The Development of Adaptive Gray Level Mapping Combined Partical Wwarm Optimization for Measuring the Dimeter Size of Automotive Nut

Pondech, Wichai; Saenthon, Anakkapon; Konghuayrob, Poom

doi:10.1109/iciea49774.2020.9102047

Cited by 2 publications

(2 citation statements)

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“…We kept the six sides and removed non-edge pixels. Next, we set the maximum value of I h as m θ , and remove the number of points with gradient direction less than 1 2 m θ . Therefore, we could obtain the angle p i of the six edges of one nut.…”

Section: Inspection Subsystemmentioning

confidence: 99%

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Nut Geometry Inspection Using Improved Hough Line and Circle Methods

Lin

Lien

2023

Sensors

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Nuts are the cornerstone of human industrial construction, especially A-grade nuts that can only be used in power plants, precision instruments, aircraft, and rockets. However, the traditional nuts inspection method is to manually operate the measuring instrument for conducting an inspection, so the quality of the A-grade nut cannot be guaranteed. In this work, a machine vision-based inspection system was proposed, which performs a real-time geometric inspection of the nuts before and after tapping on the production line. In order to automatically screen out A-Grade nuts on the production line, there are 7 inspections within this proposed nut inspection system. The measurements of parallel, opposite side length, straightness, radius, roundness, concentricity, and eccentricity were proposed. To shorten the overall detection time regarding nut production, the program needed to be accurate and uncomplicated. By modifying the Hough line and Hough circle, the algorithm became faster and more suitable for nut detection. The optimized Hough line and Hough circle can be used for all measures in the testing process.

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Section: Inspection Subsystemmentioning

confidence: 99%

“…Concerning machine vision detection, the captured images need pre-processing before the inspection. Therefore, the Adaptive Gray Level Mapping algorithm (AGLM) [1] was proposed to improve image quality. However, AGLM only performs simple circle and line detection and cannot be used in real conditions [2].…”

Section: Introductionmentioning

confidence: 99%