Defect detection of GFRP/Nomex honeycomb sandwich structure by linear frequency modulation infrared thermal imaging
| Autor: | Tang Qing-Ju, Fan Wei-Ming, Ji Juan, Song Ya-Fei |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Thermal Science, Vol 25, Iss 6 Part B, Pp 4611-4619 (2021) |
| ISSN: | 2334-7163 0354-9836 |
| DOI: | 10.2298/tsci2106611t |
| Popis: | Honeycomb sandwich material is a new material widely used in many fields, but it is easy to produce defects such as delamination and ponding in the process of manufacturing and service. First, a honeycomb sandwich sample containing delamination defects and water accumulation was built. Then, a linear frequency modulated driving halogen lamp is used as the excitation source. Finally, the surface thermal image sequence of the test sample is acquired by infrared thermal imager. Image sequences are processed by inter-frame difference-multi-frame cumulative average method, principal component analysis, Fourier transform method, and logarithmic polynomial fitting method, respectively. Define and calculate the signal-to-noise ratio of the heat map processed by each algorithm. Compared with the other three algorithms, the principal component analysis method processed the image with the highest signal-to-noise ratio and high contrast. This algorithm achieves effective identification of delamination defects and water accumulation in GFRP/Nomex honeycomb sandwich structure. |
| Databáze: | OpenAIRE |
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