Research of detection algorithm of joint twitching of powerful conveyor belt
-
摘要: 针对现有的强力输送带接头检测算法存在效率低、实时性差、精度不高的问题，提出一种基于迭代阈值法图像分割的接头抽动检测算法。由于X射线图像由不同的探测板传回的数据组成，该算法首先采用迭代法对X射线图像进行阈值分割；然后根据接头的特征，在接头与背景交接处通过Y-差分算法进行接头检测；最后根据接头相邻距离进行匹配，并计算匹配点之间的垂直距离实现接头抽动检测。实验结果表明，该算法检测精度高、速度快，满足实际应用要求，为煤矿安全运输提供了保障。Abstract: In view of problems of low efficiency, bad real-time performance and low accuracy existed in current detection algorithm of joint of powerful conveyor belt, a detection algorithm of joint twitching based on iterative threshold method for image segmentation was proposed. X-ray image is composed by data transmitted back from different detection plates, so iteration method is applied to the X-ray image for threshold segmentation firstly. Then according to characteristics of the joint, it is detected by Y-difference algorithm between the joint and background. Finally, the joints are matched based on distance between the joints, and vertical distance between the matched joints are calculated to realize detection of the joint twitching. The experimental result shows that the algorithm has high accuracy and rapid speed of detection, meets requirements of practical application, and provides guarantee for coal mine safety transportation.
-
-
期刊类型引用(2)
1. 肖汉，孙陆鹏，李彩林，周清雷. 面向GPU的直方图统计图像增强并行算法. 计算机科学与探索. 2022(10): 2273-2285 . 
百度学术
2. 裴浩. 基于GPU的Hadoop平台优化实现. 福建电脑. 2017(03): 41-42 . 百度学术
其他类型引用(0)
计量
- 文章访问数: 47
- HTML全文浏览量: 4
- PDF下载量: 11
- 被引次数: 2
下载:
