Self-healing Autonomous Sensor Network (SASNet ... · DRDC-RDDC-2017-R130 i Abstract The Self-healing Autonomous Sensor Network (SASNet) is a prototype, wireless sensor network originally

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Self-healing Autonomous Sensor Network (SASNet) Radiological/Nuclear (RN) prototype Printed Circuit Board (PCB) testing

T. Jones D. Waller DRDC – Ottawa Research Centre Terms of Release: This document is approved for Public release.

Defence Research and Development Canada Scientific Report DRDC-RDDC-2017-R130 September 2017

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IMPORTANT INFORMATIVE STATEMENTS Disclaimer: Her Majesty the Queen in Right of Canada (Department of National Defence) makes no representations or warranties, express or implied, of any kind whatsoever, and assumes no liability for the accuracy, reliability, completeness, currency or usefulness of any information, product, process or material included in this document. Nothing in this document should be interpreted as an endorsement for the specific use of any tool, technique or process examined in it. Any reliance on, or use of, any information, product, process or material included in this document is at the sole risk of the person so using it or relying on it. Canada does not assume any liability in respect of any damages or losses arising out of or in connection with the use of, or reliance on, any information, product, process or material included in this document. This document was reviewed for Controlled Goods by Defence Research and Development Canada (DRDC) using the Schedule to the Defence Production Act. Endorsement statement: This publication has been peer-reviewed and published by the Editorial Office of Defence Research and Development Canada, an agency of the Department of National Defence of Canada. Inquiries can be sent to: [email protected].

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DRDC-RDDC-2017-R130 i

Abstract

The Self-healing Autonomous Sensor Network (SASNet) is a prototype, wireless sensor network originally developed for the Canadian Army. The goal of the current work is to integrate a Radiological/Nuclear (RN) detector into the SASNet sensor nodes. The electronics were specially designed to ensure that the power consumption of the RN sensor will be very low (< 1mA); this will allow SASNet sensor nodes to operate remotely for many months on a single 3.5 V battery. The resulting printed circuit board (PCB) was designed to have the electronics and RN sensor package fit inside the existing SASNet node without modification to the form factor or enclosure. The RN sensor packages included a high-atomic number, high density scintillating crystal (bismuth germanate oxide, BGO, or lutetium yttrium silicon oxide, LYSO) and a silicon photomultiplier (SiPM).

Vertilon Corporation was contracted to produce twelve prototype PCBs (six with LYSO crystals, six with BGO). Two of the units (one with LYSO and one with BGO) were evaluated at DRDC – Ottawa Research Centre with radioactive sources. This report summarizes these measurements. The PCBs were not integrated into the SASNet node at this time. This work will be performed in the future at Valcartier Research Centre (who lead the ongoing development of SASNet).

Significance to defence and security

A wireless radiation sensor network (WRSN) could provide effective stand-off detection of RN threats. There are a number of possible military applications for a WRSN: for example, perimeter intrusion detection with an RN threat, or monitoring a remote location for movement of RN sources. One of the key challenges of developing a practical WRSN is to have sensitive detection, while maintaining a low false alarm rate and long node lifetime on a single battery. For this work, a low-power RN sensor was integrated onto an existing SASNet PCB. The PCB met the low-power requirements of the project and the sensor package was demonstrated to detect sources of radiation (cobalt-60 and cesium-137) across a range of dose-rates and temperatures. The gamma-ray count rate shows a sensitivity to temperature which can, and possibly should, be compensated for. This compensation should be considered in the future, perhaps after, or in conjunction with, testing the performance of a network of RN-enabled SASNet nodes.

ii DRDC-RDDC-2017-R130

Résumé

Le Réseau de capteurs autonomes à autorétablissement (SASNet), est un prototype sans fil créé à l’origine pour le compte de l’Armée canadienne. Les travaux actuels ont pour but d’intégrer un détecteur radiologique et nucléaire (RN) aux nœuds de capteurs du réseau. Les composants électroniques du détecteur RN ont été spécialement conçus pour ne consommer que très peu de courant (moins de 1 mA) et permettre ainsi de faire fonctionner à distance chacun des nœuds de capteurs du réseau SASNet durant de nombreux mois avec une seule batterie de 3,5 V. La carte de circuits imprimés a été conçue pour qu’on y insère les composants électroniques et l’ensemble de capteurs RN à l’intérieur du nœud actuel du réseau SASNet sans modifier le facteur de forme ni le boîtier. Les ensembles de capteurs RN comportaient un cristal scintillant de BGO (oxyde de germanate de bismuth) ou de LYSO (oxyorthosilicate d’yttrium lutécium) à haute densité et numéro atomique élevé, ainsi qu’un photomultiplicateur au silicium (SiPM).

La production de douze prototypes de cartes de circuits imprimés (six aux cristaux de BGO et six autres aux cristaux de LYSO) a été confiée à Vertilon Corporation. Deux de ces cartes, soit une de chaque type, ont été évaluées au moyen de sources radioactives au CRO de RDDC. Le présent rapport résume les mesures obtenues dans le cadre de cette évaluation. Les cartes de circuits imprimés n’ont pas été intégrées au nœud du réseau SASNet à cette étape. Elles le seront plus tard au Centre de recherches de Valcartier (qui dirige la phase actuelle de développement du réseau SASNet).

Importance pour la défense et la sécurité

Un réseau sans fil de capteurs de rayonnement assurerait une détection à distance efficace des menaces RN. Un tel réseau se prêterait à de nombreuses applications militaires, comme la détection périmétrique d’intrusion d’une menace RN ou la surveillance à distance du mouvement de sources RN. L’un des principaux enjeux consiste à obtenir le niveau requis de sensibilité de détection, tout en maintenant un taux de fausse alarme peu élevé et une longue durée de vie des nœuds de capteurs au moyen d’une seule batterie. Pour ce faire, on a intégré un capteur RN peu énergivore à une carte de circuits imprimés du réseau SASNet. Cette dernière a satisfait aux exigences relatives à la faible consommation prévue au projet, et l’ensemble de capteurs a montré qu’il permettait de détecter des sources de rayonnement au cobalt 60 et au césium 137 sur une gamme de débit de dose et de température. Le taux de comptage du rayonnement gamma montre une sensibilité à la température qui peut et devrait être compensée. Cette compensation devrait être envisagée ultérieurement, peut-être après ou en même temps que l’évaluation du rendement d’un réseau SASNet composé de nœuds de détection RN.

