基于F_υ-SVM的机械故障诊断方法

Mechanical fault diagnoses approach based on F_υ-SVM

针对机械故障诊断中存在的小样本、模糊、不确定性特征数据等问题,将改进三角模糊理论与支持向量分类机(SVM)方法相结合,提出一种Fv-SVM模型,给出相应的机械故障诊断方法.最后进行了复杂设备故障诊断的实例分析,结果表明基于Fv-SVM的机械故障诊断方法是有效和可行的.

Aiming at the problems of small samples and uncertainty data in mechanical fault diagnoses, improved triangular fuzzy theory is combined with support vector classifier machine, and a kind of fuzzy support vector classifier machine named Fv-SVM is proposed. And then, a mechanical fault diagnoses method are put forward. The results of application in complex equipment show that the fault diagnoses method based on Fv-SVM is feasible and effective.