基于时序特征模式识别的牵引电机过流实时诊断

Real-Time Diagnosis of Traction Motor Over-Current Based on Time-Series Feature Pattern Recognition

针对牵引传动系统电机过流的实时诊断与精确故障溯源问题,提出了一种基于故障时序特征模式识别的实时诊断方法。首先对导致牵引电机过流的常见故障源进行分析,接着通过总结与工况强关联的事件时序变化规律,离线设计出电机过流故障时序特征模式诊断规则库,然后在线实时采集相关的传感器信号以及系统工况信息,计算相关特征量和事件标志,并与离线设计好的工况事件时序特征模式诊断规则库中各模式及诊断规则进行实时匹配,从而实现牵引电机过流故障的实时诊断与精确溯源。最后,基于现场故障案例数据进行测试,验证了所提方法的有效性。

Aiming at the real-time diagnosis and accurate fault tracing of motor over-current in traction drive system,a real-time diagnosis method based on fault time-series feature pattern recognition is proposed.Firstly,the common fault sources leading to over-current of traction motor are analyzed.Then,by summarizing the change law of event time-series strongly related to working conditions,the diagnosis rule base of motor over-current fault time-series feature pattern is designed off-line.Then,the relevant sensor signals and system working condition information are collected online in real time,the relevant feature quantities and event flags are calculated,and the patterns and diagnostic rules in the off-line designed diagnosis rule base are matched in real time,so as to realize the real-time diagnosis and accurate tracing of traction motor over-current fault.Finally,the effectiveness of the proposed method is verified by field fault cases testing.