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作 者:何帆 赵秀栩[1,2] 何梦旗 李娇 朱成辉 HE Fan;ZHAO Xiuxu;HE Mengqi;LI Jiao;ZHU Chenghui(School of Mechanical&Electrical,Wuhan University of Technology,Wuhan 430070,China;Hubei Key Laboratory of Digital Manufacturing,Wuhan University of Technology,Wuhan 430070,China;Shaoneng Group Shaoguan Hongda Gear Co.,Ltd.,Shaoguan 512000,China)
机构地区:[1]武汉理工大学机电工程学院,武汉430070 [2]湖北省数字制造重点实验室,武汉430070 [3]韶能集团韶关宏大齿轮有限公司,韶关512000
出 处:《现代制造工程》2024年第10期49-59,共11页Modern Manufacturing Engineering
基 金:广东省科技创新战略专项项目(210907104531267)。
摘 要:在多品种小批量离散制造过程中有工艺图样、车间面板记录、机床传感器信号和质检报告单等多源异构工艺信息,如何高效地获取这些来源不一、结构多样的数据,并有效实现数据可视化、挖掘数据的潜在价值是这一类相关制造型企业面临的一个共性问题。传统纸质化工艺信息管理过程中存在信息化程度低、共享性差、获取不实时和安全性弱等弊端。为解决这一问题,研究以齿轮这一典型多品种小批量离散加工产品为对象,提出一种可综合运用图像识别、文字提取、二维码技术和TCP/IP通信等技术的多元异构数据集成方法,设计并开发了可支持文本、图像和传感器数据等多源异构数据集成的智能运维系统,实现了齿轮关键工序的多源异构数据的实时集成获取、轻量化高效管理、价值挖掘及可视化应用。In the multi-variety small-batch discrete manufacturing process,there are multi-source heterogeneous process information such as process drawings,workshop panel records,machine tool sensor signals,quality inspection reports,etc.How to efficiently obtain these data from different sources and diverse structures,effectively realize data visualization,and tap the potential value of data is a common problem faced by this kind of enterprises.In the process of traditional paper-based process information management,there are some disadvantages,such as low informatization degree,poor sharing,not real-time acquisition and weak security.In order to solve this problem,it takes gear,a typical multi-variety and small-batch discrete processing product,as the object,proposes a multi-heterogeneous data integration method that can comprehensively use image recognition,text extraction,two-dimensional code technology,TCP/IP communication and other technologies,and designs and develops an intelligent operation and maintenance system that can support the integration of multi-source heterogeneous data such as text,image and sensor data.It realizes real-time integration of multi-source heterogeneous data acquisition,lightweight and efficient management,value mining and visual application of key gear processes.
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