电力机车的故障预测与维修周期的决策

Decision of Fault Forecast and Maintenance Period of Electric Locomotives

在阐述电力机车故障诊断和维修决策流程的基础上,分别采用累积损伤理论和神经网络模式对电力机车的机械设备和电气设备进行寿命预测与诊断,并根据信息融合和模糊处理对机车故障进行综合分析与诊断。依据可靠性理论计算出机车各关键设备的定期检修周期,运用故障树理论计算出最小割集及各元素重要度,通过加权平均得到机车系统的大修周期,在理论上为机车的维护与维修提供指导。

Based on expounding fault diagnosis and maintenance decision flow of electric locomotive, the machine equipment and electric equipment of electric locomotive were carried service life forecast and diagnosis by using cumulative damage theory and neural network mode respectively, and the comprehensive analysis and diagnosis for locomotive faults were carried according to information combination and fuzzy treatment. Then the periodical repair period of key devices in locomotive was calculated by reliability theory, the minimum cut-set and each element importance were calculated by fault tree theory, and the major repair period of locomotive system was achieved through weighted average, all of which provide guidance for locomotive maintenance and repair from theory.