A Semi-empiric Compensation Model for Defect Segmentation in Ultrasonic Thermographic Inspection of Coatings Based on a Chebyshev Series

Abstract

The size of debonding between substrates and coatings are difficult to be accurately evaluated in vibro-thermography due to its complex mechanism. This paper proposes a method for quantitatively evaluating the area of debonding defects in coating systems based on ultrasonic thermography and a delamination area compensation model for defect segmentation in ultrasonic thermography of coating systems. The proposed method then has been derived and tested based on experimental data sampled from a coated aluminium alloy specimen and those from a coated carbon fiber reinforced polymer specimen, respectively. Deconvolution reconstruction based on the LR algorithm has been used to process thermal images to reduce the effect of diffusion in the transverse direction to enhance defect characterization in infrared images. Binary graphs after threshold segmentation have been compensated by the least square nonlinear curve fitting method to evaluate defect areas. The experimental results have shown that the proposed method can clearly detect debonding defects with the diameter-to-depth ratio as small as 2.5 and nondestructively evaluate areas of debonding defects, the relative measurement error of areas of debonding defects in the coated aluminium alloy specimen being 4.71%, and the relative error of the coated CFRP specimen being 10.29%.