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Guided waves (GW) allow fast inspection of a large area and hence have received great interest from the structural health monitoring (SHM) community. Fiber Bragg grating (FBG) sensors offer several advantage but their use has been limited for the GW sensing due to their limited sensitivity. But the use of the edge-filtering approach in the remote bonded configuration has enhanced their sensitivity and allows use of these sensors for GW measurement. Although these sensors are light in weight and need no additional wiring there is still significant motivation to reduce the number of sensors while maintaining the quality and reliability of the assessment due to their high cost. In addition, for the safety and reliability of the structures it is of utmost importance that the entire structure can be investigated. Hence it is necessary to optimize the locations of the sensors in order to maximize the coverage while limiting the number of sensors used. The problem posed for the optimization of the FBG sensors for GW is different from any other work in this area due to the directional sensitivity shown by these sensors. Hence a novel optimization problem is developed for the application of FBG sensors for the GW based SHM. This paper develops a genetic algorithm based optimization methodology to incorporate the directional sensitivity. The methodology is shown analytically, using inputs from experimental investigations.
Rohan Soman,Junghyun Wee,Kara Peters, andWieslaw Ostachowicz
"Optimization of sensor placement for guided waves based SHM using fiber Bragg grating sensors", Proc. SPIE 11379, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020, 113791E (23 April 2020); https://doi.org/10.1117/12.2558393
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Rohan Soman, Junghyun Wee, Kara Peters, Wieslaw Ostachowicz, "Optimization of sensor placement for guided waves based SHM using fiber Bragg grating sensors," Proc. SPIE 11379, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020, 113791E (23 April 2020); https://doi.org/10.1117/12.2558393