Incipient Bearing Fault Diagnosis Based on the Two-State Theory for Stochastic Resonance Systems

Abstract

The principle of stochastic resonance (SR) has been intensively used in designing algorithms for incipient bearing fault diagnosis based on stochastic simulation. In order to directly apply the semi-analytic result to the laboratory designs, an incipient bearing fault diagnosis algorithm based on the method of moments for stochastic resonant systems was proposed, with its real-time monitoring efficiency being assured by an available table of the involving stationary moments. Nevertheless, since the noise that buried the fault signal can only be estimated after sampling, calculation of such stationary moments might be an inconvenience. To fix this inconvenience, a brand-new fault diagnosis algorithm is designed in this paper based on the two-state theory for a biased underdamped bistable stochastic resonant system. The capability and the efficiency of the algorithm in identifying the characteristic frequency of the hidden fault signal are confirmed with the experimental data sets. This investigation actually opens a new way for improving the existing SR-based diagnosis algorithms.