Huang Xiufeng, Xu Rongwu, Yu Wenjing, Wu Shiji
Laboratory of Vibration and Noise, Naval University of Engineering, Wuhan 430033, China.
National Key Laboratory of Vibration and Noise on Ship, Naval University of Engineering, Wuhan 430033, China.
Sensors (Basel). 2024 Aug 11;24(16):5185. doi: 10.3390/s24165185.
In addressing the challenging issue of impact source localization for large-scale anisotropic stiffened compartmental cylindrical shell structures, this paper presents a novel impact localization method. The method is based on a time-reversal virtual focusing triangulation approach and does not rely on prior knowledge of the structure or specific measurements of wave velocity. By employing energy power filtering to select key sensors, wavelet packet decomposition is utilized to extract narrowband Lamb wave signals, which are then synthesized. Further enhancement of signal recognition is achieved through time-reversal amplification techniques. Experimental results demonstrate that under non-motorized operating conditions, this method achieves an average error of 0.89 m. Under motorized operating conditions, the average error is 1.12 m. Although the presence of background noise leads to an increase in error, the overall localization performance is superior to traditional triangulation methods. Additionally, selecting the top three sensors in terms of energy power ranking can more accurately record impact response.
在解决大型各向异性加筋隔舱圆柱壳结构冲击源定位这一具有挑战性的问题时,本文提出了一种新颖的冲击定位方法。该方法基于时间反转虚拟聚焦三角测量法,不依赖于结构的先验知识或波速的特定测量。通过采用能量功率滤波来选择关键传感器,利用小波包分解提取窄带兰姆波信号,然后进行合成。通过时间反转放大技术进一步提高信号识别能力。实验结果表明,在非机动运行条件下,该方法的平均误差为0.89米。在机动运行条件下,平均误差为1.12米。尽管背景噪声的存在导致误差增加,但整体定位性能优于传统三角测量法。此外,根据能量功率排名选择前三个传感器可以更准确地记录冲击响应。