采用双小波字典的齿轮箱复合故障特征提取方法

打开文本图片集

关键词：齿轮箱故障；稀疏分解；复合故障；故障诊断

中图分类号：TH17文献标志码：A

DOI：10.7652/xjtuxb202509010 文章编号：0253-987X（2025）09-0099-11

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

WANG Xiangdong 1，2 ，LIU Qiangl'²，XIANG Leilei³，SU Zhen 3 ，CHEN Baojia 1，2 ， CHEN Shu4，ZHANG Wenzhong1，2

（1. Hubei Key Laboratory of Hydroelectric Machinery Design and Maintenance， China Three Gorges University，Yichang， Hubei 443002，China；2. Colege of Mechanical and Power Engineering，China Three Gorges University，Yichang， Hubei 443002，China；3. China Yangtze Power Co.，Ltd.，Wuhan 430000，China；4. College of Hydraulic & Environmental Engineering，China Three Gorges University，Yichang，Hubei 4430o2，China）

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.

Keywords： gearbox fault; sparse decomposition; compound fault; fault diagnosis

齿轮箱在汽车、航空、能源和工程机械等关键领域中扮演着动力传递和结构支撑的重要角色，其能否正常运行对机械设备的安全服役至关重要[1]。（剩余15027字）