SMART RADAR SENSOR FOR STRUCTURAL HEALTH MONITORING

By

SHANYUE GUAN

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL

OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2017

© 2017 Shanyue Guan

To my family

4

ACKNOWLEDGMENTS

First, I would like to give all my thanks to my Ph.D. advisor Dr. Jennifer Rice who hired

me for the Ph.D. program and supported me for the last six years study at University of Florida. I

felt very luck working with her. Without her support, I could not be successful on my research. I

also would like to give my thanks to Dr. Changzhi Li’s group from Texas Tech University. My

Ph.D. research is a collaborative project between Texas Tech and University of Florida. Dr. Li’s

group has been very supportive for the last six years. Without their contribution, we could not

make the great achievements. In his group, I want to say thanks to Dr. Changzhan Gu, Dr.

Guochao Wang and Ms. Yiran Li who were Ph.D. students working with me in different phases.

They were very kind and helpful with my research. Also I would like to give thanks to all my

Ph.D. committee members: Dr. Kurtis Gurley and Dr. Gary Consolazio from our Civil

Engineering Group and Dr. Jenshan Lin from Electrical and Computer Engineering Group. It has

been a great honor to have them served as my committee. They have been strongly supportive

for my Ph.D. research and my academia job hunting. Also, I want to thank the former Ph.D.

student from Dr. Lin’s group, Dr. Changyu Wei who helped me debug my sensor board and

borrowed equipment to me. I also want to give many thanks to all my teammates: Dr. Justin

Davis, Dr. ABM Abdullah, Mr. Justin Martinez, Mr. Cody Jonson, Mr. Douglas Gelineau, Miss

Arthriya, Sukuwan, Miss Juliana Rochester, Mr. Andy Tomiczek, Mr. Neandro DeMello and Mr.

Steven Gonzalez who helped me a lot with my research. It has been a great pleasure working

with all of them in the same team. I also want to thank park rangers, Kim and Leira from the

Sweetwater Park who helped me with my vehicle load tests.

In addition, I also want to give thanks to some of my friends I made when I studied at

University of Florida. Mr. Kuangshi Li who was my first roommate when I came to Gainesville.

Dr. Zinan Zhao who was my second roommate who taught me how to drive a car. Also my

5

current roommate Ziqian Han who is a nice roommate. I also want to thank to some my friends

like Dr. Xinlai Peng and Dr. Luping Yang, Ms. Chengcheng Tao who helped me all the time

during my life at University of Florida. I also want to thank my friends Mr. Ruoying Xu, Mr.

Zhuo Yang, and Mr. Zhiyang Yang who have been great friends to share ideas.

Last I want to thank my family. They have been very supportive for my whole life. I

especially want to say thanks to my grandma who passed away during the second year of my

Ph.D. study and my grandpa in-law who passed away last year. They have been always very kind

to me since I was a kid. It is regret that they could not enjoy the moment of my Ph.D. graduation.

But I believe this dissertation is the best gift for them.

6

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...............................................................................................................4

LIST OF TABLES .........................................................................................................................10

LIST OF FIGURES .......................................................................................................................11

ABSTRACT ...................................................................................................................................16

CHAPTER

1 INTRODUCTION ..................................................................................................................18

1.1 Motivation .........................................................................................................................18

1.2 Objectives .........................................................................................................................20

1.3 Scope and Organization ....................................................................................................21

2 LITERATURE REVIEW AND BACKGROUND ................................................................22

2.1 Structural Health Monitoring ............................................................................................22

2.2 Existing Displacement Sensing Technologies ..................................................................25

2.2.1 Linear Variable Differential Transducer ................................................................26

2.2.2 String Potentiometer ...............................................................................................27

2.2.3 Accelerometer .........................................................................................................28

2.2.4 Strain Gauge ...........................................................................................................29

2.2.5 Ultrasonic Sensor ....................................................................................................30

2.2.6 Laser System ..........................................................................................................31

2.2.7 Vision Approaches .................................................................................................32

2.2.8 Global Positioning System .....................................................................................33

2.3 Radar Techniques .............................................................................................................35

2.3.1 Ground Penetrating Radar ......................................................................................36

2.3.2 Remote Sensing Radar ...........................................................................................37

2.3.3 Distance Measurement Radar .................................................................................38

2.3.3.1 Time-of-Flight Laser Radar .........................................................................38

2.3.3.2 Pulse Radar ...................................................................................................39

2.3.3.3 Frequency Modulated Continuous Wave Radar ..........................................40

2.3.3.4 Step Frequency Interferometric Radar .........................................................41

2.3.3.5 Continuous Wave Radar ...............................................................................42

2.4 Global Response Monitoring ............................................................................................47

2.4.1 Vibration Based Monitoring ...................................................................................47

2.4.2 Static Deflection Monitoring ..................................................................................49

2.5 Full-Scale Global Response Monitoring Applications .....................................................49

2.5.1 Tamar Bridge Long-Term Monitoring ...................................................................50

2.5.2 Khalifa Tower Real-Time Monitoring ...................................................................51

2.5.3 Manhattan Bridge Monitoring ................................................................................52

7

2.6 Signal Transmission System .............................................................................................53

2.6.1 Wired Signal Transmission System ........................................................................54

2.6.2 Wireless Signal Transmission System ....................................................................55

2.6.2.1 Wireless Protocols ........................................................................................55

2.6.2.2 Wireless Smart Sensor .................................................................................57

2.6.2.3 WiseMote Platform ......................................................................................60

2.7 Summary ...........................................................................................................................61

3 WISE-RADAR SENSOR HARDWARE DEVELOPMENT ................................................63

3.1 Continuous Wave Radar System ......................................................................................64

3.1.1 Antenna ...................................................................................................................66

3.1.2 RF Board ................................................................................................................67

3.1.3 Baseband Board ......................................................................................................68

3.1.4 Wireless Communication Device ...........................................................................69

3.1.5 Power System .........................................................................................................69

3.2 AC Coupled Radar ............................................................................................................70

3.2.1 AC Coupling Design ..............................................................................................71

3.2.2 Performance Characterization ................................................................................71

3.3 DC Coupled Radar ............................................................................................................79

3.3.1 RF Coarse-Tuning Architecture .............................................................................80

3.3.2 Baseband Fine-Tuning Architecture .......................................................................81

3.4 Active Transponder ..........................................................................................................82

3.5 WiseMote Platform ...........................................................................................................84

3.5.1 WiseMote Node ......................................................................................................85

3.5.2 WiseMote Base Station ..........................................................................................86

3.6 Wise-Radar System ..........................................................................................................87

3.6.1 Wise-Radar Sensor Hardware Upgrades ................................................................87

3.6.1.1 Existing Hardware Improvement .................................................................87

3.6.1.2 New Hardware Design .................................................................................88

3.6.2 Base Station Hardware Upgrades ...........................................................................93

3.6.3 Enclosure Design ....................................................................................................94

3.7 Summary ...........................................................................................................................96

4 WISE-RADAR SENSOR SOFTWARE DEVELOPMENT ..................................................97

4.1 Software Framework ........................................................................................................97

4.1.1 Software on PC (Graphic User Interface) ..............................................................98

4.1.2 Software on Base Station ......................................................................................100

4.1.3 Software on Wise-Radar Sensor ...........................................................................101

4.2 Routine Operations .........................................................................................................102

4.2.1 Sensing Mode .......................................................................................................102

4.2.2 Sleep Mode ...........................................................................................................104

4.2.3 Wireless Communication .....................................................................................105

4.3 Signal Processing Algorithms .........................................................................................108

