An investigation was performed to develop a sensor placement method to maximize the performance of a structural health monitoring (SHM) system with a minimal number of sensors for detection of impact in structures, particularly for structures made of fiber-reinforced composite materials. The performance of the SHM system is evaluated based on the probability of detection (POD). This optimization problem was formulated to maximize the POD through selection of optimal sensor locations for a given sensor network. A genetic algorithm was adopted and integrated with the SHM system to perform the optimization process. Numerical simulations on two composite panels showed that the selection of sensor network configuration is crucial for the performance of the SHM system. For a targeted POD, the proposed method can be used to configure an SHM system with a minimal number of sensors to identify impact forces that are greater than a pre-defined critical value.
This paper explores the potential of integration of damage diagnostics based on built-in sensors with a progressive failure modeling for monitoring and prediction of composite structures, from damage initiation to final failure while they are in service. A piezobased structural health monitoring system was utilized to monitor the damage initiation based on acoustic signals and to detect its growth based on ultrasonic waves generated by the piezoelectric sensors. Utilizing a damage index and an imaging algorithm, damage initiation and damage extent were estimated, respectively. A finite element code (ABAQUS) based on a progressive failure analysis was adopted to simulate damage initiation and propagation in composites under a given loading condition. The numerical data and the diagnostic images were compared to x-ray pictures of a test coupon to verify the results. The results of the study strongly indicate that damage diagnostics and health prognostics could potentially be integrated to produce a powerful tool for managing the operation of composite structures in service.
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