改进的精密机械加工零件表面缺陷检测算法  

Improved defects detection algorithm for machined part surface

作　　者：朱海荣[1] 姜平[1] 杨奕[1] 马聪[1] 

机构地区：[1]南通大学电气工程学院,江苏南通226007

出　　处：《传感器与微系统》2006年第11期66-69,共4页Transducer and Microsystem Technologies

摘　　要：对加工表面纹理缺陷进行可靠的检测分析可以有效提高机械加工零件表面精加工的水平。基于计算机视觉技术对机械加工零件表面实现自动缺陷检测,由于机械加工零件表面纹理的特殊性,常用的灰度图像分割方法对机械加工零件表面缺陷的检测不适用;且其表面的缺陷信息无法预先得知,其图像分割是一个非监督纹理分割问题,对此提出了一种改进的模糊聚类缺陷检测算法,实现了对机械加工零件表面缺陷的自动化检测,实验结果证明了该算法的可行性。Defects detection for machined part surface texture image can obviously enhance the entire efficiency for the automatic manufacturing. Because of the particularity of texture image for the machined part surface, the normal texture image segmentation is useless in this kind of defects detection. Since the infomation of defects on machined part surface don＇ t be got in advance, it is a kind of unsupervised texture segmentation. A modified fuzzy clustering method which can detect the defects on machined part surface automatically is presented. The results of experiment demonstrate the feasibility of the algorithm.

关 键 词：机械加工零件表面 缺陷检测 纹理图像 模糊C-均值算法 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]