基于FRS—SVM采煤机液压系统故障诊断的研究

结合模糊粗糙集(FRS)理论和支持向量机(SVM)分类机理,提出了一种新的液压系统故障诊断方法。应用FRS理论处理不确定、不完备信息的属性约简能力,剔除冗余信息,获得具有代表性的特征信息,再利用SVM的推广能力,对小样本数据进行故障诊断。通过此方法对采煤机牵引部液压系统的故障诊断仿真实验,结果证明大大提高了诊断精度和效率。

Research on Fault Diagnosis for Hydraulic System Based on FRS-SVM

The dissertation brings forward a new method in hydraulic system fault diagnosis based on Fuzzy-rough set(FRS) theory and support vector machine(SVM).FRS has strong attribute reduction ability in handling uncertain and incomplete information by removing the redundant parts and getting the representative features.SVM is very efficient in classification and regression.Can carry out fault diagnosis in small sample of data using FRS theory combined with SVM.It is proved that higher diagnostic precision and high...