Testability Design of the PHM System for Aero-Engines

Abstract:

PHM (Prognostics and Health Management) for Aero-engines is an effective technical approach to balance the economy and safety of the flight in the total life cycle. In this paper, we mainly analyze the popular issues in the process of designing PHM system for aero-engines including the testability design concept, the scheme of condition monitoring and the utilization extent of condition information. Then presents some useful solutions and advices for the testability design respectively; and analyzes the influence of testability on health management strategies and the main source of uncertainty; then propose a roadmap for making test program based on the PHM requirements and evaluating test program, for improve the utilizing degree of monitoring information, we lastly presented common data fusion methods and some typical examples is illustrated.

• Periodical: Advanced Materials Research (Volume 544)
• Pages: 94-98
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.544.94
• Online since: June 2012
• Authors: Zhen Hua Wen, Yuan Peng Liu, Xin Yin
• Keywords: Aero-Engine, Fusion Model, PHM, Testability Design, Uncertainty Analysis

References

[1] POWRIE H E G, FISHER C E. Engine Health Monitoring Towards Total Prognostics. Proceedings of the IEEE Aerospace Applications Conference Proceedings, CA,USA, (1999).

DOI: 10.1109/aero.1999.789759

[2] TAKATA S, KIRNURA F, VAN HOUTEN F, et al. Maintenance: changing role in life cycle management . CIRP Annals-Manufacturing Technology. 53 (2004),pp.643-655.

DOI: 10.1016/s0007-8506(07)60033-x

[3] KACPRZYNSKI G J, ROEMER M J, HESS A J, et al. Health Management System Design: Development, Simulation and Cost/Benefit Optimization. Proceedings of the Proceeding of IEEE,( 2002).

DOI: 10.1109/aero.2002.1036148

[4] SCHEUREN W. Safety & the military aircraft joint strike fighter prognostics & health management . AIAA, (1998),p.3710.

[5] ROEMER M J, KACPRZYNSKI G J, ORSAGH R F. Assessment of data and knowledge fusion strategies for prognostics and health management; Proceedings of the Proceedings of IEEE Aerospace Conference, (2001).

DOI: 10.1109/aero.2001.931318

[6] MATHUR A. Data mining of aviation data for advancing health management. Proceedings of SPIE, the International Society for Optical Engineering, (2002).

[7] Wen Zhenhua, Chen Guo. An Intelligent Fusion Technique for Diagnosis of Engine Wear Fault Based on D-S Evidence Theory. Mechanical Science and Technology, 24(2005), pp.1018-1021. (in Chinese).