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Corrosion Damage Detection with Piezoelectric Wafer Active Sensors

机译:压电晶片有源传感器的腐蚀损伤检测

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Since today's aging fleet is now intended to far exceed their proposed design life, monitoring the structural integrity of those aircraft has become a priority issue for today's Air Force. One of the most critical structural problems is corrosion. In fact the KC-135 now costs $1.2 billion a year to repair corrosion, In this paper, we plan to show the use of Lamb waves to detect material loss in thin plates representative of aircraft skins. To do this we will use embedded transducers called Piezoelectric Wafer Active Sensor (PWAS) in a pitch-catch configuration. The sensors were placed on a grid pattern. Material loss through corrosion was simulated by removing the material mechanically with an abrasive tool. Thus, simulated corrosion pits of various depths and area coverage were made. Three-count tone burst wave packets were used. The Lamb wave packets were sent in a pitch-catch mode from one transmitter PWAS to the other PWAS in the grid acting as receivers. The Lamb wave mode used in these experiments was A_1, since this was found to be more sensitive to changes due to material loss. At the frequencies considered in our experiments, the A_1 waves are highly dispersive. It was found that, as the Lamb wave travels through simulated corrosion damage, the signal changes. The observed changes were in the signal wavelength (due to change in the dispersive properties of the medium) and in signal amplitude (due to redistribution of energy in the wave packet). This change in signal can be correlated to the magnitude of damage. To achieve this, we have used several approaches: (a) direct correlation between the sent and the received signals; (b) wavelet transform of the signal followed by correlation of the wavelet coefficients time-frequency maps; (c) Hilbert transform of the signal to produce the signal envelope and comparison of the resulting envelope signals (d) neural network correlation between the sent and received signals. It was found that these methods work well together in a complementary way.
机译:由于如今老化的机队现在打算远远超过其建议的设计寿命,因此,监视这些飞机的结构完整性已成为当今空军的首要任务。腐蚀是最关键的结构问题之一。实际上,KC-135现在每年需要花费12亿美元来修复腐蚀。在本文中,我们计划展示使用兰姆波来检测代表飞机蒙皮的薄板中的材料损失。为此,我们将在音高捕获配置中使用称为压电晶片有源传感器(PWAS)的嵌入式传感器。传感器放置在网格图案上。通过使用研磨工具机械去除材料来模拟腐蚀造成的材料损失。因此,制作了各种深度和面积覆盖的模拟腐蚀坑。使用了三计数音突发波包。兰姆波数据包以音高-捕获模式从一个发送器PWAS发送到网格中另一个作为接收器的PWAS。在这些实验中使用的兰姆波模式是A_1,因为发现它对由于材料损失而引起的变化更加敏感。在我们的实验中考虑的频率下,A_1波是高度分散的。发现随着兰姆波传播经过模拟的腐蚀破坏,信号发生变化。观察到的变化是信号波长(由于介质的色散特性的变化)和信号幅度(由于波包中能量的重新分布)。信号的这种变化可以与损害的程度相关。为此,我们使用了几种方法:(a)发送信号和接收信号之间的直接相关; (b)信号的小波变换,然后是小波系数的时频图的相关性; (c)对信号进行希尔伯特变换,以产生信号包络并比较所得包络信号(d)发送和接收的信号之间的神经网络相关性。发现这些方法可以互补的方式很好地协同工作。

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