基于改进NCM算法对井下套管蚀锈程度的检测  

Detection of Underground Casing Corrosion Degree Based on Improved NCM Algorithm

作　　者：赵艺伟 朱凯俊 朱宗玖[1] Zhao Yiwei;Zhu Kaijun;Zhu Zongjiu(College of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan 232001,China)

机构地区：[1]安徽理工大学电气与信息工程学院,安徽淮南232001

出　　处：《煤矿机械》2023年第12期186-188,共3页Coal Mine Machinery

基　　金：国家自然科学基金项目(61735010,61675147)。

摘　　要：针对煤矿井下光线较暗、井下套管外的蚀锈程度不易被监测,提出了一种基于中智集的抑制式模糊C均值算法。中智集由于能更好地对不确定性像素进行聚类,从而擅长对图像边缘的分割。抑制因子通过修正隶属度来增强算法的运行速率,在算法的目标函数中引入加权模糊因子来给局部邻域像素添加空间信息从而达到抗噪的效果。实验结果表明,改进的算法对井下图像噪声的抑制效果明显,提高了对井下套管蚀锈程度的检测率和准确率。In view of the dim light in the coal mine and the difficulty of monitoring the degree of corrosion outside the underground casing,a inhibition fuzzy C-means algorithm based on the neutrosophic setwas proposed.Because of its better clustering of uncertain pixels,neutrosophic set was good at dividing the edges of images.The inhibitor enhanced the running rate of the algorithm by correcting the degree of membership,and the weighted fuzzy factor was introduced into the target function of the algorithm to add spatial information to the local neighborhood pixels to achieve noise resistance.The experimental results show that the improved algorithm has obvious effect on the image noise of the underground,and improves the detection rate and accuracy of the rust degree of the underground casing.

关 键 词：套管 图像分割 抑制因子 加权模糊因子 中智集 

分 类 号：TD76[矿业工程—矿井通风与安全]