期刊
SMART MATERIALS & STRUCTURES
卷 9, 期 3, 页码 298-303出版社
IOP PUBLISHING LTD
DOI: 10.1088/0964-1726/9/3/308
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This paper studies the problem of optimal sensor placement for impact detection and location in composite materials. The study involves a simple impact experiment on a composite box panel. The time-varying strain data are measured using piezoceramic sensors. An effective impact detection procedure is established using a neural network approach. The procedure determines the location and amplitude of impacts. A genetic algorithm is used to determine the optimum sensor positions for a diagnostic system. The main object of the paper is to study fail-safe distributions, i.e. those whose sub-distributions also have a low probability of detection error. The results are validated against an exhaustive search. The study shows that genetic algorithms combined with neural networks can be effectively used to find near-optimal sensor distributions for damage detection. The methods presented are generic and can be used in similar sensor position problems.
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