Extracting of characteristic parameters of acoustic emission signal for the metal drawing parts is particularly important to judge the quality of molding parts. This study adopted time-series analysis and MATLAB
LUO Zhi-gao, YE Hong-ying, XU AI-cheng
College of Mechanical Engineering, Jiangsu University, Zhenjiang201213, China
Abstract:Research of extracting the characteristic parameters of acoustic emission signal for the metal drawing parts is particularly important to judge the quality of molding parts. This study adopted time-series analysis and MATLAB to process the acoustic emission signal through the wavelet packet decomposition in order to extract the characteristic parameters. In the process, the type of model was judged by using the trailing property and the truncated property of time series; the order of model was chosen by using the FPE (final prediction error) rule; the model parameters ware estimated by the least-square estimation method. Finally, the characteristic parameters of acoustic emission were extracted based on the established auto-regressive spectrum model. The research results are that the characteristic parameters of acoustic emission signal for the metal drawing parts successfully extracts by means of this method, as well as its profile, providing the beneficial basis for judging the quality of molding parts.
骆志高 叶红英 胥爱成. 基于时序分析的拉深件成型裂纹的特征参数提取[J]. , 2012, 31(17): 120-123.
LUO Zhi-gao;YE Hong-ying;XU AI-cheng. Extracting of characteristic parameters of acoustic emission signal for the metal drawing parts is particularly important to judge the quality of molding parts. This study adopted time-series analysis and MATLAB. , 2012, 31(17): 120-123.