| Autor: |
Liu, Guozeng, Gao, Weicheng, Liu, Wei, Wei, Yanze, Zou, Xionghui, Bai, Weiliang, Chen, Peng |
| Předmět: |
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| Zdroj: |
Nondestructive Testing & Evaluation; Nov2024, Vol. 39 Issue 7, p1946-1959, 14p |
| Abstrakt: |
Carbon fibre reinforced polymer (CFRP) composites are widely used in the aerospace industry; they are susceptible to impact damage from low-velocity impacts throughout their service life. Long pulse thermography (LPT) was proposed to detect defect in low-velocity impact test (LVIT). In this framework, the defects of matrix fractures, fibre cracks and interface delamination were produced by LVIT in the CFRP specimens. The halogen lamps LPT test system was applied to detect the low-velocity impact damage, and an A655sc infrared camera was applied to collect the surface temperature. In order to improve the efficiency of the impact damage detection, the infrared image sequences were processed by applying different post-processing techniques such as pulse phase thermography (PPT), thermal signal reconstruction (TSR), principal component analysis (PCA), total harmonic distortion (THD), linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). The results show that the signal-to-noise ratio (SNR) was improved by PPT, TSR, PCA, THD, LDA and QDA post-processing techniques. The proposed supervised learning (SL) QDA algorithm achieves better defect identification results than the above post-processing techniques. The detectability of real defects can provide a realistic assessment by the above post-processing techniques. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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