Experimental study on infrared phase-locked thermal imaging inspection of carbon fiber reinforced polymer laminates

Abstract

Aiming at the debonding defect of carbon fiber reinforced polymer laminates, an infrared phase-locked thermal imaging inspection system was established, and the influence of different defect diameter and depth parameters on the test was analyzed. The principal component analysis algorithm and Karhunen-Loeve Transform algorithm are used to process the image sequence, and the signal-to-noise ratio is calculated. It is concluded that principal component analysis algorithm can improve the image quality more. Gray enhancement and sharpening filter are used to improve the image clarity, thus accurately segmenting the defect features, and realize a clear and intuitive visual image.