摘要
受输煤机皮带原始图像质量的影响,导致对其跑偏程度的识别结果误差难以得到有效控制,基于此,提出基于双目视觉图像识别的输煤机皮带跑偏在线识别方法。将Mech-Eye UHP-140工业级3D双目视觉相机作为具体的输煤机皮带视觉图像采集装置,在对其安装后,结合实际的输煤机皮带运行状态以及图像质量要求,对具体的采集阶段参数进行设置;在输煤机皮带跑偏程度识别结果,引入了亥姆霍兹原理,对双目视觉图像的边缘进行识别,根据双目图像边缘交叉程度与皮带中心线之间的距离关系,确定具体的跑偏距离。在测试结果中,设计对于皮带偏移量的识别结果并未受到运行速度的影响,且具体的识别结果误差始终稳定在0.1 mm以内。
Affected by the quality of the original image of coal conveyor belt,it is difficult to effectively control the error of the identification result of its deviation degree.Therefore,this paper proposes an online identification method of coal conveyor belt deviation based on binocular vision image recognition.The Mech-Eye UHP-140 industrial 3D binocular vision camera is used as a specific vision image acquisition device for coal conveyor belt.Affer its installation,the parameters of specific acquisition stage are set according to the actual running state of coal conveyor belt and image quality requirements.The Helmholtz principle is introduced to identify the edge of binocular vision image,and the specific deviation distance is determined according to the distance between the cross degree of binocular image edge and the center line of belt.In the test results,the identification result of the design for the ofset of the belt is not affected by the running speed,and the specific identification error is always stable within O.1mm.
作者
赵芳兵
徐学东
Zhao Fangbing;Xu Xuedong(Gansu Huating Coal and Electricity Co.,Ltd.Huating Coal Mine,Huating Gansu 744100,China;Huating Coal Industry Group Co.,Ltd.,Huating Gansu 744100,China)
出处
《机械管理开发》
2024年第10期329-331,共3页
Mechanical Management and Development
关键词
双目视觉图像识别
输煤机皮带
跑偏识别
工业级3D双目视觉相机
亥姆霍兹原理
皮带中心线
binocular vision image recognition
coal conveyor belt
deviation recognition
Mech-Eye UHP-140 Industrial 3D binocular vision camera
Helmholtz's principle
belt center line
