基于图像处理与磁探伤技术的工作面刮板输送机在线监测系统

On line monitoring system of face scraper based on image processing and magnetic flaw detection technology

为了在生产实践中对工作面刮板机的工作状态进行实时监测,避免因链条偏移、磨损、断链而造成的损失,提高开采过程的智能化与自动化水平,提出了一种基于语义分割和边缘检测等图像处理技术与磁探伤传感器技术的工作面刮板机在线监测系统。结果表明:在满足识别条件的前提下,该系统对刮板机链条的识别率能够达到90%,识别延迟小于2 s,能够对刮板机的链条拉伸、磨损或变形超过5%时有较高的检测准确度,并且在地面调度指挥中心能够实时接收刮板输送机断链拉斜视频、图片以及地面监控系统语音报警信息。

In order to monitor the working state of the face scraper in real time in production practice,avoid the loss caused by chain deviation,wear and breakage,and improve the intelligence and automation level of the mining process,this paper proposes an online monitoring system for the face scraper based on image processing technologies such as semantic segmentation and edge detection and magnetic flaw detection sensor technology.The results show that,on the premise of meeting the recognition conditions,the recognition rate of the scraper chain can reach 90%,the recognition delay is less than 2 seconds,and the system can have high detection accuracy when the chain of the scraper is stretched,worn or deformed more than 5%.In addition,the ground dispatching command center can receive the video,pictures and voice alarm information of the ground monitoring system of the broken chain and inclined chain of the scraper conveyor in real time.