DRDC-RDDC-2017-R130 iii

Table of contents

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i Significance to defence and security . . . . . . . . . . . . . . . . . . . . . . i Résumé . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii Importance pour la défense et la sécurité . . . . . . . . . . . . . . . . . . . . ii Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii List of figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

List of tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . vi 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2 RN sensor requirements for SASNet . . . . . . . . . . . . . . . . . . . . 2

2.1 Scintillator and SiPM requirements . . . . . . . . . . . . . . . . . . 3

3 SASNet RN prototype PCB . . . . . . . . . . . . . . . . . . . . . . . 6

4 Verification of RN PCB requirements . . . . . . . . . . . . . . . . . . . 7

4.1 Communication response . . . . . . . . . . . . . . . . . . . . . . 7

4.1.1 Protocol . . . . . . . . . . . . . . . . . . . . . . . . . 7

4.1.2 Testing the serial interface . . . . . . . . . . . . . . . . . . 9

4.1.3 Signal connections . . . . . . . . . . . . . . . . . . . . . 10

4.1.4 Interfacing the Raspberry Pi . . . . . . . . . . . . . . . . . . 10

4.2 Dose rate response . . . . . . . . . . . . . . . . . . . . . . . . 12

4.2.1 Dose rate response for RN PCB with BGO and LYSO crystals . . . . . 15

4.2.2 Dose rate response as a function of discriminator threshold . . . . . . 18

4.2.3 Temperature dependence of dose rate response . . . . . . . . . . . 21

4.3 Power measurements . . . . . . . . . . . . . . . . . . . . . . . 25

4.3.1 Picoammeter method . . . . . . . . . . . . . . . . . . . . 26

4.3.2 Series resistor method . . . . . . . . . . . . . . . . . . . . 27

5 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

List of symbols/abbreviations/acronyms/initialisms . . . . . . . . . . . . . . . . 32

iv DRDC-RDDC-2017-R130

List of figures

Figure 1: Exterior of SASNet sensor node. . . . . . . . . . . . . . . . . . . . 2

Figure 2: Interior of SASNet node (back cover removed). . . . . . . . . . . . . . 3

Figure 3: Prototype RN PCB. . . . . . . . . . . . . . . . . . . . . . . . . 6

Figure 4: Serial interface timing. . . . . . . . . . . . . . . . . . . . . . . . 10

Figure 5: Signal wires for RN PCB. . . . . . . . . . . . . . . . . . . . . . . 11

Figure 6: Raspberry Pi—GPIO signal monitoring. . . . . . . . . . . . . . . . . 11

Figure 7: Oscilloscope capture of device ID request. . . . . . . . . . . . . . . . 12

Figure 8: System block diagram for pulse counting of RN PCB. . . . . . . . . . . 13

Figure 9: RN PCB in its light-tight box. . . . . . . . . . . . . . . . . . . . . 14

Figure 10: RN PCB irradiation using the AN/UDM-1A Cs-137 source. . . . . . . . . 15

Figure 11: LYSO/BGO dose rate response (0 to 2000 µSv/h). Note that the SiPM operating voltages and discriminator thresholds are different for the BGO and LYSO detectors. . . . . . . . . . . . . . . . . . . . . . . . . . 16

Figure 12: LYSO/BGO dose rate response (0 to 600 µSv/h). A more detailed view of the low dose rate portion of Figure 11. . . . . . . . . . . . . . . . . . . 16

Figure 13: LYSO and BGO count rate responses (0 to 2000 µSv/h). . . . . . . . . . 17

Figure 14: LYSO/BGO count rate response (0 to 600 µSv/h). . . . . . . . . . . . . 17

Figure 15: LYSO count rate as a function of discriminator threshold. . . . . . . . . . 19

Figure 16: LYSO dose rate response as a function of discriminator threshold. . . . . . 19

Figure 17: BGO count rate as a function of discriminator threshold. . . . . . . . . . 20

Figure 18: BGO dose rate response as a function of discriminator threshold. . . . . . . 21

Figure 19: Temperature chamber with RN PCB inside. . . . . . . . . . . . . . . 22

Figure 20: LYSO dose rate response as a function of discriminator threshold and temperature. . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Figure 21: BGO dose rate response as a function of discriminator threshold and temperature. . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Figure 22: LYSO temperature sensitivity near nominal discriminator threshold. . . . . 24

Figure 23: BGO temperature sensitivity near nominal discriminator threshold. . . . . . 24

Figure 24: Picoammeter test configurations. . . . . . . . . . . . . . . . . . . . 26

Figure 25: Series resistor test configurations. . . . . . . . . . . . . . . . . . . 27

DRDC-RDDC-2017-R130 v

List of tables

Table 1: Off-the-shelf RN sensor technology options. The suitability of these options is assessed for use in SASNet. Grey/yellow/red colours indicate whether the option is suitable/questionable/unsuitable. . . . . . . . . . . . . . . . 4

Table 2: Candidate scintillator materials for RN detection in SASNet nodes. The temperature dependence is at -20°C and +50°C compared to the response at +20°C. Grey/yellow/red colours indicate whether the option is suitable/questionable/unsuitable. . . . . . . . . . . . . . . . . . . . 5

Table 3: Read software protocol commands. . . . . . . . . . . . . . . . . . . 7

Table 4: Write software protocol commands. . . . . . . . . . . . . . . . . . 8

Table 5: Recommended start-up sequence. . . . . . . . . . . . . . . . . . . 9

Table 6: Increase in count rate with reduced ambient temperature. . . . . . . . . . 25

Table 7: Digital voltmeter readings. . . . . . . . . . . . . . . . . . . . . . 27

vi DRDC-RDDC-2017-R130

Acknowledgements

The authors would like to thank Vincent Palermo from Vertilon Corporation for his assistance and design of the new SASNet PCBs for RN detection. We would like to thank Pierre-Luc Drouin of DRDC – Ottawa Research Centre for helping with the down-selection of detector materials to use for RN detection in SASNet. We would also like to acknowledge the SASNet scientific lead at DRDC – Valcartier Research Centre, Benoit Ricard, for his vital support in determining the specifications for the new PCBs so that they work in the SASNet nodes. Finally, we would like to thank CANSOFCOM and CJIRU for their support of this development work.

