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Wireless Sensor Nodes for Acceleration, Strain and Temperature Measurements
Available online at www.sciencedirect.com
ScienceDirect Procedia Engineering 168 (2016) 1659 – 1662
30th Eurosensors Conference, EUROSENSORS 2016
Wireless Sensor Nodes for acceleration, strain and temperature measurements Z.Herrastia,*, I.Gabilondoa, J.Berganzoa, I.Vala, F. Martíneza a
IK4-Ikerlan Technology Research Centre, Arrasate-Mondragón, Spain
Abstract The presented sensor node contains a heterogeneous signal conditioning circuit and signal processing software, which has been validated for acceleration, strain and temperature measurements. The combination of accelerometers and strain gages, which are widely used for vibration, stress, fatigue and failure analysis, constitutes the main basis for the validation of structural health monitoring (SHM) applications. In recent years, SHM has become an essential part of structural and mechanical system maintenance and in that matter, recent advances in wireless sensor networks (WSN), have enabled the realization of low cost wireless structure monitoring systems. Accordingly, the signal acquisition of the presented nodes is performed through wireless synchronized communication. Furthermore, as structures are often located in hard to access environments, an approach to the development of an autonomous system has been made. Therefore, the system works autonomously as it is powered by a small rechargeable lithium-ion polymer battery reinforced by energy harvesting. © 2016 2016The TheAuthors. Authors. Published by Elsevier Ltd. is an open access article under the CC BY-NC-ND license © Published by Elsevier Ltd. This (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the 30th Eurosensors Conference. Peer-review under responsibility of the organizing committee of the 30th Eurosensors Conference Keywords: Wireless sensor node; SHM; generic signal conditioning circuit
1. Introduction In order to provide early warning of damage, sensor nodes are located at structures, which are often in hostile and hard to access environments. Consequently, there is a need of using autonomous sensor nodes with low power signal conditioning electronics, wide range measurement, synchronous data acquisition and reliable signal transmission within large scale-networks. In this respect, advances in wireless sensor networks and energy harvesting often go hand in hand [1]. Most energy management strategies proposed in the literature assume that data acquisition consumes
* Corresponding author. Tel.:+34 943 712400; fax: +34 943 796944. E-mail address: [email protected]
1877-7058 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the 30th Eurosensors Conference
doi:10.1016/j.proeng.2016.11.484
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significantly less energy than their transmission. However, this assumption does not hold in a number of practical applications where the power consumption of the sensing activity may be comparable or even greater than that of the radio [2]. For the reduction of the energy consumption two main approaches can be followed: duty cycling or adaptative sensing. Duty cycling consists in waking up the sensorial system only for the time needed to acquire a new set of samples and powering off immediately afterwards. A better approach would require an adaptative sensing strategy able to dynamically adapt the sensor activity to the real dynamics of the process. Like the developed wireless sensor nodes are based on a heterogeneous signal conditioning circuit, a few software changes in the signal acquisition circuit are sufficient for the sensing of different physical parameters as vibration, deformation and temperature. For energy consumption reduction, the duty cycling approach is followed, adapting the duty cycle, depending on the parameter that is being monitored. The fundamental advantages of the presented node with respect to traditional signal acquisition systems, is that it has a wireless synchronized signal acquisition with a synchronization jitter of ±1 μs between the different nodes within a network [3] and that it contains an energy harvesting module for reinforcing the rechargeable battery. Recently, wireless sensor nodes, such as the V-Link ® - LXSR® LORD sensing MicroStrain [4], are commercially available. This device can be used for measuring different physical parameters, but the synchronization jitter of this device is ±32 μs, far away from the ±1 μs that are achieved with the presented device. 2. Device description The autonomous sensor nodes developed in this work are formed by 3 PCB layers which are powered by a small rechargeable lithium ion polymer battery and are encapsulated in a device that is fabricated by stereo lithography, Fig. 1(a). It contains 3 modules: signal conditioning, radio for wireless communication and energy harvesting for power supply, Fig. 1(b), which are explained in more detail. The accelerometer, which is a piezoelectric accelerometer (Model 805M1) provided by measurement SPECIALITIES TM, is embedded inside the encapsulated device. 2.1. Generic signal conditioning module The generic signal conditioning circuit contains 4 building blocks, Figure 1(b). The functionality of the blocks is governed by an EFM 32 low power microcontroller. The building blocks are adjustable or programmable for each particular case. The prefilter adjusts the input signal of the PGA for the sensor that is being measured, i.e. accelerometer or strain gage. The PGA enables gains of 2.66 to 9600 and performs offset compensation, among other configurations, which are programmed through a one wire digital (1W) communication interface. The programmable filter cut frequency is tunable through the input clock frequency and finally, the 16-bit ADC converter transforms the analog input signal into a digital one. 2.2. Radio module When vibration monitoring is performed, deterministic timing behavior and synchronized sensing with a relatively high sampling frequency are needed. Therefore, in this work, a similar approach to industrial standards has been followed by placing a TDMA MAC on top of the physical layer, but specific synchronization elements have been added for obtaining synchronized Analog-to-Digital conversion in all nodes. The performance of these WSN synchronized acquisition has been validated in [5], where the method is implemented for a real time SHM system for trains. 2.3. Energy Harvesting module Solar and piezoelectric energy harvesting solutions have been analyzed. The energy provided by the harvester can be used to power the system or in situations where the energy provided is not sufficient, it could also be used to recharge the battery and extend its life. The analyzed harvesting solutions cannot provide unlimited energy to the system, but they can provide energy for signal acquisition and then, while the system is in idle state, they can store energy in energy storage capacitors.
