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Experimental study on engine gas-path component fault monitoring using exhaust gas electrostatic signal

机译:利用废气静电信号监测发动机气路部件故障的实验研究

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摘要

This paper presents the recent development in engine gas-path components health monitoring using electrostatic sensors in combination with signal-processing techniques. Two ground-based engine electrostatic monitoring experiments are reported and the exhaust gas electrostatic monitoring signal-based fault-detection method is proposed. It is found that the water washing, oil leakage and combustor linear cracking result in an increase in the activity level of the electrostatic monitoring signal, which can be detected by the electrostatic monitoring system. For on-line health monitoring of the gas-path components, a baseline model-based fault-detection method is proposed and the multivariate state estimation technique is used to establish the baseline model for the electrostatic monitoring signal. The method is applied to a data set from a turbo-shaft engine electrostatic monitoring experiment. The results of the case study show that the system with the developed method is capable of detecting the gas-path component fault in an on-line fashion.
机译:本文介绍了结合使用静电传感器和信号处理技术的发动机气路部件健康监测的最新进展。报道了两个地面发动机静电监测实验,并提出了基于废气静电监测信号的故障检测方法。发现水洗,漏油和燃烧器线性裂化导致静电监测信号的活动水平增加,该静电监测信号可以被静电监测系统检测到。为了对气路成分进行在线健康监测,提出了一种基于基线模型的故障检测方法,并使用多元状态估计技术建立了静电监测信号的基线模型。该方法应用于来自涡轮轴发动机静电监控实验的数据集。实例研究结果表明,采用改进方法的系统能够在线检测出气路部件故障。

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