Detecting delamination defects in CFRP plates using nonlinear defect index of air-coupled Lamb waves and adaptively weighted imaging algorithm

Abstract

The air-coupled ultrasonic technique is capable of detecting defects in in-service CFRP plates and ensuring their application safety. Traditional air-coupled ultrasonic methods often rely on the linear defect index, which is not effective in characterizing small-size defects. Additionally, the scanning step length completely limits their imaging spatial resolution, resulting in the contradiction between imaging spatial resolution and detection efficiency. To address the above problems, the nonlinear defect index and the adaptively weighted imaging algorithm are proposed. The nonlinear defect index uses the relatively nonlinear coefficient of the Lamb wave to enhance the ability to detect small-size defects. Considering the beam width, the adaptively weighted imaging algorithm constructs the relationship between any imaging point and all scanning paths. At this time, the imaging spatial resolution can be set arbitrarily, eliminating the dependence on the scanning step length. The experimental results demonstrate that the proposed nonlinear defect index can characterize the small-size defect more accurately than the linear defect index. When the scanning step length is increased to improve detection efficiency, the adaptively weighted imaging algorithm can achieve better imaging spatial resolution compared to the traditional defect probability imaging algorithm. For the small-size defect with a diameter of 10 mm, the proposed method has an area detection error of only 7.8 %, whereas the traditional method has an error of 22.4 %. The proposed method is promising to detect small-size defects of in-service CFRP plates in the aircraft skin.