Design of Infrared Thermal Wave Image Defect Detection System Based on LabVIEW

TAN Dan; ZHANG Zhijie; WANG Luxiang; YIN Wuliang

Volume 46 Issue 4

Apr. 2024

Turn off MathJax

Article Contents

Article Navigation > Infrared Technology > 2024 > 46(4): 483-490

TAN Dan, ZHANG Zhijie, WANG Luxiang, YIN Wuliang. Design of Infrared Thermal Wave Image Defect Detection System Based on LabVIEW[J]. Infrared Technology , 2024, 46(4): 483-490.

Citation:

TAN Dan, ZHANG Zhijie, WANG Luxiang, YIN Wuliang. Design of Infrared Thermal Wave Image Defect Detection System Based on LabVIEW[J]. Infrared Technology , 2024, 46(4): 483-490.

TAN Dan, ZHANG Zhijie, WANG Luxiang, YIN Wuliang. Design of Infrared Thermal Wave Image Defect Detection System Based on LabVIEW[J]. Infrared Technology , 2024, 46(4): 483-490.

Citation:

TAN Dan, ZHANG Zhijie, WANG Luxiang, YIN Wuliang. Design of Infrared Thermal Wave Image Defect Detection System Based on LabVIEW[J]. Infrared Technology , 2024, 46(4): 483-490.

PDF( 1245 KB)

Design of Infrared Thermal Wave Image Defect Detection System Based on LabVIEW

TAN Dan^1
,,
ZHANG Zhijie^{1
,
,},
WANG Luxiang¹,
YIN Wuliang^{1, 2}

1.
Key Laboratory of Instrumentation Science & Dynamic Measurement of Ministry of Education, North University of China, Taiyuan 038507, China
2.
School of Electrical and Electronic Engineering, University of Manchester, Manchester M139PL, UK

Received Date: 2023-04-12
Rev Recd Date: 2023-05-23
Publish Date: 2024-04-20

Abstract

Abstract

Carbon fiber reinforced composites are widely used in aviation field, which requires higher quality. But the traditional manual detection method has high work intensity and low efficiency. In order to improve the defect detection efficiency of carbon fiber reinforced plastics (CFRP), this study designed a defect detection system based on LabVIEW software development platform, extracted defect edges and performed quantitative statistics. In this study, active infrared thermal imaging non-destructive testing technology is used to obtain the surface thermal images of damaged samples scanned by laser through infrared thermal imager. In view of the poor contrast and uniformity of infrared images, HSL(Hue, Saturation, Luminance) is used to carry out color plane extraction and gray transform, and Niback local threshold segmentation algorithm suitable for processing images with uneven illumination distribution is selected to carry out threshold segmentation processing of image of the region of interest. Finally, morphological processing is used to enhance the image and realize defect feature extraction and defect number statistics. In this study, an infrared thermal imaging defect detection experiment platform is built to complete the acquisition and processing of infrared thermal wave defect images, and the software platform and user interface are designed to realize the extraction of the defect features. Compared with manual detection, the design of this system significantly reduces the detection time and is helpful in realizing the automation of defect detection.
- LabVIEW,
- CFRP,
- infrared thermal imaging,
- defect detection

FullText(HTML)

References(9)