DRDC-RDDC-2017-R130 1

1 Introduction

The Self-healing Autonomous Sensor Network (SASNet) is a prototype wireless sensor network (WSN) that was developed for the Canadian Army in a technology demonstration project carried out by the Communications Research Centre (CRC) and Defence Research and Development Canada (DRDC) – Valcartier Research Centre [1]. The original SASNet nodes (i.e., the individual units in the WSN) have no capability for the detection of radiological or nuclear (RN) material, but in 2014, the Canadian Joint Incident Response Unit (CJIRU) of the Canadian Special Operations Forces Command (CANSOFCOM) requested that DRDC investigate the possibility of adding an RN detection capability to SASNet.

2 DRDC-RDDC-2017-R130

2 RN sensor requirements for SASNet

In general, the requirements for RN detection as part of a WRSN are that the RN detection components should be:

small in size;

light;

operational for months at a time (i.e., low power);

“disposable” (i.e., low cost);

robust;

“false alarm free” (or at least an acceptably low rate); and

as sensitive as possible (subject to the other constraints).

Having all these criteria optimized individually but simultaneously is obviously impossible, so design trade-offs must be made. In addition, there are some hard constraints imposed by the requirement to integrate the RN detection capability with the existing SASNet sensor nodes.

One of the most challenging constraints is that there is very limited, unused space inside the original SASNet nodes. Figure 1 shows the outside of a SASNet node (approximately 10 cm tall), and Figure 2 shows the interior of the back of an open node. The total volume available for the active detector material (scintillating crystal, semi-conductor or gas detector) is on the order of 1 cm3.

Figure 1: Exterior of SASNet sensor node.


Figure 2: Interior of SASNet node (back cover removed).

In order to determine which detector material would be best to incorporate into the SASNet nodes, we compiled the relevant properties of different, commercial-off-the-shelf (COTS) candidate detector materials in Table 1. We considered size (also a proxy for weight), cost, temperature and humidity response (related to robustness of technology), power requirements, and sensitivity for radiation detection. In Table 1, grey cells indicate that the detector technology is suitable for SASNet. Yellow indicates there may be problems. Red indicates features which eliminate the technology from further consideration. Gas detectors, silicon semi-conductor detectors, cadmium-zinc-telleride (CZT) semi-conductor detectors, and scintillator detectors using photo-multipliers (PMTs) for light detection are not suitable: (a) gas detectors have a very low sensitivity due to the low density of the active material; (b) due to their small size, silicon semi-conductor detectors have low sensitivity for radiation detection compared to scintillators; (c) CZT detectors are far more expensive than any other options (>$3,000 for 1 cm3 crystal); (d) PMTs are not suitable due to their large size. As the only technology option not eliminated, we chose to pursue scintillators with silicon photomultipliers (SiPMs). This technology may have problems due to the temperature sensitivity of the SiPMs; however, if this is a significant problem, the temperature sensitivity can be compensated for in hardware or software (more to follow in Section 4).

2.1 Scintillator and SiPM requirements

In order to determine the best scintillator materials for this WRSN application, we considered a number of different scintillator material properties: (a) scintillation photons per MeV of deposited energy, (b) temperature dependence of number of scintillation photons, (c) time decay constant for the scintillation light, (d) cost per cubic centimetre, (e) density and atomic number (Z) (both affect the sensitivity for gamma-ray detection), and (f) whether the material is hygroscopic (those that are may be less robust).

Having a high scintillation light yield per MeV is advantageous if the crystals are ever used for spectrometric applications. If the photon yield is less sensitive to temperature this can help with the robustness of the RN detection. A short time constant allows for high count rates without


saturation effects. It is important that the cost per cm3 be low compared to the overall cost of each SASNet node to keep the nodes “disposable”. Finally, scintillators with high density and high Z will tend to be more sensitive as gamma-rays are more likely to interact with them. The four scintillator materials we considered are listed in Table 2. We excluded cadmium tungstate (CdWO4) and sodium-activated cesium iodide (CsI(Na)) as the former has a very long decay constant of 14 micro-seconds, and the latter is hygroscopic. Both bismuth germanate (BGO) and (cerium-doped) lutetium-yttrium oxyorthosilicate (LYSO) are somewhat temperature dependent in their scintillation photon yield, but we expect their dependence will not harm their radiation detection adversely. We opted to instrument half of the ten prototype SASNet RN PCB boards with 1 cm3 BGO crystals, and half with 1 cm3 LYSO crystals. In order to test two different scintillator geometries, we purchased cubic 10 mm × 10 mm × 10 mm LYSO crystals from Epic Crystals [2] and rectangular 7 mm × 7 mm × 20 mm BGO crystals from Omega Piezo [3]. Our main motivation for this geometrical difference was that we were originally uncertain if the cubic scintillators would fit inside the SASNet nodes (they do fit).

Table 1: Off-the-shelf RN sensor technology options. The suitability of these options is assessed for use in SASNet. Grey/yellow/red colours indicate whether the option is

suitable/questionable/unsuitable.

Technology Option Size Cost Temperature Humidity Power Sensitivity

Gas ok low ok ok ok low

Semi-conductor (Silicon)

ok low ok ok ok low

Semi-conductor

(CZT) ok high ok ok ok ok

Scintillator + PMT big low ok ok,

bad (PMT) ? ok

Scintillator + SiPM ok low ? ok ok ok


Table 2: Candidate scintillator materials for RN detection in SASNet nodes. The temperature dependence is at -20°C and +50°C compared to the response at +20°C. Grey/yellow/red colours

indicate whether the option is suitable/questionable/unsuitable.

Scintill-ator

photons/MeV

Temperature dependence

(-20C to +50 C)

Decay const. (ns)

Cost/cm3

($) Density (g/cm3) Z Hygro-

scopic

BGO 8,000 1.5, 0.6 300 30 7.1 75 no

CdWO4 12,000 0.95,0.98 14,000 69 8.0 64 no

LYSO 32,000 1%/deg 41 110 7.1 66 no

CsI(Na) 41,000 0.8,0.6 630 39 4.5 54 yes

In addition to ensuring that appropriate scintillator materials are chosen, we must also choose a suitable SiPM to couple to the scintillator. SiPMs operate at much lower voltages than PMTs and also draw less power. We opted for surface mounted, C-series 6 mm x 6 mm SensL SiPMs with 35 micron pitch for the avalanche photodiodes (MircoFC-60035-SMT-TA) [4]. Their operating voltage is typically under 30 V and they have a thickness of only 0.65 mm. The temperature dependence of the SiPMs results in a reduction in gain of a factor of two going from -20°C to +50°C.


