In this paper, wavelets as signal processing tools are used to analyze the acceleration data acquired at the cylinder head for the detection and characterization of combustion malfunctions in multi-cylinder industrial engines. The objectives were to collect data on 1) normal operations, and 2) operations with a deactivated cylinder to simulate a faulty condition. Wavelet packet and local discriminatory basis algorithm are used to select wavelets that can recognize different conditions. It is shown that the wavelet packet provides a useful data analysis structure for extracting features that are capable of detecting the combustion malfunction of one cylinder in a 12-cylinder engine. Feature extraction is followed by a classification that uses a neural network for the fault identification phase.


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    Titel :

    Malfunction Detection in Multi-cylinder Engines Using Wavelet Packet Dictionary


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Sassani, F. (Autor:in) / Dumont, G. (Autor:in) / Ahmadi, H. (Autor:in) / Tafreshi, R. (Autor:in)

    Kongress:

    SAE 2005 Noise and Vibration Conference and Exhibition ; 2005



    Erscheinungsdatum :

    16.05.2005




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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