Proceedings of the 13th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2020, 27-28 August 2020, Cyberspace

Research Article

Research on Real-time Mining of New Energy Vehicle Fault Diagnosis Data under Cloud Computing

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  • @INPROCEEDINGS{10.4108/eai.27-8-2020.2294585,
        author={jiatong  wei and Yan  XU and Chun-hua  KONG},
        title={Research on Real-time Mining of New Energy Vehicle Fault Diagnosis Data under Cloud Computing },
        proceedings={Proceedings of the 13th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2020, 27-28 August 2020, Cyberspace},
        publisher={EAI},
        proceedings_a={MOBIMEDIA},
        year={2020},
        month={11},
        keywords={cloud computing; new energy vehicles; fault diagnosis; data mining},
        doi={10.4108/eai.27-8-2020.2294585}
    }
    
  • jiatong wei
    Yan XU
    Chun-hua KONG
    Year: 2020
    Research on Real-time Mining of New Energy Vehicle Fault Diagnosis Data under Cloud Computing
    MOBIMEDIA
    EAI
    DOI: 10.4108/eai.27-8-2020.2294585
jiatong wei,*, Yan XU1, Chun-hua KONG1
  • 1: Department of Automotive Engineering,Jilin Communications Polytechnic
*Contact email: ouyangmeixue100@163.com

Abstract

In order to effectively improve the semantic retrieval ability and information analysis ability of network database, and improve the accuracy of data mining of new energy vehicle fault diagnosis, a real-time data mining method of new energy vehicle fault diagnosis under cloud computing is proposed. The modern signal mining technology is used to analyze the fault diagnosis data of new energy vehicles, and a data signal analysis model is established. On this basis, the fault diagnosis data of each section of new energy vehicles are segmented matched and filtered, and the characteristic input of the fault diagnosis data of new energy vehicles is obtained, combining the optimal classification surface of the fault diagnosis data characteristics of new energy vehicles and the fault of new energy vehicles The feature vector track of the fault diagnosis data can realize the extraction of the feature value of the fault diagnosis data of new energy vehicles, and complete the real-time mining of the fault diagnosis data of new energy vehicles under the cloud computing. Experimental results show that the proposed method has high accuracy and real-time performance.