基于粗糙集的机车牵引变流器故障诊断方法

利用粗糙集对故障特征数据库中的数据进行处理和约简,过滤冗余属性,提取出有效的故障模式规则.依据这些规则,对新加入数据进行判别并归类,识别出故障的类型,依此找到故障的原因并排除故障,从而使机车实现“状态修”成为可能.从实验结果可知,基于粗糙集的故障诊断方法非常有效,可以很大程度减少数据处理的工作量.

Fault diagnosis of locomotive converter based on Rough Set

The prepared data and information in database was processed, simplified so that the redundant attributes were filtered and the available fault pattern rules were extracted. According to these rules, the input fault data could be discriminated and classified in order to identify fault types, find and remove the corresponding faults. This made locomotive repairing on condition possible. The experiment results showed that the fault diagnosis based on the rough set was very effective, greatly reduced data processing workload.