Equipment Fault Diagnosis Based on Self-Organizing Neural Network

Abstract

Self-organizing map mentor information could not be applied as unsupervised network faults, this paper proposes a method of artificially joining mentor information in output of neuronal topology in self-organizing network, developed for the method of ideological classification criteria. The use of self-organizing map neural network system of intelligent BIT equipment failure prediction information extracted vector self-organization of pattern classification, and the method used in diesel fuel injection system of the intelligent BIT to verify. The simulation results indicate that this algorithm effectively distinguishing the equipment system of the running state, the feasibility of the method is proved by actual fault diagnosis.

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Cite this paper

@article{FangXi2012EquipmentFD, title={Equipment Fault Diagnosis Based on Self-Organizing Neural Network}, author={Li Fang-Xi and Chen Gui-Ming and Zhang Qian and Fang Xiao-Dong}, journal={2012 International Conference on Computer Science and Service System}, year={2012}, pages={1212-1215} }