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-  2018 

基于改进灰靶理论的航空发动机健康监测方法
Aero-engine Health Monitoring Method Based on Optimized Grey Target Theory

DOI: 10.16450/j.cnki.issn.1004-6801.2018.02.002

Keywords: 航空发动机, 健康监测, 灰靶决策, 层次分析法, 熵理论
aero-engine
, health monitoring, target decision, analytic hierarchy process, entropy theory

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Abstract:

为实现航空发动机状态等级的划分与识别、可靠性和剩余寿命的分析以及典型故障的诊断,基于灰靶决策理论、层次分析法和熵理论提出一种航空发动机健康监测方法。首先,以新航空发动机状态监测值作为靶心,用经层次分析法和熵理论综合算法优化权重系数后的灰靶模型计算靶心度;然后,结合故障严酷度和发生概率制定各健康状态等级的划分标准,并将靶心度转化为可靠度,在此基础上结合发动机性能退化曲线计算剩余寿命;最后,计算典型故障数据的靶心度作为参照实现故障类型的诊断。用某型航空发动机气路性能参数监测数据进行验证,结果表明笔者提出的算法可有效实现航空发动机健康监测,该算法具有较好的实用性和准确性。
To recognize and classify the performance, analyze reliability and residual life and diagnose typical faults, an aero-engine health monitoring method is proposed based on grey target decision, analytic hierarchy process (AHP) and entropy theory. First, the monitoring values of a new type of aero-engine are taken as the target center. The grey target model whose weight coefficient is optimized with AHP and entropy theory is used to calculate the approaching degrees. Then, the health level standard is formulated based on the severe degree and failure probability. The approaching degree is translated into the reliability degree for the calculation of residual life combining with the engine performance degradation curve. Finally, the approaching degrees of typical failure data is calculated as the reference of fault diagnosis. The verification result of performance parameters data from a Honeywell aero-engine gas path shows that the algorithm proposed in this paper can effectively monitor the aero-engine health. Therefore, the algorithm proposed in this paper is practical and accurate.

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