基于EAIDK的智能煤矸分拣系统设计

现有基于图像识别的煤矸石分拣方法实时性较差且整体分拣准确率不高,而基于密度的分拣方法适用于井下初选,成本较高。针对上述问题,设计实现了一种基于EAIDK的智能煤矸分拣系统。采用嵌入式人工智能开发平台EAIDK构建矸石识别和分拣控制硬件平台,在嵌入式深度学习框架Tengine下利用深度学习算法搭建卷积神经网络,建立端到端可训练图像检测模型,并利用智能摄像机获取的图像数据训练模型;通过手眼标定获得摄像机坐标系与机械臂坐标系之间的关系,控制机械臂进行矸石追踪和分拣。实验结果表明,该系统矸石识别准确率稳定保持在95%以上,机械臂跟踪时间小于30 ms,执行误差为1 mm左右,可以满足煤矸分拣工艺要求。

Design of intelligent coal and gangue sorting system based on EAIDK

Existing coal and gangue sorting method based on image identification has poor real-time performance and low sorting accuracy,the density-based sorting method is suitable for underground preparation but has high cost.In view of above problems,an intelligent coal and gangue sorting system based on EAIDK was designed.Embedded artificial intelligence development platform EAIDK is used to build hardware platform for gangue recognition and sorting control,deep learning algorithm is used to build a convolutional neural network under embedded deep learning framework Tengine,and end-to-end trainable image detection model is established and trained by image data obtained by smart cameras.Relationship between the camera coordinate system and the robot arm coordinate system is obtained through hand-eye calibration,and the gangue is tracked and sorted by robot arm.The experimental results show that the system's gangue recognition accuracy remains stable above 95%,the tracking time of robot arm is less than 30 ms,and the execution error is about 1 mm,which can meet the requirements of coal gangue sorting process.