Virtual Framework for Validation and Verification of System Design Requirements to enable Condition Based Maintenance
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Abstract
During the last decade Condition Based Maintenance [CBM] became an important area of interest to reduce maintenance and logistic delays related down times and improve system effectiveness. Reliable diagnostic and prognostic capabilities that can identify and predict incipient failures are required to enable such a maintenance concept. For a successful integration of CBM into a system, the challenge beyond the development of suitable algorithms and monitoring concepts is also to validate and verify the appropriate design requirements. To justify additional investments into such a design approach it is also important to understand the benefits of the CBM solution. Throughout this paper we will define a framework that can be used to support the Validation & Verification [V&V] process for a CBM system in a virtual environment. The proposed framework can be tailored to any type of system design. It will be shown that an implementation of failure prediction capabilities can significantly improve the desired system performance outcomes and reduce the risk for resource management; on the other hand an enhanced online monitoring system without prognostics has only a limited potential to ensure the return on investment for developing and integrating such technologies. A case study for a hydraulic pump module will be carried out to illustrate the concept.
How to Cite
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Condition Based Maintenance, Model-Based Design, Validation and Verification, Fault Diagnosis and Prognosis
Bechhoefer, E., (2008). A method for generalized prognostics of a component using Paris law. Proceedings of American Helicopter Society 64th Annual Forum, April 29 - May 1, Montreal, CA
Blumenfeld, D. (2001). Operations Research Calculations Handbook. CRC Press, p. 7
Byer, B., Hess, A. & Fila, L. (2001). Writing a convincing cost benefit analysis to substantiate autonomic logistics. Aerospace Conference
Dunsdon, J., Harrington, M. (2009). The application of open system architecture for condition based maintenance to complete IVHM. Aerospace Conference
Elandt-Johnson, R.C. & Johnson, N.L. (1980). Survival Models and Data Analysis. John Wiley and Sons, New York, p.69
Endo, H. (2005). A study of gear faults by simulation, and the development of differential diagnostic techniques. Ph.D. Dissertation, UNSW, Sydney
Orchard, M. E., (2007). A particle filtering-based framework for on-line fault diagnosis and failure prognosis. Doctoral dissertation. Georgia Institute of Technology, Atlanta, GA, USA.
Reimann, J., Kacprzynski, G., Cabral, D. & Marini, R. (2009). Using condition based maintenance to improve the profitability of performance based logistic contracts. Annual Conference of the Prognostics and Health Management Society
Sawalhi, N., Randall, R.B. (2008). Simulation gear and bearing interactions in the presence of faults. Part I: The combined gear bearing dynamic model and the simulation of localised faults. Mechanical Systems and Signal Processing, vol. 22, pp. 1924-1951
Saxena, A., Roychoudhury, I., Celaya, J.R., Saha, S., Saha, B. & Goebel, K. (2010). Requirements Specifications for Prognostics: An Overview. American Institute of Aeronautics and Astronautics
Spare, J.H. (2001). Building the business case for conditionbased maintenance. Transmission and Distribution Conference and Exposition
Stuart, A & Ord, K. (1998). Kendall’s Advanced Theory of Statistics. Arnold. London, 6th edition, p.351
Yacoub, M.D., Benevides da Costa, D., Dias U.S. & G.Fraidenraich (2005). Joint Statistics for Two Correlated Weibull Variates. IEEE Antennas and Wireless Propagation Letters, Vol. 4
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