Application for diesel engine in fault diagnose based on fuzzy neural network and information fusion

According to a variety of diesel engine malfunctions, a method for fault diagnoses of diesel engine based on neural net work and information fusion is put forward. The model has the characteristic of fast inference speed applying fuzzy membership functions to depict the fault extent. The model of fa...

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Bibliographische Detailangaben
Hauptverfasser: Liang Guihang, Wang Qiang, Wang Jian, Song Jingui
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:According to a variety of diesel engine malfunctions, a method for fault diagnoses of diesel engine based on neural net work and information fusion is put forward. The model has the characteristic of fast inference speed applying fuzzy membership functions to depict the fault extent. The model of fault diagnoses is set up by using the state parameter of diesel engine as learning samples. The data from diesel engine state is identified are sample. It is verified the validity of the model of fuzzy neural network after experiments. The results show that it has a great improvement in convenient operation and facilitates to use. This method for diagnosis faults of diesel engine has more accurately. It can improve the veracity for diagnose the fault. It can also develop the optimal control of diesel engine.
DOI:10.1109/ICCSN.2011.6014398