摘要
将采集到的数据进行模糊化处理,然后运用支持向量机对计算出的模糊样本进行训练,并对其进行模拟仿真,结果与实际试验结果基本相符。克服了根据单一的频谱变化来判断故障的类型,有效地提高了故障诊断性能。
It was first processed the collected data with fuzzy theory,used SVM training the result of samples calculated by fuzzy theory,and then simulated for it.The result of the simulation matched with the result of actual experiment.it was overcome the singleness method of determine the type of fault in the basis of the changing of spectrum,and the algorithm greatly improved the performance of fault diagnosis.
出处
《铁路计算机应用》
2010年第12期15-17,共3页
Railway Computer Application
关键词
模糊理论
支持向量机
故障诊断
fuzzy theory
SVM（Support Vector Machine）
fault diagnosis
