摘要
大型起重机械金属材料常见的气孔缺陷识别是脉冲式红外热波检测技术的新方向。介绍了脉冲式红外热波检测技术原理并搭建了红外热波检测系统,对其采集的图像通过OpenCV环境下实现对图像缺陷识别,将图像灰度转化、高斯滤波、阈值分割、形态学处理等操作得到图像的二值黑白位图,提取出图像的缺陷轮廓特征。将提取出的轮廓特征进一步进行图像后处理、数学特征计算等研究,分别提取缺陷的位置、周长和面积,并与实际缺陷特征进行比较。通过试验对比验证,红外热波无损检测用于大型起重机械金属气孔缺陷检测是可行的。
The recognition of common pore defects in metal materials of large lifting machinery is a new research direction of pulse infrared thermal wave detection technology.The principle of pulse infrared thermal wave detection technology was introduced.The NDT system was established on the basis of these.The image acquired by the system was recognized by image defects under OpenCV environment,and the binary and black and white bitmap of the original image was gotten by using the image processing techniques,such as gray-scale processing,Gauss filtering,threshold segmentation and morphological operation,and then the profile feature was extracted.The extracted profile feature can be used in the image post-processing and calculation of mathematical characteristics to extract the location,perimeter and area of defects respectively,which were compared with the actual defect features.By test comparison verification,the infrared thermal wave detection is feasible for the metal pore defect detection of large crane.
作者
陈曦
殷晨波
许明阳
郑龙海
CHEN Xi;YIN Chenbo;XU Mingyang;ZHENG Longhai(Institute of Automobile and Construction Machinery,Nanjing Tech University,Nanjing 211816,China)
出处
《热加工工艺》
北大核心
2020年第12期66-70,共5页
Hot Working Technology
基金
江苏省质量技术监督局科技项目(KJ175914)
国家自然科学基金项目(51575255)。
关键词
缺陷识别
红外热波检测
OPENCV
轮廓特征
identification of defects
infrared thermal wave detection
openCV
profile features
