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A Signal Decomposition Method for Ultrasonic Guided Wave Generated from Debonding Combining Smoothed Pseudo Wigner-Ville Distribution and Vold–Kalman Filter Order Tracking

机译:借助于借鉴伪Wigner-Ville分布和Vold-Kalman滤波器跟踪产生的超声波引导波的信号分解方法

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摘要

Carbon fibre composites have a promising application future of the vehicle, due to its excellent physical properties. Debonding is a major defect of the material. Analyses of wave packets are critical for identification of the defect on ultrasonic nondestructive evaluation and testing. In order to isolate different components of ultrasonic guided waves (GWs), a signal decomposition algorithm combining Smoothed Pseudo Wigner-Ville distribution and Vold–Kalman filter order tracking is presented. In the algorithm, the time-frequency distribution of GW is first obtained by using Smoothed Pseudo Wigner-Ville distribution. The frequencies of different modes are computed based on summation of the time-frequency coefficients in the frequency direction. On the basis of these frequencies, isolation of different modes is done by Vold–Kalman filter order tracking. The results of the simulation signal and the experimental signal reveal that the presented algorithm succeeds in decomposing the multicomponent signal into monocomponents. Even though components overlap in corresponding Fourier spectrum, they can be isolated by using the presented algorithm. So the frequency resolution of the presented method is promising. Based on this, we can do research about defect identification, calculation of the defect size, and locating the position of the defect.
机译:由于其优异的物理性质,碳纤维复合材料具有有前途的应用未来的未来。剥夺是材料的重大缺陷。波浪包的分析对于识别超声波无损评估和测试的缺陷至关重要。为了隔离超声波引导波(GWS)的不同组分,介绍了相结合平滑的伪Wigner-Ville分布和Vold-Kalman滤波器跟踪的信号分解算法。在算法中,首先通过使用平滑的伪Wigner-Ville分布获得GW的时频分布。基于频率方向上的时频系数的求和来计算不同模式的频率。在这些频率的基础上,通过Vold-Kalman滤波器追踪来完成不同模式的隔离。模拟信号的结果和实验信号表明,所示的算法成功地将多组分信号分解成单一组分。即使组件在相应的傅里叶频谱中重叠,也可以通过使用所呈现的算法来分离它们。因此,所提出的方法的频率分辨率是有前途的。基于此,我们可以执行关于缺陷识别,计算缺陷尺寸的研究,并定位缺陷的位置。

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