Data fusion of ultrasonic and thermal nondestructive testing of metal-polymer composite

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Non-destructive testing is an integral part of quality inspection for critical products. The complex structure of metalpolymer hydrogen cylinders makes it difficult to reliably detect defects using a single type of an NDT technique. In this context, the application of hybrid NDT is of interest. This paper considers the combined use of acoustic and thermal techniques of defect detection and the fusion of their results. Experimental verification has shown that the fusion of thermal and acoustic inspection data using the approach developed in this study provides an increase in defect detection compared to the separate use of these types of NDT methods.

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作者简介

D. Dolmatov

National Research Tomsk Polytechnic University

编辑信件的主要联系方式.
Email: dolmatovdo@tpu.ru
俄罗斯联邦, 634050 Tomsk, 30 Lenin Ave

A. Chulkov

National Research Tomsk Polytechnic University

Email: chulkovao@tpu.ru
俄罗斯联邦, 634050 Tomsk, 30 Lenin Ave

D. Nesteruk

National Research Tomsk Polytechnic University

Email: nden@tpu.ru
俄罗斯联邦, 634050 Tomsk, 30 Lenin Ave

E. Kashkarov

National Research Tomsk Polytechnic University

Email: ebk@tpu.ru
俄罗斯联邦, 634050 Tomsk, 30 Lenin Ave

V. Vavilov

National Research Tomsk Polytechnic University

Email: vavilov@tpu.ru
俄罗斯联邦, 634050 Tomsk, 30 Lenin Ave

参考

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2. Fig. 1. Test sample: photograph of the sample (a); diagram of defects (b).

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3. Fig. 2. Laboratory setup for thermal control.

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4. Fig. 3. Laboratory setup for acoustic control.

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5. Fig. 4. Results of TC of the control sample (one-way procedure, heating for 15 s): original thermogram at 40 s (a); PCA image (3rd component) (b); TSR image (1st derivative) (c).

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6. Fig. 5. Results of acoustic testing of the test sample: defect map, depth 2-3 mm (a); defect map, depth 3-4 mm (b); defect map, depth 4-5 mm (c).

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7. Fig. 6. Typical images and signal profiles: original IR thermogram (a); acoustic image, depth range 5-7 mm (b); temperature profile (c); profile of ultrasonic echo signals (d).

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8. Fig. 7. Synthesis of acoustic images and thermograms of a test sample without using threshold values.

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9. Fig. 8. Results of data synthesis using the algorithm with the introduction of thresholds: synthesis of acoustic images (a); synthesis of IR thermograms (b); synthesis of acoustic images and IR thermograms without noise suppression (c); synthesis of acoustic images and IR thermograms with the introduction of noise suppression thresholds (d).

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