摘要
针对传统煤与矸石分选方法存在效率低、污染环境、成本高等问题,设计了一种基于X射线和机器视觉的煤与矸石识别分选系统。该系统首先利用机器视觉技术获取煤和矸石图像,用图像处理算法得到煤和矸石的厚度信息;然后采用X射线扫描并获取煤和矸石图像,经处理后得到图像的灰度值信息;最后综合灰度值信息和厚度信息确定煤和矸石的分离阈值,实现煤和矸石的分离。实验结果表明,该系统利用分离阈值能有效识别煤和矸石,且识别率高,识别精度满足工业生产要求。
In view of problems of low efficiency,environmental pollution and high cost existed in traditional coal and gangue separation method,a separation system of coal and gangue based on X-ray and machine vision was designed.The system uses machine vision to obtain visual images which were identified through image processing algorithm to get the thickness of coal and gangue.Then X-ray was used to scan and obtain coal and gangue images which were identified through the image processing algorithm to get the gray value.Finally,the gray value was combined with thickness of coal and gangue to draw the sorting threshold,so as to separate the gangue from the coal.The test result shows that the system can recognize coal and gangue effectively through the threshold with high recognition rate,and recognition precision meets requirements of industrial production.
出处
《工矿自动化》
北大核心
2017年第3期85-89,共5页
Journal Of Mine Automation
关键词
煤炭开采
煤和矸石识别
煤和矸石分选
分离阈值
X射线
机器视觉
coal mining
coal and gangue recognition
coal and gangue separation
separation threshold
X-ray
machine vision