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On-line conveyor belts inspection based on machine vision

机译:基于机器视觉的在线传送带检查

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摘要

Under the background that mining conveyor belts are prone to failure in operation, the on-line fault detection technique based on machine vision for conveyor belts is investigated. High-brightness linear light sources arranged to a vaulted shape provide light for a line-array CCD camera to capture high-quality belt images. A fast image segmentation algorithm is proposed to deal belt images on-line. The algorithm for detecting longitudinal rip and belt deviation which are serious threat to the mine safety production from binary belt images is presented. Then, an on-line visual belt inspection system is developed. The laboratory testing results testify the validity of the visual inspection system.
机译:在采矿输送带容易出现故障的背景下,研究了基于机器视觉的输送带在线故障检测技术。排列成拱形的高亮度线性光源为线阵CCD相机提供光线,以捕获高质量的皮带图像。提出了一种快速的图像分割算法来在线处理皮带图像。提出了从二元安全带图像中检测对矿山安全生产构成严重威胁的纵向裂隙和安全带偏差的算法。然后,开发了在线视觉带检查系统。实验室测试结果证明了外观检查系统的有效性。

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