According to the analysis on the fault diagnosis technology of Servo DC motor in aerospace measurement and control, LVQ Neural Network is studied in this paper. The ability of feature extraction and pattern recognition is the characteristics of LVQ neural network, and it is applied to analyze current signals in different branches. We proposed a servo DC motor fault diagnosis model based on LVQ neural network theory, determined the input, output, network structure and inference of the model, and designed a DC motor fault diagnosis system to identify the failure mode in the fault diagnosis of DC motor. In order to demonstrate the superiority of LVQ neural network, a classical BP neural network has been developed to solve the same problem for comparison. The simulation results shows that the LVQ neural network is effective and superiority in fault location.


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    Title :

    The Research on Servo DC Motor Fault Diagnosis with LVQ Neural Network Theory


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Shen, Rongjun (editor) / Qian, Weiping (editor) / Sun, Qing (author) / Liu, Guangping (author) / Qiu, Demin (author) / Zhang, Qi (author) / Xi, Jiaqing (author)


    Publication date :

    2014-10-07


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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