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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2022, Vol. 43 ›› Issue (10): 527347-527347.doi: 10.7527/S1000-6893.2022.27347

• Solid Mechanics and Vehicle Conceptual Design • Previous Articles     Next Articles

Life estimation of aircraft hydraulic pump based on failure physics and data driven

WANG Shaoping1,2, GENG Yixuan1, SHI Cun1   

  1. 1. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China;
    2. Ningbo Institute of Technology, Beihang University, Ningbo 315800, China
  • Received:2022-04-29 Revised:2022-05-15 Published:2022-06-08
  • Supported by:
    NSFC Projects of International Cooperation and Exchanges (51620105010); National Science and Technology Major Project (J2019-V-0016-0111)

Abstract: The hydraulic pump is an important component of aircraft hydraulic system with long life, and most of operational time is in the actual flight. It is difficult to estimate its useful life only using in-situ test data. However, the real flight data of hydraulic pump have some uncertainties, and the load profiles imposed are different from those in manufactory. Therefore, it is urgent to find an effective method to integrate the manufactory and real flight data to achieve an accurate life estimation of the aircraft hydraulic pump. In this paper, a remaining useful life estimation method is proposed based on failure physics and real flight data. Considering the mixed lubrication condition and multi-field coupling, the physics-based degradation model of hydraulic pump is constructed, and the performance degradation is described as a stochastic process. After that, the real flight data are collected, and are processed by a particle filter to modulate the physics-based degradation model dynamically. To eliminate the uncertainty of real flight data, the optimal importance sampling and the regular granule resampling are used to overcome the particle degeneracy. Experimental results demonstrate that the proposed method can effectively improve the life estimation accuracy of aircraft hydraulic pump.

Key words: physics of failure, data driven, life prediction, particle filter, aircraft hydraulic pump

CLC Number: