GB/T 42201-2022 English PDFUS$199.00 ยท In stock
Delivery: <= 3 days. True-PDF full-copy in English will be manually translated and delivered via email. GB/T 42201-2022: Intelligent manufacturing - Time series data acquisition and storage management for industrial big data Status: Valid
Basic dataStandard ID: GB/T 42201-2022 (GB/T42201-2022)Description (Translated English): Intelligent manufacturing - Time series data acquisition and storage management for industrial big data Sector / Industry: National Standard (Recommended) Classification of Chinese Standard: L67 Classification of International Standard: 35.240.50 Word Count Estimation: 10,113 Date of Issue: 2022-12-30 Date of Implementation: 2023-07-01 Issuing agency(ies): State Administration for Market Regulation, China National Standardization Administration GB/T 42201-2022: Intelligent manufacturing - Time series data acquisition and storage management for industrial big data---This is a DRAFT version for illustration, not a final translation. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.) will be manually/carefully translated upon your order. ICS 35.240.50 CCSL67 National Standards of People's Republic of China smart manufacturing Industrial big data time series data acquisition and storage management Posted on 2022-12-30 2023-07-01 implementation State Administration for Market Regulation Released by the National Standardization Management Committee table of contentsPreface I 1 Scope 1 2 Normative references 1 3 Terms and Definitions 1 4 Abbreviations 2 5 Time Series Data Acquisition 2 5.1 Collection process 2 5.2 Acquisition system function 2 6 Time series data storage management 3 6.1 Storage management process 3 6.2 Storage management system function 4 Reference 7forewordThis document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for Standardization Work Part 1.Structure and Drafting Rules for Standardization Documents" drafting. Please note that some contents of this document may refer to patents. The issuing agency of this document assumes no responsibility for identifying patents. This document is proposed and managed by the Ministry of Industry and Information Technology of the People's Republic of China. This document is drafted by. Tsinghua University, China Electronics Standardization Institute, Huawei Technologies Co., Ltd., Alibaba Cloud Computing Co., Ltd. Company, Tencent Cloud Computing (Beijing) Co., Ltd., Merrill Lynch Data Technology Co., Ltd., Inspur Electronic Information Industry Co., Ltd., United Think (Beijing) Co., Ltd., Beijing Goldwind Kechuang Wind Power Equipment Co., Ltd., Petrochemical Yingke Information Technology Co., Ltd., Beijing University of Technology, Inspur Software Technology Co., Ltd., Beijing Jixinxing Software Technology Co., Ltd., Transwarp Information Technology (Shanghai) Co., Ltd., Shanghai Maijie Technology Co., Ltd., Sun Yat-sen University, Tianjin University, Xidian University, Beijing University of Posts and Telecommunications, Jiangsu Saixi Technology Development Co., Ltd. Division, Shenzhen Saixi Information Technology Co., Ltd. The main drafters of this document. Wang Jianmin, Wang Chen, Huang Xiangdong, Zhang Qun, Wei Fenglin, Yin Zhuo, Wang Weizhong, Song Binghua, Guan Tao, Wang Jieping, Li Xiaohui, Cheng Hongbin, Yu Chentao, Li Ying, Wan Hai, Shen Yulong, Yang Huihua, Lei Jianjun, Pan Zhaoqing, Peng Bo, Shen Lili, Zhang Xingxing, Zhou Gang, Deng Qiao, Liu Yuan, Suo Hansheng, Han Honggui, Xu Zhe, Cao Youlin, Zhao Liang, Yang Yongjun, Yang Hongshan. smart manufacturing Industrial big data time series data acquisition and storage management1 ScopeThis document specifies the process and system functions of industrial big data time series data acquisition and storage management. This document is applicable to the research, development, testing and application of industrial big data time series data acquisition and storage management system.2 Normative referencesThis document has no normative references.3 Terms and DefinitionsThe following terms and definitions apply to this document. 3.1 industrial big data industrial big data The data produced in the process of industrial activities have the characteristics of huge volume, diverse sources, extremely fast generation, changeable and other characteristics, and it is difficult to use traditional data Data containing large datasets that are efficiently processed by the architecture. Note. It is generally divided into three categories, namely, enterprise informatization data, industrial Internet of Things data, and external cross-border data. Among them, enterprise informatization and industrial Internet of things The massive time series data generated by servers is the main source of industrial data scale. [Source. GB/T 41778-2022,3.21] 3.2 Acquisition system acquisitionsystem A system for collecting and generating time series data. Note. Including systems, subsystems, modules and components, etc. 3.3 A system for storing and managing time series data. Note. Including systems, subsystems, modules and components, etc. 3.4 Time series identifier timeseriesidentifier A unique identifier that characterizes specific time series data in a system. 3.5 timestamp timestamp The data obtained by signing the time and other data to be signed, and used to indicate the time attribute of the data. [Source. GB/T 25069-2022, 3.541] 3.6 time series data timeseriesdata A time-arranged set of data observed or measured at multiple points in time. ...... |
