Infrared Image Defect Detection Based on the Algorithm of Intuitionistic Fuzzy C-Means Clustering
-
摘要: 红外热成像技术常被用来检测碳纤维增强复合材料的内部缺陷，但常用的光学热源加热效率低，需要近距离加热试件。激光具有能量集中、衰减小的优点，其作为加热源有助于实现远距离检测。本文介绍了线激光扫描红外热成像无损检测技术，并对加热过程中材料内部热传导进行了分析。其次，针对红外图像均匀性差、对比度弱，不利于缺陷特征提取的问题，本文引入基于直觉模糊C均值聚类算法的图像分割方法来提取缺陷边缘，与K-Means聚类方法相比，该方法可以提升缺陷模糊边缘的识别和检测能力，保留更多图像的细节信息，有助于准确提取缺陷边缘特征。Abstract: Infrared thermal imaging technology is often used to detect internal defects in carbon-fiber-reinforced polymers; however, commonly used optical heat sources are inefficient and require the specimen to be heated over a short distance. Lasers offer the advantages of energy concentration and low-energy attenuation. As a heating source, it helps achieve long-distance nondestructive testing (NDT). This paper introduces the technology of line laser scanning infrared thermal imaging and analyzes the thermal transmission process inside the material during the heating process. Second, the uniformity and contrast of the infrared image are poor, which is not conducive to defect-feature extraction. Here, image segmentation methods were based on the intuitionistic fuzzy C-means (IFCM) clustering algorithm to extract defect edges. Compared with the K-means clustering method, this method can improve the recognition and detection of fuzzy edges of defects, retain more detailed information of images, and help extract the features of the defect edges accurately.
-
Key words:
- carbon fiber reinforced polymer /
- infrared thermal imaging /
- NDT /
- IFCM
-
图 1 线激光扫描检测原理示意图
Figure 1. Schematic diagram of linear laser scanning inspection principle
图 3 激光扫描热成像无损检测系统
Figure 3. Diagram of laser scanning thermal imaging non-destructive testing system
图 4 3 mm圆盘形孔激励过程的序列图像
Figure 4. Sequential images of 3 mm disc-shaped hole in the excitation process
图 6 IFCM算法缺陷特征提取流程
Figure 6. Flow chart of defect feature extraction in IFCM algorithm
表 1 T800型CFRP热特性
Table 1. Thermal properties of T800 CFRP
Properties Parameters Density ρ/(kg/m3) 1536 Specific heat capacity c/(J/(kg·K)) 865 Thermal conductivity k/(W/(m·K)) 4.2
(Along fiber direction)
0.56
(Perpendicular to fiber direction)
下载: 导出CSV
-
[1] 张晓虎, 孟宇, 张炜. 碳纤维增强复合材料技术发展现状及趋势[J]. 纤维复合材料, 2004(1): 50-53. https://www.cnki.com.cn/Article/CJFDTOTAL-QWFC200401015.htmZHANG Xiaohu, MENG Yu, ZHANG Wei. The state of the art and trend of carbon fiber reinforced polymer[J]. Fiber Composite, 2004(1): 50-53. https://www.cnki.com.cn/Article/CJFDTOTAL-QWFC200401015.htm [2] 王扬, 李科, 刘俊岩. CFRP复合材料层板缺陷的红外热波成像检测方法[J]. 航空制造技术, 2016(4): 36-42. https://www.cnki.com.cn/Article/CJFDTOTAL-HKGJ201604008.htmWANG Yang, LI Ke, LIU Junyan. Defect detection method of CFRP composite lamina-tes by infrared thermal wave imaging[J]. Aeronautical Manufacturing Technology, 2016(4): 36-42. https://www.cnki.com.cn/Article/CJFDTOTAL-HKGJ201604008.htm [3] 李晓丽, 金万平, 张存林, 等. 红外热波无损检测技术应用与进展[J]. 