4.3.1 Automated DC Tuning Process ............................................................................108

4.3.2 Automatic Displacement Processing Algorithm ..................................................110

8

4.3.2.1 Initial Signal Processing Step .....................................................................111

4.3.2.2 DC Offset Calibration ................................................................................113

4.3.2.3 Phase Demodulation ...................................................................................124

4.4 Auxiliary Functions of Embedded Programs .................................................................126

4.5 Summary .........................................................................................................................126

5 WISE-RADAR PERFORMANCE CHARACTERIZATION .............................................127

5.1 Routine Operations Performance ....................................................................................127

5.1.1 Operating Time .....................................................................................................127

5.1.1.1 Experimental Configurations .....................................................................128

5.1.1.2 Number of Sensors .....................................................................................131

5.1.2 Power Management Performance .........................................................................132

5.1.2.1 Power consumption ....................................................................................132

5.1.2.2 Power supplying component ......................................................................134

5.1.2.3 Battery Life Prediction ...............................................................................136

5.1.3 Wireless Transmission Performance ....................................................................137

5.2 Wise-Radar Measurement Performance .........................................................................139

5.2.1 Low Frequency Vibration Experiments ...............................................................140

5.2.1.1 Radar Signal Comparison ...........................................................................140

5.2.1.2 Multipath Effects ........................................................................................141

5.2.1.3 Radar Signal Comparison with Strong Reflector .......................................144

5.2.1.4 Dynamic Displacement Measurement Accuracy .......................................147

5.2.2 Static Deflection Tests ..........................................................................................151

5.2.3 Moving Load Tests ...............................................................................................154

5.2.4 Oblique Angle Tests .............................................................................................155

5.3 Summary .........................................................................................................................158

6 WISE-RADAR FULL-SCALE STRUCTURE EXPERIMENTS VALIDATION .............159

6.1 O’ Leno State Park Bridge Experiment ..........................................................................159

6.1.1 O’Leno State Park Bridge ....................................................................................159

6.1.2 Instrumentation .....................................................................................................160

6.1.3 Description of Load Conditions ...........................................................................161

6.1.4 Measurement Results ............................................................................................162

6.2 Sweetwater Park Bridge Experiment ..............................................................................164

6.2.1 Sweetwater Park Bridge .......................................................................................165

6.2.2 Instrumentation .....................................................................................................166

6.2.3 Description of Load Conditions ...........................................................................167

6.2.3.1 Dynamic Displacement Experiment ...........................................................167

6.2.3.2 Vehicle Load Experiment ...........................................................................168

6.2.4 Measurement Results ............................................................................................168

6.2.4.1 Dynamic Load Experiment ........................................................................168

6.2.4.2 Vehicle Load Experiment ...........................................................................173

6.3 Summary .........................................................................................................................175

7 CONCLUSIONS AND RECOMMENDATIONS ...............................................................176

9

7.1 Conclusions .....................................................................................................................176

7.2 Recommendations ...........................................................................................................179

7.2.1 Hardware Improvements ......................................................................................179

7.2.2 Software Improvements ........................................................................................180

7.2.3 Power Consumption Improvements .....................................................................181

7.2.4 Full-Scale Structure Testing Improvements .........................................................181

7.2.5 Potential Applications ..........................................................................................181

LIST OF REFERENCES .............................................................................................................183

BIOGRAPHICAL SKETCH .......................................................................................................197

10

LIST OF TABLES

Table page

2-1 Existing displacement sensing technologies comparison. .................................................34

4-1 SSE values. ......................................................................................................................120

4-2 Fixed-fixed boundary condition. ......................................................................................123

4-3 Pinned-pinned boundary condition. .................................................................................124

5-1 Power consumption of one duty cycle. ............................................................................137

5-2 RMS error vs. target distance. ..........................................................................................153

5-3 RMS error vs. deflection amplitude. ................................................................................153

5-4 RMS error vs different reflection surfaces. ......................................................................153

11

LIST OF FIGURES

Figure page

2-1 Schematics of LVDT. ........................................................................................................26

2-2 Schematics of piezoelectric based accelerometer. .............................................................29

2-3 Diagram of passive backscattering configuration. .............................................................43

2-4 DC offset calibration process. ............................................................................................46

2-5 WiseMote sensor node. ......................................................................................................61

3-1 Block diagram of CW radar. ..............................................................................................65

3-2 XBee base station for CW radar. .......................................................................................66

3-3 Patch antenna. ....................................................................................................................67

3-4 Block diagram of CW radar. ..............................................................................................68

3-5 The assembled AC coupled radar. .....................................................................................70

3-6 Dynamic displacement experimental setup. ......................................................................72

3-7 The displacement results at different distances in both time and frequency domain. .......73

3-8 RMS error between LVDT and radar sensors vs. target distance. .....................................74

3-9 Truss bridge model test configuration (left) and picture of a radar sensor on node 8. ......74

3-10 Representative response data from truss bridge impact tests. ............................................75

3-11 Power spectral densities of bridge response measured by accelerometers (integrated

twice) and radar sensors at nodes 6 and 8 and a linear displacement sensor at node 6. ....76

3-12 Diagram of the observed frequency responses of the sensors used to capture lateral

bridge vibration. .................................................................................................................76

3-13 Radar sensor testing on seven story building model. .........................................................77

3-14 Displacement results from accelerometer (double integrated) and CW radar. ..................78

3-15 Frequency domain of displacement results from CW radar. .............................................78

3-16 Fully assembled DC coupled radar. ...................................................................................79

3-17 DC tuning architecture including RF coarse-tuning and baseband fine-tuning. ................80

12

3-18 Diagram of active transponder strategy. ............................................................................83

3-19 Active transponder node. ...................................................................................................83

3-20 Block diagram of transponder node. ..................................................................................84

3-21 WiseMote base station. ......................................................................................................86

3-22 Wise-Radar interface board. ..............................................................................................89

3-23 Wise-Radar extension board. .............................................................................................91

3-24 Block diagram of Wise-Radar. ..........................................................................................93

3-25 Base station for Wise-Radar system. .................................................................................94

4-1 Software framework of Wise-Radar. .................................................................................98

4-2 GUI for WiseMote platform. .............................................................................................99

4-3 GUI for Wise-Radar system. ..............................................................................................99

4-4 Flowchart of sensing operation (operations happen on the PC are labeled as green;

operation happen on the base station are labeled as blue; operations happen on the

Wise-Radar sensor are labeled as purple). .......................................................................103

4-5 Flowchart of controlling the sleep mode. ........................................................................105

4-6 XCTU user interface. .......................................................................................................106

4-7 Centralized data collection network of Wise-Radar. .......................................................108

4-8 Automated DC tuning algorithm. ....................................................................................110

4-9 Flowchart of the signal processing steps. ........................................................................111

4-10 Flowchart of the initial signal processing. .......................................................................112

4-11 Before and after the baseband signals are lined up. .........................................................113

4-12 Convergence analysis of the LM method. .......................................................................117

4-13 DC offset calibration selection strategy. ..........................................................................118

4-14 Experimental setup of SSE study. ....................................................................................119

4-15 Experimental setup...........................................................................................................121

13

4-16 Convergence results. (Case 1 convergence rate not checked; Case 2 convergence rate

checked and improved).. ..................................................................................................122

4-17 Measurement results from radar and LVDT for fixed-fixed end case. ............................123

4-18 Measurement results from radar and LVDT for pinned-pinned end case. ......................124

5-1 Operating time of benchmark case. .................................................................................128

5-2 Operating time comparison with different channel numbers. ..........................................129

