Abstract
The present work introduces a different data processing strategy, proposed in order to improve sub-surface defect detection on industrial composites; in addition, a resume of thermal data processing with most common algorithms in literature is presented and applied with new data. A deep comparison between the common absolute contrast, DAC, PCT, TSR and derivative methods and a new proposed contrast mapping procedure is implemented. Thermographic inspection was done in reflection mode on a Glass Fiber Reinforced Plastic plate, with flat bottom hole defects. Thermal data computation method is found to be critical for simultaneous defect detection and automatic mapping, optimized to identify defect boundaries at specific depth, with help of accurate image processing, implemented in a Matlab GUI for a reliable and rapid characterization of internal damage. The new processing approach, the Local Boundary Contrast method, elaborates different contrast maps and facilitates recognition of damage extension. Tanimoto criterion and the signal-to-noise ratio method were applied as a criterion to assess defect detectability of various processing methods.
Highlights
Non-destructive testing with active thermography involves verification of mechanical properties and material integrity [1, 2], investigating discontinuities and internal defects present in analyzed component [3]
Since flat bottom hole sample is suitable for defect analysis in terms of depth and size, heat preaccumulation appears only at depth around 1 mm (see Fig. 2(a)), disturbing thermal processing as illustrated in example Fig. 5(b)
This paper presented mainly a comparison between several experimental results of established and standard image processing techniques for NDA thermal inspection on composites, compared with a different algorithm, based on new proposed approach, applied to GFRP flat bottom holes’ plate
Summary
Non-destructive testing with active thermography involves verification of mechanical properties and material integrity [1, 2], investigating discontinuities and internal defects present in analyzed component [3]. The main advantages of IRT enhanced international interest for thermal inspection systems in several applications, i.e. the industrial, military defense, archaeological or medical fields [4–7]. Manufacturing, repair processes and in service load history could induce several flaw typologies in composite components, as delamination, diffused porosity, or fiber-matrix cracking [11–13]; interest on active thermographic methods is provided in numerous applications on large and complex composite surfaces [14, 15], for which wide inspected parts of elevated value, as for aeronautical parts, are detected by temperature response under thermal pulses with reliable results. Since the IRT inspections are focused on rapid and real-time application in the production field, thermal-processing and software tools are continuously improved to overcome thermal NDE limitations [18, 19]. The main IRT challenge is represented by the automatic thermal processing of large data sets and the /reliable detection of all anomalies, avoiding false negative information
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