面向工业生产的大数据管理与可视化系统设计

Design of big data management and visualization system for industrial production

随着中国制造2025的提出,我国工业生产正从传统制造迈向智能制造时代,工业生产的各类数据从纸质记录到电子数据管理已成为必然。然而工业数据具有种类多,数量大,动态更新以及增长快等特点。如何管理好这些海量数据,从中自动提取有价值的信息并以直观的形式呈现,是研究的难点和热点问题。本文设计了一种面向工业生产的大数据管理与可视化系统,通过研究深度学习和云端数据集中存储等关键技术实现大数据的有效管理,通过研究WebSocket实时交互和web页面等关键技术实现生产信息的可视化。经过该系统升级改造的工业设备,可从海量生产数据中快速提取关键信息,并直观清晰的通过网页浏览器实时交互,可应用于各类工业生产领域.

With the proposal of made in China 2025,China's industrial production is moving from traditional manufacturing to intelligent manufacturing era,and all kinds of industrial production data from paper records to electronic data management has become inevitable.However,industrial data is characterized by variety,quantity,dynamic update and rapid growth.How to manage these massive data,automatically extract valuable information and present it in an intuitive form,is a difficult and hot issue in research.This paper designs a big data management and visualization system for industrial production.It realizes the effective management of big data by studying key technologies such as deep learning and cloud data centralized storage,and realizes the visualization of production information by studying key technologies such as WebSocket real-time interaction and web page.The industrial equipment upgraded by this system can extract key information quickly from mass production data and interact with each other directly and clearly through web browser in real time,which can be applied to various industrial production fields.