5-3 Operating time with different sampling time. ..................................................................130

5-4 Operating time with different retransmissions. ................................................................131

5-5 Operating time with different number of sensors in the network. ...................................132

5-6 Power consumption without the power control kit. .........................................................134

5-7 Power consumption with the power control kit. ..............................................................134

5-8 Voltage supply using AAA batteries. ..............................................................................135

5-9 Voltage supply with D-cell batteries. ...............................................................................136

5-10 Experimental setup of wireless transmission range experiment. .....................................138

5-11 Success rate of the wireless transmission over distance between the two sensors. .........139

5-13 Comparison of the radar-detected baseband signal power in passive backscattering

(PB) and using the active transponder (AT) for a target distance of 298 cm. .................141

5-14 Radar’s signal power pattern related to distance between radar and transponder. ..........144

5-15 Experimental setup of radar’s signal power amplification with transponder strategy

and whiteboard. ................................................................................................................145

5-16 Radar’s signal power pattern related to distance between transponder and

whiteboard........................................................................................................................146

5-17 Experimental setup of dynamic displacement experiment. .............................................148

5-18 A representative measurement results of 1.25 Hz sinusoidal motion by radar and

LVDT. ..............................................................................................................................148

5-19 Measurement errors between radar and LVDT vs. different amplitudes and

frequencies. ......................................................................................................................149

5-20 Experimental setup of radar's measurement performance vs. target distance. ................149

14

5-21 A representative measurement results of 1.0 Hz sinusoidal motion by radar and

LVDT with 1 m distance between the radar and target. ..................................................150

5-22 Absolute errors between radar and VLDT vs. target distance, with one standard

deviation indicated. ..........................................................................................................150

5-23 Experimental setup of static deflection measurements using radar and LVDT. ..............152

5-24 Deflection measured results from radar and LVDT. .......................................................152

5-25 Measured results of two steps deflections. ......................................................................154

5-26 Moving load test. .............................................................................................................155

5-27 Experimental setup of the oblique angle test with the transponder strategy. ...................157

5-28 Vertical displacement measurement results from the sensors. ........................................157

6-1 O’Leno State Park bridge.................................................................................................160

6-2 Experimental setup of the full-scale bridge test at O’ Leno State Park. ..........................161

6-3 The experimental setup of the full-scale bridge test. .......................................................162

6-4 The time history record of displacement measurement results from all the sensors. ......163

6-6 Radar’s signal results from different distance between the radar and the transponder. ..164

6-7 Sweetwater Park Bridge. ..................................................................................................165

6-8 Schematic of the bridge. ..................................................................................................166

6-9 Experimental setup at Sweetwater Park Bridge. ..............................................................167

6-10 Displacement results from stringpot and LVDT. .............................................................168

6-11 PSD of displacement measurement results. .....................................................................169

6-12 Displacement results from three Wise-Radar sensors. ....................................................169

6-13 PSD of displacement results from three Wise-Radar sensors. .........................................170

6-14 3D FEM bridge model. ....................................................................................................171

6-15 First bending mode of the bridge model. .........................................................................172

6-16 Mode shape comparison between the FEM and experimental results. ............................172

6-17 Cross-correlation value between Wise-Radar 2 and Wise-Radar 3. ................................173

15

6-18 Static deflection measurement results from all the sensors. ............................................174

6-19 Deflection results from two Wise-Radar sensors with low-pass filter applied. ...............174

16

Abstract of Dissertation Presented to the Graduate School

of the University of Florida in Partial Fulfillment of the

Requirements for the Degree of Doctor of Philosophy

SMART RADAR SENSOR FOR STRUCTURAL HEALTH MONITORING

By

Shanyue Guan

August 2017

Chair: Jennifer A. Rice

Major: Civil Engineering

Structural health monitoring (SHM) technologies have developed quickly in the last two

decades in an effort to achieve structural and operational safety of civil infrastructure. However,

many challenges must be addressed to realize practical and effective SHM applications. One of

the challenges is the lack of technologies and methods to detect structural displacements

accurately, efficiently and affordably. The drawbacks of conventional displacement

measurement technologies limit their implementation.

This dissertation presents a promising technology, Continuous Wave (CW) radar, which

originated as a sensor for vital sign and tumor detection, to measure displacement accurately and

inexpensively. The goal of this project is to develop and validate a new type of CW radar which

is suitable for structural displacement measurement applications within a low-cost wireless

sensor network.

This dissertation presents the limitations of conventional displacement measurement

technologies and introduces the theory and operation of the CW radar as a proposed alternative

for SHM. The merits of implementing SHM with wireless smart sensors are discussed and the

“WiseMote” platfrom is introduced. The smart radar sensor developed in this research is the

result of integrating the WiseMote with the CW radar. The enabling hardware and software

17

required to achieve this smart radar are presented. The performance of the CW radar sensor is

characterized in laboratory experiments and the performance of radar sensor for the field test has

also been validated by a series of full-scale bridge tests. Finally discussion and future work

related to smart radar sensor’s application are summarized.

18

CHAPTER 1

1 INTRODUCTION

1.1 Motivation

Modern society relies on the consistent and stable functionality of its civil infrastructure.

However, after structures are in service for many years, their performance may degrade, resulting

in functionality and safety problems. In the United States, about eight decades after a period of

increased construction during the 1930s, the condition of many bridges has declined, yielding

maintenance concerns and even failures (Johnson, 2001), such as the I-35W Mississippi River

Bridge collapse in 2007. In 2017, the American Society of Civil Engineers gave a grade D+ to

the state of infrastructure in the US (ASCE). Aging infrastructure is a worldwide concern. For

example, according to the Japan Transport Ministry, in Japan the country has about 140,000

bridges with 15 m or longer and approximately 20% of the bridges were 50 years or older in

2016. The number will increase to 47% in less than ten years.

Assessing and quantifying the condition of a structure is critical to maintaining its

performance. In addition to degrading performance caused by long-term loading or

environmental effects, structures are vulnerable to natural catastrophes such as earthquakes,

hurricanes, and tsunamis. For instance, many structures were damaged or collapsed, after the

Northridge (1994) (Youssef, Bonowitz, & Gross, 1995) and Kobe (1995) earthquakes (Tremblay

et al., 1996). Monitoring and protecting structure’s pre- and post-disaster performance are

important for the assurance of public safety and the allocation of repair and maintenance

resources.

The necessity of monitoring structural conditions has led to the development of structural

health monitoring (SHM) technologies over the last two decades. SHM provides a range of

approaches to capture structural conditions for various purposes. First, vibration-based

19

monitoring is capable of identifying structural models from measured structural response under

different load cases such as wind loads. Second, long-term monitoring systems can provide

structural responses before and after severe natural or manmade catastrophes. This information

can be analyzed to assess the damage and integrity of structures before investing money to repair

or reconstruct them. In addition, field tests can be conducted on structures to determine whether

the as-built structures have a similar response to that expected of the original design, which may

also provide a better prediction of structural response under extreme loads.

Some modern structures have been monitored from the construction stage to understand

their life-cycle characteristics. For instance, a comprehensive monitoring system was installed on

Guangzhou Tower to capture the response of the structure to under extreme events such as

typhoon (Ni, Xia, Liao, & Ko, 2009). A trend towards installing monitoring systems from day

one is seen in large and important structures, especially since it is easier and more cost-effective

to integrate instrumentation with the structure during construction.

