Based on analyzing the disadvantages of traditional adaptive stochastic resonance, for example, optimizing only one parameter which ignores the interaction between parameters and the convergence speed of genetic algorithm slowing down with the increasing population, a new adaptive stochastic resonance method is proposed. With a wide range of initial value and parameter setting, the proposed method adaptively realizes the optimal stochastic resonance system matching input signals, utilizing the ability of parallel processing and the characteristics that the algorithm has faster convergence speed with the increasing of the number of artificial fish. The analysis of the simulation data and the bearing fault data shows that the new adaptive stochastic resonance method effectively realizes the weak signal detection and early fault diagnosis.