Measuring system for elongation at break of cable insulation sheath based on machine vision

Xu Su; Gangwei Wang; Zhiqiang Zhang; Jiale Yang; Zhijia Zhang

doi:10.1117/12.2643116

12 October 2022 Measuring system for elongation at break of cable insulation sheath based on machine vision

Xu Su, Gangwei Wang, Zhiqiang Zhang, Jiale Yang, Zhijia Zhang

Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 123422G (2022) https://doi.org/10.1117/12.2643116
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China

Abstract

In the production of power cables, the performance test of the cable insulation sheath is an important part. Compared with traditional testing methods, machine vision has the advantages of stable operation, high precision, and high efficiency. Because of this situation, firstly, based on machine vision theory, the structure of the old-fashioned tensile machine was reconstructed, and the whole tensile test process of the cable insulation sheath test was imaged by a CMOS camera, and the color recognition algorithm, effective area segmentation algorithm, and workpiece were proposed. The fracture judgment detection algorithm and the corrosion difference algorithm are used to calculate the distance between the marked lines and then calculate the elongation at the break of the cable material. Through systematic experiments on the same batch of cable jackets, the deviation of the elongation at break measured by visual inspection is the largest, no more than 1%. The experimental results and practical applications show that the machine vision-based visual inspection system has higher accuracy, faster efficiency, and more stable and reliable operation than the traditional inspection system.

Citation Download Citation

Xu Su, Gangwei Wang, Zhiqiang Zhang, Jiale Yang, and Zhijia Zhang "Measuring system for elongation at break of cable insulation sheath based on machine vision", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 123422G (12 October 2022); https://doi.org/10.1117/12.2643116

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KEYWORDS

Distance measurement

Machine vision

Image processing

Image segmentation

Cameras

Corrosion

Sensors

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