北京航空航天大学学报 ›› 2015, Vol. 41 ›› Issue (3): 545-550.doi: 10.13700/j.bh.1001-5965.2014.0190

• 论文 • 上一篇    下一篇

基于蒙特卡罗模拟的航空发动机故障风险预测

赵洪利1, 刘宇文2   

  1. 1. 中国民航大学 航空工程学院, 天津 300300;
    2. 中国民航大学 中欧航空工程师学院, 天津 300300
  • 收稿日期:2014-04-06 出版日期:2015-03-20 发布日期:2015-04-02
  • 通讯作者: 赵洪利(1964—),男,天津人,副教授,tyyazx@163.com,主要研究方向为航空维修与管理. E-mail:tyyazx@163.com

Forecasting for aero-engine failure risk based on Monte Carlo simulation

ZHAO Hongli1, LIU Yuwen2   

  1. 1. College of Aviation Engineering, Civil Aviation University of China, Tianjin 300300, China;
    2. Sino-European Institute of Aviation Engineering, Civil Aviation University of China, Tianjin 300300, China
  • Received:2014-04-06 Online:2015-03-20 Published:2015-04-02

摘要: 针对航空发动机结构复杂、故障模式多样,传统故障风险预测方法难以实现的现状,基于蒙特卡罗模拟技术,给出了航空发动机故障风险预测方法,用于评估发动机各个部件在未来发生故障的可能性.针对航空发动机故障数据的特点,以威布尔分布建立故障概率模型,利用中位秩回归参数法,估计威布尔分布参数.利用乘同余组合发生器与反变换法相结合的方式产生满足威布尔分布的随机数.在单故障模式风险预测的基础上,给出了多种故障模式并存的航空发动机风险预测方法,并且给出了蒙特卡罗模拟步骤和算法,针对实例,对比发动机厂商提供的预测数据,验证了算法的有效性与蒙特卡罗模拟方法在航空发动机故障风险预测中的可用性.

关键词: 航空发动机, 多故障模式, 定期检查, 风险预测, 蒙特卡罗模拟

Abstract: In view of the fact that aero-engines have complicated structure and multiple failure modes, traditional methods are difficult to meet the requirements. A forecasting method for aero-engine failure risk based on Monte Carlo simulation is presented, which is used to evaluate the possibility of failure for each component of engine in the future. According to the characteristics of aero-engine failure data, the failure probability model is based on the Weibull distribution whose parameters are estimated by the method of rank regression. Combining multiplicative congruent generator with the inverse transform method, the random numbers are produced to satisfy Weibull distribution. The method used to forecast failure risk for engines with multi-failure modes is based on the one with single failure mode. The simulation procedures and algorithm, by comparing the simulation results with the forecasting datum from the engine manufacture are presented, it proves that the algorithm and Monte Carlo simulation are effective in aero-engine failure risk forecast.

Key words: aero-engine, multi-failure modes, scheduled maintenance, risk forecast, Monte Carlo simulation

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