Vibration-based monitoring methods are commonly used to measure response and assess

structural conditions. These methods, using displacement, velocity, and acceleration

measurements, have been widely applied on various infrastructure around the world. In addition

to dynamic measurements, designers and owners often select static deflections as an important

approach to evaluate structural design, especially for bridges. Besides monitoring structural

responses, some sensors have been implemented to monitor environmental conditions such as

wind speed, temperature or humidity.

There are several commonly-used sensors to measure or extract displacement of

structures. Some sensors, such as accelerometers lack either accuracy or practicality for realizing

displacement measurements. Other technologies such as Global Position Systems do not provide

20

adequate sampling rate or accuracy of measurements, unless expensive units are used (J. M. Ko

& Ni, 2005). Laser Doppler Vibrometers have better accuracy, but their high price does not

allow implementing a sensor network for practical applications.

1.2 Objectives

The technology of continuous wave (CW) radar is a promising approach to measuring

structural displacement. CW radars transmit and receive signals that are reflected by a target. The

phase difference between the transmitted and received signal is a function of the relative distance

between the radar and the target.

Establishing a sensor network with traditional wired monitoring system may be costly,

since the cables for transmissions and the installation of the cables can be expensive (Lynch,

2006). Wireless smart sensors transmit signals by Radio Frequency (RF), providing the

possibility to establish a sensor network with a lower cost than a wired monitoring system. In

addition, by leveraging the microprocessor embedded on each sensor, the smart sensor network

has the capability of conducting signal processing and other analysis within the network, which

may significantly reduce the amount of transmitted data. In most cases, low-cost accelerometers

or strain gauges are integrated with the smart sensor. However, to capture the structural

conditions from direct displacement measurements through a wireless smart sensor network, a

displacement sensing device must be integrated with the smart sensor.

The goal of this project is to develop a wireless smart radar sensor network that can

measure static and dynamic displacement of structures, process the data on the sensor nodes

within the network and transmit the signal wirelessly. Using a CW radar within a smart sensor

network provides a lower cost and more convenient approach to measuring structural

displacement than currently available technologies.

21

1.3 Scope and Organization

The smart radar sensor network can be implemented on various types of civil structures

and other applications; however, bridge health monitoring is the focus of this research. To

achieve the goals of this project: 1) specific hardware has been developed for SHM applications;

2) a supporting software framework has been developed to process the radar signals and collect

the displacement information automatically; 3) full-scale bridge tests have been conducted to

validate the sensor and sensor network capabilities and develop sensor design improvements.

Chapter 2 provides background for this research by introducing general SHM

technologies and then describing current technologies for structural displacement measurements.

Chapter 2 also provides background information on continuous wave radar and wireless smart

sensor networks. Chapter 3 provides the hardware development of the smart radar sensor tailored

for SHM applications. Chapter 4 outlines the software development of smart radar sensor,

including some routine operations and the automated algorithm for outputting structural

displacement from the radar’s signal. Chapter 5 introduces performance characterization of the

smart radar sensor under different conditions and Chapter 6 describes a series of full-scale bridge

tests to validate the smart radar sensor’s performance. Chapter 7 summarizes the research

presented in this dissertation and discusses potential future studies to continue the advancement

SHM using smart radar sensor.

22

CHAPTER 2

2 LITERATURE REVIEW AND BACKGROUND

2.1 Structural Health Monitoring

SHM technologies aims to monitor, evaluate and maintain structural integrity and safety.

SHM has developed rapidly since the 1950s, and consists of many instrumentations and

methodologies applied to observe, measure, assess and diagnose the conditions of engineering

structures in civil engineering (P. C. Chang, Flatau, & Liu, 2003), mechanical engineering

(Doebling, Farrar, Prime, & Shevitz, 1996), aerospace engineering (Giurgiutiu, Zagrai, & Jing

Bao, 2002) and other fields. SHM development requires interdisciplinary knowledge. Early SHM

technologies were applied mostly on machinery and aircraft (Wolowicz, 1966; WYKES &

MORI, 1965); however, in the last three decades, SHM technologies have also been applied

widely to civil engineering structures.

For civil engineering structures, the primary cause of structural defects is deterioration

due to aging problem. In addition, extreme loading events, such as hurricanes, earthquakes or

over loading may cause damage to structures (Tremblay, et al., 1996; Youssef, et al., 1995).

Developing fast, efficient and low-cost approaches for evaluating structural condition due to

deterioration and extreme events is a challenging task for civil engineers. Another role for

structural monitoring is to evaluate the performance of the as-built structure compared to its

intended design. There are often some deviations between the final constructed structures and the

original design; comparing the structural performance to the design calculations can be carried

out through analysis of SHM data.

Many aspects of SHM have been developed to address the above challenges. Researchers

have developed many types of sensors to capture the structural response accurately and created

new damage detection techniques to quantify the damage conditions of structures. Also, many

23

full-scale experiments have been conducted on different structures to validate whether the

response of practical structures is similar to the theoretical calculations from the design (Breuer,

Chmielewski, Górski, Konopka, & Tarczyński, 2008; J. Brownjohn, Dumanoglu, Severn, &

Taylor, 1987). Furthermore, newer, high profile structures are often designed with integrated,

real-time monitoring systems installed during construction. Real-time monitoring systems are

intended to monitor the structures response under normal and extreme cases which could provide

understanding of the structural conditions in real-time and protect structures subjected to extreme

events (Adeli & Jiang, 2006; Calebi, 2002).

As SHM technologies have developed, they have been implemented on various

structures. SHM has been implemented broadly on bridges (J. M. Ko & Ni, 2005; Soh, Tseng,

Bhalla, & Gupta, 2000), buildings (J. M. Brownjohn, 2005; Nayeri, Masri, Ghanem, & Nigbor,

2008), dams (Darbre & Proulx, 2002; De Sortis & Paoliani, 2007), pipelines (Jawhar, Mohamed,

Mohamed, & Aziz, 2008; Stoianov, Nachman, Madden, Tokmouline, & Csail, 2007), tunnels

(Fujihashi, Kurihara, Hirayama, & Toyoda, 2005; Sharma, Hefny, Zhao, & Chan, 2001), and

other types of engineering structures (Carstensen, Henriksen, & Teilmann, 2006; Ciang, Lee, &

Bang, 2008). SHM technologies have been developed in a range of areas including novel sensor

development, signal processing techniques, structural control, real-time monitoring, signal

transmission, data management, damage detection and diagnosis, and full-scale experiments.

The SHM system’s major elements include: transducer (sensor), data acquisition system,

data transfer mechanism, data storage mechanism, data management, and data interpretation and

diagnosis. To establish a successful SHM system, one of the most critical tasks is selecting the

appropriate transducer or sensor to conduct the measurements. Beyond detecting the structural

conditions by visual inspections, a sensor measures the physical response and converts it into an

24

electrical signal which the data acquisition system can read or observe. For each physical

response value of interest, there are corresponding sensors to measure that response. Focusing on

SHM applications, sensors can be classified by the response they measure:

• Mechanical: strain, deformation, displacement, acceleration, cracks opening, stress, load

• Environmental: Temperature, humidity, pore pressure

• Chemical: Chloride penetration, sulfate penetration, pH, carbonation penetration, rebar oxidation, steel oxidation, timber decay

There are many types of sensors for measuring mechanical responses. Strain is the

relative amount deformation of a body due to an applied force. Strain gauges are the common

method for measuring strain changes. Dynamic displacement may be used to understand the

dynamic characteristics of a structure. Static deflection measurement is important for validating

structural designs, especially for bridges. Both dynamic and static displacement may be

measured by displacement transducers such as Linear Variable Differential Transducer (LVDT)

or string potentiometer. Measuring acceleration is also a common approach to detect vibrations

and determine the dynamic characteristics of a structure. Accelerometers are commonly used for

SHM application. Cracking is a challenge for concrete structures, which may be monitored by

methods such as video, camera, or ultrasound.

