基于强化缓冲算子的六相永磁容错电机故障预测

Fault Prediction of Six-phase Permanent Magnet Fault Tolerant Motor Based on Strengthening Buffer Operator

永磁容错电机属于高阶非线性强耦合的复杂系统,受到外界干扰后,提取的故障特征信号容易失真。针对永磁容错电机系统受到外在冲击时,传统灰色模型故障预测精度不高的问题,提出了一种新的故障预测改进方法。采用强化缓冲算子对数据序列进行处理,还原数据,排除冲击干扰,而后通过建立的GM(1,1)基本模型对故障能量特征数据序列进行预测。结果表明,故障原始序列经过各类强化缓冲算子作用后,预测精度提高到96.3%以上,预测相对误差较原始序列基本模型平均降低了43.06%,有效提高了行为数据的故障预测精度。

A study of the fault prediction problem of permanent magnet fault-tolerant motor equipped in the aircraft actuation system is advantageous to monitoring aircraft health status accurately, and providing de- cision support for aircraft maintenance. For a permanent magnet fault-tolerant motor system in case of a hit from the outside, the traditional grey model is not high prediction accuracy. A new improved forecast method based on grey theory is proposed in the paper. The permanent magnet fault-tolerant motor is a complex system belonging to high order, nonlinear and strong coupling. The paper adopts a strengthening buffer operator to deal with data sequence, restore data, eliminate the interference of shock, and forecast the failure energy data sequence through the establishment of the basic model. The results show that the o- riginal sequence is processed by strengthening buffer operator, the prediction accuracy is increased to 96.3% above, the relative prediction error is reduced by 43.06~ on average compared to the primitive se- quence basic model, and the fault prediction of the behavior is improved effectively.