Study of lamb wave hybrid imaging technology in high noise environments

Abstract

Ultrasonic Lamb waves often face challenges in extracting valid signals due to environmental noise when detecting damage in composite materials. Additionally, the presence of excessive invalid data can significantly reduce detection efficiency. To solve this issue, a hybrid damage detection method, based on box-counting dimensions and optimized path probabilistic imaging (OPPIBCD), is proposed for use in noisy environments. A damage detection platform is established, with sensors evenly arranged in a circular grid on a composite material plate to simulate real damage through bonded mass blocks. Experimental results indicate that, in high-noise environments, the detection efficiency for single and multiple damage imaging paths improves by 80 % and 65 %, respectively, with maximum errors of 8 mm and 11 mm. The proposed method does not require signal denoising techniques and can directly use the collected noisy signals for damage detection, achieving both high efficiency and accuracy.