This paper presents a new automated diagnosis methodology which attempts to bridge the gap between reliability at the design phase and diagnosis at the usage phase. The methodology takes advantage of dynamic fault tree qualitative and quantitative data to develop a diagnostic importance measure. The methodology produces a diagnostic decision tree based on the fault tree and on the diagnostic importance measure. To enhance the diagnosis process the presented methodology incorporates evidence from sensors to improve diagnosis.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Automatic Diagnosis via Sensors Modeled by Dynamic Fault Trees


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE 2005 World Congress & Exhibition ; 2005



    Publication date :

    2005-04-11




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Automatic diagnosis via sensors modeled by dynamic fault trees

    Assaf,T. / Dugan,J.B. / Univ.of Virginia,US | Automotive engineering | 2005


    2005-01-1442 Automatic Diagnosis via Sensors Modeled by Dynamic Fault Trees

    Assaf, T. / Dugan, J. B. / Society of Automotive Engineers | British Library Conference Proceedings | 2005


    Fault diagnosis for discrete event systems modeled by bounded petri nets

    Ran, Ning / Wang, Shouguang / Su, Hongye et al. | British Library Online Contents | 2017


    Dynamic Fault Diagnosis of Aeroengine Control System Sensors Based on LSTM-CNN

    Li, Huihui / Gou, Linfeng / Li, Huacong et al. | IEEE | 2023


    Dynamic fault trees: semantics, analysis and applications

    Volk, Matthias | TIBKAT | 2022

    Free access