For problem that uncertainty of model of the flight control system of an unmanned tandem helicopter, a tandem unmanned helicopter intelligent fault diagnosis method based on support vector machine is proposed. First, the method uses fuzzy sample support vector machine (FS-SVM) diagnostics to conduct actuator fault diagnosis for flight control system. Then, the fuzzy membership function is selected according to factors of the cost of the decision-making loss, damage, etc. Meanwhile, the fault pattern classification is conducted more effective, intelligent diagnosis and stability of flight control system of unmanned helicopter fault are achieved. The simulation experiment results show that the proposed algorithm can put all the fault sample accurate grouping, reduce the misjudgment phenomenon. The method can effectively carry out UAVs fault diagnosis, to ensure the safety and reliability of flight control.


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    Title :

    Research on UAV Intelligent Fault Diagnosis Method Based on FS-SVM


    Contributors:
    Guo-qing, Liu (author) / Xiao-chun, Shi (author) / Ning, Wang (author)


    Publication date :

    2021-08-20


    Size :

    952028 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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