【摘要】 提出了一种基于高斯线调频小波变换诊断电机故障的新方法。线调频小波变换是信号的时间-频率-尺度变换, 具有比小波变换及其它时频分析更强的非平稳信号分析功能。利用高斯线调频小波变换作电机故障信号的能量谱估计,可提取电机故障信号的频率成份。试验结果表明,这种方法比Fourier变换和小波变换频率分布的能量更集中。更多还原

【Abstract】 In this paper, a new method of diagnosing electric machine fault, which based on gauss chirplet transforms, is presented. Chirplet transforms (CTs) are variation of the time, the frequency, and the scale of the signal. CTs have more effective than wavelet transforms in time-frequency analyzing of non-stable signals. Energy spectrums of electric machine fault signal can be gauged by using Gauss CTs, so the frequencies of the signal can be extracted. Experiment results show this method is more concentrated in energy than fourier transform and wavelet transform.更多还原