基于相对小波能量的滚动轴承故障诊断  

Fault diagnosis of roller bearing based on relative wavelet energy

作　　者：赵志宏[1,2] 杨绍普[2] 

机构地区：[1]北京交通大学机械与电子控制工程学院,北京100044 [2]石家庄铁道大学信息科学与技术学院,石家庄050043

出　　处：《电子测量与仪器学报》2011年第1期44-49,共6页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金(编号:10902074)资助项目;教育部科学技术研究(编号:210023)资助项目;河北省自然科学基金(编号:E2010001095)资助项目

摘　　要：利用相对小波能量作为特征进行滚动轴承故障诊断。首先将滚动轴承振动信号进行离散小波分解,然后利用各频带的相对小波能量作为特征向量,使用支持向量机作为分类器对轴承故障进行分类。针对轴承内圈故障、滚动体故障、外圈故障3种故障及不同损伤程度的实测数据进行多种分类实验,实验结果表明利用相对小波能量作为滚动轴承故障诊断的特征非常有效,该方法能够识别滚动轴承的故障类型及故障程度,具有一定的工程应用价值。The relative wavelet energy technique is introduced to roller bearing fault diagnosis in this paper.The original bearing vibration signal is decomposed by discrete wavelet transform.Then the relative wavelet energy is served as feature vector.In the classification,the support vector machine method is used to identify the different faults.Experiments were conducted on roller bearing with three different fault categories and several levels of fault severity.The experimental results indicate that the proposed approach could reliably identify the different fault categories.Thus,the proposed approach has possibility for bearing fault diagnosis.

关 键 词：小波变换 相对小波能量 故障诊断 支持向量机 

分 类 号：TH165.3[机械工程—机械制造及自动化]