Square groove detection based on Förstner with canny edge operator using laser vision sensor

Mohd Shah, Hairol Nizam and Nik Anwar, Nik Syahrim and Mohammed Naji, Osamah Abdullah Ahmed and Johan, Nurul Fatiha (2023) Square groove detection based on Förstner with canny edge operator using laser vision sensor. International Journal of Advanced Manufacturing Technology, 125 (5-6). pp. 2885-2894. ISSN 0268-3768

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Abstract

Weld seam recognition is critical for providing information for automated welding control, promoting the advancement of welding sensing technology, and improving welding manufacturing automation. The extraction of the square groove’s feature points using a new method is presented in this paper. Noise is produced in signifcant quantities due to the difcult method used to acquire the weld image. To process images, a specifc method must be utilized. In this work, the central line of the laser stripe is extracted based on Canny edge detection with Haralicks facet model. Based on the central line, the Förstner algorithm is used to recognize the corner points of the square weld groove. Following the establishment of a test platform, a series of detection tests for various sizes of the square groove is established. The acquired detection results are sufciently accurate, with maximum relative errors of less than 3.19%, demonstrating the rationale of the suggested visual sensor’s physical design and the validity of the proposed detection algorithms

Item Type:	Article
Uncontrolled Keywords:	Weld seam detection, Förstner algorithm, Harris algorithm, Laser-structured light detection, Square-type butt groove
Divisions:	Faculty of Electrical Engineering
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	26 Jun 2024 11:43
Last Modified:	26 Jun 2024 11:43
URI:	http://eprints.utem.edu.my/id/eprint/27183
Statistic Details:	View Download Statistic

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