FBG based strain sensor with temperature compensation for structural health monitoring

2018 ◽  
Author(s):  
Jayant Kumar ◽  
Devendra Chack
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Temperature Compensation ◽  
Strain Sensor ◽  
Structural Health

Printed strain sensor with temperature compensation and its evaluation with an example of applications in structural health monitoring

2017 ◽  
Vol 56 (5S2) ◽  
pp. 05EC02 ◽  
Author(s):  
Daniel Zymelka ◽  
Takahiro Yamashita ◽  
Seiichi Takamatsu ◽  
Toshihiro Itoh ◽  
Takeshi Kobayashi
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Temperature Compensation ◽  
Strain Sensor ◽  
Structural Health

scholarly journals A Wireless Strain Sensor Network for Structural Health Monitoring

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Chengyin Liu ◽  
Jun Teng ◽  
Ning Wu
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Evaluation System ◽  
Strain Sensor ◽  
Modal Testing ◽  
Dynamic Strain ◽  
Structural Dynamic ◽  
Structural Health ◽  
Strain Monitoring

Structural strain under external environmental loads is one of the main monitoring parameters in structural health monitoring or dynamic tests. This paper presents a wireless strain sensor network (WSSN) design for monitoring structural dynamic strain field. A precision strain sensor board is developed and integrated with the IRIS mote hardware/software platform for multichannel strain gauge signal conditioning and wireless monitoring. Measurement results confirm the sensor’s functionality regarding its static and dynamic characterization. Furthermore, in order to verify the functionality of the designed wireless strain sensor for dynamic strain monitoring, a cluster-star network evaluation system is developed for strain modal testing on an experimental steel truss structure. Test results show very good agreement with the finite element (FE) simulations. This paper demonstrates the feasibility of the proposed WSSN for large structural dynamic strain monitoring.

scholarly journals Numerical Study of a Multi-Layered Strain Sensor for Structural Health Monitoring of Asphalt Pavement

Proceedings ◽  
2019 ◽  
Vol 42 (1) ◽  
pp. 41
Author(s):  
Jiayue Shen ◽  
Minghao Geng ◽  
Abby Schultz ◽  
Weiru Chen ◽  
Hao Qiu ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Polyurethane Foam ◽  
Health Monitoring ◽  
Numerical Study ◽  
Asphalt Pavement ◽  
Strain Sensor ◽  
Traffic Load ◽  
Structural Health ◽  
Initiation And Propagation ◽  
Load Monitoring

Crack initiation and propagation vary the mechanical properties of the asphalt pavement and further alter its designate function. As such, this paper describes a numerical study of a multi-layered strain sensor for the structural health monitoring (SHM) of asphalt pavement. The core of the sensor is an H-shaped Araldite GY-6010 epoxy-based structure with a set of polyvinylidene difluoride (PVDF) piezoelectric transducers in its center beam, which serve as a sensing unit, and a polyurethane foam layer at its external surface which serves as a thermal insulation layer. Sensors are coated with a thin layer of urethane casting resin to prevent the sensor from being corroded by moisture. As a proof-of-concept study, a numerical model is created in COMSOL Multiphysics to simulate the sensor-pavement interaction, in order to design the strain sensor for SHM of asphalt pavement. The results reveal that the optimum thickness of the middle polyurethane foam is 11 mm, with a ratio of the center beam/wing length of 3.2. The simulated results not only validate the feasibility of using the strain sensor for SHM (traffic load monitoring and damage detection), but also to optimize design geometry to increase the sensor sensitivity.

scholarly journals Improving sensitivity and coverage of structural health monitoring using bulk ultrasonic waves

2020 ◽  
pp. 147592172096512
Author(s):  
Stefano Mariani ◽  
Yuan Liu ◽  
Peter Cawley
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Temperature Compensation ◽  
Signal Amplitude ◽  
Guided Wave ◽  
Ultrasonic Waves ◽  
Back Wall ◽  
Environmental Chamber ◽  
Structural Health ◽  
Specific Temperature

Practical ultrasonic structural health monitoring systems must be able to deal with temperature changes and some signal amplitude/phase drift over time; these issues have been investigated extensively with low-frequency-guided wave systems but much less work has been done on bulk wave systems operating in the megahertz frequency range. Temperature and signal drift compensation have been investigated on a thick copper block specimen instrumented with a lead zirconate titanate disc excited at a centre frequency of 2 MHz, both in the laboratory at ambient temperature and in an environmental chamber over multiple 20°C–70°C temperature cycles. It has been shown that the location-specific temperature compensation scheme originally developed for guided wave inspection significantly out-performs the conventional combined optimum baseline selection and baseline signal stretch method. The test setup was deliberately not optimised, and the signal amplitude and phase were shown to drift with time as the system was temperature cycled in the environmental chamber. It was shown that the ratio of successive back wall reflections at a given temperature was much more stable with time than the amplitude of a single reflection and that this ratio can be used to track changes in the reflection coefficient from the back wall with time. It was also shown that the location-specific temperature compensation method can be used to compensate for changes in the back wall reflection ratio with temperature. Clear changes in back wall reflection ratio were produced by the shadow effect of simulated damage in the form of 1-mm diameter flat-bottomed holes, and the signal-to-noise ratio was such that much smaller defects would be detectable.

Printing of microstructure strain sensor for structural health monitoring

2017 ◽  
Vol 123 (5) ◽  
Author(s):  
Minh Quyen Le ◽  
Florent Ganet ◽  
David Audigier ◽  
Jean-Fabien Capsal ◽  
Pierre-Jean Cottinet
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Strain Sensor ◽  
Structural Health
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