基于小波变换与粗集理论的滚动轴承故障诊断  

Roller Bearing Fault Diagnosis Approach Based on Wavelet Transform and Rough Set Theory

作　　者：张邦基[1] 于德介[1] 杨胜[1] 

机构地区：[1]湖南大学汽车车身先进设计制造国家重点实验室,长沙410082

出　　处：《中国机械工程》2008年第15期1793-1795,1831,共4页China Mechanical Engineering

基　　金：国家自然科学基金资助项目(50275050)

摘　　要：结合小波和粗集理论的优点,提出了一种基于小波变换和粗集理论的故障诊断规则获取方法并成功应用于滚动轴承的故障诊断。该方法提取小波变换能量特征时不需要精确计算滚动轴承的故障特征频率,与传统的提取时域和频域参数方法相比,具有更高的诊断正确率。研究结果为滚动轴承和其他机械设备的故障诊断提供了新的思路,也为基于规则的智能故障诊断系统提供了一种更为简单的知识库自动构造方法。A new method was presented for fault diagnosis rule acquisition based on wavelet trans form and rough set. It linked the wavelet and rough set theory. The method was applied to roller bearing fault diagnosis successfully. It gives a higher fault diagnosis ratio using energy feature than the traditional method using time and frequency parameters. It proposes a new method for fault diagnosis of roller bearings and other machine equipment, and gives a new method for building the simpler knowledge base of intelligent fault diagnosis system.

关 键 词：小波变换 能量特征 粗集理论 故障诊断 滚动轴承 

分 类 号：TH165.3[机械工程—机械制造及自动化]