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Reconstructed Order Analysis-Based Vibration Monitoring under Variable Rotation Speed by Using Multiple Blade Tip-Timing Sensors

机译:通过使用多刀片尖端调速器,在可变旋转速度下基于订单分析的振动监测

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摘要

On-line vibration monitoring is significant for high-speed rotating blades, and blade tip-timing (BTT) is generally regarded as a promising solution. BTT methods must assume that rotating speeds are constant. This assumption is impractical, and blade damages are always formed and accumulated during variable operational conditions. Thus, how to carry out BTT vibration monitoring under variable rotation speed (VRS) is a big challenge. Angular sampling-based order analyses have been widely used for vibration signals in rotating machinery with variable speeds. However, BTT vibration signals are well under-sampled, and Shannon’s sampling theorem is not satisfied so that existing order analysis methods will not work well. To overcome this problem, a reconstructed order analysis-based BTT vibration monitoring method is proposed in this paper. First, the effects of VRS on BTT vibration monitoring are analyzed, and the basic structure of angular sampling-based BTT vibration monitoring under VRS is presented. Then a band-pass sampling-based engine order (EO) reconstruction algorithm is proposed for uniform BTT sensor configuration so that few BTT sensors can be used to extract high EOs. In addition, a periodically non-uniform sampling-based EO reconstruction algorithm is proposed for non-uniform BTT sensor configuration. Next, numerical simulations are done to validate the two reconstruction algorithms. In the end, an experimental set-up is built. Both uniform and non-uniform BTT vibration signals are collected, and reconstructed order analysis are carried out. Simulation and experimental results testify that the proposed algorithms can accurately capture characteristic high EOs of synchronous and asynchronous vibrations under VRS by using few BTT sensors. The significance of this paper is to overcome the limitation of conventional BTT methods of dealing with variable blade rotating speeds.
机译:在线振动监测对于高速旋转刀片显着,并且叶片尖端定时(BTT)通常被认为是有希望的解决方案。 BTT方法必须假设旋转速度是恒定的。该假设是不切实际的,并且在可变操作条件下始终形成和累积刀片损坏。因此,如何在可变旋转速度(VRS)下进行BTT振动监测是一个很大的挑战。基于角度采样的顺序分析已广泛用于旋转机械的振动信号,具有可变速度。然而,BTT振动信号良好采样,并且香农的采样定理不满足,以便现有的订单分析方法无法正常工作。为了克服这个问题,本文提出了一种基于重建的基于订单分析的BTT振动监测方法。首先,分析了VRS对BTT振动监测的影响,并提出了VRS下基于角度采样的BTT振动监测的基本结构。然后提出了一种基于带通采样的发动机顺序(EO)重建算法,用于均匀的BTT传感器配置,因此可以使用很少的BTT传感器提取高EOS。另外,提出了一种基于周期性的基于采样的EO重建算法,用于非均匀的BTT传感器配置。接下来,完成数值模拟以验证两个重建算法。最后,建立了实验设置。收集均匀和不均匀的BTT振动信号,并进行重建的顺序分析。仿真和实验结果证明了所提出的算法可以通过使用几个BTT传感器准确地捕获VRS下同步和异步振动的特性高EOS。本文的重要性是克服传统BTT方法处理可变叶片旋转速度的限制。

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