首页|基于LabVIEW的红外热波图像缺陷检测系统设计

基于LabVIEW的红外热波图像缺陷检测系统设计

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碳纤维增强复合材料大量应用于航空领域,对其质量提出了更高的要求.但是传统人工检测方法工作强度高、效率低.为了提高碳纤维复合材料的缺陷检测效率,本文基于LabVIEW软件开发平台设计CFRP(carbon fiber reinforced plastics)缺陷检测系统,提取缺陷边缘并进行数量统计.本研究采用主动式红外热成像无损检测技术,通过红外热像仪获取激光扫描的损伤试样表面热图像.针对红外图像对比度及均匀性差的特点,使用HSL(hue,saturation,luminance)进行颜色平面提取,灰度变换,选用适用于处理光照分布不均匀图像的 Niback 局部阈值分割处理算法进行感兴趣区域图像阈值分割处理.最后通过形态学处理增强图像并实现缺陷特征提取和缺陷数量统计.本文通过搭建红外热成像缺陷检测实验平台完成红外热波缺陷图像的采集、处理,设计软件平台及用户界面以实现缺陷特征的提取.相比于人工检测,该系统的设计极大地减少了检测用时,有助于实现缺陷检测的自动化.
Design of Infrared Thermal Wave Image Defect Detection System Based on LabVIEW
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.

LabVIEWCFRPinfrared thermal imagingdefect detection

谭丹、张志杰、王禄祥、尹武良

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中北大学 仪器科学与动态测试教育部重点实验室,山西 太原 038507

曼彻斯特大学 电气与电子工程学院,英国 曼彻斯特 M139PL

LabVIEW CFRP 红外热成像 缺陷检测

2024

红外技术
昆明物理研究所 中国兵工学会夜视技术专业委员会

红外技术

CSTPCD北大核心
影响因子:0.914
ISSN:1001-8891
年,卷(期):2024.46(4)
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