面向工业4.0的数据通道机制初探

2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) Pub Date : 2019-11-01 DOI:10.1109/APSIPAASC47483.2019.9023089

Kheng Hui Ng, Y. Tew, M. Yip

{"title":"面向工业4.0的数据通道机制初探","authors":"Kheng Hui Ng, Y. Tew, M. Yip","doi":"10.1109/APSIPAASC47483.2019.9023089","DOIUrl":null,"url":null,"abstract":"Data are increasing in volume, variety and velocity in this Internet of things and big data era. It applies from industry (or manufacturing) process monitoring control to video surveillance analysis to track human and machines activities. Therefore, fast and accurate approaches in data channelling are needed to effectively deal with these big data. This paper presents practical methods to manage and transfer the data from industry manufacturing site to a centralized data processing hub. In this hub, data are transformed into understandable information, which can assist human in understanding and monitoring manufacturing situation autonomously. These data are collected and channelled to desired location for analysis through Open Platform Communication Unified Architecture (OPC UA). Industrial protocols and standards are used to interpret the data channelling methods and tested on several industrial machines. Result shows that size of data and number of OPC UA Client that connects to OPC Server affects the data channelling speed,","PeriodicalId":145222,"journal":{"name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Prefatory Study on Data Channelling Mechanism towards Industry 4.0\",\"authors\":\"Kheng Hui Ng, Y. Tew, M. Yip\",\"doi\":\"10.1109/APSIPAASC47483.2019.9023089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data are increasing in volume, variety and velocity in this Internet of things and big data era. It applies from industry (or manufacturing) process monitoring control to video surveillance analysis to track human and machines activities. Therefore, fast and accurate approaches in data channelling are needed to effectively deal with these big data. This paper presents practical methods to manage and transfer the data from industry manufacturing site to a centralized data processing hub. In this hub, data are transformed into understandable information, which can assist human in understanding and monitoring manufacturing situation autonomously. These data are collected and channelled to desired location for analysis through Open Platform Communication Unified Architecture (OPC UA). Industrial protocols and standards are used to interpret the data channelling methods and tested on several industrial machines. Result shows that size of data and number of OPC UA Client that connects to OPC Server affects the data channelling speed,\",\"PeriodicalId\":145222,\"journal\":{\"name\":\"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APSIPAASC47483.2019.9023089\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIPAASC47483.2019.9023089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

在物联网和大数据时代，数据的数量、种类和速度都在不断增加。它适用于从工业(或制造)过程监控控制到视频监控分析，以跟踪人和机器的活动。因此，需要快速准确的数据通道方法来有效地处理这些大数据。本文提出了一种实用的方法来管理和传输工业制造现场的数据到一个集中的数据处理中心。在这个中心，数据被转化为可理解的信息，可以帮助人类自主地了解和监控制造状况。这些数据被收集并通过开放平台通信统一架构(OPC UA)传送到所需的位置进行分析。工业协议和标准用于解释数据信道方法，并在几台工业机器上进行了测试。结果表明，数据的大小和OPC UA客户端连接到OPC服务器的数量影响数据通道的速度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A Prefatory Study on Data Channelling Mechanism towards Industry 4.0

Data are increasing in volume, variety and velocity in this Internet of things and big data era. It applies from industry (or manufacturing) process monitoring control to video surveillance analysis to track human and machines activities. Therefore, fast and accurate approaches in data channelling are needed to effectively deal with these big data. This paper presents practical methods to manage and transfer the data from industry manufacturing site to a centralized data processing hub. In this hub, data are transformed into understandable information, which can assist human in understanding and monitoring manufacturing situation autonomously. These data are collected and channelled to desired location for analysis through Open Platform Communication Unified Architecture (OPC UA). Industrial protocols and standards are used to interpret the data channelling methods and tested on several industrial machines. Result shows that size of data and number of OPC UA Client that connects to OPC Server affects the data channelling speed,

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)

自引率

0.00%

发文量