C_SDA_SI I2C_SDA_SI

General-purpose digital I/O pin/slave out/master in ofUSART0/SPI mode

P2 SO SO

General-purpose digital I/O pin/external clock input−

USART0/UART or SPI mode, clock output – USART0/SPImode, I2C clock − USART0/I2C mode

P3 I2C_SCL_SCLK I2C_SCL_SCLK

General-purpose digital I/O pin/slave transmit enable –USART0/SPI mode

P4 GIO10 GIO10

General-purpose digital I/O pin/Timer_A, clock signal atINCLK

P5 GIO4

General-purpose digital I/O pin/Timer_A, compare: Out1output/Comparator_A input

P5 GIO5

General-purpose digital I/O pin/ACLK output P6 GIO3

General-purpose digital I/O pin/conversion clock – 12-bit ADC/DMA channel 0 external trigger

P6 GIO8

General-purpose digital I/O pin/Timer_A, compare: Out2output

P7 GIO2

General-purpose digital I/O pin/transmit data out –USART0/UART mode

P7 GIO11


P8 GIO1

General-purpose digital I/O pin/receive data in –USART0/UART mode

P8 GIO12


P9 GIO0

General-purpose digital I/O pin/main system clock MCLKoutput P9 GIO13

Digital supply voltage, positive terminal. Supplies all digitalparts.

P10 DVCC DVCC

Reset input, nonmaskable interrupt input port, or bootstraploader start (in Flash devices). Connected via 1nF to GNDand pull up resistor 47k to DVCC

P11 \RESET \RESET

Digital supply voltage, negative terminal. Supplies all digitalparts.

P12 GND GND

General-purpose digital I/O pin/analog input a7 – 12-bit ADC/DAC12.1 output/SVS input

P13 ADC7

General-purpose digital I/O pin/analog input a2 – 12-bit ADC P13 ADC2

General-purpose digital I/O pin/analog input a6 – 12-bit P14 ADC6




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ADC/DAC12.0 output


General-purpose digital I/O pin/analog input a3 – 12-bit ADC P15 ADC3 ADC0

Output of positive terminal of the reference voltage in the ADC12 / or external reference voltage via Ref-IC and solder

bridge

P16 VREF+OUT VREF+OUT

Negative terminal for the reference voltage for both sources,the internal reference voltage, or an external appliedreference voltage

P17 VEREF-_IN VEREF-_IN

Analog supply voltage, negative terminal. Supplies only theanalog portion of ADC12 and DAC12.

P18 AGND AGND

Table 10: MCU Sensor board connector X4 and X5


Digital supply voltage, negative terminal. Supplies all

digital parts.

P1 GND GND

Digital supply voltage, negative terminal. Supplies alldigital parts.

P2 GND GND

Table 11: MCU supply board connector X3

Item / Parameter Pin MCU-X3

Main supply voltage input, positive terminal. (+3.6V max) P1 VCC

Main supply voltage input, negative terminal. This is the main ground. P2 GND

Main supply voltage input, negative terminal. This is the main ground. P3 GND

General-purpose digital I/O pin/input for external resistor defining the DCOnominal frequency

P4 GIO7

Analog ground. Supplies all analog parts. Can be connected via resistor 0R0 toGND

P5 AGND

General-purpose digital I/O pin/Timer_A, capture: CCI1A input, compare: Out1output

P6 P_DVCC

General-purpose digital I/O pin/Timer_A, compare: Out0 output P7 GIO9

General-purpose digital I/O pin/Timer_A, compare: Out2 output/Comparator_Ainput

P8 GIO6

General-purpose digital I/O pin/switch all PWM digital output ports to highimpedance − Timer_B TB0 to TB6/SVS comparator output

P9 GIO16

General-purpose digital I/O pin/auxiliary clock ACLK output P10 GIO15General-purpose digital I/O pin/submain system clock SMCLK output P11 GIO14



Test clock. TCK is the clock input port for device programming test andbootstrap loader start

P14 TCK

Test mode select. TMS is used as an input port for device programming andtest.

P15 TMS

Test data input or test clock input. The device protection fuse is connected toTDI/TCLK.

