基于改进DFA和LDA的永磁同步电机机械故障检测

为提高故障检测的精度，研究了变转速工况下永磁同步电机的机械故障检测方法.首先，分析了电机轴承、转子偏心及其复合故障的振动特性；其次，采用Vold-Kalman算法对故障特征分量进行跟踪提取，并通过信号重构消除转速变化对故障特征分量的影响；提出一种基于改进去趋势波动分析和线性判别式分析的机械故障检测方法，实现对重构信号的故障特征提取和故障检测；最后，对所提出故障检测方法的有效性进行实验验证.实验结果表明文中所提出方法的故障检测精度为88%.

Mechanical Fault Detection of Permanent Magnet Synchronous Motor Based on Improved DFA and LDA

In order to improve the detection accuracy, a mechanical faults detection method was studied for permanent magnet synchronous motors under variable speed conditions. Firstly, the vibration characteristics of the bearing, the eccentricity, and the compound faults were analyzed. Secondly, the components of fault characteristic were extracted with Vold-Kalman arithmetic. And the extracted signals were reconstructed to remove the influence of the speed change on the components of fault characteristic. And then, a mechanical fault detection method was proposed based on improved detrended fluctuation analysis (DFA) and linear discriminant analysis (LDA) to realize the reconstructed signal feature extraction and fault detection. Finally, a verification experiment was carried out for the proposed fault detection method. The results show that the detection accuracy of the proposed fault detection method can reach up to 88%.