پایان نامه تشخیص خطای سیم بندی استاتور با آنالیز موجک و شبکه عصبی

مراجع فارسی

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چکیده انگلیسی:

Abstract : Based upon wavelet transformation analysis and BP neural network , a method for the fault diagnosis of stator winding is proposed . Firstly wavelet transformation was used to decompose  vibration time signal of stator to extract the characteristic values-wavelet transformation energy, and features were input in to the BPNN.  After training the BPNN could be used to identify the stator winding fault (turn to turn fault) patterns.

Seven typical turn to turn fault as 10 turn, 15 turn, 20turn, 26turn,31turn and 35 turn were studied. The result showed that the method of BPNN with wavelet transformation could not only detect the exiting of the fault in stator winding, but also effectively identify the fault patterns.

Key Words: wavelet transformation, BP network, stator winding, fault diagnosis