There is a growing interest in fusing the wealth of data generated by aircraft sensors and airborne systems into prognostic information and automated decisions that lead to significant improvements in aircraft management, affordability, availability, airworthiness and performance (MAAAP). Over the past five years, Smiths and BAE SYSTEMS have launched collaborative work to evolve a certifiable practical system that addresses this interest. The collaborative work has built on the BAE SYSTEMS vast advanced technology experiences and on the Smiths unique experience that has produced prognostic and decision support algorithms combining model-based and artificial intelligence (AI) techniques. This paper reports on certifiable techniques that fuse flight data into prognostic information. The techniques were blind tested on legacy data covering 15 years of military operations. The paper presents a fusion/decision support technique targeted at identifying sensor/system faults. The paper also presents preliminary collaborative work on a structural damage detection technology where AI and fusion methods have been used to mitigate technology risks.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Fusion and decision making techniques for structural prognostic health management


    Contributors:
    Azzam, H. (author) / Beaven, F. (author) / Hebden, T. (author) / Gill, L. (author) / Wallace, M. (author)

    Published in:

    Publication date :

    2005


    Size :

    12 Seiten, 11 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Fusion and Decision Making Techniques for Certifiable, Affordable Structural Prognostic Health Management

    Azzam, H. / Hebden, I. / Gill, L. et al. | British Library Conference Proceedings | 2005


    Hybrid Health-Aware Supervisory Control Framework with a Prognostic Decision-Making

    Cieslak, Jérôme / Gucik-Derigny, David / Chang, Jing | Springer Verlag | 2020


    Hybrid Health-Aware Supervisory Control Framework with a Prognostic Decision-Making

    Cieslak, Jérôme / Gucik-Derigny, David / Chang, Jing | TIBKAT | 2021


    Optimisation of Fusion and Decision Making Techniques for Affordable SPHM

    Azzam, H. / Wallace, M. / Beaven, F. et al. | IEEE | 2006


    Decision Fusion Methods With Applications to Structural Health Monitoring

    Zein-Sabatto, Saleh / Mikhail, Maged / Bodruzzaman, Mohammad et al. | AIAA | 2012