基于故障检测的某涡扇发动机维修决策方法

张莹松; 吴灿; 唐海龙; 林军; 郝明

doi:10.13224/j.cnki.jasp.2017.01.012

基于故障检测的某涡扇发动机维修决策方法

doi: 10.13224/j.cnki.jasp.2017.01.012

张莹松^1,2,
吴灿³,
唐海龙¹,
林军³,
郝明³

1.
北京航空航天大学能源与动力工程学院,北京 100191
2.
中国人民解放军第5713工厂技术与培训中心,湖北襄阳 441000
3.
中国人民解放军第5713工厂技术与培训中心,湖北襄阳 441000

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出版历程
- 收稿日期: 2016-04-26
- 刊出日期: 2017-01-28

Maintenance decision method of a turbofan engine based on fault detection

摘要

摘要: 为有效解决某涡扇发动机过度维修造成发动机性能衰减、维修周期长、维修成本高的难题,以某涡扇发动机大修手册和维修工艺为依据,研究了基于故障检测的发动机维修流程和修理模式,建立专家诊断系统和基于BP(back propagation)神经网络的故障诊断模型,并用数台涡扇发动机真实性能数据验证故障诊断模型的可靠性,其诊断准确率高达95%,综合两者的诊断信息,制定可靠的维修方案,优化维修流程,提出了一种基于故障检测的维修决策方法.通过某涡扇真实排气温度高发动机应用验证表明：所提出的维修决策方法,有效排除故障,提高发动机的修理质量,降低维修成本,具有良好的工程应用价值.
- 涡扇发动机 /
- BP神经网络 /
- 专家系统 /
- 故障检测 /
- 维修决策
Abstract: In the maintenance process traditional excessive maintenance of turbofan engines may result in performance deterioration, long maintenance cycle and high maintenance cost. In order to solve this problem effectively, based on turbofan engine overhaul manual and maintenance technology, the fault detection process and repair mode were studied in depth, and the fault diagnosis expert system and fault diagnosis model were established based on BP(back propagation) neural network, verifying the reliability of fault diagnosis model with several sets of real performance data, with the diagnostic accuracy rate up to 95%. Secondly, the two kinds of diagnostic information were combined to develop reliable maintenance program and optimize the maintenance process. Then a maintenance decision method was put forward. By a certain type of turbofan real validation, it shows that this method can effectively eliminate the fault of high exhaust temperature, helping to improve maintenance quality and reduce maintenance cost of the engine.
- turbofan engines /
- BP neural network /
- expert system /
- fault detection /
- maintenance decision

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参考文献(16)

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