Abstract: A novel coupled fault isolation scheme is proposed to deal with multiple, simultaneous and coupled nonlinear faults for traction motor with structural damage. The structural damage reduced-order model is firstly built by introducing the relative balance factor associated with big data driven classifier algorithm. The proposed discrete-time fault model has been established with the help of Delta operator and support vector machine (SVM). Meanwhile, fault isolation condition and threshold determination techniques are used to isolate the coupled faults. Finally, through a coupled fault isolation experiments using real data of fault-injection benchmark for traction drive control system, the effectiveness of the proposed algorithm is justified.

Key words: Traction motor, relative balance factor, reduced-order model, coupled fault isolation, fault threshold

摘要： 针对牵引电机结构损伤引起的一类非线性耦合问题，提出了一种新的复合故障分离方案。通过引入电机相对平衡因子和大数据驱动的分类算法，该方案首先建立了牵引电机结构损伤下的降阶模型。联合Delta域故障模型和支持向量机动态补偿模型，并借助故障可分离条件和阈值确定方法完成对复合故障的分离。最后通过牵引电机故障注入平台的真实数据进行实验，实验结果表明了所提方法的有效性。

关键词: 牵引电机, 相对平衡因子, 降阶模型, 复合故障分离, 故障阈值