煤炭工程 ›› 2022, Vol. 54 ›› Issue (11): 182-186.doi: 10.11799/ce202211032

• 研究探讨 • 上一篇    下一篇

基于机器视觉的输送带撕裂在线检测系统研究

熊辉,周冉,陈磊   

  1. 1. 湖北能源鄂州发电有限公司
    2. 华中科技大学武汉光电国家研究中心
    3. 鄂州发电有限公司
  • 收稿日期:2022-03-15 修回日期:2022-05-12 出版日期:2022-11-15 发布日期:2023-03-09
  • 通讯作者: 周冉 E-mail:zhouran0524@foxmail.com

Research on the on-line detection of conveyor belt tearing based on machine vision

  • Received:2022-03-15 Revised:2022-05-12 Online:2022-11-15 Published:2023-03-09
  • Contact: Ran Zhou E-mail:zhouran0524@foxmail.com

摘要: 针对电厂煤炭输送带运行过程中时常产生的撕裂或断裂问题,结合输送带的工作环境和检测要求,设计制造了一套基于机器视觉的在线检测系统。该系统选用亮度大的网格状线激光作为结构光照射输送带下表面,并通过高分辨率的工业相机实时捕捉输送带下表面图像,利用图像中的网格特征识别撕裂痕迹,整个过程用时仅40ms,识别准确率高达96%,误报率仅为2%,相比于传统的检测方法,时间大大缩短,检测过程中输送带不需停机,在保证安全高效生产的同时实现对输送带运行状态实时监测,有效降低输送带运行事故率。

关键词: 输送带撕裂, 机器视觉, 在线检测, 网格状线激光, 二值化处理

Abstract: To deal with the tearing or rupture problem occurred during the movement process of the conveyor belt in the power plant, a detection device based on machine vision and image recognition was designed according to the working environment and testing requirements. The grid line laser, used as structural light, was irradiated under the conveyor belt surface, and the real-time images of the belt were acquired through the high resolution industrial camera. The belt tearing was identified by feature of gird line in images, which cost only 40 ms, the recognition accuracy rate is as high as 96%, and the false alarm rate is only 2%. Compared to traditional detection methods, the whole time is shortened greatly, and the conveyer belt does not need stop, which ensures the safe and efficient production of the conveyor belt, reduces the accident rate effectively.

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