Analysis of machine vision-based defect detection for logistics conveyor belts

Mengfan Xie

doi:10.1117/12.2684287

1 August 2023 Analysis of machine vision-based defect detection for logistics conveyor belts

Mengfan Xie

Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127540P (2023) https://doi.org/10.1117/12.2684287
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China

Abstract

The logistics industry is an important pillar of national economic development. In the logistics and warehousing industry, conveyor belts are one of the important equipment for transporting goods. However, long-term operation can easily lead to various types of defects such as belt breakage, cracking, and wear, which seriously affect logistics operations. Therefore, this paper proposes a defect detection solution for logistics conveyor belts based on machine vision technology. By using machine vision technology to filter, segment, and edge detect images, the corresponding feature parameters are extracted and input into a BP neural network for learning, so as to identify different types of defects. This study uses this solution to process and analyze the surface images of conveyor belts samples through machine vision technology, which can accurately identify different types of defects and their locations, achieving automated defect detection of conveyor belt surfaces and improving logistics operation efficiency and safety.

Citation Download Citation

Mengfan Xie "Analysis of machine vision-based defect detection for logistics conveyor belts", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127540P (1 August 2023); https://doi.org/10.1117/12.2684287

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