航空发动机单元体送修等级决策方法研究

贾宝惠; 黄婕; 王玉鑫; 李耀华

doi:10.13433/j.cnki.1003-8728.2018.0325

航空发动机单元体送修等级决策方法研究

doi: 10.13433/j.cnki.1003-8728.2018.0325

1.
中国民航大学航空工程学院, 天津 300300

基金项目:

中国民航局科技引领重大专项项目（MHRD20160105）、民用飞机专项、其他国家级项目（MJZ-2014-Y-61）及中央高校B类项目（3122016B003）资助

详细信息

作者简介:
贾宝惠(1971-),教授,硕士,研究方向为航空维修,航空器适航管理,jiabaohui@sina.com

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- 文章访问数: 259
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- 被引次数: 0
出版历程
- 收稿日期: 2017-02-28
- 刊出日期: 2018-03-05

Research on Decision-making Method of Maintenance Level for Aero Engine Module

1.
College of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China

摘要

摘要: 为对发动机单元体送修等级提供决策支持，在对状态参数与单元体送修等级间的模糊关系进行特征提取的基础上，从性能衰退角度提出通过状态参数组合变化确定单元体送修等级的决策方法。针对现有的数据规则有限的问题，建立模糊综合评价模型，采用BP神经网络训练各参数对不同送修等级的隶属函数，采用熵权法衡量状态参数在单元体送修等级确定中的权重。最后以高压涡轮单元体送修的仿真结果证明了该决策方法的有效性，能够为更多状态参数组合提供一种便捷高效确定送修等级的方法。
- 航空发动机 /
- 单元体 /
- 送修等级 /
- 模糊综合评价 /
- BP神经网络 /
- 隶属函数
Abstract: A decision-making method of maintenance level from the view point of performance degradation for aeroengine module is proposed to support the determination on maintenance level for the aeroengine module based on feature extraction of fuzzy relation between state parameter and module maintenance level. To solve the problem of limited existing data rules, a mathematical model of fuzzy comprehensive evaluation is established. The back propagation (BP) neural network is built to train the membership function of each parameter for different maintenance level. The entropy weight method is adopted to measure the weight of the state parameter in decision-making. Finally, the computer simulation result of the high-pressure turbine module verify that the proposed decision-making method is effective and capable of providing a efficient method for making maintenance level decision for the case with more state parameter combinations.
- aeroengine /
- maintenance level /
- fuzzy comprehensive evaluation /
- BP neural networks /
- membership functions /
- MATLAB

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参考文献(15)

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