Optimization of Bond Locations for Guided Waves Based SHM Using Coupled Optical Fibers

R. Soman, W. Ostachowicz, J. Kim, Aboubakr Sherif, K. Peters
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Abstract

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 advantages but their use has been limited for the GW sensing due to its limited sensitivity. FBG sensors in the edge-filtering configuration have overcome this issue with sensitivity and there is a renewed interest in their use. Unfortunately, the FBG sensors and the equipment needed for interrogation is quite expensive and their number is restricted. In the previous work by the authors the number and location of the actuators was optimized for developing a SHM system with single sensor and multiple actuators. But through the use of the phenomenon of acoustic coupling, multiple locations on the structure may be interrogated with a single FBG sensors. As a result, a sensor network with multiple sensing locations and few actuators is feasible and cost effective. Hence this paper develops the optimization problem for designing an SHM network for use with FBG sensors making use of acoustic coupling. The optimization problem is implemented on a simple aluminum plate. The directionality, bond efficiency and the factors influencing the acoustic coupling are taken into consideration for optimizing the sensor network. A multi-objective optimization problem is defined and solved using non-sorting genetic algorithm (NSGA). The results indicate that indeed a multi-objective optimization is necessary and has potential to improve the SHM system performance.
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基于耦合光纤的导波SHM键位置优化
导波(GW)可以快速检测大面积区域,因此引起了结构健康监测(SHM)界的极大兴趣。光纤布拉格光栅(FBG)传感器具有许多优点,但由于其灵敏度有限,限制了其在GW传感中的应用。边缘滤波配置的FBG传感器已经克服了这个灵敏度问题,并且对它们的使用重新产生了兴趣。不幸的是,FBG传感器和审问所需的设备非常昂贵,而且数量有限。在作者之前的工作中,为了开发具有单传感器和多个执行器的SHM系统,对执行器的数量和位置进行了优化。但通过使用声耦合现象,可以用单个光纤光栅传感器询问结构上的多个位置。因此,具有多个传感位置和少数执行器的传感器网络是可行且经济有效的。因此,本文提出了利用声耦合设计用于光纤光栅传感器的SHM网络的优化问题。优化问题是在一个简单的铝板上实现的。考虑了传感器网络的方向性、键效率和影响声耦合的因素,对传感器网络进行了优化。定义了一个多目标优化问题,并用非排序遗传算法求解。结果表明,多目标优化确实是必要的,并且有可能提高SHM系统的性能。
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