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LMD的LabVIEW实现及其在齿轮故障诊断中的应用

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作者:唐贵基, 王晓龙

作者单位:华北电力大学机械工程学院, 河北 保定 071003


关键词:LMD模块; LabVIEW系统; 齿轮故障


摘要:

将局部均值分解(local mean decomposition,LMD)算法在LabVIEW平台上加以实现,开发出LabVIEW的LMD模块。为减小误差,采用三次样条插值法代替滑动平均法来获得局部均值函数和包络估计函数,用形态学滤波算法得到瞬时频率和瞬时幅值的平滑曲线,并通过仿真信号验证LMD算法对于多分量信号的分解能力。最后,利用开发的模块对实测齿轮磨损、断齿故障信号进行分析,成功提取出故障特征频率信息,结果表明开发的LMD模块可以有效应用于齿轮故障的诊断。


LMD realization by LabVIEW and its application in gear fault diagnosis

TANG Gui-ji, WANG Xiao-long

School of Mechanical Engineering, North China Electric Power University, Baoding 071003, China

Abstract: According to the local mean decomposition (LMD) algorithm, the LabVIEW LMD module was developed. It used cubic spline interpolation instead of sliding average method to obtain local mean function and envelope estimation function in order to reduce the error and used morphological filtering algorithm to smooth the instantaneous frequency and amplitude curve. The simulation signal was used to verify the decomposition ability of LMD for multi-component signals. Finally, the developed module was used to measure wear fault signal and broken teeth fault signal and successfully extract the fault characteristic frequency information. The results show that the developed LMD module could diagnosis the gear fault effectively.

Keywords: LMD; LabVIEW; gear fault

2014, 40(1): 101-105  收稿日期: 2013-4-21;收到修改稿日期: 2013-6-3

基金项目: 

作者简介: 唐贵基(1962-),男,山东龙口市人,教授,博士,研究方向为机械设备状态监测及故障诊断。

参考文献

[1] 陈亚农,郜普刚,和田,等. 局部均值分解在滚动轴承故障综合诊断中的应用[J]. 振动与冲击,2012,31(3):73-78.
[2] 任达千,杨世锡,吴昭同,等. LMD时频分析方法的端点效应在旋转机械故障诊断中的影响[J]. 中国机械工程,2012,23(8):951-956.
[3] 程军圣,杨宇,张亢. 基于噪声辅助分析的总体局部均值分解方法[J]. 机械工程学报,2011,47(3):55-62.
[4] Smith J S. The local mean decomposition and its application to EEG perception data[J]. Journal of the Royal Society Interface,2005,2(5):443-454.
[5] Rilling G, Flandrin P, Goncalves P. On empirical mode decomposition and its algorithms[C]//IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing,2003(6):9-11.
[6] 胡劲松,杨世锡. 基于样条的振动信号局域均值分解方法[J].数据采集与处理,2009,24(1):82-86.
[7] 毛博,高斐,孟军. 一种基于分段幂函数插值法的经验模态分解方法及其应用研究[J]. 中国测试,2013,39(2):125-128.
[8] 唐贵基,王维珍,胡爱军. 数学形态学在旋转机械振动信号处理中的应用[J]. 汽轮机技术,2005,47(4):271-273.