基于 Lamb 波椭圆算法和 RAPID 算法融合的多重损伤定位研究

Lijun Meng, Zhengang Guo, Chenglong Ma
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引用次数: 0

摘要

目前的损伤定位方法通常需要许多传感器和复杂的信号处理方法。本文提出了一种基于椭圆定位和损伤概率检测重构算法(RAPID)的融合算法,用于对多个损伤进行定位和成像。对损伤算法进行了实验验证。使用超声波探头在铝合金板上激发 Lamb 信号,测量板内不同位置在多重损伤下的超声波响应信号,并使用所构建的算法对损伤位置进行成像。在实验中,该方法通过排除传感器网络中的无效传感路径提高了定位效率,节省了 31.32% 的计算时间。当传感器网络中的一些传感器受损时,该算法确保了定位精度,定位误差为 5.83 毫米。最后,该算法被用于定位传感器网络中的多个损坏点,结果表明该算法具有良好的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on multiple damage localisation based on fusion of the Lamb wave ellipse algorithm and RAPID algorithm
Current damage localisation methods often require many sensors and complex signal processing methods. This paper proposes a fusion algorithm based on elliptical localisation and the reconstruction algorithm for probabilistic inspection of damage (RAPID) to locate and image multiple damages. Experimental verification of the damage algorithm was conducted. An ultrasonic probe was used to excite Lamb signals on an aluminium alloy plate, the ultrasonic response signals at different positions within the plate under multiple damages were measured and the constructed algorithm was employed to image the damage location. In the experiment, this method improved localisation efficiency by excluding invalid sensing paths in the sensor network, saving 31.32% of computational time. When some sensors in the sensor network were damaged, this algorithm ensured a positioning accuracy with a positioning error of 5.83 mm. Finally, the algorithm was used to locate multiple damages in the sensor network and the results showed the good robustness of the algorithm.
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