Z. Herrasti et al. / Procedia Engineering 168 (2016) 1659 – 1662
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Fig. 1. (a) Sensor node: (left) encapsulated device; (right) electronic circuit formed by 3 PCB layers, 2 antennas and a small electronic circuit for half bridge strain measurements; (b) Sensor architecture.
3. Results and discussion 3.1. Energy harvesting module Piezoelectric and solar energy harvesting modules are analyzed and the best results are obtained with the solar harvester, which provides an energy supply of 1.5 mJ. This energy is enough to power the system while it is in signal acquisition state, where the system needs a 20 mA current load. 3.2. Acceleration measurement SHM measurements are performed in a laboratory wind turbine. For that, 3 sensor nodes are positioned at different locations of the structure for vibration measurements. With the obtained data, a Fast Fourier Transform (FFT) analysis is performed to calculate the vibrations modes of the structure. The obtained results are compared to the results obtained with a commercial National Instrument CompactDAQ system, Fig. 2.
Fig. 2. (a) Laboratory wind turbine with sensor position specified; (b) and (c) FFT analysis of the measurements performed with wireless sensor node and commercial accelerometer, respectively.
3.3. Strain measurement Measurements are performed in a beam for strain measurement validation, Fig. 3(a). For that, different weights are loaded in the beam and the strain measurements are performed in quarter-bridge Fig. 3(a) and half-bridge configuration Fig. 3(b). Measurements are shown and compared to the measurements obtained with a National Instrument CompactDAQ NI9237 module acquisition system.
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Fig.3 (a) Quarter-bridge measurements with sensor node and CompactDAQ; (b) half-brige measurements with sensor node and CompactDAQ.
3.4. Temperature measurement Finally, for temperature measurement validation, the sensor node with a thermistor was left measuring indoor temperature overnight, Fig. 4. At the same time a thermopar connected to a datalogger was left measuring temperature. As it is shown in Fig.4, the temperature variations during the night show the same behavior in both sensors.
Fig.4 Overnight temperature measurements with sensor node thesmistor and thermocouple connected to datalogger.
4. Conclusions The autonomous sensor node presented in this work has been developed with a programmable electronic circuit, which enables the measurement of acceleration and strain. The device is powered by a small rechargeable lithium ion polymer battery reinforced by a solar harvester and the signal acquisition is performed through wireless synchronized acquisition, with acquisition times in the range of ±1 µs. Finally, measurements performed in the laboratory wind turbine validate the use of the node for SHM applications. In addition, the sensor node has been validated for strain and temperature measurements. References [1] F.K. Shaikh, S. Zeadally, Energy harvesting in wireless sensor networks: A comprehensive review, Renewable and Sustainable Energy Reviews, 55(2016) 1041-54. [2] C. Alippi, G. Anastasi, M.D. Francesco, M. Roveri, Energy management in wireless sensor networks with energy-hungry sensors, IEEE Instrumentation & Measurement Magazine, 12(2009) 16-23. [3] I. Val, A. Arriola, C. Cruces, R. Torrego, E. Gomez, X. Arizkorreta, Time-synchronized Wireless Sensor Network for structural health monitoring applications in railway environments, Factory Communication Systems (WFCS), 2015 IEEE World Conference on2015, pp. 1-9. [4] V-Link(R) - LXRS(R) Wireless 7 Channel Analog Input Sensor Node, LORD Corporation2015. [5] I. Val, A. Arriola, C. Cruces, R. Torrego, E. Gómez and X. Arrizkorreta, Time Synchronized Wireless Sensor Network for Structural Health Monitoring Applications in Railway Environments, IEEE Word Conference on Factory Communication Systems (WCFCS), (2015).