Many sensors have been used to measure environmental factors. Humidity and

temperature sensors can provide insight into temperature-dependence structural responses and

conditions leading to corrosion. Pore pressure sensors have been applied for many geotechnical

projects to monitor the soil pressure.

Chemical factors that may contribute to corrosion, such as chloride penetration, pH,

carbonation penetration and steel oxidation can be monitored to protect the structures. Examples

25

include measuring material pH unbalance using a pH meter or fiber optic sensors used to monitor

the steel oxidation in concrete structures.

2.2 Existing Displacement Sensing Technologies

In general, vibration monitoring and static deflection monitoring are commonly adopted

approaches to measure structural motion, and the results may be used for structural conditions

evaluation (T. Liu et al., 2011) and damage detection (Fan & Qiao, 2011). As previously

mentioned, accelerometers are used to measure vibration. However, to detect the displacement

(both static and dynamic) directly with a high accuracy is still challenging.

The history of measuring structural displacement can be traced back a century. After the

Eiffel Tower was constructed, engineers wanted to know the movement of the tower and

conducted a series of displacement measurement by using the vertical telescope (Davenport,

1975). Compared with early stage displacement measurement approaches, modern technologies

tend to be more convenient, more accurate, and less expensive, making them better suited to

long-term applications. Based on different operating mechanisms, displacement sensors can be

classified into seven major categories: electromechanical, electromagnetic, electroacoustic,

laser/high power energy, imaging, surveying technology, and radar techniques.

To select the most appropriate sensor for the application, factors including accuracy, cost,

and convenience must be balanced and compared comprehensively. The accuracy of a sensor is

determined by its resolution, sensitivity, noise level, measurement range (amplitude, frequency,

distance), and repeatability. In addition to accuracy, the cost of the sensor, and the cost and ease

of its installation are also important factors in sensor selection. The following paragraphs

provide detail on commonly used displacement sensors based on accuracy, cost, and ease of

implementation.

26

2.2.1 Linear Variable Differential Transducer

Linear Variable Differential Transducer (LVDT) is one of the most commonly used

displacement sensor types. LVDTs are installed between two points to measure their distance

relative to one another. LVDT converts the relative distance change from a mechanical value to

a proportional analog electrical signal, which contains magnitude (distance) and phase (direction)

information. An LVDT consists of an insulating, nonmagnetic cylinder and a core. Inside the

cylinder is a primary coil in the mid-segment and a secondary coil symmetrically located in the

two end segments. A core made of ferromagnetic material is inserted coaxially into the cylinder

without touching it. Thus, there is no friction generated when the core moves inside the cylinder.

The schematics of LVDT is shown in Figure 2-1.

Figure 2-1. Schematics of LVDT.

LVDTs provide accurate measurements at a reasonable price for laboratory structural

testing and some SHM applications. Theoretically the LVDT has infinite resolution. In practice,

the LVDT resolution is a function of the data acquisition system characteristics. The

displacement measurement range of the LVDT varies from several millimeters to several meters,

providing multiple options for common SHM applications. The LVDT has wide frequency range

of measurements, the lower limit may be close to zero hertz and upper limit could reach several

hundred hertz. One drawback of LVDTs is that the cylinder must be shielded as it is sensitive to

27

magnetic fields. Another limitation is that they must be attached to a fixed stationary reference

point at one end which is difficult to achieve for large-scale structural testing. The distance

between the two ends of LVDTs cannot be adjusted easily based on their measurement range

(Lee & Shinozuka, 2006). For full-scale structure testing, it is labor and cost intensive to obtain

global structural conditions by installing LVDTs at many locations.

LVDTs have been implemented to measure static deflection and dynamic displacement

from laboratory experiments to large-scale structural tests. LVDTs have been used for many

different applications s such as bridge monitoring (Feng, Fukuda, Feng, & Mizuta, 2015; Nassif,

Gindy, & Davis, 2005), structural response under wind loads (Habte, Mooneghi, Chowdhury, &

Irwin, 2015) and seismic measurements (Shan, Gao, & Shen, 2016; Silva, Vasconcelos,

Lourenço, & Akhoundi, 2016). Because of the LVDTs reasonable price and high accuracy, they

are often deployed as a reference sensor to compare the measurement results with other sensors

(Wan & Leung, 2007).

2.2.2 String Potentiometer

Similar to the LVDT, a string potentiometer directly measures relative displacement

between two points. It includes four main parts: a measuring cable, spool, spring, and rotational

sensor. One end of the measuring cable is connected to the target, the other end of the sensor is

fixed to a stationary point. The resistance of the coil is proportional to its length. With the target

moving, the string potentiometer creates an electrical signal proportional to the cable’s linear

extension.

Compared with LVDT string potentiometer is more convenient to install using the

extension cable which allows one end of the sensor to be installed away from the structure. The

measurement ranges vary from several millimeters to several meters. The string potentiometer

provides reasonable accuracy with relatively low cost. High frequency or transient measurements

28

are not feasible because of friction and inertia resistance within the sensor. Also, to conduct the

measurements successfully, the cable of the string potentiometer must be always in tension.

However, there may be some deflections added to string potentiometer’s cable caused by wind or

gravity when it is applied for field tests.

The original application of the string potentiometer in the 1960s was aerospace cyclic

fatigue testing. More recently, it has been used for structural testing such as roofs under wind

loading (Habte, et al., 2015), deflections of bridge deck under vehicle load (Fuhrman, Rafiee-

Dehkharghani, Lopez, Aref, & O’Connor, 2014) and building monitoring under vibrations

(Kosnik & Dowding, 2014).

2.2.3 Accelerometer

Accelerometers are used to measure structural vibration. There are two main

accelerometer categories, depending on the sensing mechanisms: capacitive and piezoresistive.

In general, the accelerometer behaves as a damped mass on a spring. When the accelerometer

experiences motion, the mass shifts from neutral position and the deformation is measured. As

the stiffness of the spring is known, the spring force causing the acceleration can be calculated.

Since the mass is known, the acceleration could be obtained using D’Alembert’s principle. The

schematics of a piezoelectric based accelerometer is shown in Figure 2-2. Accelerometers come

in a wide range of sizes with widely varying accuracy, acceleration ranges, and frequency

ranges. Based on the directions of the measurement, there are single axis, dual-axis, triaxial

accelerometers available.

29

Figure 2-2. Schematics of piezoelectric based accelerometer.

The cost of accelerometers varies depending on the measurement accuracy and

measurement range. The accelerometers provide a reasonable accuracy with a relatively low

cost. Accelerometers have been applied to monitor dynamic motions of structures including high

frequency and low frequency vibrations. In this dissertation, the structural motion is

differentiated as low frequency motion or high frequency motion based on its frequency. If the

frequency is lower than 20 Hz, the structural motion is low frequency motion. Otherwise, the

structural motion is high frequency motion. Accelerometers have also been used to obtain the

structural displacement information on bridges and buildings (Celebi, 2000; Moschas & Stiros,

2011). To obtain the displacement information from the acceleration measurement, double

integration must be conducted. However, the process of double integration may introduce

considerable errors due to the integration of the low frequency noise (Stiros, 2008; Yang, Li, &

Lin, 2006). Displacement measurements using accelerometers require the application of a high-

pass filter followed by double integration to ensure accuracy.

