Robust fault analysis (FA) including the diagnosis of faults and predicting their level of fault severity is necessary to optimize maintenance and improve reliability. This study aimed at presenting a technique to diagnosis faults of electronic switch in permanent magnet synchronous motor in Aircraft. The current output of both thyristor bridges and the diode of system excitation is monitored under healthy and faulty operations. Features extracted at different operations using Multi-scale wavelet decomposition (MSWD) to extract the useful features. MSWD features are used to train nonlinear autoregressive with exogenous model which sequentially operated to evaluate the fault level in case open circuit that developing across a switch under different operating condtions. The two models have been tested and designed due to the simulated data, where the results showed acceptable effectiveness in the diagnosis of various types of fault.

中文翻译：

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外源模型非线性自回归诊断不同工况下飞机电机故障

包括故障诊断和故障严重程度预测在内的稳健故障分析 (FA) 是优化维护和提高可靠性所必需的。本研究旨在提出一种飞机永磁同步电机电子开关故障诊断技术。晶闸管桥和系统励磁二极管的电流输出在正常运行和故障运行下均受到监控。使用多尺度小波分解 (MSWD) 在不同操作中提取的特征来提取有用的特征。MSWD 特征用于训练带有外生模型的非线性自回归模型，该模型按顺序运行以评估在不同工作条件下在开关上发生开路的情况下的故障水平。由于模拟数据，这两个模型已经过测试和设计，