Hydraulic systems are an important power source in modern aircraft. Most aircraft employ hydraulic power for flight control systems and landing gears actuation. Pumps are a critical component in hydraulic system and monitoring the health of such components may provide economic and operational benefits to aircraft operators. This work describes the use of Kalman Filter techniques for the estimation of remaining useful life of aircraft hydraulic pumps. An empirical model of degradation evolution is employed for this purpose. Low sampling rate measurements of the hydraulic pressure of the aircraft hydraulic systems are the only measurements employed. In order to illustrate and validate the method, two time series of actual run to failure data are analyzed. Results provide evidence that the method can be successfully employed for actual aircraft hydraulic pump failure prognosis.
How to Cite
Kalman Filter, failure prognostics, hydraulic pump
Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. Transactions of the ASME - Journal of Basic Engineering, v.82, Series D, p.35-45.
Hancock, K. M.; Zhang, Q. (2006). A hybrid approach to hydraulic vane pump condition monitoring and fault detection. Transactions of the American Society of Agricultural and Biological Engineers, v. 49 (4), p. 1203- 1211.
Byington, C. S.; Watson, M.; Edwards, D. and Dunkin, B. (2003). In-line health monitoring system for hydraulic pumps and motors. IEEE Aerospace Conference Proceedings, Big Sky, MO.
Bechhoefer, E.; Clark, S. and He, D. (2010). A state space model for vibration based prognostics. Proceedings of the Annual Conference of the Prognostics and Health Management Society.
Leão, B. P. (2011). Failure prognosis methods and offline performance evaluation. Ph.D. thesis. Instituto Tecnológico de Aeronáutica.
Orchard, M; Vachtsevanos, G. (2009) A particle filtering approach for online fault diagnosis and failure prognosis. Transactions of the Institute of Measurement and Control, no. 3-4, p. 221–246.
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