3 SASNet RN prototype PCB

The SASNet RN prototype PCB (RN PCB) was developed under contract by Vertilon Corporation. The RN PCB is a modified version of a previous SASNet board: redundant components were removed from the old board in order to make room for the SiPM, BGO or LYSO crystal and associated read-out electronics. The new RN PCB also includes logic that supports an existing infra-red (IR) communications port used by the SASNet node. This allows one to program the RN PCB from outside the SASNet node. The IR port and RN detection systems are separated by the use of a digital enable signal line (ENB). When the line is “low”, the IR port is enabled and when it is “high” the RN portion of the board is active.

After delivery of the prototype RN PCBs from Vertilon, we performed experiments to verify that the RN PCB met three primary requirements:

1. allows communications to ensure pre-determined commands were accepted and responses were returned as specified by the manufacturer;

2. provides an approximately linear gamma-ray dose rate response with the two scintillation detector types selected for this application;

3. meets power requirement design specifications.

Figure 3 shows a photograph of the RN PCB.

Figure 3: Prototype RN PCB.

Comm port

SiPM

Electronic Serial Number dip switches


4 Verification of RN PCB requirements

In order to determine if the RN PCB met the minimum requirements of the contract, three main types of experiments were performed:

Control of RN detection hardware and data retrieval

Dose rate response

Power consumption

The following sub-sections provide details about these experiments.

4.1 Communication response

The SASNet node must be able to control its hardware and retrieve data from the RN PCB on a demand basis.

The communication protocol, as designed by the manufacturer of the RN PCB [5], is formatted in two parts. First an address command is asserted which distinguishes what part of the RN PCB is being accessed. Second, data are sent to or received from the RN PCB. Each packet of information, command or data, is 16 bits each.

4.1.1 Protocol

Tables 3 to 5 outline the communication protocol.

Table 3: Read software protocol commands.

Addr Function Data Hex Value Default

x6000 Device ID xA55A xA55A

x6040 Electronic Serial Number (ESN) x0000 to x00FF x0000

x6180 Event Count / Counter Status Bit 11 to Bit 0 = Count; Bit 12 = Overload

x0000


Table 4: Write software protocol commands.

Addr Function Data Hex Value Default

x4060 Global Enable / Disable xC000 = Enable, x8000 = Disable, x0000 = Transparent

Disable

x4080 SiPM Bias Enable x8000 = Enable, x0000 = Disable Disable

x40A0 Discriminator Enable x8000 = Enable, x0000 = Disable Disable

x40C0 Dual DAC Enable x8000 = Enable, x0000 = Disable Disable

x40E0 Counter Enable x8000 = Enable, x0000 = Disable Disable

x4100 Counter Man/Auto Reset Mode x8000 = Manual, x0000 = Auto Auto

x4120 Reset Counter x8000 = Reset, x0000 = No Op No Op

x41A0 DAC Power Mode xD000 = Normal, xC000 = Standby xE0000 = Shutdown

Standby

x41C0 SiPM Bias Control x0000 = 29.5 V, x0FFF = 24.5 V 24.5 V

x41E0 Discriminator Threshold Control X0000 = 0.000 V, x0FFF = 1.214V 0.000 V


Table 5: Recommended start-up sequence.

Addr Function Data Hex Value

x6000 Read Device ID xA55A

X6040 Read Electronic Serial Number x0000 to x00FF

x4060 Set Global Enable / Disable to Transparent x0000

x40C0 Enable Dual DAC only x8000

x41C0 Set SiPM voltage x0000 to x0FFF

x4060 Enable all hardware xC000

x41E0 Set discriminator threshold x0000 to x0FFF

x6180 Read event counts / counter status x0000 to x2000

4.1.2 Testing the serial interface

The RN PCB signal interface from the SASNet node (shown in Figure 3 as the “Trans Serial” connector) emulates a Serial Peripheral Interface (SPI) single data line configuration. In total, the communication interface to the RN PCB requires four signal wires plus 3.3 V power and ground connections. The four signals (as described by the RN PCB user manual [5]) are:

DIO—The bi-directional data input/output line. Every serial transfer cycle begins with this line acting as an input receiving an address to the serial controller. For write commands from the master, this line remains as an input and receives the programming data to the PCB hardware. For read commands, this line switches to an output after 17 clock cycles and transfers 16 bits of data that can include configuration data or the event count.

CS—This input signal is used as a chip select to the serial controller. Data can be written to and read from the controller only when this signal is low and enable (ENB) is high.

CLK—The serial clock to the interface. Thirty-two (32) clock cycles are required from the start of CS to completely shift in the address and programming data or shift out the configuration / count data on the DIO line.

ENB—This signal unconditionally disables the RN portion of the PCB when low. As a result, all controller configurations are reset and all external hardware is turned off.


Figure 4: Serial interface timing.

4.1.3 Signal connections

In order to communicate with the RN PCB, a small, single-board Raspberry Pi computer was selected as an interface. The Raspberry Pi has a fully programmable General Purpose Input/Output (GPIO) port which was used to create each of the four signals in the above section.

The port is fully accessible via software programming control. In this case, we wrote C++ code which includes the WiringPi header file [6].

4.1.4 Interfacing the Raspberry Pi

Using the Raspberry Pi as the interface proved to be challenging. While the Pi does have an SPI port within the GPIO header, it is a dual SPI interface where the data in and out are two separate signal lines; therefore, the SPI port could not be used.

Instead, from the GPIO port the following signal lines were selected:

Pin 11 – GPIO17 – CLK

Pin 12 – GPIO18 – CS

Pin 15 – GPIO22 – DIO

Pin 16 – GPIO23 – ENB

In order to connect the two boards, first we devised a method to bring the signals off the RN PCB: this was accomplished by soldering half of an integrated circuit (IC) socket onto the board and then short, pre-fabricated wires with pin terminations (which came with the Raspberry Pi kit) were inserted in the socket. Next we made a short ribbon cable that could connect to the Pi but keep the signal length short to minimize noise. The signal wires could then be inserted directly into the ribbon cable. In order to verify that the signals were propagating properly to the RN PCB, they were monitored with an oscilloscope attached to a small breadboard which came with the Raspberry Pi.


Figure 5: Signal wires for RN PCB.

Figure 6: Raspberry Pi—GPIO signal monitoring.

The code had to be configured such that the data were properly clocked in the SPI format. In this case, data are valid only on the rising edge of the clock pulse; therefore, the signal clock and data had to be properly aligned. This alignment (for a device ID request) can be seen in the oscilloscope capture image in Figure 7.