P16 TDI

Test data output port. TDO/TDI data output or programming data input terminal P17 TDO

Reset input, nonmaskable interrupt input port, or bootstrap loader start (in Flashdevices). Connected via 1nF to GND and pull up resistor 47k to DVCC

P18 \RESET




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General-purpose digital I/O pin/receive data in – USART1/UART mode P19 UART1RX

General-purpose digital I/O pin/transmit data out – USART1/UART mode P20 UART1TX

I2C addressing

The address of the silicon serial number chip DS28CM00 (IC8) is fixed at 0x50.

11.1.2 Power module

Pin definitions

Table 12: Power supply board connector X5 connected to MCU-X3


Not used, grounded via resistor 47k. Set MCU’s port to input or to output low ifnot other ways used

P1 UART1TX

Not used, grounded via resistor 47k. Set MCU’s port to input or to output low ifnot other ways used

P2 UART1RX

Resetting the MCU, connected via 10nF to ground and to X6 for reset button P3 \RESET

Open P4 TDO

Open P5 TDI

Open P6 TMS

Open P7 TCK

Measuring the current consumption at the ILIM-pin of IC5. Set MCU’s port toanalog input. The max. value is about 0.5V if VCC is shorted

P8 ADC5

Measuring the battery voltage or the main supply voltage VCC, this is selectablevia 0R0 resistor. The voltage is divided by 2. Set MCU’s port to analog inputand MCU’s reference to 2.5V for converting

P9 ADC4

Digital output via resistor 330R to X6, anode LED (green) on external keyboard.H = LED on

P10 GIO14

Digital output via resistor 330R to X6, anode LED (yellow) on external keyboard.H = LED on

P11 GIO15

Digital output via resistor 330R to X6, anode LED (red) on external keyboard. H= LED on

P12 GIO16

Connected to X6 via 1µF to GND and pull up resistor 47k to VCC. Used forfunction key on external keyboard. Set MCU’s port to input. L = button pressed

P13 GIO6

Connected to X6 via 1µF to GND and pull up resistor 47k to VCC. Used for

function key on external keyboard. Set MCU’s port to input. L = button pressed

P14 GIO9

Connected via resistor 47k to GND. Set MCU’s port to input. L = no connectionwith PC via USB (signal is used on programmer board)

P15 P_DVCC

Analog ground. Supplies all analog parts. This line is connected via resistor 0R0to GND

P16 AGND

Power state signal, connected via pull up resistor 100k to VCC. Important: SetMCU’s port to input! This signal is internal used for the power management. H =battery power, L = solar power

P17 GIO7

Main supply voltage output, negative terminal. This is the main ground. P18 GND

Main supply voltage output, negative terminal. This is the main ground. P19 GND

Main supply voltage output, positive terminal. (+3.6V max) P20 VCC




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Table 13: Connector X6 for plastic foil keyboard

Item / Parameter Pin X6

Output to anode low current LED P1 LED_RED

Output to anode low current LED P2 LED_GREEN

Output to anode low current LED P3 LED_YELLOWDigital ground. Supplies all digital parts. P4 GND

Function button, switch to GND P5 USERINT_EXT

Function button, switch to GND P6 LED_on_off

Reset button, switch to GND P7 \RESET

Open P8 VCC_OUT

Table 14: Connector X7 for extern power (for example a small solar module)


Supply voltage input, negative terminal. This is the main ground. P1 GNDSupply voltage input, positive terminal. (optimal +5.2V to +6V) P2 V-EXT1

Table 15: Connector X8 for extern power (for example a small solar module)


Supply voltage input, negative terminal. This is the main ground. P1 GND

Supply voltage input, positive terminal. (optimal +5.2V to +6V) P2 V-EXT2

11.1.3 Multi-sensor board

Pin definitions

Table 16: Multi-sensor board connector X1 connected to MCU-X1 or to MCU-X2


I2C serial data, SHT15 serial data P1 I2C_SDA_SI I2C_SDA_SI

Open P2 SO SO

I2C serial clock, SHT15 serial clock P3 I2C_SCL_SCLK I2C_SCL_SCLK

Programmable I/O1 of ZMD31050 (IC101), removeresistor R113 if not used and set MCU’s port to output

low if not other ways used

P4 GIO10 GIO10

Power on Ch1 and Ch2 (L = power on, H = power off) P5 GIO4 GIO5

Event detection (INT, output of SMB380) P6 GIO3 GIO8

Programmable I/O2 of ZMD31050 (IC101), removeresistor R114 if not used and set MCU’s port to outputlow if not other ways used

