FUMS Technologies for Advanced Structural PHM

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.