Figure 7: Oscilloscope capture of device ID request.

The device ID request is constituted by address x6000 being sent to the RN PCB with the return data xA55A; in binary these are 0110000000000000 and 1010010101011010 respectively. In Figure 7, the signal clock is represented by trace 1 (in yellow) and the data are represented by trace 3 (in purple). Figure 7 also shows that CS (trace 2 in blue) must be low and ENB (trace 4 in green) must be high for valid data to be returned.

4.2 Dose rate response

Once it was established that the RN PCB was responding as intended to the communication protocols, the next step was to determine if the radiation detection portion (the most important aspect) of the unit was functional.

Gamma detection is achieved through the use of a scintillation crystal mounted on top of a digital light amplification device (SiPM) which feeds analog voltage signals to analog-to-digital conversion (ADC) circuitry. The SiPM requires a positive bias voltage in order to operate. Radiation detection is achieved, as per the manufacturer specifications [5] and shown in Figure 8, by converting the radiation-event-induced current pulse signal from the SensL SiPM into a voltage by a 200 Ω load resistor (“R” in Figure 8). The pulse’s voltage is added to a +25 mV offset that is used to keep all circuitry within the 0 V to +3V constraint of the power supply. This voltage is compared in a discriminator to a threshold that is set through the serial interface. When the threshold is crossed, a digital pulse is produced.


The SiPM bias can be varied from 24.5 to 29.5 V to control the gain of the SiPM. The gain can be varied to offset changes in the SiPM response due to changes in ambient temperature. There are 4095 bins which represent these voltage levels (or 1.22 mV per bin).

Figure 8: System block diagram for pulse counting of RN PCB.

The discriminator threshold (maximum = 1.214V) is also subdivided into 4095 bins (296 mV per bin). The manufacturer recommends setting the discriminator threshold above the 25 mV offset mentioned above. For these tests, a minimum value of 36 mV was used (or 3% of the maximum discrimination setting).

SiPM signal pulses are counted and stored locally on the RN PCB and then transferred to the master on a demand basis. As stated above, the maximum number of counts that can be stored locally is x0FFF (in hexadecimal) or 4096, an overflow is indicated by x1FFF or 8192 counts.

There were two types of gamma-ray scintillators tested:

1. lutetium-yttrium oxyorthosilicate (LYSO), and

2. bismuth germanate (BGO)

Each crystal was hand-wrapped with Teflon tape in order to maximize light detection by the SiPM: the Teflon tape reflects photons that would otherwise leave the scintillator crystals. An area of approximately 6 × 6 mm2 (the area of SiPM) was left unwrapped for the interface to the SiPM.

The ultimate configuration SASNet nodes will require the scintillator crystals to be permanently affixed to the SiPMs (and PCBs) by an optically transparent, adhesive compound (e.g., EJ-500 optical cement [7]). For this experiment the wrapped crystal was placed on top of the SiPM and simply held in place by tape attached to the PCB. The prototype RN PCB was then placed in a light-tight enclosure.


Figure 9: RN PCB in its light-tight box.

The SASNet radiation detectors (scintillators plus RN PCBs) were irradiated by Co-60 and Cs-137 sources (DRDC’s AN/UDM-1 and AN/UDM-1A fixed sources, respectively) at specific distances. The sources are well-calibrated by distance and each has three radiation levels of operation: low, medium and high.

Some preliminary testing with the Co-60 source was done to determine a nominal SiPM bias voltage and discriminator setting that would work for dose rates from 2 to 2,000 µSv/h. For the RN PCB with a LYSO crystal, 27.5 V bias and 20% discriminator threshold were selected. For the BGO crystal, 29.0 V bias and 5% discriminator threshold were selected.


Figure 10: RN PCB irradiation using the AN/UDM-1A Cs-137 source.

Count data from the RN PCB was downloaded to the Raspberry Pi and stored in a separate data file for each exposure. The data were subsequently transferred to a computer for offline analysis.

4.2.1 Dose rate response for RN PCB with BGO and LYSO crystals

The RN PCB was exposed to the (1173.2 and 1332.5 keV) Co-60 source first, and the (661.7 keV) Cs-137 source. Data for the two sources are shown in Figures 11 and 12. As can be seen from the BGO data, the Co-60 response is only plotted up to 600 µSv/h. The unit’s count rate saturates above this dose rate. The response of the BGO and LYSO detectors, in CPS per µSv/h, is significantly different due to the different operating voltages for the SiPM and the different discriminator thresholds. The SiPM bias voltage was set to 29.0 V and 27.5 V for the BGO and LYSO detectors, respectively. The discriminator thresholds were set to 5% (BGO) and 20% (LYSO) of the reference voltage. Each of these settings increased the sensitivity of the BGO detector compared to the LYSO detector, so that even though the LYSO crystal produces four times more scintillation photons per eV of gamma ray energy deposited (see Table 2), the BGO detector is approximately two times more sensitive for detecting Co-60 gamma rays (see Figures 13 and 14). The difference is even larger for Cs-137 gamma rays (again, see Figures 13 and 14) as the vast majority of the Cs-137 gamma ray interactions in the LYSO crystal produce pulses that are below the relatively high (20%) discriminator threshold.


Figure 11: LYSO/BGO dose rate response (0 to 2000 µSv/h). Note that the SiPM operating voltages and discriminator thresholds are different for the BGO and LYSO detectors.

Figure 12: LYSO/BGO dose rate response (0 to 600 µSv/h). A more detailed view of the low dose rate portion of Figure 11.


Another way of looking at the data is to map out the background-subtracted count rate response relative to the dose rate. These data are shown in Figure 13.

Figure 13: LYSO and BGO count rate responses (0 to 2000 µSv/h).

Figure 14: LYSO/BGO count rate response (0 to 600 µSv/h).


