摘要
在机械故障诊断中,故障通常表现为输出信号发生突变这一特点,而传统的傅里叶变换在处理时域上有变化的信号存在不足之处,本文利用小波分析检测信号突变点的典型实例,论证了小波分析在检测信号突变点上具有比傅里叶变换无法比拟的优越性,利用小波分析可以精确地检测出突变的时间点。
In machinery diagnosis, fault always happens with the output signal breaking. Traditional Fourier transform can＇t process unstable signal well. Typical examples of detecting break point of signal by the use of wavelet analysis were presented. It proved that wavelet analysis has the superiority over Fourier analysis in detecting the break point of signal. Wavelet analysis can precisely detect the break point.
出处
《电子测量技术》
2007年第3期42-43,109,共3页
Electronic Measurement Technology
关键词
小波分析
故障诊断
奇异性
wavelet analysis
fault diagnosis
singularity
