Feature Extraction of Acoustic Emission Signals from Low Carbon Steel Pitting Based on Independent Component Analysis and Wavelet Transforming
According to the characteristics of low-carbon steel pitting acoustic emission signal, one new characteristic analysis-WICA is proposed. The main idea of WICA is that based on the independent component analysis blind source separation technology as well as the wavelet transformation decomposition technology, proposed determines the low-carbon steel pitting source number according to the energy characteristic vector the method. The experiment results show that to some extent, WICA can overcome the difficulties caused by the uncertainty of low-carbon steel pitting independent source and get better results of low-carbon steel pitting acoustic emission signal pattern recognition.
Wavelet transform Independent component analysis (ICA) Pattern recognition
Wei LI Guang DAI Feifei LONG Peng JIANG
Mechanical Science and Engineering College, Daqing Petroleum Institute Daqing, Heilongjiang Province, China 163318
国际会议
第十七届世界无损检测会议(17th World Conference on Nondestructive Testing)
上海
英文
1592-1597
2008-10-25（万方平台首次上网日期，不代表论文的发表时间）