Automatic data processing based on the skewness statistic parameter for subsurface defect detection by active infrared thermography
نویسندگان
چکیده
Non-destructive testing (NDT) by active infrared thermography requires of data processing techniques in order to: i. improve the thermal contrast between defective and non-defective areas, and ii. reduce the large quantity of images recorded during the inspection without losing relevant information. In this paper, the use of the skewness statistic parameter is proposed for the automatic processing of thermographic sequences obtained by active thermography. The main interest is to compress data from a 3D thermogram sequence to a unique skewness parameter image containing all the relevant information about the subsurface defects. Experimental thermographic data from three CFRP specimens with different surface shape (planar, curved and trapezoidal), containing 25 artificial defects (Teflon ® inserts) at different depths and having several sizes, have been processed using the skewness parameter. The results presented herein demonstrate the potential of this technique for automatic defect detection by active thermography.
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