Continuous laser-line scanning thermography with data-processing algorithm for rapid and accurate defect inspection

As an emerging nondestructive evaluation method, line-scanning thermography is efficient for defect detection and location. In this study, continuous laser-line scanning thermography combined with a corresponding dataprocessing algorithm is developed to realize highly accurate and highly efficient nondestructive evaluation of large structures. First, the configuration of continuous laser-line-scanning thermography is investigated, and a data-processing algorithm is established using the visual reconstruction method and the distortion correction of captured thermal sequence images. Subsequently, experiments are conducted on samples with defects at different scanning speeds to verify the stability and accuracy of the proposed method. The results indicate that the continuous laser-line scanning thermography is robust for defect detection at different scanning speeds. Highly accurate measurements of defects can be obtained under information redundancy or absence when the sampling frequency does not exactly match the scanning speed. Quantitative experimental comparison shows that the relative error of the defect measurement reduces significantly after the distortion of the initial reconstructed thermal image is corrected. Finally, the effects of the scanning velocity and selected pixel line on the defect detectability are investigated for image reconstruction. The proposed approach is shown to be promising for the continuous nondestructive evaluation of large structures in terms of accuracy and efficiency.