基于EEMD和MSB方法的采煤机轴承故障诊断研究  

Research on Coal Cutter Bearing Fault Diagnosis Based on EEMD and MSB Methods

作　　者：和建荣 HE Jianrong(Shaanxi Huoshizui Coal Mine Co.,Ltd.,Xianyang 713599,China)

机构地区：[1]陕西火石咀煤矿有限责任公司,陕西咸阳713599

出　　处：《机械制造与自动化》2025年第1期285-288,共4页Machine Building & Automation

摘　　要：为提高采煤机轴承故障诊断能力,设计一种通过集合经验模态分解(EEMD)与调制信号双谱(MSB)来诊断轴承故障特征的技术。利用EEMD方法对信号实施分解,对各IMF和加权平均系数乘积处理得到EEMD滤波信号,以MSB处理EEMD滤波信号实现分量调制。进行电机轴承运行故障的实验测试。结果表明:应用EEMD-MSB方法后检测信号内形成了强度很高的背景噪声与干扰信号,并获得良好的噪声抑制效果,能够有效实现采煤机轴承的故障诊断。In order to upgrade the bearing fault diagnosis ability of shears,a new technology is designed to diagnose bearing fault characteristics by integrating empirical mode decomposition(EEMD)and modulated signal bispectral(MSB).The EEMD method is used to decompose the signal,and the product of IMF and weighted average coefficients is processed to obtain the EEMD filtered signal,and MSB is applied to process the EEMD filtered signal to achieve component modulation.The running fault of motor bearing is determined and experimental test is carried out.The analysis results of bearing outer ring and inner ring show that high intensity background noise and interference signal are formed in the detection signal with the application of EEMD-MSB method,and good noise suppression effect is obtained,which realizes the fault diagnosis of coal cutter bearing effectively.

关 键 词：故障诊断 集合经验模态分解 调制信号双谱 轴承 特征提取 

分 类 号：TH133.3[机械工程—机械制造及自动化]