The Characteristic Parameters Extraction of the Drawing Forming Cracks Based on Time-Series Analysis and ICA

Abstract:

The purpose of the study is to extract the characteristic parameters of the forming crack acoustic emission (AE) signals generated by the metal deep drawing. Time-series analysis and MATLAB were used to adopt independent component analysis (ICA) to isolate the crack AE signals and extracted the characteristic parameters of AE signals. This study isolate the crack AE signals of the drawing parts by the FastICA method based on the maximum negative entropy, the data was processed by MATLAB and the regression model of the various decomposition established by time-series analysis to extract the characteristic parameters of the crack AE signals. The results suggested that this method can isolate the crack AE signals of the deep drawing successfully and can extract the characteristic parameters and distribution maps of the crack AE signals of the metal drawing parts effectively, provide a favorable basis for the judgment of the molding part quality.

• Periodical: Applied Mechanics and Materials (Volumes 239-240)
• Pages: 1259-1263
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.239-240.1259
• Online since: December 2012
• Authors: Zhi Gao Luo, Jing Jing Zhang, Jun Li Zhao, Xu Dong Li
• Keywords: AE, Characteristic Parameters, Forming Cracks, ICA, Time-Series Analysis

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