机器视觉技术支持下的纸病智能检测系统架构设计研究  

Research on the Architecture Design of Paper Defect Intelligent Detection System Supported by Machine Vision Technology

作　　者：张燕 李诚志 ZHANG Yan;LI Chengzhi(Xinjiang Normal Univetsity,Urumqi 830000,China)

机构地区：[1]新疆师范大学,新疆乌鲁木齐830000

出　　处：《造纸科学与技术》2024年第2期106-109,共4页Paper Science & Technology

基　　金：国家自然科学基金(41561100);新疆师范大学自治区“十四五”重点学科招标课题(23XJKD0202)。

摘　　要：随着工业自动化技术的迅速发展,精确和高效的质量控制系统成为提升生产效率和产品质量的关键。传统的纸病检测方法依赖人工视觉,存在效率低下和误差率高的问题。为解决这些问题,对一种基于机器视觉技术的纸病智能检测系统设计展开研究。首先设计了包括硬件配置和软件算法在内的完整系统架构,其次通过实际生产环境下的严格测试,验证了系统的有效性。测试结果表明,该系统能够实时准确地识别多种纸病,显著提高了检测的准确率和效率。With the rapid development of industrial automation technology,accurate and efficient quality control system has become the key to improve production efficiency and product quality.The traditional paper disease detection method relies on artificial vision,which has the problems of low efficiency and high error rate.In order to solve these problems,this paper studies and implements an intelligent paper disease detection system based on machine vision technology.The system utilizes advanced image processing technology and deep learning methods to automatically detect and classify paper disease types.Firstly,the complete system architecture including hardware configuration and software algorithm is designed,and then the effectiveness of the system is verified by strict testing in actual production environment.The test results show that the system can accurately identify various paper diseases in real time,and the accuracy and efficiency of detection are significantly improved.

关 键 词：机器视觉 纸病检测 图像处理 卷积神经网络 检测系统 

分 类 号：TS736.2[轻工技术与工程—制浆造纸工程]