ScienceDirect Procedia Engineering 168 (2016) 1659 – 1662
30th Eurosensors Conference, EUROSENSORS 2016
Wireless Sensor Nodes for acceleration, strain and temperature measurements Z.Herrastia,*, I.Gabilondoa, J.Berganzoa, I.Vala, F. Martíneza a
IK4-Ikerlan Technology Research Centre, Arrasate-Mondragón, Spain
Abstract The presented sensor node contains a heterogeneous signal conditioning circuit and signal processing software, which has been validated for acceleration, strain and temperature measurements. The combination of accelerometers and strain gages, which are widely used for vibration, stress, fatigue and failure analysis, constitutes the main basis for the validation of structural health monitoring (SHM) applications. In recent years, SHM has become an essential part of structural and mechanical system maintenance and in that matter, recent advances in wireless sensor networks (WSN), have enabled the realization of low cost wireless structure monitoring systems. Accordingly, the signal acquisition of the presented nodes is performed through wireless synchronized communication. Furthermore, as structures are often located in hard to access environments, an approach to the development of an autonomous system has been made. Therefore, the system works autonomously as it is powered by a small rechargeable lithium-ion polymer battery reinforced by energy harvesting. © 2016 2016The TheAuthors. Authors. Published by Elsevier Ltd. is an open access article under the CC BY-NC-ND license © Published by Elsevier Ltd. This (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the 30th Eurosensors Conference. Peer-review under responsibility of the organizing committee of the 30th Eurosensors Conference Keywords: Wireless sensor node; SHM; generic signal conditioning circuit
1. Introduction In order to provide early warning of damage, sensor nodes are located at structures, which are often in hostile and hard to access environments. Consequently, there is a need of using autonomous sensor nodes with low power signal conditioning electronics, wide range measurement, synchronous data acquisition and reliable signal transmission within large scale-networks. In this respect, advances in wireless sensor networks and energy harvesting often go hand in hand [1]. Most energy management strategies proposed in the literature assume that data acquisition consumes
* Corresponding author. Tel.:+34 943 712400; fax: +34 943 796944. E-mail address: [email protected]
1877-7058 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of the 30th Eurosensors Conference
doi:10.1016/j.proeng.2016.11.484
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Z. Herrasti et al. / Procedia Engineering 168 (2016) 1659 – 1662
significantly less energy than their transmission. However, this assumption does not hold in a number of practical applications where the power consumption of the sensing activity may be comparable or even greater than that of the radio [2]. For the reduction of the energy consumption two main approaches can be followed: duty cycling or adaptative sensing. Duty cycling consists in waking up the sensorial system only for the time needed to acquire a new set of samples and powering off immediately afterwards. A better approach would require an adaptative sensing strategy able to dynamically adapt the sensor activity to the real dynamics of the process. Like the developed wireless sensor nodes are based on a heterogeneous signal conditioning circuit, a few software changes in the signal acquisition circuit are sufficient for the sensing of different physical parameters as vibration, deformation and temperature. For energy consumption reduction, the duty cycling approach is followed, adapting the duty cycle, depending on the parameter that is being monitored. The fundamental advantages of the presented node with respect to traditional signal acquisition systems, is that it has a wireless synchronized signal acquisition with a synchronization jitter of ±1 μs between the different nodes within a network [3] and that it contains an energy harvesting module for reinforcing the rechargeable battery. Recently, wireless sensor nodes, such as the V-Link ® - LXSR® LORD sensing MicroStrain [4], are commercially available. This device can be used for measuring different physical parameters, but the synchronization jitter of this device is ±32 μs, far away from the ±1 μs that are achieved with the presented device. 2. Device description The autonomous sensor nodes developed in this work are formed by 3 PCB layers which are powered by a small rechargeable lithium ion polymer battery and are encapsulated in a device that is fabricated by stereo lithography, Fig. 1(a). It contains 3 modules: signal conditioning, radio for wireless communication and energy harvesting for power supply, Fig. 1(b), which are explained in more detail. The accelerometer, which is a piezoelectric accelerometer (Model 805M1) provided by measurement SPECIALITIES TM, is embedded inside the encapsulated device. 2.1. Generic signal conditioning module The generic signal conditioning circuit contains 4 building blocks, Figure 1(b). The functionality of the blocks is governed by an EFM 32 low power microcontroller. The building blocks are adjustable or programmable for each particular case. The prefilter adjusts the input signal of the PGA for the sensor that is being measured, i.e. accelerometer or strain gage. The PGA enables gains of 2.66 to 9600 and performs offset compensation, among other configurations, which are programmed through a one wire digital (1W) communication interface. The programmable filter cut frequency is tunable through the input clock frequency and finally, the 16-bit ADC converter transforms the analog input signal into a digital one. 2.2. Radio module When vibration monitoring is performed, deterministic timing behavior and synchronized sensing with a relatively high sampling frequency are needed. Therefore, in this work, a similar approach to industrial standards has been followed by placing a TDMA MAC on top of the physical layer, but specific synchronization elements have been added for obtaining synchronized Analog-to-Digital conversion in all nodes. The performance of these WSN synchronized acquisition has been validated in [5], where the method is implemented for a real time SHM system for trains. 2.3. Energy Harvesting module Solar and piezoelectric energy harvesting solutions have been analyzed. The energy provided by the harvester can be used to power the system or in situations where the energy provided is not sufficient, it could also be used to recharge the battery and extend its life. The analyzed harvesting solutions cannot provide unlimited energy to the system, but they can provide energy for signal acquisition and then, while the system is in idle state, they can store energy in energy storage capacitors.