2.2.4 Strain Gauge

External force applied to a metallic material generates physical deformation and electrical

resistance change of the material. When the material is affixed onto a test specimen and

electrically insulated, the material produces a change of electrical resistance corresponding to the

30

deformation of the test specimen. Strain gauges consist of electrical resistance material and

measure strain proportional to the resistance changes. Gauges must be selected carefully to

measure the strain changes on different materials. The Wheatstone bridge with different

combinations of strain gauges (quarter-bridge, half-bridge, full-bridge) is usually applied to

convert the measurement of changes in resistance to changes in voltage. It is easier and more

accurate to measure the voltage changes than the resistance changes. Multiple strain gauges can

be integrated into one unit such as the two-element rosette and the three-element rosettes to

measure the strain changes at different directions simultaneously.

Strain gauges are inexpensive and quite sensitive to micro strain changes. The size of the

strain gauge varies from several millimeters to several centimeters. To install the strain gauge

securely and to obtain good measurement results, some sophisticated installation skills are

necessary. Ideally, the voltage source connected to the sensor should have zero output

impedance. In reality, the non-zero output impedance (load effect) may cause considerable errors

of strain gauge measurement. In addition, the resistance of strain gauges varies with temperature

changes which results in drift of measurements over long time (J. M. Ko & Ni, 2005).

Strain gauges are mostly applied to monitor the strain changes on test specimens or full-

scale structures to understand the local condition of structures (Pérez-Mora, Palin-Luc, Bathias,

& Paris, 2015; Zha, Zhang, Li, & Dang, 2016). Some researchers have applied strain gauges to

measure strain changes of the structure and with the help of advanced algorithms to calculate the

displacement of bridges indirectly with promising results (S.-J. Chang & Kim, 2012; Park, Sim,

& Jung, 2013).

2.2.5 Ultrasonic Sensor

The ultrasonic sensor is a non-contact sensor that generates ultra-sound waves in the

ultrasonic range (above 18 kHz). After the ultrasound wave hits the target, the echo is reflected

31

by the target and then captured by the sensor. By interpreting the reflected signals, the distance

between the sensor and the target could be obtained. By calculating the traveling time between

sending the signal and receiving the echo, distance is determined and then the relative

displacement is measured as the target moves. Also, ultrasonic sensors have been used for non-

destructive material damage detections (Gupta, Ray, & Keller, 2007; Rojas, Baltazar, & Loh,

2015) because of its high energy and strong penetrating performance.

The ultrasonic sensor is easy to install and operate. It is also a non-contact sensor which

provides some flexibility if the accessibility to the structure is difficult. On the other hand, the

material and the surface conditions of the structure are the limitations of using the ultrasonic

sensors. Some structures will diffuse the reflection due to its surface shape. Other material may

absorb the sound wave and then there is no way for the sensor to detect the target.

Some researchers have proposed a method for applying the ultrasound device to measure

lateral displacement of structures under seismic load (Matsuya, Matsumoto, & Ihara, 2015). The

sensor provided a sub-millimeter accuracy which is promising.

2.2.6 Laser System

Laser-based systems provide high accuracy displacement measurements. A laser emits

high energy light through optical amplification based on the stimulated emission of

electromagnetic radiation. The device transmits the laser beam to the target and receives the

reflected laser beam. Since the light speed is known, the travel time of the laser beam indicates

the distance between the target and the laser. If the target is moving during the measurements,

the laser measures the displacement in time. The laser usually works for single direction distance

measurement.

The laser system has very high energy and very good concentration performance which

enables good transmission and focus over a long distance. As a result, lasers usually have better

32

accuracy measuring displacement or distance compared to other sensors. Lasers operate as non-

contact devices, enabling the measurement of deflection at points on the structure which are

difficult to obtain access. The challenge of using the laser system is the laser beam may be

overwhelmed by the brightness in the environment, making it difficult to recognize. Also, the

high power of the laser beam may cause damage to human’s eyes. The largest drawback for

using the laser is its high cost.

Different types of laser devices have been applied to measure the displacement of

structures (Mori, Stamenov, & Dorneles, 2015; OBrien & Malekjafarian, 2016). Among several

types of laser measurement systems, Laser Doppler Vibrometer (LDV) has been widely used to

measure bridge and building vibrations (Nassif, et al., 2005; Rossi, Marsili, Gusella, & Gioffre,

2002). The LDV generates a two-beam laser interferometer that measures the frequency (or

phase) difference between an internal reference beam and a test beam. The measurement

accuracy can be micrometer level. However, the large size of the device makes adjusting its

position challenging and is not well-suited to long-term continuous monitoring applications.

2.2.7 Vision Approaches

Camera and video technologies have improved dramatically since digital cameras were

invented. Currently available cameras provide very high resolution images. With the ongoing

development of various image processing techniques, some information such as the shape and

the size of the object in the image can be assessed automatically. Recently, image processing

integrated with good quality cameras have been widely applied for robotics, autonomous

vehicles, object detections and SHM. Cameras have been used to measure the displacement of

structures through analyzing continuous time history photo frames (Fu & Moosa, 2002; Lee &

Shinozuka, 2006; Ojio, Carey, OBrien, Doherty, & Taylor, 2016).

33

Cameras are part of the surveillance systems on different structures, especially bridges.

Besides using the camera to monitor the traffic flow (Ojio, et al., 2016; Zaurin, Khuc, & Catbas,

2016) or environment conditions, the camera can be used to measure structural displacement.

Cameras could be used to monitor the displacement at different locations at the same time if they

are used with a wide angle. Cameras are convenient to install and operate; however, there are

some disadvantages of using camera or video systems. First, high speed camera or video can be

quite costly. In addition, on cloudy days or at nighttime, the image quality is poor and causes

difficulties for analysis. Furthermore, sometimes wind or heavy vehicle load on the bridge can

cause some disturbance on the camera, which will impact the measurement results (Lee &

Shinozuka, 2006). Third, outputting the displacement results in real-time with the image

processing algorithms requires significant computation.

2.2.8 Global Positioning System

Global Positioning System (GPS) operates based on the position of specialized satellites.

The position of a GPS receiver is determined by monitoring the known positions of the satellites

and solving the coordinate equations. By installing the GPS receivers at different points on a

structure, the spatial locations of different points can be obtained. As the structure is vibrating,

using appropriate numerical algorithms to calculate the coordinate changes, displacement can be

calculated from the spatial locations changes. The displacement obtained from the GPS provides

the movement of points on the structure in three-dimensions (3D). Most surveying technologies

such as total station (Psimoulis & Stiros, 2013), and GPS measure displacement by calculating

the receiver’s coordinate changes in one, two or three dimensions. However, one limitation of

GPS technology is its low accuracy for civil applications. The accuracy of civilian GPS is

approximately 5 to 10 meters, which is not sufficient for many SHM applications; centimeter

level accuracy GPS is costly but more useful for displacement measurements since the

34

displacements of the structures are usually within this range. Another drawback of the GPS

technology is its low sampling rate (usually less than 10 Hz) which may not be adequate to

capture all the dynamic characteristics of structures in the real-time (J. M. Ko & Ni, 2005). Also,

sometimes the GPS receiver may lose the signal due to obstructions and multi-path effects may

add some considerable errors to the measurement. (Kijewski-Correa & Kochly, 2007)

GPS has been used to measure the motion of different types of structures: buildings,

dams, and bridges (Moschas & Stiros, 2011, 2014) (Hristopulos, Mertikas, Arhontakis, &

Brownjohn, 2007; Hudnut & Behr, 1998; Meng, Dodson, & Roberts, 2007). Recently, many

structures have used the GPS system during the construction process (Pradhananga & Teizer,

2013).

