Dual-Wavelet Dictionary Based Feature Extraction Method for Compound Faults in Gearboxes

WANG Xiangdong; LIU Qiang; XIANG Leilei; SU Zhen; CHEN Baojia; CHEN Shu; ZHANG Wenzhong

doi:10.7652/xjtuxb202509010

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Dual-Wavelet Dictionary Based Feature Extraction Method for Compound Faults in Gearboxes

更新时间：2025-09-11

- Dual-Wavelet Dictionary Based Feature Extraction Method for Compound Faults in Gearboxes
- Journal of Xi’an Jiaotong University Vol. 59, Issue 9, Pages: 99-109(2025)
- 作者机构：
  
  1.三峡大学水电机械设备设计与维护湖北省重点实验室， 443002，湖北宜昌
  2.三峡大学机械与动力学院， 443002，湖北宜昌
  3.中国长江电力股份有限公司， 430000，武汉
  4.三峡大学水利与环境学院， 443002，湖北宜昌
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202509010
  CLC： TH17
- Received：17 February 2025，
  
  Online First：09 June 2025，
  
  Published：10 September 2025
- 稿件说明：
移动端阅览
WANG Xiangdong, LIU Qiang, XIANG Leilei, et al. Dual-Wavelet Dictionary Based Feature Extraction Method for Compound Faults in Gearboxes[J]. Journal of Xi’an Jiaotong University, 2025, 59(9): 99-109.
DOI：

WANG Xiangdong, LIU Qiang, XIANG Leilei, et al. Dual-Wavelet Dictionary Based Feature Extraction Method for Compound Faults in Gearboxes[J]. Journal of Xi’an Jiaotong University, 2025, 59(9): 99-109. DOI： 10.7652/xjtuxb202509010.

摘要

针对齿轮箱复合故障诊断中齿轮与轴承特征相互干扰、现有方法难以有效分离高频谐波与冲击成分的难题，提出一种基于双小波字典的稀疏正则化特征提取方法。通过构建Morlet小波-齿轮振动匹配模型与Laplace小波-轴承冲击响应模型的联合字典，结合广义极小极大凹惩罚函数优化稀疏分解过程，在保证目标函数凸性的同时克服了传统

范数导致的幅值衰减问题。仿真与实验结果表明：所提方法实现了齿轮局部损伤与轴承外圈故障的同步解耦，相比MOMEDA及IESFOgram方法，特征频率谐波提取完整度高；对于前5倍故障特征频率的信噪比提升了1~2 dB。

Abstract

To address the challenges of mutual interference between gear and bearing features in gearbox compound fault diagnosis and the difficulty of existing methods in effectively separating high-frequency harmonics and impact components

a sparse regularization feature extraction method based on a dual wavelet dictionary is proposed. By constructing a joint dictionary comprising a Morlet wavelet-gear vibration matching model and a Laplace wavelet-bearing impact response model

combined with the generalized minimax concave penalty function to optimize the sparse decomposition process

the convexity of the objective function is preserved while overcoming the amplitude attenuation issue caused by traditional norms. Simulations and experiments demonstrate that the proposed method achieves synchronous decoupling of gear localized damage and bearing outer ring faults. Compared to the MOMEDA and IESFOgram methods

it exhibits higher completeness in extracting harmonic features of fault characteristic frequencies

with a 1—2 dB improvement in the signal-to-noise ratio for the first five multiples of the fault characteristic frequency.

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references

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