Foreign Object Damage Diagnosis of Aero-Engine Compressor Based on Damping Averaging Built-in Matrix Method

Shuming Wu, Xuefeng Chen, P. Russhard, Shibin Wang, Zhi Zhai, Zhibin Zhao
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引用次数: 4

Abstract

Blade Tip Timing (BTT) methods are being implemented that have led to a non-intrusive technique being deployed in certain sectors of Industry. Data sets produced during the development cycle are now providing upfront information that is being used to develop monitoring capability supporting in-service health monitoring. Recent years have witnessed a growing interest in blade health monitoring and its potential to detect the occurrence of both transient and permanent foreign object damage (FOD) and estimate the severity of damage to blades. FOD damage detection is beneficial to both the fan and first stage compressors and the ability to detect it leads to a reduction in the number of inspection that recurrently scheduled. The expected behaviour under transient FOD condition is a ‘ringing’ signal which is a damped exponential signal. The lack of real FOD data collected requires that a signal is simulated and used to develop and validate detection systems. Blade tip timing is an effective implementation of non-intrusive technology by circumferentially arranged sensors to obtain the time of arrival (TOA) of blades. However, due to the high degree of undersampling inherent in the data the detection of short-lived events poses a problem. In this paper the use of a method called ‘Damping Averaging Built-in Matrix’ (DABM), which use the combination of several revolutions data and OPR (once per revolution) data to enhance the sample rate while eliminating the damping effect. After solving the matrix we are able to obtain the frequency and damping of the blade when transient FOD occurs. The FEM (finite element model) of the blade is also built to infer the stress of blade at different levels of FOD. The method is applied to both the simulated data and experimental data to verify its effectiveness. By developing this method further we can provide a capability that could reduce the operation and maintenance cost and increase the security of the engine whilst in operation.
基于阻尼平均内嵌矩阵法的航空发动机压气机异物损伤诊断
叶片尖端定时(BTT)方法正在实施,导致非侵入性技术在工业的某些部门得到部署。在开发周期中产生的数据集现在提供了前期信息,用于开发支持在职运行状况监测的监测功能。近年来,人们对叶片健康监测及其在检测瞬时和永久性异物损伤(FOD)发生和估计叶片损伤严重程度方面的潜力越来越感兴趣。FOD损坏检测对风扇和第一级压缩机都是有益的,并且检测它的能力可以减少定期安排的检查次数。在瞬态FOD条件下的预期行为是一个“振铃”信号,这是一个阻尼指数信号。由于收集不到真实的FOD数据,因此需要对信号进行模拟,并用于开发和验证检测系统。叶尖定时是通过周向布置传感器获取叶片到达时间(TOA)的非侵入式技术的有效实现。然而,由于数据中固有的高度欠采样,短时间事件的检测提出了一个问题。在本文中,使用了一种称为“阻尼平均内置矩阵”(DABM)的方法,该方法使用几转数据和OPR(每转一次)数据的组合来提高采样率,同时消除了阻尼效应。求解矩阵后,可以得到瞬态失稳时叶片的频率和阻尼。建立叶片有限元模型,推导出叶片在不同FOD水平下的应力。通过仿真数据和实验数据验证了该方法的有效性。通过进一步开发这种方法,我们可以提供一种能够降低运行和维护成本并提高发动机运行时安全性的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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