The characteristic analysis of stochastic resonance and bearing fault diagnosis based on NWSG model driven by trichotomous noise

Abstract In this paper, a new system whose potential function (NWSG) based on the joint of New Woods-Saxon potential function(NWSP) and Gaussian potential function(GP), driven by trichonomous is proposed to optimize the perform in bearing fault diagnosis. Firstly, exploring the influence of various system parameters on the shape of NWSG, besides, presenting a method of numerical simulation for trichotomous noise. The results show that the potential function can convert between three state, which is monostable, bistable, and tristable respectively, under different system parameter values. In addition, the mean of signal-noise ratio increase(MSNRI) is served as the measurement index of stochastic resonance (SR) for periodic signal detection, while traditional SR under optimal parameters. Finally, bearing fault diagnosis is carried out. It is found that the performance of the proposed system is better than traditional system which also verified in the bearing fault diagnosis.

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