Balance Sparse Decomposition Method with Nonconvex Regularization for Gearbox Fault Diagnosis  

作　　者：Weiguo Huang Jun Wang Guifu Du Shuyou Wu Zhongkui Zhu 

机构地区：[1]School of Rail Transportation,Soochow University,Suzhou 215131,China [2]Wuhan Second Ship Design and Research Institute,Wuhan 430060,China

出　　处：《Chinese Journal of Mechanical Engineering》2024年第5期258-271,共14页中国机械工程学报（英文版）

基　　金：Supported by National Natural Science Foundation of China(Grant Nos.52075353,52007128).

摘　　要：As an important part of rotating machinery,gearboxes often fail due to their complex working conditions and harsh working environment.Therefore,it is very necessary to effectively extract the fault features of the gearboxes.Gearbox fault signals usually contain multiple characteristic components and are accompanied by strong noise interference.Traditional sparse modeling methods are based on synthesis models,and there are few studies on analysis and balance models.In this paper,a balance nonconvex regularized sparse decomposition method is proposed,which based on a balance model and an arctangent nonconvex penalty function.The sparse dictionary is constructed by using Tunable Q-Factor Wavelet Transform(TQWT)that satisfies the tight frame condition,which can achieve efficient and fast solution.It is optimized and solved by alternating direction method of multipliers(ADMM)algorithm,and the non-convex regularized sparse decomposition algorithm of synthetic and analytical models are given.Through simulation experiments,the determination methods of regularization parameters and balance parameters are given,and compared with the L1 norm regularization sparse decomposition method under the three models.Simulation analysis and engineering experimental signal analysis verify the effectiveness and superiority of the proposed method.

关 键 词：Gearbox fault diagnosis Balance model Sparse decomposition Non-convex regularization 

分 类 号：TH132.41[机械工程—机械制造及自动化]