The mean count rate responses are:

Co-60: LYSO = 3.09 ± 0.50 CPS per µSv/h,

BGO = 5.61 ± 0.28 CPS per µSv/h

Cs-137: LYSO = 0.03 ± 0.01 CPS per µSv/h,

BGO = 0.94 ± 0.23 CPS per µSv/h

4.2.2 Dose rate response as a function of discriminator threshold

In these experiments, the detector (with BGO or LYSO crystal) was placed at a fixed distance in front of the Cs-137 and Co-60 sources (for a constant dose rate). The SiPM bias voltage was kept at the voltages previously used: 27.5 V for LYSO and 29.0 V for BGO. The discriminator threshold was varied from relatively low to high values (5% to 27.5% of the maximum value for LYSO, and 3% to 9.5% for BGO). Count rate data were recorded for background only, a low exposure rate (for each isotope), and a medium exposure rate (for each isotope). The data were analysed to provide the raw count rates (Figures 15 and 17), and the background-subtracted count rate responses (Figures 16 and 18). Figure 15 shows that even with the intrinsic background of the LYSO crystal (beta-gamma decays of Lu-176), the background count rate was always significantly below signal count rates, except for the low rate (15 µSv/hr) Cs-137 signal with the discriminator threshold above 12.5%. This indicates that with the LYSO crystal and SiPM at 27.5 V, the discriminator should be set to 12.5% or less in order to detect Cs-137 reliably. The high rate Cs-137 exposure causes the count rate to saturate for discriminator thresholds below 12.5%, but this is acceptable if the SASNet nodes are used simply to detect the presence of radiation (and not quantify the source of radiation).


Figure 15: LYSO count rate as a function of discriminator threshold.

Figure 16: LYSO dose rate response as a function of discriminator threshold.

Figure 16 indicates that the Cs-137 dose rate experienced by the LYSO crystal (with a SiPM at 27.5 V) must be less than somewhere between 9 and 533 µSv/h in order to obtain a linear response between applied dose rate and count rate. The Co-60 data in Figure 16 show an approximately linear response for dose rates of 19 and 190 µSv/h.


The background count rate in the BGO-based detector is much lower as there is no intrinsic background in BGO. The Cs-137 and Co-60 signals are significantly greater than the background except for the low rate Cs-137 signal using discriminator thresholds above 6.5%. This indicates that the photopeak from Cs-137 is below this threshold. As a result, a lower threshold should be used if one wants to detect Cs-137. Although the count rate saturates for the high rate Cs-137 source for discriminator thresholds at or below 4%, there is no concern with saturation if the purpose of the SASNet radiation detectors is simply to detect the presence of a radioactive source. The discriminator threshold could be set to 3% in order to have a high sensitivity to weaker sources of radiation than those tested for this work.

Figure 17: BGO count rate as a function of discriminator threshold.


Figure 18: BGO dose rate response as a function of discriminator threshold.

The BGO dose rate response shown in Figure 18 shows a linear response to Co-60, similar to the LYSO response. The Cs-137 count rate saturates below 4% threshold for the 533 µSv/h dose rate.

4.2.3 Temperature dependence of dose rate response

During the course of the dose rate testing it was noted that there were some variations between runs when testing with the Co-60 source (several tests were performed). The conclusion was that this was potentially due to a variation in the temperature of the room. As such, it was decided to perform a series of measurements with the detectors inside a temperature chamber.

A low activity Co-60 source was placed inside the chamber with the RN PCB unit and either the BGO or LYSO crystal such that there were a few hundred counts per second at room temperature. A repeat of the discriminator threshold measurements from the previous section was performed across a range of pre-set temperatures. The unit was allowed to acclimate at each temperature for one hour before each set of measurements was taken.

The Co-60 source used for this experiment was a NIST calibrated source. The applied dose rate to the RN PCB was calculated using the RadPro [8] calculator and the decay-corrected activity of the source. The calculation yielded a dose rate estimate at the detector of 73.6 µSv/h. Figures 20 to 23 summarize the measurements that were taken. Figures 20 and 21 demonstrate that as the temperature increases, the count rate decreases (for a constant discriminator threshold). This is consistent with expectations of the temperature response of the SiPM: the SiPM’s gain is reduced as the temperature increases, so fewer events fall above the discriminator threshold, diminishing the count rate.


Figure 19: Temperature chamber with RN PCB inside.

Figure 20: LYSO dose rate response as a function of discriminator threshold and temperature.


Figure 21: BGO dose rate response as a function of discriminator threshold and temperature.

In Figures 22 and 23 we zoom in to enhance the view around the discriminator thresholds used for the main experiments (i.e., 20% for LYSO and 5% for BGO).


Figure 22: LYSO temperature sensitivity near nominal discriminator threshold.

Figure 23: BGO temperature sensitivity near nominal discriminator threshold.


Table 6 shows the changes in the count rate with respect to the rate at 30°C. The discriminator thresholds are the “standard” 20% for LYSO and 5% for BGO. The difference between the LYSO and BGO data is at least partly due to the different SiPM bias voltages and discriminator thresholds. The temperature sensitivities of LYSO1 and BGO2 are different, but BGO’s light yield temperature sensitivity is actually larger: approximately 41% reduction from 30°C to 0°C, while LYSO’s reduction is expected to be only 8.4%. The reduction in count rate depends very much on where the photopeak and Compton edge (whose amplitudes vary with temperature) sit with respect to the discriminator threshold. A detailed analysis is beyond the scope of this report.

Table 6: Increase in count rate with reduced ambient temperature.

Temperature (°C) LYSO (%∆) BGO (%∆) 30.0 0 0 22.5 49.3 21.3 20.0 64.6 30.9 17.5 74.3 37.4 15.0 88.2 40.3 12.5 96.8 48.9 10.0 111.8 56.5 7.5 112.0 55.6 5.0 110.5 56.7 2.5 119.4 55.4 0.0 115.9 58.4

4.3 Power measurements

The third portion of the testing was to determine the power utilization of the RN PCB.

The contract statement of work stipulated that:

the active power consumption will be less than 1 mA average, and less than 10 mA peak; and

standby power consumption will be less than 50 µA.

Two methods were used to determine the power consumption. These are detailed in the following sub-sections.

1 The average temperature coefficient for light yield from LYSO from +25 to +50°C (%/°C) is -0.28% [9]. 2 The average temperature coefficient for light yield from BGO from -30 to +30°C (%/°C) is -1.38% [10].


4.3.2 Series resistor method

Figure 25: Series resistor test configurations.

For this method, a 29 Ω resistor was placed in series on the 3.3V power line between the Raspberry Pi and the RN PCB. The voltage drop across the resistor was measured with a digital voltmeter (DVM) using the millivolt scale. This setup allowed the RN PCB to function normally, plus the DVM data seemed reasonable given expected values provided by the contractor. Table 7 shows what conditions were applied to the RN PCB and the resulting currents that were measured.

Table 7: Digital voltmeter readings.

