Abstract: Aiming at the problem that in the actual working environment of mechanical equipment, the useful signal was usually weak and submerged in strong noise, which made it difficult to extract the fault features, a mechanical fault signal detection method of time-delay constrained potential stochastic resonance was proposed. First of all, a time-delay constrained potential stochastic resonance model was established, the structure and functional characteristics of its potential function were described, the mathematical expression of the output signal-to-noise ratio was theoretically derived, and the influence of system parameters, time extension and feedback strength on the relationship between signal-to-noise ratio and noise intensity was investigated. Then, the optimal matching of the stochastic resonance system was achieved by using the parameter optimization capability of the ant colony algorithm. Finally, the proposed method was applied to the experiment of simulating the fault signal and the actual rolling bearing outer ring fault signal. The results are compared with those obtained by the bistable stochastic resonance method. The research results show that the proposed time-delay constrained potential stochastic resonance method has higher spectral peaks than the classical bistable stochastic resonance method at fault frequencies of 60Hz and 143.08Hz, and is less disturbed by noise. The fault identification effect is obvious, which improves the weak fault diagnosis capability of the rolling bearing and other mechanical equipment.

Key words:  mechanical fault diagnosis; rolling bearing; time-delay constrained potential; stochastic resonance; signal-to-noise ratio

LI Zhi-xing, WANG Guang-jin, BAO Hui-ru.Mechanical fault diagnosis method based on time-delay  constrained potential stochastic resonance[J].Journal of Mechanical & Electrical Engineering,2021,38(10):1238-1245.