Experimental study on infrared phase-locked thermal imaging inspection of carbon fiber reinforced polymer laminates
-
Published:2022
Issue:2 Part A
Volume:26
Page:1105-1111
-
ISSN:0354-9836
-
Container-title:Thermal Science
-
language:en
-
Short-container-title:THERM SCI
Author:
Tang Qing-Ju1, Ji Juan1, Fan Wei-Ming1, Ran Ling1, An Si-Jie1, Zhang Tao1, Bu Chi-Wu2
Affiliation:
1. School of Mechanical Engineering, Heilongjiang University of Science and Technology, Harbin, China 2. School of Light Industry, Harbin University of Commerce, Harbin, China
Abstract
Aiming at the debonding defect of carbon fiber reinforced polymer laminates,
an infrared phase-locked thermal imaging inspection system was established,
and the influence of different defect diameter and depth parameters on the
test was analyzed. The principal component analysis algorithm and
Karhunen-Loeve Transform algorithm are used to process the image sequence,
and the signal-to-noise ratio is calculated. It is concluded that principal
component analysis algorithm can improve the image quality more. Gray
enhancement and sharpening filter are used to improve the image clarity,
thus accurately segmenting the defect features, and realize a clear and
intuitive visual image.
Publisher
National Library of Serbia
Subject
Renewable Energy, Sustainability and the Environment
Reference9 articles.
1. Kolobkov, A. S., et al., Development of Carbon Fiber Production Technologies A Review, Fibre Chemistry, 52 (2020), 1, pp. 1-5 2. Qin, F. V., et al., Mechanical and Electrical Properties of Carbon Fiber Composites with Incorporation of Graphene Nanoplatelets at the Fiber-Matrix Interphase, Composites Part B, 69 (2015), Feb., pp. 335- 341 3. Chen, H., et al., Research Status of Carbon Fiber/Polymer Composites Based on Additive Manufacturing, China Plastics Industry, 47 (2019), 10, pp. 15-17 4. Ngo, A., et al., Nondestructive Evaluation of Defects in Carbon Fiber Reinforced Polymer (CFRP) Composites, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, and Civil Infrastructure (H. Felix Wu), Society of Photo-optical Instrumentation Engineers Society of PhotoOptical Instrumentation Engineers (SPIE) Conference Series, Oregon, United States, 2017, Vol. 1, pp. 6 5. Vallejo, Z., J., et al., Principal Component Analysis, Pattern Processing & Machine Intelligence Division Research Note Dra, 1 (2012), 2, pp. 704-706
|
|