References

[1]	杨福挺, 杨冲冲, 李英昊, 等. 乙醇对碳纤维复合材料界面的影响[J]. 功能高分子学报, 2020, 33(1): 63-69. https://www.cnki.com.cn/Article/CJFDTOTAL-GNGF202001009.htm YANG Futing, YANG Chongchong, LI Yinghao, et al. Ethanol's influence on the carbon fiber composite material interface[J]. Journal of Functional Polymer, 2020, 33(1): 63-69. https://www.cnki.com.cn/Article/CJFDTOTAL-GNGF202001009.htm
[2]	杨红娟, 杨正岩, 杨雷, 等. 碳纤维复合材料损伤的超声检测与成像方法研究进展[J]. 复合材料学报, 2023, 40(8): 4295-4317. https://www.cnki.com.cn/Article/CJFDTOTAL-FUHE202308001.htm YANG Hongjuan, YANG Zhengyan, YANG Lei, et al. Research progress of ultrasonic detection and imaging methods for damage of carbon fiber composites [J]. Journal of Composite Materials: 2023, 40(8): 4295-4317. https://www.cnki.com.cn/Article/CJFDTOTAL-FUHE202308001.htm
[3]	康爽, 陈长征, 刘石, 等. 基于最优多尺度集的形态学红外图像缺陷检测研究[J]. 太阳能学报, 2022, 43(6): 145-152. https://www.cnki.com.cn/Article/CJFDTOTAL-TYLX202206020.htm KANG Shuang, CHEN Changzheng, LIU Shi, et al. Morphological infrared image defect detection based on optimal multi-scale set[J]. Acta Solar-Energy Sinica, 2022, 43(6): 145-152. https://www.cnki.com.cn/Article/CJFDTOTAL-TYLX202206020.htm
[4]	王亚丽, 孙坚, 徐红伟. 基于红外成像太阳能板缺陷检测方法研究[J]. 测控技术, 2015, 34(7): 59-61, 66. https://www.cnki.com.cn/Article/CJFDTOTAL-IKJS201507017.htm WANG Yali, SUN Jian, XU Hongwei. Based on infrared imaging solar panels defect detection method research[J]. Journal of Measurement and Control Technology, 2015, 34(7): 59-61, 66. https://www.cnki.com.cn/Article/CJFDTOTAL-IKJS201507017.htm
[5]	郭辉, 沈勇, 岳林峰, 等. 基于LabVIEW麻花钻几何角度的测量[J]. 工具技术, 2014, 48(1): 82-85. https://www.cnki.com.cn/Article/CJFDTOTAL-GJJS201401062.htm GUO Hui, SHEN Yong, YUE Linfeng, et al. Measurement of geometric angle of twist drill based on LabVIEW [J]. Tool Technology, 2014, 48(1): 82-85. https://www.cnki.com.cn/Article/CJFDTOTAL-GJJS201401062.htm
[6]	郑中华, 施鑫铭, 刘伟斌, 等. 基于Labview机器视觉的SIM卡槽缺陷检测系统研究[J]. 东莞理工学院学报, 2021, 28(5): 50-56. https://www.cnki.com.cn/Article/CJFDTOTAL-DGLG202105006.htm ZHENG Zhonghua, SHI Xinming, LIU Weibin, et al. Research on SIM card slot defect detection system based on Labview machine vision[J]. Journal of Dongguan University of Technology, 2021, 28(5): 50-56. https://www.cnki.com.cn/Article/CJFDTOTAL-DGLG202105006.htm
[7]	王娜. 颗粒图像分割与分析方法研究[D]. 成都: 电子科技大学, 2009. WANG Na. Research on Segmentation and Analysis Method of Granular Image[D]. Chengdu: University of Electronic Science and Technology of China, 2009.
[8]	杨高科. 图像处理、分析与机器视觉(基于LabVIEW)[M]. 北京: 清华大学出版社, 2008. YANG Gaoke. Image Processing, Analysis and Machine Vision (Based on LabVIEW)[M]. Beijing: Tsinghua University Press, 2008.
[9]	王雪晴, 刘锦涛, 卫亚博, 等. 基于机器视觉和LabVIEW的有机玻璃缺陷检测研究[J]. 吉林化工学院学报, 2021, 38(1): 68-73. https://www.cnki.com.cn/Article/CJFDTOTAL-JHXY202101014.htm WANG Xueqing, LIU Jintao, WEI Yabo, et al. Research on defect detection of Plexiglass based on machine vision and LabVIEW[J]. Journal of Jilin Institute of Chemical Technology, 2021, 38(1): 68-73. https://www.cnki.com.cn/Article/CJFDTOTAL-JHXY202101014.htm