Compound fault diagnosis technology is one of the key ways to solve muti-failure problems in industrial equipment condition monitoring and fault diagnosis.To solve the problem that the core components of large-scale machinery and equipment groups inevitably suffer from composite faults since that they are often operated in the environment with complex working conditions,a novel composite fault diagnosis method based on nonconvex regu-larization and sparse component analysis is proposed in this paper.The accuracy of the sparse component analysis method is improved as much as possible by constructing a nonconvex penalty function to improve the sparsity of the signal and ensuring the global convexity of the objective function.This can generate the diagnostic results by con-structing a sparse optimization framework without knowing the number of fault sources in advance.The optimal value of RMSE based on non-convex regularization in the simulation experiments is less than 0.5,which is signifi-cantly smaller than the traditional method.Taking 900 r/min and 1 300 r/min bearing fault experiments as an example,the characteristic frequencies of the outer ring,inner ring and rolling element can be recognized effec-tively,which shows that the proposed method can effectively diagnose compound faults.
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