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局域均值分解方法在机械故障诊断中的应用
Local Mean Decomposition and Its Application to the Machine Fault Diagnosis
【摘要】 局域均值分解(Local Mean Decomposition,LMD)是近年来出现的一种新的时频分析方法。介绍局域均值分解的定义、基本算法。仿真验证LMD方法的有效性,结果表明LMD计算所得的瞬时频率均有物理意义,能更好地反映实际系统的状态。将该方法应用到轴承故障诊断中,实验证明该方法是有效的。
【Abstract】 The definition and algorithm of local mean decomposition(LMD),which was a new time-frequency method,were introduced.The effection of LMD was verified through simulation.The results show that all the instantaneous frequencies calculated by LMD have physical sense.They can reflect state of actual system.LMD was applied in bearing fault diagnosis.The experimental result reflects that this method is effective.
【关键词】 局域均值分解;
故障诊断;
非平稳信号;
时频分析;
特征提取;
【Key words】 Local mean decomposition(LMD); Fault diagnosis; Non-stationary signal; Time-frequency analysis; Feature extraction;
【Key words】 Local mean decomposition(LMD); Fault diagnosis; Non-stationary signal; Time-frequency analysis; Feature extraction;
【基金】 国家自然科学基金项目(50775208);河南省教育厅自然科学基金项目(2008C460003,2006460005)
- 【文献出处】 机床与液压 ,Machine Tool & Hydraulics , 编辑部邮箱 ,2011年01期
- 【分类号】TH165.3
- 【被引频次】14
- 【下载频次】307