• DocumentCode
    2440481
  • Title

    FUMS Technologies for Advanced Structural PHM

  • Author

    Azzam, Hesham ; Beaven, Frank ; Smith, Andrew ; Hebden, Iain

  • Author_Institution
    Smiths Aerosp., Eastleigh
  • fYear
    2007
  • fDate
    3-10 March 2007
  • Firstpage
    1
  • Lastpage
    12
  • Abstract
    Over the past seven years, Smiths and BAE SYSTEMS have launched collaborative work to evolve a certifiable practical Structural Prognostic Health Management (SPHM) system. The collaborative work has built on BAE SYSTEMS´ vast advanced technology experience and on Smiths´ unique experience that has produced intelligent Fleet and Usage Management Software (FUMSTM ) including fusion, prognostic and decision support algorithms combining model-based and Artificial Intelligence (AI) techniques. This paper describes the recent advances and optimisation of the Smiths algorithms for damage detection and Operational Load Monitoring (OLM). A combination of FUMSTM signal processing and AI techniques have been applied to acoustic emission sensor data to locate and classify damage of different types in composite and metallic structures. The FUMSTM damage detection software has been embedded in real-time hardware to support ground tests. Techniques have been implemented to enable adequate calibration of OLM algorithms using data from flight tests. The techniques should address concerns raised about the accuracy of algorithms trained to synthesise strains throughout the entire flight envelope from data recorded close to the edge of the flight envelope. Working with the UK MOD, Smiths has continued the evaluation of FUMSTM software that allows aircraft design authorities and military operators to build their force life management applications without the need for software rewriting.
  • Keywords
    aerospace computing; artificial intelligence; decision support systems; groupware; Smiths algorithms; aerospace computing; aircraft testing; artificial intelligence techniques; damage detection software; decision support algorithms; force life management applications; intelligent fleet and usage management software; operational load monitoring; real-time hardware; signal processing; software rewriting; structural prognostic health management; Acoustic signal detection; Artificial intelligence; Collaborative software; Collaborative work; Military aircraft; Monitoring; Prognostics and health management; Signal processing algorithms; Software algorithms; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace Conference, 2007 IEEE
  • Conference_Location
    Big Sky, MT
  • ISSN
    1095-323X
  • Print_ISBN
    1-4244-0524-6
  • Electronic_ISBN
    1095-323X
  • Type

    conf

  • DOI
    10.1109/AERO.2007.352908
  • Filename
    4161665