Automated Prognostics and Health Management (PHM) is a requirement for advanced military aircraft. PHM is the key to achieving true condition-based maintenance. PHM processing strategies include modules for the processing of known nominal and fault conditions. However in real operations there will also occur faults and other off-nominal operations that were never anticipated nor ever encountered before. We call these events anomalies. Missing the presence of an anomaly could potentially be catastrophic with the loss of the pilot and aircraft. Several different anomaly detectors (ADs) have been developed for advanced military aircraft to solve this problem. Fusion of these ADs can significantly reduce false alarms while at the same time substantially improving detection performance. Fusion is a way of approaching the goal of perfect detection with zero false alarms. We have developed a neural net approach for performing AD fusion. Presented is a description of that technique and the application to military aircraft subsystem data.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Anomaly detector fusion processing for advanced military aircraft


    Contributors:
    Brotherton, T. (author) / Mackey, R. (author)


    Publication date :

    2001-01-01


    Size :

    2065661 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





    Propulsion Integration Aspects in Advanced Military Aircraft

    Hienz, E. / Illuzzi, L. / Herrmann, P. et al. | British Library Conference Proceedings | 1996



    Advanced U. S. Military Aircraft Battery Systems

    Eskra, Michael D. / Flake, Richard A. | SAE Technical Papers | 1990