To select the appropriate sensors to measure structural displacement, the performance of

commonly used technologies is summarized in the Table 2-1.

Table 2-1. Existing displacement sensing technologies comparison.

Approach Advantages Disadvantages

LVDT • Provides both amplitude and phase information

• Good accuracy (especially low

frequency) and

reasonable cost

• Wide frequency range measurement

• Sensitive to magnetic field

• Must be attached to a fixed stationary

reference point

STRING POTENTIOMETER • Large measurement range

• Reasonable accuracy and cost

• Sensor may be installed far away from the

structure

• Affected by wind and gravity

• High frequency or transient

measurements are

not feasible

• The cable must be installed carefully

35

Table 2-1. Continued

Approach Advantages Disadvantages

ACCELEROMETER • Compact size, easy to transport, reasonable cost

• Excellent at measuring high frequency vibrations

• Sensitive to slight motion

• Low cost sensors have bad accuracy at

low frequency

measurements

• Conversion from acceleration to

displacement may

introduce errors

STRAIN GAUGE • Low cost, easy to transport

• Sensitive to micro strain changes

• Sophisticated installation

• Loading effects and temperature drift

ULTRASONIC SENSOR • Easy to install and operate

• Structural material and surface are

limitations

LASER SYSTEM • Maintain a good focus over a long distance

• Non-contact monitoring

• Best accuracy of displacement

measurements

• Signal may be overwhelmed by

brightness

• Very costly

• May cause damage to human’s eyes

VISION APPROACH • Convenient to install and operate

• Multiple position measurements

simultaneously

• High speed camera or video can be quite

costly

• Image quality may be affected by the

environment

• Real-time analysis needs computation

complexities

GLOBAL POSITIONING

SYSTEM • Multiple position

measurements

simultaneously

• Three-dimensional displacement

• Not very high accuracy

• Low sampling rate

• Signal loss, multi-path effects

2.3 Radar Techniques

In addition to the above existing technologies to measure displacement, radar techniques

are a large group of systems to detect and locate objects. Radar is the acronym for Radio

Detection And Ranging (radar) named by the United States Navy in 1940. Based on their

36

operating mechanisms, many types of radars have been developed: detection and search radars,

weather sensing radar, navigational radar, mapping radar, radars for biological research, etc. In

general, the radar system operates by emitting the radar wave (pulse, sinusoidal, sawtooth,

square wave) from a transmitting antenna. Then the radar wave reaches the target and the

reflected radar wave is captured by the receiving antenna. By analyzing the reflected signal, the

location or velocity of the target may be obtained. The radar’s signal is often modulated by

frequency or amplitude to carry some information in the transmission. After receiving the signal,

the transmitted information is obtained by demodulation from the radar signal which is the

inverse process of modulation. Via this approach, the information can be transmitted over long

distance without too much signal loss. Radar has been applied widely for military (Allison,

1981), aerospace (Gong & Chan, 2002), and communication applications (Elsherbini &

Sarabandi, 2012). More recently, radar has also been adopted for civil engineering applications

(Giurgiutiu & Bao, 2004; Hughes, Kim, El-Korchi, & Cyganski, 2015), including the detection

of debonding in concrete structures (T.-Y. Yu & Büyüköztürk, 2008), and for monitoring

deteriorating concrete dams (Rhim, 2001). Applications of radars for SHM, including ground

penetrating radar, remote sensing radar, and distance measurement radars, are introduced in this

section.

2.3.1 Ground Penetrating Radar

Ground penetrating radar (GPR) transmits the radar pulse which has very strong

penetration performance through some materials such as ground surface to image the subsurface.

By comparing the transmitted signal with the received signal, the subsurface conditions can be

obtained. The radar wave frequency stays in the range from 10 MHz to 2.6 GHz. A GPR

transmitter emits electromagnetic energy into the ground. When the energy encounters a buried

object or a boundary between materials with different permittivities, it may be reflected to the

37

surface. A receiving antenna can then record the variations in the return signal. The depth to a

target is determined based on the amount of time it takes for the radar signal to reflect to the

unit’s antenna. Radar signals travel at different velocities through different types of materials. It

is possible to use the depth to a known object to determine a specific velocity and then calibrate

the depth calculations.

GPR is a non-destructive testing (NDT) approach which can be used to scan a large area

if it is carried by a mobile vehicle or airborne. Because of its high penetrating performance, it

may be used to monitor many types of materials. The largest limitations of using the GPR is in

high-conductivity material such as clay soils that are salt contaminated, the reflected signal

strength is weak. Performance is also limited by signal scattering in heterogeneous conditions

(rocky soils).

GPR has been applied for NDT on concrete structures (Maierhofer, 2003). Mobile GPRs

have been used to detect the pavement (Maser, 1996) and bridge deck (Alani, Aboutalebi, &

Kilic, 2013) conditions. The resolution of mobile-based radar systems depends on the radar’s

performance and the speed of the transportation. The speed at which a radar signal travels is

dependent on the composition of the material being penetrated. Sometimes, to get higher quality

measurements, more cycles of the measurements may need to be conducted.

2.3.2 Remote Sensing Radar

The radars can be installed on the satellites to conduct the sensing remotely. The radar

transmits the microwave over large areas and captures the reflected microwave from the target

areas. Remote sensing is an example where the time delay between emission and return is

measured, from which the location, speed and direction of an object can be calculated.

38

Remote sensing makes it possible to collect data of dangerous or inaccessible areas such

as post-disaster area. Remote sensing is more focused on monitoring conditions over a large area

with side length up to 1000 m while the detailed local condition is not detected.

Satellite radar has been used widely for remote sensing for archaeological sites (Tapete,

Fanti, Cecchi, Petrangeli, & Casagli, 2012), dams (D. Tarchi, E. Ohlmer, & A. Sieber, 1997),

and to assess changes of large areas after disasters such as earthquakes (Motagh, Beavan,

Fielding, & Haghshenas, 2014; Yun et al., 2015) or tornados (Atkins, Butler, Flynn, &

Wakimoto, 2014). However, the image quality from the satellite radar is easily affected by

atmospheric conditions. Frequency of image updating is low (approximately one image for

several hours) which is challenging to develop a real-time monitoring system.

2.3.3 Distance Measurement Radar

Besides detecting the structural conditions using penetrating performance or conducting

remote sensing to monitor large areas, there are many types of radars that have been used for

displacement or distance measurements. To measure the distance between the radar and the

target, there are two general approaches: time-of-flight radar and interferometric radar. The

theory of the time-of-flight radar is similar to a laser or ultrasonic system. By calculating the

travelling time between transmitting the radar wave and receiving the radar wave, the distance

between the radar and the target may be measured as the radar wave travels with the speed of

light. The interferometric radar compares the difference between the transmitted signal and

received signal on signal amplitude, frequency or phase difference to calculate the distance

between the radar and the target.

2.3.3.1 Time-of-Flight Laser Radar

The mechanism of the time-of-flight radar is the transmission of a pulse signal. By

calculating the time difference between transmitting and receiving the laser pulse signal, as the

39

speed of the pulse transmission is known, the distance between the radar and the target can be

calculated.

The advantage of using this type of radar is the operating theory of the radar is

straightforward and it is convenient to deploy and conduct measurement. Usually this type of

radar is installed at a stationary location and keeps transiting the pulse to the target over long

distance. However, the time difference measurement between transmitting and receiving

measurement is not very accurate, the distance obtained from this type of radar has some

considerable errors.

