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。
To deal with the tearing or rupture occurred during the conveyor belt operation in power plants,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 took only 40 ms,the recognition accuracy rate was 96%,and the false alarm rate was only 2%.Compared with traditional detection methods,the whole time is shortened greatly without the need to stop the conveyor,which ensures the safe and efficient production and reduces the accident rate significantly.
作者
熊辉
周冉
陈磊
XIONG Hui;ZHOU Ran;CHEN Lei(Hubei Energy Group Ezhou Power Co.,Ltd.,Ezhou 436032,China;Wuhan National Laboratory for Optoelectronics,Huazhong University of Science and Technology,Wuhan 430074,China)
出处
《煤炭工程》
北大核心
2022年第11期182-186,共5页
Coal Engineering
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
conveyor belt tearing
machine vision
on-line detection
grid line laser
binary processing
