| More and more thin composite materials have been applied in industry of aeronautics and astronautics for their superior performance. Disastrous accidents happen in process of working at times for bonding defect of composite material, so it is urgently needed to make accurate detection for bonding interface and insure the quality of products and working safety. Ultrasonic echo method is widely applied in non-destructive detection for its advantage of accurate defect locating, wide application, and convenient operation and so on.How to make classify and recognize echo signal of ultrasonic detection takes information of interface bonding quality is the key and difficulty of ultrasonic detection of thin composite materials. In this paper, we use fuzzy pattern recognition method to judge bonding quality. Firstly, we establish the fuzzy membership function between each characteristic and bonding quality by BP neural network. Simulation results show that this method is convenient, simple, and it conforms to the practical application. Secondly, we establish the fuzzy subsets of each bonding quality and design a fuzzy pattern recognition algorithm. Then we design a fuzzy pattern recognition algorithm to judge bonding quality, and the algorithm selects hamming approach degree and the arithmetic mean least approach degree. Then we use the nearest principle to recognize bonding quality. Simulation results show that the algorithm is very exact for quantitative recognition of bonding quality. The establishing of membership function is the key of fuzzy pattern recognition. Fuzzy pattern recognition algorithm overcomes the problem that caused by the internal structure of composite material and the complexity of the work of environmental and so on. Fuzzy pattern recognition is applied in bonding quality ultrasonic detection of thin composite plate is very helpful for design and realization of digital ultrasonic detection instrument. |
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