Ultrasonic total focusing imaging of wrinkles in composites with maximum eigenvalue vector coherence factor weighting

Fiber reinforced polymer (FRP) composites play a critical role in key industries including aerospace and automotive, and transportation. However, internal wrinkles compromise their structural performance. Nondestructive testing techniques play a vital role in the detection and evaluation of structural failures in FRP composites. The total focusing method (TFM), which utilizes ultrasonic data acquired in full matrix capture (FMC) mode, offers superior resolution compared with conventional phased array methods. However, it performs poorly for internal wrinkles detection, as the weak echoes caused by wrinkles are ofen overlapped with interlayer reflections, mechanical noises and multiple reflection waves. In this paper, a maximum eigenvalue vector coherence factor (MEVCF) weighted TFM is proposed to quantify the wrinkle geometry. Wrinkle angle information is extracted using the structural tensor-based image processing method. The signal phase concentration and the eigenvalue size are jointly applied to measure the phase information validity, thereby enhancing the continuity of the fiber ply. On this basis, a beam focusing deflection angle threshold is processed to effectively suppress the background noises and improve the imaging quality. Experimental results show that the texture clarity and image contrast are improved by approximately 18% and 43% compared with VCF, respectively. Meanwhile, the structural tensor method is less sensitive to noises compared with the gradient operator method. The fiber ply orientation can be accurately captured, enabling the quantitative assessment of wrinkle severity.