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Blade vibration study by spectral analysis of tip-timing signals with OMP algorithm

机译:通过OMP算法对尖端定时信号进行频谱分析研究叶片振动

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摘要

Blades vibrations must be measured in operations to validate blade design. Tip-timing is one of the classical measurement methods but its main drawback is the generation of sub-sampled and non-uniform sampled signals. Consequently tip-timing signals cannot be processed with conventional methods. Assuming that blade vibration signals yield to line spectra, we introduced a sparse signal model that uses speed variation of the engine. The usual solutions of inverse problems are given with the LASSO method. This paper presents a new approach based on a l(0)-regularization. It is solved with the OMP algorithm adapted to our model. Results from synthetic and real signals are presented to illustrate the efficiency of this method, including a real blade crack test case. The main advantages of the proposed method are to provide accurate estimations with a computational cost drastically reduced with respect to existing methods. Besides, the method does not need to set up regularization parameters while taking into account the speed variation of the engines. Finally, results show that this approach greatly reduces frequency aliasings caused by the low sampling frequency of the measured signals. (C) 2019 Elsevier Ltd. All rights reserved.
机译:必须在操​​作中测量叶片振动,以验证叶片设计。提示定时是经典的测量方法之一,但其主要缺点是生成了二次采样和非均匀采样信号。因此,尖端定时信号不能用常规方法处理。假设叶片振动信号产生线谱,我们引入了一个稀疏信号模型,该模型利用了发动机的速度变化。反问题的通常解决方案是用LASSO方法给出的。本文提出了一种基于l(0)-正则化的新方法。它可以通过适用于我们模型的OMP算法来解决。给出了来自合成信号和实际信号的结果,以说明该方法的有效性,包括实际叶片裂纹测试案例。所提出的方法的主要优点是相对于现有方法提供了准确的估计,并且大大降低了计算成本。此外,该方法不需要在考虑发动机的速度变化的情况下设置正则化参数。最后,结果表明,该方法大大减少了由被测信号的低采样频率引起的频率混叠。 (C)2019 Elsevier Ltd.保留所有权利。

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