The current paper presents a leakage diagnosis system for elucidating the leakage source and identifying the leakage degree of gasoline engines. The proposed diagnostic system consists of a crankcase-ventilation detecting system, a pressure-regulator detecting system, a leakage-source detecting system, and a decision system. Being based on neural networks, the three detecting systems are trained using the steepest-descent method and a back-propagation algorithm. Although the engine non-linearity and noise may spoil the leakage identification, the decision system can be employed to enhance the identification of leakage source and leakage degree. Genetic algorithms are used to train the initial weights and biases of the neural networks such that the training performance is raised. Experimental results indicate that the proposed diagnostic system for elucidating the leaking source and leakage degree is feasible and effective.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A novel diagnostic system for gasoline-engine leakage detection


    Contributors:
    Chen, P-C (author)


    Publication date :

    2011-05-01


    Size :

    13 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    A novel diagnostic system for gasoline-engine leakage detection

    Chen,P.C. / Southern Taiwan Univ.of Technol.,TW | Automotive engineering | 2011



    Gasoline Engine

    Online Contents | 1997


    Gasoline engine strategy

    Scoltock,J. | Automotive engineering | 2010


    Novel Characterization of GDI Engine Exhaust for Gasoline and Mid-Level Gasoline-Alcohol Blends

    Kaul, Brian / Nafziger, Eric / Szybist, James et al. | SAE Technical Papers | 2014