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《Computer Measurement & Control》 2016-08
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Study for Vibration Fault Diagnosis of Hydro-turbine Generating Unit Based on SA-WNN

Liang Hongmei;Xiao Zhihuai;Xinjiang Changji Vocational and Technical College;Ministerial Key Laboratory for Hydrodynamic Transients,Wuhan University;  
Aiming at fault diagnosis for the vibration fault symptoms and fault types the fault diagnosis model based on simulated annealing algorithm of the wavelet neural network(SA-WNN)is proposed.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.
【Fund】: 国家自然科学基金项目(51379160)
【CateGory Index】: TV738;TP18
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