Research on composites damage identification based on power spectral density and lamb wave tomography technology in strong noise environment
Research on composites damage identification based on power spectral density and lamb wave tomography technology in strong noise environment
复制标题
强噪声环境下基于功率谱密度和兰姆波层析技术的复合材料损伤识别研究
DOI：
10.1016/j.compstruct.2022.115466
复制
发表时间：
2022-03-11
影响因子：
6.3
通讯作者：
Sui, Qingmei
中科院分区：
文献类型：
--
作者：
Su, Chenhui;Bian, Huihui;Sui, Qingmei
兰姆波因其检测范围广、对缺陷的灵敏度高而在复合材料无损检测中得到广泛研究。为了解决强噪声环境下损伤有效信号的提取问题，提高损伤定位的准确性。提出一种基于功率谱密度和兰姆波层析成像的损伤定位成像方法。分别通过仿真和实验实现了强噪声环境下复合材料损伤定位成像。首先，仿真分析了兰姆波在复合材料中的传播特性。圆形传感器阵列均匀排列在复合材料上。每个传感器用作执行器，按顺时针方向依次产生兰姆波。其他传感器负责收集信号。在采集的信号中加入强噪声，模拟强噪声环境下采集的信号。最后，利用功率谱密度对损伤信息进行表征，确定损伤因子，并利用概率成像算法，完全实现损伤定位成像。实验结果表明，强噪声环境下单损伤和多损伤成像定位最大误差分别为5.10 mm和8.04 mm。该方法不需要对强噪声信号进行预处理，可以直接对原始信号进行成像。同时，避免了复杂反射信号的提取过程，在强噪声环境下复合材料损伤的定位和识别方面具有巨大潜力。
Lamb wave is widely studied in the non-destructive testing of composite materials due to its wide detection range and high sensitivity to defects. In order to solve the problem of extracting the effective signal of damage in a strong noise environment to improve the accuracy of damage location determination. A damage location imaging method based on power spectral density and Lamb wave tomography is proposed in this paper. The damage location imaging of composite materials under strong noise environment is realized through simulation and experiment respectively. Firstly, the simulation analysis the propagation characteristics of Lamb waves in composite materials. The circular sensor array is evenly arranged on the composite material. Each sensor is used as an actuator to generate Lamb wave in turn clockwise. Other sensors are responsible for collecting signals. Strong noise is added to the collected signal to simulate the signal collected in the strong noise environment. Finally, the damage information is characterized by power spectral density to determine the damage factor, and by using the probability imaging algorithm, the damage location imaging is totally realized. The experimental results show that the maximum error of imaging positioning for single damage and multiple damage under strong noise environment is 5.10 mm and 8.04 mm, respectively. This method does not need to pretreatment the signal with strong noise, and can directly image the original signal. At the same time, the extraction process of complex reflected signals is avoided, and it has a great potential in the location and identification of composite materials damage in a strong noise environment.