基于图像识别的煤矿带式输送机自适应调速系统设计

Self-adaptive speed control system of coal mine conveying belt based on image recognition

为了实现节能减排,设计了一种基于图像识别的煤矿带式输送机自适应调速系统。针对调速系统的关键问题——准确快速地获取煤流信息,基于普通摄像机设计了一种高效准确的煤流检测方法,通过基准图像和待测图像的配准获取煤流的横截面,再采用蒙特卡洛法计算煤流区域面积。对该方法采用Python语言和OpenCV图像处理函数编程进行试验,试验结果表明,该系统煤流检测速度快、精度高,满足调速系统的实时性要求,且具备改造升级成本低、维护容易、环境适应性强等特点,在煤炭开采领域具有广阔的应用前景。

In order to save energy and reduce emission,we have designed a self-adaptive speed control system of coal mine transportation belt based on image recognition.The core of the speed control system is to obtain the coal flow accurately and quickly,so an efficient and accurate coal quantity detection method is designed based on common cameras.The cross section of coal flow is obtained through the registration of reference image and test image,and the area of coal flow area is calculated by Monte Carlo method.The experimental results show that the system is fast and accurate for coal flow detection,meeting the real-time requirements of the speed regulation system.The system has the characteristics of low cost of transformation and upgrading,easy maintenance,strong environmental adaptability,and it has broad application prospects in coal mining industry.