Condition—software commands to RN PCB Current (µA) ENB—Enable Line LOW (rad circuitry disabled / IR enabled) 4820

ENB HIGH, Global Enable sent 308 ENB HIGH, HV Enable sent 250 ENB HIGH, Get count data 133

ENB HIGH, Global Disable sent 133 ENB HIGH, DAC Power Mode Disable sent 133

From these measurements, our conclusion is that the overall requirement of an average power consumption < 1 mA is met; however, we measured a minimum current draw 133 µA which is greater than the stipulated value of 50 µA. After discussions with the contractor, it was decided that the RN PCB did meet the lower current specifications. Our use of a Raspberry Pi caused problems for the lower current measurements due to our lack of complete information about the Pi’s operating characteristics while connected to the RN PCB. The contractor employed test circuitry that was quite different (it did not rely on a Raspberry Pi); their detailed test results were shared with us and they showed that the RN PCB did achieve its power requirement objectives.


5 Future work

Despite the success of the work described in this report, a significant amount of work remains to be done before SASNet is ready to detect sources of radiation. Additional work could also be done to optimize the design of the radiation detection portion of SASNet.

The work that must be done before SASNet is “radiation ready” is summarized below.

1. The BGO and/or LYSO crystals must be permanently mounted to the SiPM on the RN PCB and made light-tight. All of our tests involved the crystals resting on top of the SiPM, but not permanently attached. The crystals and RN PCB were placed in a temporary, light-tight box for our measurements. We have discussed possible mounting and light-tight schemes with our collaborators at Valcartier Research Centre, but there was not sufficient time to investigate these.

2. After mounting the crystals, the RN PCBs must be incorporated into the SASNet nodes. We tested that the PCBs fit, but the PCBs have not been connected to the rest of the SASNet PCBs and circuitry to ensure that they compatible with each other.

3. The count rate threshold(s) for generating a radiation alarm must be determined. Figures 15 and 17 are instructive for making this decision, but the false alarm rate that will result from a specific threshold must be determined after consultation with military users. The count rate threshold will also depend on the crystal that is used and the type of radiation threats that will be considered relevant.

4. Code should be written for the SASNet nodes to correlate multiple radiation measurements together and generate a “global” alarm. Cross-correlating radiation detections in multiple detectors will help to significantly reduce false alarm rates with a minor impact on detection sensitivity.

In addition to the above work, some optimization studies could be pursued to maximize the effectiveness of SASNet for military radiation detection applications:

1. If a temperature sensor is incorporated in the SASNet unit then some temperature compensation can be applied to the count rate data. Our temperature testing showed the count rate can vary as much as 50% for the BGO and over 100% for the LYSO, just in the temperature region from 0 to 30°C. If no temperature sensor is available then a high detection threshold would have to be established to keep false alarm rates to an acceptable level and the minimum detectable limit would be correspondingly low.

2. With the SiPM bias voltages and discriminator thresholds we used for this work the BGO crystal performed better than the LYSO for lower energy gammas (i.e., Cs-137 662 keV gammas); however, much work could be done to optimize the SiPM voltages and discriminator thresholds for the two crystals. It would be very interesting to test the unit with lower energy gamma-ray sources like Am-241 to see how the crystals respond.


3. More extensive testing with a larger number of crystals could also be done to ensure that the results that are obtained are representative of a large population of crystals. Ultimately, this could lead to a decision regarding a superiority of BGO or LYSO for SASNet radiation detection. The experiments required to make this decision were beyond the scope of this report.


6 Conclusion

Our main conclusion is that the RN PCB with either a BGO or LYSO crystal functions as required by the contract’s statement of work. With either crystal, we demonstrated that radiation sources of different energies and dose rates could be easily detected. Temperature sensitivity of the count rates was observed, but this can be compensated for by adding temperature-based voltage compensation for the SiPMs and/or software corrections in SASNet. The RN PCB had a very low current draw while operating and in a stand-by state. This will make it amenable for use in SASNet for a range of military applications.

There are a number of tasks for future work before SASNet is ready to detect radiation, but they could be accomplished quickly (less than a year) with sufficient resources (two dedicated people). Ultimately, this could provide a novel, effective tool in the CAF’s tool box for radiation detection.


References

[1] D. Waller, I. Chapman, M. Michaud-Shields, “Concept of Operations for the Self-healing Autonomous Sensor Network,” DRDC CORA TM 2008-052, Defence R&D Canada, July 2009.

[2] Epic Crystal, http://www.epic-crystal.com/shop_reviews/lyso-scintillator (Access Date: July 27, 2017).

[3] Piezo Omega, http://omegapiezo.com/crystal_scintillators.html (Access Date: July 27, 2017).

[4] SensL website (online), http://sensl.com/estore/microfc-60035-smt/ (Access Date: May 28, 2017).

[5] SASNet Hardware & Software Manual (Rev. 04), Vertilon Corporation, 2017.

[6] Wiring Pi header file (online), http://wiringpi.com/download-and-install/ (Access Date: May 1, 2017).

[7] Eljen Technology Optical Cement (online), EJ-500 http://www.eljentechnology.com/products/accessories/ej-500 (Access Date: July 27, 2017).

[8] RadPro Calculator (online), http://www.radprocalculator.com/Gamma.aspx (Access Date: May 1, 2017).

[9] St Gobain Crystals – LYSO data sheet, http://www.crystals.saint-gobain.com/sites/imdf.crystals.com/files/documents/lyso-material-data-sheet.pdf (Access Date: August 9, 2017).

[10] P. Wang, Y. Zhang, Z. Xu, X. Wang, “Study on the temperature dependence of BGO light yield,” Sci China-Phys Mech Astron 57 (2014) pp. 1898–1901.

http://www.epic-crystal.com/shop_reviews/lyso-scintillator

http://omegapiezo.com/crystal_scintillators.html

http://sensl.com/estore/microfc-60035-smt/

http://wiringpi.com/download-and-install/

http://www.eljentechnology.com/products/accessories/ej-500

http://www.radprocalculator.com/Gamma.aspx

http://www.crystals.saint-gobain.com/sites/imdf.crystals.com/files/documents/lyso-material-data-sheet.pdf

http://www.crystals.saint-gobain.com/sites/imdf.crystals.com/files/documents/lyso-material-data-sheet.pdf


