A method and apparatus for characterizing defects in large flat composite structures by Line Scan Thermography and neural network techniques; Frattura ed Integrita Strutturale; Vol. 17, iss. 63
| Parent link: | Frattura ed Integrita Strutturale.— .— Cassino: Gruppo Italiano Frattura Vol. 17, iss. 63.— 2023.— P. 110-121 |
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| Other Authors: | , , , , |
| Summary: | The principle of Line Scan Thermography (LST) was used to develop a self-propelled infrared thermographic nondestructive testing device for the inspection of large, relatively flat composite aerospace parts, such as aircraft wings. The design of the unit allowed the suppression of noise from reflected radiation. Using the LST method, the new equipment, provided defect detectability similar to that achieved with a classic, static, flash heating procedure, but with a higher inspection rate. Also, the line heating principle ensured more uniform thermal patterns, and the proper choice of scan speed and field of view allows the selection of optimal time delays and the creation of maps of defects at different depths. Defect characterization efficiency was improved by using a trained neural network Текстовый файл AM_Agreement |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://doi.org/10.3221/IGF-ESIS.63.11 |
| Format: | Electronic Book Chapter |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=685516 |
| Summary: | The principle of Line Scan Thermography (LST) was used to develop a self-propelled infrared thermographic nondestructive testing device for the inspection of large, relatively flat composite aerospace parts, such as aircraft wings. The design of the unit allowed the suppression of noise from reflected radiation. Using the LST method, the new equipment, provided defect detectability similar to that achieved with a classic, static, flash heating procedure, but with a higher inspection rate. Also, the line heating principle ensured more uniform thermal patterns, and the proper choice of scan speed and field of view allows the selection of optimal time delays and the creation of maps of defects at different depths. Defect characterization efficiency was improved by using a trained neural network Текстовый файл AM_Agreement |
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| DOI: | 10.3221/IGF-ESIS.63.11 |