Adaptive fixed rank kriging-based thermographic data processing for material defect detection

Tung-Yu Hsiao; Nan-Jung Hsu; Stefano Sfarra; Yuan Yao

doi:10.1117/12.2657667

25 April 2023 Adaptive fixed rank kriging-based thermographic data processing for material defect detection

Tung-Yu Hsiao, Nan-Jung Hsu, Stefano Sfarra, Yuan Yao

Proceedings Volume 12489, NDE 4.0, Predictive Maintenance, Communication, and Energy Systems: The Digital Transformation of NDE; 124890J (2023) https://doi.org/10.1117/12.2657667
Event: SPIE Smart Structures + Nondestructive Evaluation, 2023, Long Beach, California, United States

Conference Poster

Abstract

Data collected in active infrared thermography (AIRT) experiments for non-destructive defect detection in materials are often contaminated by undesired noise and backgrounds. In this study, an AIRT data processing method, which adopts adaptive fixed-rank kriging, is proposed. This approach computes a set of ordered functions that represent data features at the different resolution levels, called multi-resolution spline basis functions. Multiresolution spline functions were extracted from the thin-plate splines and ordered by the degree of smoothness. The only tuning parameter for this method is the resolution level, making this approach extensively applicable. The performance of the proposed method was evaluated by conducting a mosaic sample defect detection. The results showed that the proposed AIRT data processing method is not only efficient but also effective.

Citation Download Citation

Tung-Yu Hsiao, Nan-Jung Hsu, Stefano Sfarra, and Yuan Yao "Adaptive fixed rank kriging-based thermographic data processing for material defect detection", Proc. SPIE 12489, NDE 4.0, Predictive Maintenance, Communication, and Energy Systems: The Digital Transformation of NDE, 124890J (25 April 2023); https://doi.org/10.1117/12.2657667

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