小波在采煤机异步电动机故障诊断中的应用  

Application of Wavelet in Shearers Motor Fault Diagnosis

作　　者：谢国民[1] 佟莹[2] 陆文斌[3] 

机构地区：[1]辽宁工程技术大学电控学院,辽宁葫芦岛125105 [2]辽宁工程技术大学营销学院,辽宁葫芦岛125105 [3]中国民航大学航空自动化学院,天津300300

出　　处：《控制工程》2013年第4期711-714,共4页Control Engineering of China

基　　金：国家自然科学基金资助项目(50874059);教育部博士点基金资助项目(200801470003)

摘　　要：为了能及时准确的发现采煤机电机故障,快速做出电机故障诊断决策,减小损失,针对采煤机电动机中常见的滚动轴承故障,在对采煤机机械故障信号进行深入分析的基础上,提出一种基于正交小波的采煤机电机故障诊断方法。利用小波变换在特征分析过程中所得到的小波熵值、峭度值以及平滑指数三大特征参数,通过对参数的比较分析,得到不同参数下电机滚动轴承故障的不同类型,并设计开发了基于小波分析的采煤机电机故障诊断专家系统。实验结果表明,故障诊断系统能正确判断故障部位及类型,并给出针对性维修策略,大大减少了故障诊断时间,具有较好实际应用价值。Aiming at salving the problem of rolling beating fault in the motor of coal mining machine , diagnosing the fault of coal mining machine motor timely and exactly, and making decision quickly to reduce the loss, a kind of Orthogonal wavelet transformation motor diagnose method is put forward by thoroughly analyzing the mechanical fault signal. Three characteristic parameters are got in the process of analyzing wavelet transformation features ： wavelet entropy, kurtosis value and smoothness index. By comparing and analyzing these parameters, different types of motor rolling bearing fault are obtained and the corresponding fault diagnosis expert system based on wavelet analysis is designed. The experimental results show that this fault diagnosis system can correctly determine the location and the type of the fault and make targeted maintenance decision quickly, and can thus greatly reduce the time of fault diagnosis and has high application of practical value.

关 键 词：小波变换 专家系统 电机滚动轴承 故障诊断 

分 类 号：TP27[自动化与计算机技术—检测技术与自动化装置]