峰度
小波包分解
小波
包络线(雷达)
解调
信号(编程语言)
计算机科学
网络数据包
语音识别
断层(地质)
声学
模式识别(心理学)
算法
人工智能
数学
小波变换
物理
统计
电信
地质学
频道(广播)
地震学
计算机网络
雷达
程序设计语言
作者
Lin Li,Qiang Xu,Yong Zhou
出处
期刊:Springer proceedings in physics
日期:2017-01-01
标识
DOI:10.1007/978-3-319-29052-2_9
摘要
This chapter presents an envelope demodulation method based on wavelet packets and kurtosis to extract the fault features of an acoustic emission signal. De-noising was performed first to reduce the noise. Then, we calculated the coefficients of wavelet packet nodes and the kurtosis value after wavelet packet decomposition. Finally, we performed an envelope spectrum analysis on the reconstructed signal based on the maximum degree of kurtosis. To correctly extract fault features of the acoustic emission signal, we compared the maximum amplitude of different nodes’ envelope spectra and the kurtosis value. The method can improve the accuracy of fault diagnosis.
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