基于自适应噪声参数优化ELMD的行星齿轮箱故障诊断研究

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摘要针对总体局部平均分解(Ensemble Local Mean Decomposition, ELMD)中添加白噪声的振幅和集成次数两个关键参数设置依赖使用者经验，以及添加噪声后在信号重构过程中存在残余噪声污染和运算量大的问题，提出一种自适应噪声参数优化的总体局部均值分解（Adaptive Parameter Optimized Ensemble Local Mean Decomposition, APOELMD）方法。该方法首先在局部均值分解(Local mean decomposition, LMD)过程中添加成对高频正负白噪声，噪声的幅值和集成次数分别固定为0.01SD（SD为原始信号的标准差）和2；然后不断地改变白噪声的上限频率，利用相对均方根误差这一指标来自适应地选取白噪声的最佳上限频率；白噪声的最佳上限频率确定之后，APOELMD方法即可实现最理想的分解效果。仿真实验结果表明，该方法显著提升了ELMD的性能，提高了诊断效率。将该方法应用于行星轮箱故障诊断中，能够精确提取故障特征信息，实现了对行星齿轮箱局部损伤故障的准确判别。

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	王朝阁1
	李宏坤1
	杨蕊1
	任学平2

关键词 ：总体局部均值分解, 噪声最佳上限频率, 参数优化, 行星齿轮箱, 特征提取

Abstract：

The selection mechanism of the two critical parameters (the amplitude of the added white noise and the number of ensemble trials) for adding white noise in the ensemble local mean decomposition is not clear. After adding white noises generate some tough problems including the pollution of the residue noise in the signal reconstruction, and the large computational cost. To overcome these problems, an adaptive noise parameter optimized ensemble local mean decomposition (APOELMD) is proposed in this paper. The method first adds a pair of pairs of high frequency positive and negative white noise in the process of local mean decomposition. The amplitude of the added white noise and the number of ensemble trials are respectively fixed as 0.01 times standard deviation of the original signal and two. Then the upper limit frequency of white noise is constantly changed, and the best upper limit frequency of white noise is selected by the index of relative root-mean-square error. After determining the best upper limit frequency of white noise, the APOELMD method can achieve the most ideal decomposition effect. The simulation results showed that the proposed method greatly improves the performance of ensemble local mean decomposition and improves the diagnostic efficiency. The method was applied to fault diagnosis of planetary gearbox, which could extract fault feature information accurately, and achieved accurate discrimination of local damage faults of planetary gearbox.

Key words： ensemble local mean decomposition optimal upper bound frequency of white noise parameter optimization planetary gearboxes feature extraction

收稿日期: 2019-03-11 出版日期: 2020-09-15

引用本文:

王朝阁1，李宏坤1，杨蕊1，任学平2. 基于自适应噪声参数优化ELMD的行星齿轮箱故障诊断研究[J]. 振动与冲击, 2020, 39(18): 60-69.
WANG Chaoge1，LI Hongkun1，YANG Rui1，REN Xueping2. Fault diagnosis of planetary gearboxes based on adaptive parameter optimized ensemble local mean decomposition. JOURNAL OF VIBRATION AND SHOCK, 2020, 39(18): 60-69.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2020/V39/I18/60

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