基于倒频谱分析的电机故障检测

Fault detection for motor based on cepstrum analysis

介绍了倒频谱分析的基本原理及在电机故障检测中的应用。对于电机运行过程中所形成的耦合故障导致故障类型识别困难的问题,提出了运用倒频谱分析与小波分解相结合的电机故障检测方法。它能将功率谱上成族的边频带谱线简化为更易于观察的单根谱线,将两者优势相结合,实现电机耦合故障分离和故障特征提取,为电机复合故障诊断提供了新的途径和方法。

The principle of cepstrum analysis is introduced and a method of fault detection for motor based on cepstrum analysis is presented.For coupling fault in the process of the motor running resulting in difficult identification of fault type,cepstrum analysis combined with wavelet decomposition for motor fault detection is recommended.It can make the family of side-band spectrum in power spectrum be simplified to more easily observed single spectrums,taking advantages of the two,achieving motor coupling fault isolation and fault feature extraction,providing a new approach and methodology for complex motor fault diagnosis.