End Face Attitude Detection of Special Steel Bars Based on Improved DBSCAN
Source abstract
Abstract
An end face attitude detection system for special steel bars is designed to solve the problem of defect localization for steel bar grinding. A circle detection method based on improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is proposed for calculating special steel bars’ end face attitude. Firstly, the images are subjected to edge detection, connected region marking, and improved DBSCAN in accordance with the image characteristics. After that, the arcs belonging to the same circle are clustered into the same category to create virtual connected regions. Then, circle parameters of a virtual connected region are clustered using an improved DBSCAN algorithm. The actual circle parameter is obtained by calculating the centroid of each category. Finally, the vector is generated under the set coordinate system, passing through the center of the circumcircle of the steel bar end and one endpoint of the two-dimensional code, and the angle of the vector is calculated to determine the attitude of the special steel bar’s end face. The experimental results demonstrate that the method can obtain an attitude angle resolution of 0.2 degrees with an error range of ±0.1 degrees. This will provide accurate defect localization support for the digitization and intelligence of the grinding platform on the special steel bar production line.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Image and Object Detection Techniques · Industrial Vision Systems and Defect Detection · Advanced Surface Polishing Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China
School of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China
Funding
National Key Research and Development Program of China · National Nature Science Foundation of China
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