P7 GIO2 GIO11


P8 GIO1 GIO12

Programmable I/O2 of ZMD31050 (IC102), removeresistor R214 if not used and set MCU’s port to output

low if not other ways used

P9 GIO0 GIO13

Supply voltage. Supplies all digital and analog parts. P10 DVCC DVCC




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Open P11 \RESET \RESET

Digital ground. Supplies all digital parts. P12 GND GND

Open, set MCU’s port to output low if not other waysused

P13 ADC7 ADC2

Analog output of ZMD31050 (IC101) P14 ADC6 ADC1


Open P16 VREF+OUT VREF+OUT

Not used, connected to AGND P17 VEREF-_IN VEREF-_IN

Analog ground. Supplies all analog parts P18 AGND AGND

Table 17: Multi-sensor board connector X4, connected to MCU-X4 or to MCU-X5


Open P1 GND GND

Open P2 GND GND

Socket definition

Table 18: Sensor connector BU101 and BU201, female sockets 4-pin

Item / Parameter Pin BU101 BU201

Normally negative supply to the sensor bridge(configurable)

P1 Measuringcircuit IC101

Measuringcircuit IC102

Normally negative signal from sensor bridge(configurable)



Normally positive signal from sensor bridge (configurable) P4 Measuring

circuit IC101

Measuring

circuit IC102Normally positive supply to the sensor bridge(configurable)



Figure 24. Female socket 4-pin, front side.

I2C addressing

Each ZMD31050 chip has a base address 0x78 that is always valid, but it is possible to program asecond address into the EE-Prom of the ZMD31050.

Table 19: I2C addresses

Item / Parameter Position IC101 IC201

Module connected with MCU’s connector X1 Slot 1 0x74 0x75




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Module connected with MCU’s connector X2 Slot 2 0x76 0x77

11.1.4 Tilt and inclination sensor

Pin definitions

Table 20: Inclination and tilt sensor board connector X1 connected to MCU-X1 or to MCU-X2


I2C serial data, SPI serial data (master out, slave in),

SHT15 serial dataP1 I2C_SDA_SI I2C_SDA_SI

SPI serial data (master in, slave out) P2 SO SO

I2C serial clock, SPI serial clock, SHT15 serial clock P3 I2C_SCL_SCLK I2C_SCL_SCLK

Chip select, digital input of SCA830 (IC5), active lowenables serial data communication of IC5. This line isconnected via connector BU101 to the line CSB2 of

the external sensor board. If the power of the externalsensor board is switched off, hold this line low! A highwill provide a current flow into IC5.

P4 GIO10 GIO10

Active low enables the SPI-bus at the connectorBU201 and power on the external sensor board

P5 GIO4 GIO5

Event detection (INT, output of SMB380) P6 GIO3 GIO8

Chip select, digital input of SCA830 (IC4), active lowenables serial data communication of IC4. This line isconnected via connector BU201 to the line CSB1 ofthe external sensor board. If the power of the externalsensor board is switched off, hold this line low! A highwill provide a current flow into IC4.

P7 GIO2 GIO11


P8 GIO1 GIO12


P9 GIO0 GIO13





P13 ADC7 ADC2

Open, set MCU’s port to output low if not other ways

used

P14 ADC6 ADC1


P15 ADC3 ADC0




Table 21: Inclination and tilt sensor board connector X4, connected to MCU-X4 or to MCU-X5


Open P1 GND GNDOpen P2 GND GND




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Table 22: Sensor connector BU101, female socket 3-pin

Item / Parameter Pin Extern sensor board

Ground, supplies the external sensor board P1 GND

Chip select, digital input of SCA830 (IC5), active lowenables serial data communication of IC5 on the externalsensor board

P3 CSB2

Supply voltage, switched. Supplies the external sensorboard

P4 VDD

Socket definition


Item / Parameter Pin Extern sensor board

Chip select, digital input of SCA830 (IC4), active lowenables serial data communication of IC4 on the externalsensor board

P1 CSB1

SPI serial data, switched (master out, slave in) P2 MOSI

SPI serial data, switched (master in, slave out) P4 MISO

SPI serial clock, switched P3 SCK

Figure 25. Female sockets 4-pin and 3-pin, front side.

