基于声音信号和改进MS-LMD的风电齿轮箱故障诊断

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振动与冲击 ›› 2021, Vol. 40 ›› Issue (11) : 230-239.

论文

刘少康1，武英杰1,2，安伟伦1，辛红伟1,2 ，杨彦军1，王建国1,2

作者信息 +

Wind turbine gearbox fault diagnosis based on sound signal and improved MS-LMD

LIU Shaokang1, WU Yingjie1,2, AN Weilun1, XIN Hongwei1,2, YANG Yanjun1, WANG Jianguo1,2

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文章历史 +

摘要

基于声音信号的机械故障诊断切实可行，但风电齿轮箱声音信号可拾取到机舱内的多个振源信号和干扰噪声，影响故障的精确定位，为此，提出一种改进的局部均值分解（local mean decomposition， LMD）方法，通过分离声音信号中的调频调幅成分，实现齿轮箱复合故障诊断。根据掩膜信号(masking signal ，MS)可抑制模态混叠的特点，采用二分法在幅值加权平均频率的1.0倍~1.5倍内搜索MS频率，提出MS与LMD多次结合的循环迭代方式，依次判断、抑制多组模态混叠现象。通过两类易发生模态混叠的仿真信号验证了该方法有效性，并将其应用于现场风电齿轮箱声音信号分析中，成功诊断出齿轮箱复合故障。

Abstract

Machinery’s fault diagnosis based on sound signal is feasible, but sound signal sensors of wind turbine gearbox can pick up multiple vibration source signals and interference noise in its engine room to affect accurate locating of faults.Here, an improved local mean decomposition (LMD) method was proposed to realize gearbox composite fault diagnosis through separating frequency modulation (FM) and amplitude modulation components of a sound signal.According to the feature of masking signal (MS) being able to suppress mode aliasing, the dichotomy method was used to search MS frequency in the range of 1.0-1.5 times of amplitude weighted average frequency.A cyclic iterative method to combine repeatedly MS and LMD was proposed to judge and suppress multi-group mode aliasing in turn.The effectiveness of the proposed method was verified using two kinds of simulated signals being easy to have modal aliasing.The proposed method was applied in sound signal analysis of an actual wind turbine gearbox to successfully diagnose its composite faults.

导出引用

刘少康1，武英杰1,2，安伟伦1，辛红伟1,2,杨彦军1，王建国1,2. 基于声音信号和改进MS-LMD的风电齿轮箱故障诊断[J]. 振动与冲击, 2021, 40(11): 230-239

LIU Shaokang1, WU Yingjie1,2, AN Weilun1, XIN Hongwei1,2, YANG Yanjun1, WANG Jianguo1,2. Wind turbine gearbox fault diagnosis based on sound signal and improved MS-LMD[J]. Journal of Vibration and Shock, 2021, 40(11): 230-239

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