论文摘要
Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which sometimes cannot be measured in engineering. The most typical one is the High-Pressure Turbine(HPT) exit pressure, which is vital to distinguishing failure modes between different turbines. For the case of an abrupt failure occurring in a single turbine component, a model-based sensor measurement reconstruction method is proposed in this paper. First,to estimate the missing measurements, the forward algorithm and the backward algorithm are developed based on corresponding component models according to the failure hypotheses. Then,a new fault diagnosis logic is designed and the traditional nonlinear filter is improved by adding the measurement estimation module and the health parameter correction module, which uses the reconstructed measurement to complete the health parameters estimation. Simulation results show that the proposed method can well restore the desired measurement and the estimated measurement can be used in the turbofan engine gas path diagnosis. Compared with the diagnosis under the condition of missing sensors, this method can distinguish between different failure modes, quantify the variations of health parameters, and achieve good performance at multiple operating points in the flight envelope.
论文目录
文章来源
类型: 期刊论文
作者: Xin ZHOU,Feng LU,Jinquan HUANG
来源: Chinese Journal of Aeronautics 2019年05期
年度: 2019
分类: 工程科技Ⅱ辑
专业: 航空航天科学与工程
单位: College of Energy and Power Engineering, Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing University of Aeronautics and Astronautics
基金: supported by the Fundamental Research Funds for the Central Universities(NO.NS2018018)
分类号: V235.13
页码: 1156-1170
总页数: 15
文件大小: 1235K
下载量: 26
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