基于OpenCV的耐张线夹压接缺陷的X射线图像识别方法

X-ray Image Recognition Method for Crimping Defects of Strain Clamp Based on OpenCV

线路耐张线夹压接质量影响着电网运行安全,但目前对耐张线夹压接质量的检测方法存在一定局限性。对此提出了基于OpenCV的耐张线夹X射线图像检测方法。首先采集耐张线夹的X射线图像,并进行预处理。其次通过选取典型缺陷样本缺陷部分图像,使用Python中OpenCV-Python库部分语句实现快速识别检测其他X射线图片,并对其他图片的缺陷部分进行标注。最后根据所标注的缺陷部位区域的灰度值分布的累计值图像确定是否为缺陷。通过该研究,可实现耐张线夹压接部位的X射线图像快速识别,对耐张线夹压接质量检测的工程应用具有重要的参考价值。

The crimp quality of the tension clamp of the line affects the safety of the power grid.At present,the measurement of the quality of the tension clamp has certain limitations.An X-ray image detection method for strain clamp based on image processing technology is proposed.Firstly,the X-ray image of the strain clamp is taken and the image is preprocessed.Secondly,by selecting the defect part image of the typical defect sample,using some statements of OpenCV Python Library in Python to quickly identify and detect other X-ray pictures,and mark the defect part of other pictures.Finally,whether it is a defect is determined according to the cumulative value image of the gray value distribution of the marked defect area.Through the research in this paper,the rapid identification of the X-ray image of the crimping position of the tension clamp can be realized,which has important reference value for the engineering application of the crimping quality inspection of the tension clamp.