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    • Research on Fault Diagnosis Method of Injection System of Marine Low-Speed Diesel Engine Based on Transfer Learning
    DOI：10.13949/j.cnki.nrjgc.2023.01.003
    Key Words:low speed engine  fuel injection system  fault simulation  fault diagnosis  transfer learning
    Author NameAffiliationE-mail
    DONG Fei* School of Naval Architecture， Ocean and Energy Power Engineering， Wuhan University of Technology， Wuhan 430063， China feidongfly@163.com 
    YANG Jianguo* School of Naval Architecture， Ocean and Energy Power Engineering， Wuhan University of Technology， Wuhan 430063， China
    Key Laboratory of Marine Power Engineering and Technology Granted by MOT， Wuhan 430063， China
    National Engineering Laboratory for Marine and Ocean Engineering Power System， Wuhan 430063， China     		jgyang@whut.edu.cn 
    FAN Yu School of Naval Architecture， Ocean and Energy Power Engineering， Wuhan University of Technology， Wuhan 430063， China
    Key Laboratory of Marine Power Engineering and Technology Granted by MOT， Wuhan 430063， China
    National Engineering Laboratory for Marine and Ocean Engineering Power System， Wuhan 430063， China     		 
    HU Lei School of Naval Architecture， Ocean and Energy Power Engineering， Wuhan University of Technology， Wuhan 430063， China
    Key Laboratory of Marine Power Engineering and Technology Granted by MOT， Wuhan 430063， China
    National Engineering Laboratory for Marine and Ocean Engineering Power System， Wuhan 430063， China     		 
    XIE Liangtao School of Naval Architecture， Ocean and Energy Power Engineering， Wuhan University of Technology， Wuhan 430063， China  
    BAI Zefang School of Naval Architecture， Ocean and Energy Power Engineering， Wuhan University of Technology， Wuhan 430063， China  
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    Abstract:To solve the problem that the low speed diesel engine fault simulation tests cost is high and its sample data are hard to get， a marine low speed diesel engine injection system model and a one-dimensional diesel engine model were established. Based on simulation， the samples of the injector nozzle wear， the volume of injection reducing and the injection timing fault were simulated and analyzed. Seven fault characteristic parameters were selected based on the percentage change of fault parameters. The effectiveness of the characteristic parameters selected for the fault diagnosis and the fault classification was verified by the principal component analysis. Considering that traditional machine learning fault diagnosis algorithm requires the data is independently and identically distributed， a diagnosis model of the marine low speed diesel engine fuel injection system based on TrAdaBoost transfer learning algorithm was proposed. The 3 560 simulation fault samples and the verification result indicated that the accuracy of diagnosis was above 85%. The results show that the model can transfer diagnosis knowledge between different loads of low speed diesel engine.
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