List of symbols/abbreviations/acronyms/initialisms

ADC Analog-to-Digital Conversion

BGO bismuth germanate oxide

CANSOFCOM Canadian Special Operations Forces Command

CJIRU Canadian Joint Incident Response Unit

COTS Commercial-off-the-Shelf

CRC Communications Research Centre

CZT cadmium-zinc-telleride

DRDC Defence Research and Development Canada

ENB Enable

GPIO General Purpose Input/Output

IC Integrated Circuit

LYSO lutetium yttrium silicon oxide

PCB Printed Circuit Board

PMTs Photo-Multipliers

R&D Research & Development

RN Radiological/Nuclear

SASNet Self-Healing Autonomous Sensor Network

SPI Serial Peripheral Interface

SiPM Silicon Photo Multiplier

WRSN Wireless Radiation Sensor Network

WSN Wireless Sensor Network

DOCUMENT CONTROL DATA (Security markings for the title, abstract and indexing annotation must be entered when the document is Classified or Designated)

1. ORIGINATOR (The name and address of the organization preparing the document. Organizations for whom the document was prepared, e.g., Centre sponsoring a contractor's report, or tasking agency, are entered in Section 8.) DRDC – Ottawa Research Centre Defence Research and Development Canada 3701 Carling Avenue Ottawa, Ontario K1A 0Z4 Canada

2a. SECURITY MARKING (Overall security marking of the document including special supplemental markings if applicable.)

CAN UNCLASSIFIED

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(NON-CONTROLLED GOODS) DMC A

3. TITLE (The complete document title as indicated on the title page. Its classification should be indicated by the appropriate abbreviation (S, C or U) in parentheses after the title.) Self-healing Autonomous Sensor Network (SASNet) Radiological/Nuclear (RN) prototype Printed Circuit Board (PCB) testing

4. AUTHORS (last name, followed by initials – ranks, titles, etc., not to be used) Jones, T.; Waller, D.

5. DATE OF PUBLICATION (Month and year of publication of document.) September 2017

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38

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e.g., interim, progress, summary, annual or final. Give the inclusive dates when a specific reporting period is covered.) Scientific Report

8. SPONSORING ACTIVITY (The name of the department project office or laboratory sponsoring the research and development – include address.) DRDC – Ottawa Research Centre Defence Research and Development Canada 3701 Carling Avenue Ottawa, Ontario K1A 0Z4 Canada

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06be

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10a. ORIGINATOR’S DOCUMENT NUMBER (The official document number by which the document is identified by the originating activity. This number must be unique to this document.) DRDC-RDDC-2017-R130

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13. ABSTRACT (A brief and factual summary of the document. It may also appear elsewhere in the body of the document itself. It is highly desirable that the abstract of classified documents be unclassified. Each paragraph of the abstract shall begin with an indication of the security classification of the information in the paragraph (unless the document itself is unclassified) represented as (S), (C), (R), or (U). It is not necessary to include here abstracts in both official languages unless the text is bilingual.)

The Self-healing Autonomous Sensor Network (SASNet) is a prototype, wireless sensor network originally developed for the Canadian Army. The goal of the current work is to integrate a Radiological/Nuclear (RN) detector into the SASNet sensor nodes. The electronics were specially designed to ensure that the power consumption of the RN sensor will be very low (< 1mA); this will allow SASNet sensor nodes to operate remotely for many months on a single 3.5 V battery. The resulting printed circuit board (PCB) was designed to have the electronics and RN sensor package fit inside the existing SASNet node without modification to the form factor or enclosure. The RN sensor packages included a high-atomic number, high density scintillating crystal (bismuth germanate oxide, BGO, or lutetium yttrium silicon oxide, LYSO) and a silicon photomultiplier (SiPM).

Vertilon Corporation was contracted to produce twelve prototype PCBs (six with LYSO crystals, six with BGO). Two of the units (one with LYSO and one with BGO) were evaluated at DRDC – Ottawa Research Centre with radioactive sources. This report summarizes these measurements. The PCBs were not integrated into the SASNet node at this time. This work will be performed in the future at Valcartier Research Centre (who lead the ongoing development of SASNet). ---------------------------------------------------------------------------------------------------------------

Le Réseau de capteurs autonomes à autorétablissement (SASNet), est un prototype sans fil créé à l’origine pour le compte de l’Armée canadienne. Les travaux actuels ont pour but d’intégrer un détecteur radiologique et nucléaire (RN) aux nœuds de capteurs du réseau. Les composants électroniques du détecteur RN ont été spécialement conçus pour ne consommer que très peu de courant (moins de 1 mA) et permettre ainsi de faire fonctionner à distance chacun des nœuds de capteurs du réseau SASNet durant de nombreux mois avec une seule batterie de 3,5 V. La carte de circuits imprimés a été conçue pour qu’on y insère les composants électroniques et l’ensemble de capteurs RN à l’intérieur du nœud actuel du réseau SASNet sans modifier le facteur de forme ni le boîtier. Les ensembles de capteurs RN comportaient un cristal scintillant de BGO (oxyde de germanate de bismuth) ou de LYSO (oxyorthosilicate d’yttrium lutécium) à haute densité et numéro atomique élevé, ainsi qu’un photomultiplicateur au silicium (SiPM).

La production de douze prototypes de cartes de circuits imprimés (six aux cristaux de BGO et six autres aux cristaux de LYSO) a été confiée à Vertilon Corporation. Deux de ces cartes, soit une de chaque type, ont été évaluées au moyen de sources radioactives au CRO de RDDC. Le présent rapport résume les mesures obtenues dans le cadre de cette évaluation. Les cartes de circuits imprimés n’ont pas été intégrées au nœud du réseau SASNet à cette étape. Elles le seront plus tard au Centre de recherches de Valcartier (qui dirige la phase actuelle de développement du réseau SASNet).

14. KEYWORDS, DESCRIPTORS or IDENTIFIERS (Technically meaningful terms or short phrases that characterize a document and could be helpful in cataloguing the document. They should be selected so that no security classification is required. Identifiers, such as equipment model designation, trade name, military project code name, geographic location may also be included. If possible keywords should be selected from a published thesaurus, e.g., Thesaurus of Engineering and Scientific Terms (TEST) and that thesaurus identified. If it is not possible to select indexing terms which are Unclassified, the classification of each should be indicated as with the title.) radiation detection; wireless sensor network; low power; silicon photomultiplier; scintillator

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Self-healing Autonomous Sensor Network (SASNet ... · DRDC-RDDC-2017-R130 i Abstract The Self-healing Autonomous Sensor Network (SASNet) is a prototype, wireless sensor network originally