Mining dump trucks are one of the most important transportation equipment in the mining industry, and the complexity between the signs of failure and the cause of the failure is getting higher and higher. The traditional diagnosis technology alone is far from being able to meet the needs of fault diagnosis. An intelligent fault diagnosis system based on fault tree and BP neural network is proposed. The idea of this method is: first analyze the structure of mining dump trucks, establish a system fault tree, analyze the fault tree, and determine the cause of the system failure Minimal cut set, then select feature vector as the input node of neural network, use BP neural network for training, establish a fault diagnosis model based on BP neural network. Verification by a large amount of experimental data shows that the fault diagnosis model combining fault tree and BP neural network is effective, and the model greatly improves the accuracy of fault diagnosis.


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    Title :

    Intelligent Fault Diagnosis System of Mining Dump Truck Based on Fault Tree and Neural Network


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Qin, Yong (editor) / Jia, Limin (editor) / Liang, Jianying (editor) / Liu, Zhigang (editor) / Diao, Lijun (editor) / An, Min (editor) / Gao, Hongri (author) / Li, Lishan (author) / Mu, Yan (author) / Cai, Junliang (author)

    Conference:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2021 October 21, 2021 - October 23, 2021



    Publication date :

    2022-02-23


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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