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Weight Training Algorithm of BP Neural Network Based on Iterative Learning

ZHOU Xiaoyong, ZHAI Chunyan, LI Shuchen, SU Chengli

Abstract （448）

PDF （1396KB）（210）

A weight training algorithm of neural network based on iterative learning was proposed for the shortcoming of traditional BP algorithm, such as slow convergence and easily trapped into local minimal. The algorithm combined the principle of iterative learning with neural network, and it made use of the current and the previous training error to correct the neural network weights. It improved the speed of neural network training. Simulation results show the effectiveness of the algorithm.

2013, 33 (4): 83-86.

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Application of Algorithm for Turbine Rotor Fault Diagnosis

LIU Da, ZHAI Chunyan, LI Shuchen, SU Chengli

Abstract （422）

PDF （1659KB）（218）

Turbine rotor fault diagnosis is the key to ensuring the safe operation of the steam turbine. Vibration signal analysis is widely used in turbine rotor fault diagnosis. The wavelet packet analysis method was adopted to extract the vibration signal eigenvalue as the input of BP neural network, the nonlinear mapping relationship between signal features and fault type and realizing the fault diagnosis with BP neural network was established. The simulation results show that this method can effectively diagnosis turbine rotor fault.

2013, 33 (3): 67-69.