Optimisation of active SHM system based on optimal number and placement of piezoelectric transducers

Abstract

This paper concerns optimal placement and number of discrete piezoelectric macro fibre composite (MFC) sensors to optimise SHM systems. Its novelty lies in a two-stage placement methodology for discrete piezoelectric transducers, with fitness and objective functions to optimise the location and number of discrete piezoelectric sensors in order to reduce the cost and complexity of data processing and increase the effectiveness in damage detection. The maximisation of sensor voltage amplitude at multiple modes of vibration and the average of sensor normal damage index $RMS D^{nor}$ measured for several plates artificially cracked at different positions and orientations are proposed as objective functions to optimise the locations and the number of efficient piezoelectric sensors. A non-normalised root-mean-square deviation $RMSD$ is introduced in this study in place of the conventional normalised $NRMSD$ to assess the degree of damage and sensor effectiveness. Furthermore, normal damage indices $RMS D^{nor}$ and $NRMS D^{nor}$ normalised to 100% are proposed as the fitness functions. The placement methodology is utilised and verified for stiffened and unstiffened plates; stiffeners are used to break the dynamic symmetry and increase plate complexity. The performance of the placement methodology is tested for a healthy and 12 damaged plates to optimise SHM system based on the maximisation of sensor voltage and average normal damage index $RMS D^{nor}$ as objective functions. The results show that the placement methodology is efficient in determining the optimum number and placement of piezoelectric sensors at a low computational effort. The optimum placement of two piezoelectric sensors can efficiently monitor the crack’s initiation at different positions and multiple modes of vibration. The optimal placement and number of sensors have a positive impact on the cost, data acquisition and processing of the active SHM system

Keywords

Piezoelectric optimal placement genetic algorithms normal damage index SHM

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