11.1.5 Air sensor

Pin definitions

Table 24: Air velocity sensor board connector X1 connected to MCU-X1 or to MCU-X2Item / Parameter Pin MCU-X1 MCU-X2

I2C serial data, SHT15 serial data P1 I2C_SDA_SI I2C_SDA_SI

Open P2 SO SO

I2C serial clock, SHT15 serial clock P3 I2C_SCL_SCLK I2C_SCL_SCLK


P4 GIO10 GIO10

Power on sensor bridge (ZMD31050) and air velocitysensor (L = power on, H = power off)

P5 GIO4 GIO5

Event detection (INT, output of SMB380) P6 GIO3 GIO8Programmable I/O2 of ZMD31050 (IC101), remove P7 GIO2 GIO11




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resistor R114 if not used and set MCU’s port to outputlow if not other ways used


P8 GIO1 GIO12

Open, set MCU’s port to output low if not other ways

used

P9 GIO0 GIO13





P13 ADC7 ADC2


Analog output of air velocity sensor, set the internalMCU’s reference to 2.5V for converting

P15 ADC3 ADC0


Not used, connected to AGND P17 VEREF-_IN VEREF-_IN Analog ground. Supplies all analog parts P18 AGND AGND

Table 25: Air velocity sensor board connector X4, connected to MCU-X4 or to MCU-X5


Open P1 GND GND

Open P2 GND GND

Socket definition


Item / Parameter Pin BU101

Normally negative supply to the sensor bridge(configurable)

P1 Measuring circuit IC101

Normally negative signal from sensor bridge(configurable)


Normally positive signal from sensor bridge (configurable) P4 Measuring circuit IC101

Normally positive supply to the sensor bridge(configurable)



Item / Parameter Pin Air velocity sensor

Ground. Supplies the air velocity sensor P1 GND

Ground. Supplies the air velocity sensor P2 GND

Analog output of the air velocity sensor P4 Vout

Supply voltage, switched. Supplies the air velocity sensor P3 VCC




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I2C addressing

Each ZMD31050 chip has a base address 0x78 that is always valid, but it is possible to program asecond address into the EE-Prom of the ZMD31050.

11.1.6 Impedance Sensor

Pin definitions

Table 28: Impedance converter board connector X1 connected to MCU-X1 or to MCU-X2


I2C serial data, SHT15 serial data (selectable) P1 I2C_SDA_SI I2C_SDA_SI

Open P2 SO SO

I2C serial clock, SHT15 serial clock (selectable) P3 I2C_SCL_SCLK I2C_SCL_SCLK

Select measuring frequency, input DIVA (bit0) ofoscillator-IC LTC6930

P4 GIO10 GIO10

Power on oscillator and measuring circuits (L = power

on, H = power off)

P5 GIO4 GIO5

SHT15 serial data (selectable) P6 GIO3 GIO8

Select measuring frequency, input DIVC (bit2) ofoscillator-IC LTC6930

P7 GIO2 GIO11

SHT15 serial clock (selectable) P8 GIO1 GIO12

Select measuring frequency, input DIVB (bit1) ofoscillator-IC LTC6930

P9 GIO0 GIO13





P13 ADC7 ADC2


P14 ADC6 ADC1


P15 ADC3 ADC0




Table 29: Impedance converter board connector X4, connected to MCU-X4 or to MCU-X5





Rev. 2010-07-07 47/52

Open P1 GND GND

Open P2 GND GND

Socket definition

Table 30: Connector BU101 to measuring object, female socket 4-pin


Analog ground P1

Measuring frequency output to measuring object P2

Measuring signal input from measuring object P4

Analog ground P3

Table 31: Connector BU201, female socket 4-pin


Open P1

Open P2

Open P4

Open P3


I2C addressing

The AD5933 chip has a base address 0x0D.

