Defect detection in steel bars up to 600 °C using laser line thermography

Puthiyaveettil, Nithin; Thomas, K. Renil; Myrach, Philipp; Ziegler, Mathias; Rajagopal, Prabhu; Balasubramaniam, Krishnan

doi:10.1016/j.infrared.2020.103565

Cited by 5 publications

(2 citation statements)

References 21 publications

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“…In Equation (11), N is the number of elements in the current category, and then the circle parameter corresponding to the minimum value of i S C d is regarded as the actual circle parameter of the category.…”

Section: Determination Of Circle Parametersmentioning

confidence: 99%

“…At present, steel bar surface defect detection methods include the eddy current detection method [1][2][3], the magnetic flux leakage detection method [4][5][6], the laser ultrasonic detection method [7][8][9], the infrared imaging detection method [10][11][12], the machine vision detection method [13][14][15], and so on. These detection methods, however, focus only on the presence of defects on the surface of the steel bar.…”

Section: Introductionmentioning

confidence: 99%

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End Face Attitude Detection of Special Steel Bars Based on Improved DBSCAN

Li,

Zhang,

Wang

et al. 2023

Applied Sciences

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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.

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Section: Determination Of Circle Parametersmentioning

confidence: 99%