The radar has been used to measure a target with a periodic motion successfully

(Palojarvi, Maatta, & Kostamovaara, 1997). The radar has also been applied to measure the

spatial motion of a target (Makynen, Kostamovaara, & Myllyla, 1994).

2.3.3.2 Pulse Radar

Pulse radar is a system that transmits short wavelength and high energy pulses over long

distance. Compared with the time-of-flight laser pulse radar, the pulse signal energy of pulse

radar is higher. It is usually designed for long distance measurements and transmits a relatively

high-power pulse. For each transmission, only one pulse will be transmitted. The pulse radar

transmits short pulses which are reflected by the target. By measuring the travelling time

between sending a pulse of radar wave and receiving the echo of the object, as the radar wave

travels at the speed of light, the distance between the radar and the target may be calculated.

Besides the distance measurements, the speed of the target may also be calculated based on the

Doppler Effect by calculating the difference between the transmitted and received signal’s

frequency.

40

Pulse radar is useful for measuring over long distance and may output both the distance

and velocity. However, pulse radar systems are large, which may make them impractical for

SHM applications.

Pulse radar has been used for aircraft range detections (Shariff & Wray, 2002) and wind

speed measurement (Lund, Graber, & Romeiser, 2012). It has also been applied in human health

care, such as fall risk assessment and fall detection (Wu et al., 2013).

2.3.3.3 Frequency Modulated Continuous Wave Radar

Due to the errors of the measuring the time-of-flight, interferometric radars are used more

frequently to measure distance or displacement. Frequency modulated continuous wave

(FMCW) radar transmits continuous wave and the frequency of signals varies over a stable

period. The received signal reflected from the target is mixed with the transmitted signal to

produce the interference (beat signal) since the frequencies of the transmitted signal and received

signal are similar. The beat signal provides the distance between the target and the radar after

demodulation. (Brooker, 2005) A variety of modulations are possible: sine wave, sawtooth wave,

triangle wave, square wave.

FMCW radar is a short-range measuring radar capable of determining distance. It

provides distance measurement along with speed measurement, which is essential when there is

more than one source of reflection arriving at the radar antenna. Another advantage of FMCW is

that radar operates at relatively low frequencies which makes hardware design easier to achieve.

Conversely, the FMCW radar transmission range is shorter and the power consumption is lower

compared with the pulse radar. FMCW radar has been used to measure the distance between a

metallic target and the radar (Jaeschke, Bredendiek, Küppers, & Pohl, 2014). It has also been

tested in-door to measure the speed of a moving bicycle and the distance between the bicycle and

the radar (Roehr, Gulden, & Vossiek, 2008).

41

2.3.3.4 Step Frequency Interferometric Radar

The step frequency interferometric radar transmits the microwave with the signal

frequency increasing in linear steps. The general working principle of using the step frequency

interferometric radar to measure the distance is to compare the transmitted signal and the

reflected signal. The radar’s received signal includes both the amplitude and phase information

of the signal reflected by the target. The peak of the amplitude signal corresponds to the reflected

signal which has the highest strength. The phase difference between the reflected radar wave and

the transmitted radar wave may be used to calculate the distance between the radar and the

target.

The step frequency interferometric radar has a very good accuracy over many other radar

systems for measuring displacement. The accuracy may be close to sub-millimeter level

(Massimiliano Pieraccini, Fratini, Parrini, Atzeni, & Bartoli, 2008). However, the radar system is

large and bulky which is inconvenient to transport. Also cost of the interferometric radar (up to

several thousand US dollars) is much higher than most displacement sensors.

The interferometric continuous wave step frequency radar has been validated for

displacement monitoring on many types of structures, including vibrating stable cables (Gentile,

2010), bridges (Dei, Pieraccini, Fratini, Atzeni, & Bartoli, 2009; Gentile & Bernardini, 2008,

2009; Massimiliano Pieraccini et al., 2007; M Pieraccini et al., 2000), and buildings

(Massimiliano Pieraccini, et al., 2008). Another type of interferometric radar has been used for

SHM application is the interferometric synthetic aperture radar (InSAR). The InSAR has also

been used for monitoring the concrete structure deformation (D Tarchi, E Ohlmer, & A Sieber,

1997; Torfs et al., 2013) and it has also been used to monitor subsidence and structural stability

(Atzeni, Barla, Pieraccini, & Antolini, 2015). Interferometric radar has also been applied in

42

human health care, such as fall risk assessment and fall detection (H. Wang, Ren, Mao, & Fathy,

2016).

2.3.3.5 Continuous Wave Radar

Continuous wave (CW) radar is a promising technology to measure structural

displacement. The CW radar transmits a known stable-frequency continuous microwave and then

receives the reflected from the target. The motion information of the target is modulated into the

radar’s signal by comparing the phase difference between the transmitted and received signal.

Through the demodulation of the radar’s signal, the displacement of the target can be measured.

Different from the pulse radar, the CW radar is transmitting the microwave continuously.

The size of the CW radar may be very compact, making it easy to install and transport.

The cost of the CW radar is reasonable compared with other sensors. In addition, the CW radar

has a sub-millimeter accuracy which is very promising for SHM applications (Rice, Li, Gu, &

Hernandez, 2011).

CW radar has been applied to conduct non-contact vital sign detections (Droitcour,

Boric-Lubecke, Lubecke, Lin, & Kovacs, 2004; Li & Lin, 2008; C. Li, Lubecke, Boric-Lubecke,

& Lin, 2013; C. Li, Xiao, & Lin, 2006) and cancer radiotherapy (Gu & Li, 2014; Gu et al., 2012)

. It has been applied on some preliminary SHM applications to monitor the structural

displacement (Lu, Li, & Rice, 2011; Moll, Bechtel, Hils, & Krozer, 2014; MOLL & KROZER,

2016; Rice, et al., 2011). Some full-scale experiments to validate the CW radar’s performance

will be introduced in Chapter 5 and 6.

To apply the CW radar sensor for bridge monitoring, the passive backscattering strategy

may be used. To enable bridge dynamic and static displacement monitoring, one or more radars

may be mounted to the underside of the bridge. For the passive backscattering mode, each

sensor transmits a continuous microwave to a stationary target surface (ground or other reflective

43

materials such as metallic surface which is sensitive to the microwave) under the bridge and then

in turn receives the reflected signal (Rice, Guan, Li, & Gu, 2012), as illustrated in Figure 2-3.

The received signal is modulated with the relative motion between each sensor and the stationary

target surface. The displacement of bridge at each sensor location is obtained through appropriate

signal processing and demodulation.

Figure 2-3. Diagram of passive backscattering configuration.

The passive backscattering strategy is convenient to setup for measuring displacement.

However, the largest challenge of the backscattering strategy is that the signal strength attenuates

quickly as the target distance increases. For the case of a single transmitter and receiver pair, a

free space microwave propagation model is used to illustrate the signal attenuation:

2

2 2( )

(4 )

t t rr

PG GP d

d L (2-1)

where Pr is the received power, Pt is the transmitted power, Gt is the transmitter antenna

gain, Gr is the receiver antenna gain, d is the distance between the transmitter and receiver, L is

the system loss factor not related to propagation, and λ is the microwave wavelength (Rappaport,

1996). For the case when the transmitter also acts as the receiver, such as when the radar

operates in the passive backscattering mode, the signal is reflected by the target surface and

44

travels round trip before it is received. According to Equation (2-1), assuming there is no energy

loss during the signal reflection at the target surface, the received signal power of the radar in the

backscattering mode will be (Changzhi et al., 2010):

2 2 2