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_{: Fault diagnosis for the vibration fault symptoms and fault types of the fault and the fault type of the fault type and the fault diagnosis of the traditional wavelet network in the fault diagnosis of the fault diagnosis model based on simulated annealing algorithm of the wavelet neural network (SA-WNN) fault diagnosis model. The SA-WNN diagnostic model is applied to four kinds of typical faults of hydro power plant to verify its feasibility. The results show that, compared with the traditional wavelet network and BP, the number of wavelet neural network training based on simulated annealing algorithm is less, and the convergence precision is high, which provides a new way for the fault diagnosis of hydroelectric generating units.}