11.1.7 Electrometer

Pin definitions

Table 32: Electrometer board connector X1 connected to MCU-X1


Open P1 I2C_SDA_SI

Open P2 SO

Open P3 I2C_SCL_SCLK

Open, set MCU’s port to output low if not other ways used P4 GIO10







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Open P10 DVCC

Open P11 \RESET

Open P12 GND

Open, set MCU’s port to output low if not other ways used P13 ADC7



Open P16 VREF+OUT

Not used, connected to AGND at X2 P17 VEREF-_IN

Open P18 AGND

Table 33: Electrometer board connector X2 connected to MCU-X2


I2C serial data, SHT15 serial data (selectable) P1 I2C_SDA_SI

Open P2 SO

I2C serial clock, SHT15 serial clock (selectable) P3 I2C_SCL_SCLK


Power on measuring circuits and enables the SPI-bus at the connector BU1(H = power on, L = power off)

P5 GIO5

SHT15 serial data (selectable) P6 GIO8


SHT15 serial clock (selectable) P8 GIO12


Supply voltage. Supplies all digital and analog parts. P10 DVCC

Open P11 \RESET

Digital ground. Supplies all digital parts. P12 GND



Analog output of the measuring amplifier, set the internal MCU’s referenceto 2.5V for converting

P15 ADC0

MCU´s internal reference voltage, used for the measuring amplifier. Activatethis MCU’s output.

P16 VREF+OUT

Not used, connected to AGND P17 VEREF-_IN

Analog ground. Supplies all analog parts P18 AGND

Table 34: Electrometer board connector X5, connected to MCU-X5


Open P1 GND

Open P2 GND




Rev. 2010-07-07 49/52

Socket definition

Table 35: Connector BU1 to scanner board, female socket 4-pin

Item / Parameter Pin Multiplexer

Positive supply +5V for the scanner board P1 VCC

I2

C serial clock P2 SCLI2C serial data P4 SDA

GND P3 GND

Table 36: Connector BU2, female socket 4-pin


Open P1

Open P2

Open P4

Open P3

Table 37: Connector BU101of scanner board, female socket 4-pin


VCC input, positive supply +5V P1

SDA, I2C serial data P2

SCL, I2C serial clock P4

GND P3


I2C addressingThe multiplexer has an I2C address of 0x20, but it is possible to change the address with hardware.

11.2 Database Description

Table 38: Table structure for table Cluster

Field Type Description Example

clusterid int

project int




Rev. 2010-07-07 50/52

name varchar(32)

description varchar(400)

sensors varchar(4096) Comma separated list of sensor IDs 1,2,3

Clusters are used to define a group of sensors.

Table 39: Table structure for table Command


cmdid int index

mote int Mote to process command

cmd varchar(40) Cmd text R 1000 2

timesend timestamp CURRENT_TIMESTAMP

timeanswer timestamp Time when answer is incominganswer varchar(40) Ok 1234

Command transfer table. The user interface writes commands. The Gates are looking forcommands for their motes.

Table 40: Table structure for table Gates


gateid int

project intname varchar(32)


Each gate has its entry

Table 41: Table structure for table Motes


moteid int 0x27

gate int 0


x int X GPS Coordinate

y int Y GPS Coordinate

z int Z GPS Coordinate

Miranda int flashed Miranda ID 2

Wboot int flashed Wboot ID 1




Rev. 2010-07-07 51/52

Each mote has its entry.

Table 42: Table structure for table Project


projectid int

name varchar(32)


date timestamp CURRENT_TIMESTAMP

Table 43: Table structure for table SHT15data


dataid int(10) 125445

sensor int(10) 1

time timestamp CURRENT_TIMESTAMP 1/12/2009 11:40:34

temp float 1.56

hum float 40.56

Data Table for all SHT15 data.

Table 44: Table structure for table SensorType


typeid int 1

name varchar(32) SHT15

description varchar(400) temperature and humidity sensor

tablename varchar(20) SHT15data

Table 45: Table structure for table Sensors


sensorid int 1

mote int 0x27

type int 1

description varchar(40)With drypack sealedwaterproof

position varchar(32) Church floor south west

Table 46: Table structure for table Software





softwareid int 1 2

name varchar(32) Wboot Miranda SHT15app

svn int 125 120

description varchar(400) Wboot version 125

SHT15app version

Johanniskirche

crc int 0x1234 0x5678

length int 0x978 0x1234

data var(32000) //binary //binary

Table 47: Table structure for table SoftwareParameter


pramid int 1

software int 2

name varchar(32) sleep time

description varchar(400) measurement interval

address int 0x1080

length int 2

type int 1

upperlimit int 1200

lowerlimit int 1

Documents

WP3-P09-100628- D3 2 Smart Wireless Sensor Network Platform