摘要
机械臂构件一般工作强度较大,很容易出现各种缺陷问题,若不及时发现和处理,很容易影响其工作质量。因此,进行机械臂构件缺陷检测是十分必要的。在此背景下,研究一种基于三角激光的机械臂构件缺陷检测方法。该研究中借助三角激光法扫描机械臂构件,得到构件图像并开展灰度化和去噪处理。利用USAN法提取图像的角点特征以及通过灰度共生矩阵提取两个纹理特征。对特征参量实施归一化和模糊处理,通过计算贴近度确定缺陷类型,完成机械臂构件缺陷检测。结果表明:所研究方法应用下,欠分割率数值最小,由此说明所研究针对机械臂构件缺陷更为有效,方法检测准确性更高。
The mechanical arm components generally have high working strength and are prone to various defects.If they are not found and handled in time,their working quality will be easily affected.Therefore,it is very necessary to detect the defects of mechanical arm components.Under this background,a defect detection method of mechanical arm components based on triangular laser is studied.In this study,the triangular laser method is used to scan the mechanical arm components to obtain the component image and carry out the graying and denoising processing.The corner feature of the image is extracted by USAN method and two texture features are extracted by gray level co-occurrence matrix.The feature parameters are normalized and fuzzed,and the defect type is determined by calculating the proximity degree to complete the defect detection of the mechanical arm components.The results show that under the application of the method,the under-segmentation rate is the smallest,which shows that the research is more effective for the defects of the mechanical arm components,and the detection accuracy of the method is higher.
作者
张丽娜
ZHANG Lina(College of Information,Mechanical And Electrical Engineering,Zhengzhou Business University,Zhengzhou 451200,China)
出处
《激光杂志》
CAS
北大核心
2024年第4期233-237,共5页
Laser Journal
基金
河南省科技攻关计划项目(No.222102220111)
河南省高等学校重点科研项目(No.22B510019)。
关键词
三角激光
机械臂构件
特征提取
缺陷检测方法
triangle laser
mechanical arm components
feature extraction
defect detection method
