小波包与样本熵相融合的PMSM失磁故障诊断

Demagnetization fault diagnosis in permanent magnet synchronous motor combination wavelet packet with sample entropy

为了研究永磁同步电机失磁故障最为敏感的特征量和区分故障频率来源,提出采用小波包与样本熵相融合的失磁故障诊断方法,研究该诊断方法的数学机理,并给出小波包分析定子电流频谱的详细步骤和小波包变换后最大能量频率子带样本熵的计算过程,通过比较样本熵的大小,确定故障频率来源。搭建实验平台,采集不同工况下的永磁同步电机定子电流数据,用该诊断方法进行分析,其结果表明,永磁同步电机失磁故障宜取5次、7次谐波作为故障特征量;样本熵的大小因电机运行状态不同而不同,可以确定故障频率来源于永磁同步电机失磁故障。

In order to study the most sensitive fault characteristic quantities of permanent magnet synchronous motor （PMSM） demagnetization fault and distinguish the fault frequency source,a new fault diagnosis method based on combination Wavelet Packet （WP） transform with sample entropy was proposed.Mathematics mechanism of the fault diagnosis method was studied,and detailed steps on stator current frequency spectrum analysis using WP and maximum energy frequency sub bands sample entropy calculation process were given.By comparing the size of sample entropy,the fault frequency source was ascertained.The experimental platform was set up,the stator current data under different conditions of the PMSM was acquired,and the acquisition data by the combination fault diagnosis method was analyzed.The results show that the 5th and 7th harmonic are suitable as demagnetization fault characteristic quantity and fault frequencies from demagnetization fault of the PMSM is verified because sample entropy size changes with the PMSM running state difference.