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Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 628792, 10 pages
Research Article

Maintenance Decision Based on Data Fusion of Aero Engines

1College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2Department of Management, Shijiazhuang Mechanical Engineering College, Shijiazhuang 050003, China

Received 18 January 2013; Accepted 4 April 2013

Academic Editor: H. K. Leung

Copyright © 2013 Huawei Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Maintenance has gained a great importance as a support function for ensuring aero engine reliability and availability. Cost-effectiveness and risk control are two basic criteria for accurate maintenance. Given that aero engines have much condition monitoring data, this paper presents a new condition-based maintenance decision system that employs data fusion for improving accuracy of reliability evaluation. Bayesian linear model has been applied, so that the performance degradation evaluation of aero engines could be realized. A reliability evaluation model has been presented based on gamma process, which achieves the accurate evaluation by information fusion. In reliability evaluation model, the shape parameter is estimated by the performance degradation evaluation result, and the scale parameter is estimated by failure, inspection, and repair information. What is more, with such reliability evaluation as input variables and by using particle swarm optimization (PSO), a stochastic optimization of maintenance decision for aircraft engines has been presented, in which the effectiveness and the accuracy are demonstrated by a numerical example.