无损检测, 2015(6): 19-23. https://www.cnki.com.cn/Article/CJFDTOTAL-WSJC201506005.htmLI Xiaoli, JIN Wanping, ZHANG Cunlin, et al. The application and progress of infrared thermal wave nondestructive detection technology[J]. Nondestructive Testing, 2015(6): 19-23. https://www.cnki.com.cn/Article/CJFDTOTAL-WSJC201506005.htm [4] 杨晓. 基于红外热波技术的大尺寸复合材料缺陷检测研究[D]. 成都: 电子科技大学, 2021.YANG Xiao. A Research On Defect Detection of Large-Scale Composite Materials Based on infrared Thermal Wave Technology[D]. Chengdu: University of Electronic Science and Technology of China, 2021. [5] 朱笑, 袁丽华. 基于红外热成像的碳纤维增强树脂复合材料低速冲击损伤表征[J]. 复合材料学报, 2022, 39(8): 4164-4171.ZHU X, YUAN L H. Low-velocity impact damage characterization of CFRP based on infrared thermography[J]. Acta Materiae Compositae Sinica, 2022, 39(8): 4164-4171. [6] FENG Q Z, GAO B, LU P, et al. Automatic seeded region growing for thermo-graphy debonding detection of CFRP[J]. NDT & E International, 2018, 99: 36-49. [7] Sreeshan K, Dinesh R, Renji K. Enhancement of thermographic images of composite laminates for debond detection: an approach based on Gabor filter and watershed[J]. NDT & E International, 2019, 103: 68-76. [8] Ogasawara N, Ban A, Yamada H, Kojima R. Paint delamination inspection for light buoys by infrared thermography with distance heating[J]. Adv. Experim. Mech. , 2016(1): 167-172. [9] Masashi Ishikawa, Masaki Ando, Masashi Koyama, et al. Active thermographic inspection of carbon fiber reinforced plastic laminates using laser scanning heating[J]. Composite Structures, 2019, 209: 515-522. [10] 丁超. 碳纤维材料红外热波无损检测技术研究[D]. 北京: 中国科学院大学, 2021.DING Chao. Research on Infrared Thermal Wave Nondestructive Testing Technology of Carbon Fiber Materials [D]. Beijing: University of Chinese Academy of Sciences, 2021. [11] 汪权, 张志杰, 陈昊泽, 等. 线激光扫描的碳纤维复合材料表面损伤研究[J]. 激光与红外, 2022, 52(3): 458-464. https://www.cnki.com.cn/Article/CJFDTOTAL-JGHW202203023.htmWANG Quan, ZHANG Zhijie, CHEN Haoze, et al. Study on surface damage of carbon fiber composites based on line laser scanning[J]. Laser & Infrared, 2022, 52(3): 458-464. https://www.cnki.com.cn/Article/CJFDTOTAL-JGHW202203023.htm [12] 梅晨. 热障涂层结构缺陷脉冲红外热波无损检测技术研究[D]. 哈尔滨: 黑龙江科技大学, 2016.MEI Chen. Research on the Technology of Thermal Barrier Coating Structure Defects Detection Using Pulsed Infrared Thermal Wave Non-Destructive Testing Method[D]. Harbin: Heilongjiang University of Science and Technology, 2016. [13] 孙长友. 工程扫描仪滑架部件力学特性和热特性分析[D]. 西安: 西安电子科技大学, 2008.SUN Changyou. Analysis of Mechanics Characteristic and Thermal Characteristic of Engineering Scanner's Carriage Part[D]. Xi'an: Xidian University, 2008. [14] GUO X W, XU W H. Comparative study on pulsed thermography and modulated thermography of composite honeycomb panels[J]. Acta Materiae Compositae Sinica, 2012, 29(2): 172-179. [15] Fiat A, Shamir A. How to prove yourself: practical solution to identification and signature problems[C]//Advances in Cryptology-CRYPTO, 1987: 186-194. -
点击查看大图
图(8) / 表(1)
计量
- 文章访问数: 24
- HTML全文浏览量: 2
- PDF下载量: 8
- 被引次数: 0
