基于时间-小波能量谱熵的滚动轴承故障诊断研究

针对轴承振动信号中存在周期性冲击这一现象，提出了时间-小波能量谱熵的计算方法，用于滚动轴承的故障诊断。首先构造脉冲小波，采用连续小波变换的方法得到时间域内小波能量谱，再沿时间轴计算能量谱熵，定量描述振动信号沿时间的分布情况，不同故障下轴承的冲击振动随时间变化程度不同，其时间-小波能量谱熵值也就不同。将不同故障轴承信号的时间-小波能量谱熵作为向量特征输入建立支持向量机，实现了对轴承的工作状态和故障类型的判断。实验结果表明，时间-小波能量谱熵可以有效地对滚动轴承进行故障诊断。

Rolling Element Bearing Fault Diagnosis Based on Time-wavelet Energy Spectrum Entropy

There have periodic impulses in vibration signals of bearing, so a new method, so called time-wavelet energy spectrum entropy, is proposed for rolling element bearing fault diagnosis. Firstly, the impulse response wavelet is constructed to extract wavelet energy spectrum in time domain by using continuous wavelet transform, then energy spectrum entropy which represents vibration signals quantitatively change with time is calculated along the time axis, bearings with different faults have different variation complexity, and the entropy is different. To identify the fault pattern and condition of bearing, entropy of different fault signal could as input vectors of support vector machine. Practical examples showed the method can diagnose efficiently faults of rolling element bearings.