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Fig. 1. (a) Sensor node: (left) encapsulated device; (right) electronic circuit formed by 3 PCB layers, 2 antennas and a small electronic circuit for half bridge strain measurements; (b) Sensor architecture.
3. Results and discussion 3.1. Energy harvesting module Piezoelectric and solar energy harvesting modules are analyzed and the best results are obtained with the solar harvester, which provides an energy supply of 1.5 mJ. This energy is enough to power the system while it is in signal acquisition state, where the system needs a 20 mA current load. 3.2. Acceleration measurement SHM measurements are performed in a laboratory wind turbine. For that, 3 sensor nodes are positioned at different locations of the structure for vibration measurements. With the obtained data, a Fast Fourier Transform (FFT) analysis is performed to calculate the vibrations modes of the structure. The obtained results are compared to the results obtained with a commercial National Instrument CompactDAQ system, Fig. 2.
Fig. 2. (a) Laboratory wind turbine with sensor position specified; (b) and (c) FFT analysis of the measurements performed with wireless sensor node and commercial accelerometer, respectively.
3.3. Strain measurement Measurements are performed in a beam for strain measurement validation, Fig. 3(a). For that, different weights are loaded in the beam and the strain measurements are performed in quarter-bridge Fig. 3(a) and half-bridge configuration Fig. 3(b). Measurements are shown and compared to the measurements obtained with a National Instrument CompactDAQ NI9237 module acquisition system.
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Fig.3 (a) Quarter-bridge measurements with sensor node and CompactDAQ; (b) half-brige measurements with sensor node and CompactDAQ.
3.4. Temperature measurement Finally, for temperature measurement validation, the sensor node with a thermistor was left measuring indoor temperature overnight, Fig. 4. At the same time a thermopar connected to a datalogger was left measuring temperature. As it is shown in Fig.4, the temperature variations during the night show the same behavior in both sensors.
Fig.4 Overnight temperature measurements with sensor node thesmistor and thermocouple connected to datalogger.
4. Conclusions The autonomous sensor node presented in this work has been developed with a programmable electronic circuit, which enables the measurement of acceleration and strain. The device is powered by a small rechargeable lithium ion polymer battery reinforced by a solar harvester and the signal acquisition is performed through wireless synchronized acquisition, with acquisition times in the range of ±1 µs. Finally, measurements performed in the laboratory wind turbine validate the use of the node for SHM applications. In addition, the sensor node has been validated for strain and temperature measurements. References [1] F.K. Shaikh, S. Zeadally, Energy harvesting in wireless sensor networks: A comprehensive review, Renewable and Sustainable Energy Reviews, 55(2016) 1041-54. [2] C. Alippi, G. Anastasi, M.D. Francesco, M. Roveri, Energy management in wireless sensor networks with energy-hungry sensors, IEEE Instrumentation & Measurement Magazine, 12(2009) 16-23. [3] I. Val, A. Arriola, C. Cruces, R. Torrego, E. Gomez, X. Arizkorreta, Time-synchronized Wireless Sensor Network for structural health monitoring applications in railway environments, Factory Communication Systems (WFCS), 2015 IEEE World Conference on2015, pp. 1-9. [4] V-Link(R) - LXRS(R) Wireless 7 Channel Analog Input Sensor Node, LORD Corporation2015. [5] I. Val, A. Arriola, C. Cruces, R. Torrego, E. Gómez and X. Arrizkorreta, Time Synchronized Wireless Sensor Network for Structural Health Monitoring Applications in Railway Environments, IEEE Word Conference on Factory Communication Systems (WCFCS), (2015).