摘要
数学形态学是一种非线性、非平稳分析方法，具有很强的抑制脉冲干扰的能力，但滤除白噪声的能力却不行。针对这一不足，提出一种基于LMD的多尺度形态学解调方法。该方法是将多分量调频调幅故障信号分解为一系列单分量调频调幅信号（PF），实现对故障信号的降噪处理，同时还可以获得原始信号的全部调制信息。选取能量高的PF分量求和重构，再用多尺度形态学差值滤波器提取出故障信号的频率特征。通过仿真和齿轮故障模拟实验证实了该方法的有效性。
Abstract
Mathematical morphology is a kind analysis method of nonlinear and non-stationary, it has a strong ability to restrain pulse interference, but has no ability to filter the white noise. Aim at this shortage, an multi-scale morphology method based on local mean decomposition(LMD) is proposed. the fault signal of multi-component frequency modulation and amplitude modulation is decomposed into a series of single component (PF), thus can
implement signal de-noising processing and also can obtain the total amplitude modulation information of original signal.
Select the high energy PFs and sum them, then reconstitute them, finally use multi-scale morphological difference filter to extract the fault characteristic frequency. It can show the validity of this method through simulation and gear fault simulation.
关键词
数学形态学 /
局部均值分解 /
故障特征频率 /
齿轮故障
{{custom_keyword}} /
Key words
mathematical morphology /
LMD /
Fault characteristic frequency /
Gear fault
{{custom_keyword}} /
侯高雁;吕勇;肖涵;郝志强.
基于LMD的多尺度形态学在齿轮故障诊断中的应用[J]. 振动与冲击, 2014, 33(19): 69-73
HOU Gao-yan;Lv Yong;XIAO Han;HAO Zhi-qiang.
Approach to application in the gear fault diagnosis based on the LMD and multi-scale morphology [J]. Journal of Vibration and Shock, 2014, 33(19): 69-73
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}
PDF(1270 KB)
