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Identification of acoustic emission signals ofoffshore structures with both local wave method and neural network

LIN Li,ZHAO De-you (Department of Naval Architecture,Dalian University of Technology,Dalian 116085,China)  
This paper presented a new approach for extraction and identification of acoustic emission(AE) signals from offshore structures by using both local wave method and neural network.First the local wave method was used to decompose the acoustic emission signals of offshore structures into a number of intrinsic mode functions(IMFs);then the energy feature parameters extracted from IMFs were employed as the input parameters of the neural network to identify the acoustic emission signals of the offshore structures.Through the analysis on the experimental data of acoustic emission signals of offshore platform,it showed that neural network method in conjunction with local wave method will effectively recognize the offshore structure's AE signals,thus providing a new and effective tool for feature extraction and identification of acoustic emission signal from offshore structures.
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