航空发动机全寿命维修概率建模与仿真

孙见忠; 易杨; 文洪; 王鹏; 邵传金

doi:10.13224/j.cnki.jasp.20210160

航空发动机全寿命维修概率建模与仿真

doi: 10.13224/j.cnki.jasp.20210160

1.
南京航空航天大学民航学院，南京 211106
2.
中国东方航空江苏有限公司培训中心，南京 211113
3.
中国航空发动机集团有限公司商用航空发动机有限责任公司，上海 200241

基金项目: 国家自然科学基金（91860139， 52072176）

详细信息

作者简介:
孙见忠（1983-），男，副教授，博士，主要从事航空发动机健康管理与维修工程研究。

中图分类号: V232.4
计量
- 文章访问数: 249
- HTML浏览量: 77
- PDF量: 100
- 被引次数: 0
出版历程
- 收稿日期: 2021-04-09
- 刊出日期: 2022-03-28

Life cycle probabilistic modeling and simulation of aero-engine maintenance

1.
College of Civil Aviation，Nanjing University of Aeronautics and Astronautics，Nanjing 211106，China
2.
Training Center， China Eastern Airlines Jiangsu Limited，Nanjing 211113，China
3.
Commercial Aircraft Engine Company Limited，Aero Engine Corporation of China，Shanghai 200241，China

摘要

摘要: 由于生产制造、运行环境和使用条件等个体性差异，航空发动机部件性能/寿命不确定，进一步导致机队送修率和小时维修费率等运维指标不确定。为了量化评估部件设计可靠性、运行环境、维修决策等不确定性因素对机队运维指标（送修率、送修原因、平均拆换时间间隔、小时维修费率等）的影响，提出了一种航空发动机全寿命周期维修概率建模方法。该方法基于不同环境下各潜在送修原因的寿命分布，结合维修决策规则和维修任务成本，通过离散事件仿真，对发动机进行全寿命周期维修事件概率建模。以典型民用大涵道比涡扇发动机为仿真对象，3种运行环境下发动机送修率均值分别是0.029 1、0.038 4和0.059 8，单位飞行小时维修成本分别为每飞行小时82、91和119美元，综合部件设计可靠性与维修决策对运维指标的影响，结果证明所提出建模方法可行性和有效性。
- 维修概率建模 /
- 维修决策 /
- 蒙特卡洛仿真 /
- 小时费率 /
- 离散事件仿真
Abstract: In order to evaluate the impact of different component design reliability，different operating environments and maintenance decisions on fleet operation and maintenance indicators （shop visit rate，shop visit cauce，mean time between removal，rate per flight hour，etc.），a model method for the probabilistic repair of aero-engine life cycle was proposed.Based on the life distribution of the potential reasons for repairs in different environments，and combined with maintenance decision rules and maintenance task costs，this method was employed to model the life cycle maintenance event probability of the fleet through discrete event simulation and Monte Carlo sampling.A simulation study was carried out on a typical commercial turbo fan engine.Under three different operating environments，the average shop visit rates of engines were 0.029 1，0.038 4 and 0.059 8，respectively，and the rates per flight hour were 82，91 and 119 dollars per flight hour，respectively.The simulation results showed the effectiveness of the proposed method.
- maintenance probabilistic modeling /
- maintenance strategy /
- Monte Carlo simulation /
- rates per flight hour /
- discrete event simulation

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