基于机器视觉的瓶装水漏装检测系统设计

Design of Bottles Short Shipment Detection System Based on Machine Vision

针对饮料行业装箱工序完成后,经常出现漏装的问题,设计了一种基于机器视觉的瓶装水漏装检测系统。以瓶盖的颜色、形状为特征,采用Python中OpenCV视觉处理模块在HSV颜色空间中对图像进行预处理,并用霍夫变换圆检测算法对瓶装水的数量信息进行统计。采用LabVIEW调用Python图像处理程序的方式设计人机交互系统,以PLC作为下位机控制机械臂运行。试验结果表明:系统运行稳定、效果良好,能够准确识别箱中瓶装水的个数,准确率达到100%,满足实际需求。

Aiming at the problem of short shipment of bottles after completion of packaging process in beverage industry,the system of detecting short shipment of bottles based on machine vision was designed.Taking the color and shape of the bottle cap as the feature,OpenCV visual processing module in Python was used to preprocess the image in the HSV color space,and hough transform circle detection algorithm was used to conduct statistics on the quantity information of bottles.The man-machine interaction system was designed by using LabVIEW to call Python image processing program,and PLC was used as the lower machine to control the operation of the mechanical arm.The test results show that the system is stable and effective,and can accurately identify the number of bottles in the box with an accuracy of 100%,which meets the actual needs.