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GB/T 40571-2021: Intelligent service - Predictive maintenance - General requirements
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Intelligent service - Predictive maintenance - General requirements
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GB/T 40571-2021
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Basic data | Standard ID | GB/T 40571-2021 (GB/T40571-2021) | | Description (Translated English) | Intelligent service - Predictive maintenance - General requirements | | Sector / Industry | National Standard (Recommended) | | Classification of Chinese Standard | N19 | | Word Count Estimation | 22,287 | | Issuing agency(ies) | State Administration for Market Regulation, China National Standardization Administration | GB/T 40571-2021: Intelligent service - Predictive maintenance - General requirements---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.
Intelligent service - Predictive maintenance - General requirements
ICS 25.040.40
CCSN19
National Standards of People's Republic of China
General requirements for predictive maintenance of intelligent services
Released on 2021-10-11
2022-05-01 implementation
State Administration of Market Supervision and Administration
Issued by the National Standardization Management Committee
Table of contents
Foreword Ⅲ
1 Scope 1
2 Normative references 1
3 Terms and definitions 1
4 Abbreviations 2
5 General 2
5.1 Classification 2
5.2 Work Flow 2
5.3 System Architecture 4
6 Device and function recognition 4
7 Failure mode influence analysis function 5
7.1 Failure mode analysis 5
7.2 Equipment impact analysis 5
8 Feasibility analysis function 5
8.1 Analysis of data status 5
8.2 Risk analysis 6
9 Condition monitoring function 6
10 Fault diagnosis function 7
11 Life prediction function 7
12 Maintenance and management functions 7
Appendix A (Informative) Discrete Manufacturing Predictive Maintenance Implementation Case 8
Appendix B (informative) Typical equipment predictive maintenance implementation case 11
Appendix C (informative) Equipment monitoring parameters 15
Reference 17
Foreword
This document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for Standardization Work Part 1.Structure and Drafting Rules of Standardization Documents"
Drafting.
Please note that some of the contents of this document may involve patents. The issuing agency of this document is not responsible for identifying patents.
This document was proposed by China Machinery Industry Federation.
This document is under the jurisdiction of the National Process Measurement Control and Automation Standardization Technical Committee (SAC/TC124).
Drafting organizations of this document. Institute of Comprehensive Technology and Economics of Machinery Industry Instrumentation, China University of Petroleum (Beijing), China Engineering Physics Research Institute
Research Institute Power Department, Dongfeng Design and Research Institute Co., Ltd., Liaoning University, Shenyang Institute of Automation, Chinese Academy of Sciences, Tsinghua University, Beijing Chemical Industry
University, Chongqing University of Posts and Telecommunications, Beijing Tianze Zhiyun Technology Co., Ltd., Shanghai Dazhi Technology Co., Ltd., Siemens (China) Co., Ltd.,
Mitsubishi Electric Automation (China) Co., Ltd., Endress+Hauser (China) Automation Co., Ltd., Schneider Electric (China) Co., Ltd., Wei
Demuller Electric Connection (Shanghai) Co., Ltd., Delta Intelligent Technology (Beijing) Co., Ltd., Beijing Benz Automotive Co., Ltd., Shenyang Zhongke Bowei
Technology Co., Ltd., Central Research Institute of Shanghai Electric Group Co., Ltd., Baker Hughes Inspection and Control Technology (Shanghai) Co., Ltd.,
Schaeffler (China) Co., Ltd., Chongqing Mengxun Electronic Technology Co., Ltd., State Grid Electric Power Research Institute Wuhan Nanrui Co., Ltd.,
Wuxi Vocational and Technical College, Anhui Rongzhi Rixin Technology Co., Ltd., Beijing Bohua Xinzhi Technology Co., Ltd., Dalian University of Technology,
Xi'an Huayun Zhilian Information Technology Co., Ltd., CSSC Ninth Design and Research Institute Engineering Co., Ltd., China Shipbuilding Industry Corporation Haizhuang Wind Power Co., Ltd.
Co., Ltd., Wuhan Marine Machinery Co., Ltd., China Aviation Industry Corporation Shenyang Aircraft Design and Research Institute, Sun Yat-sen University, Shanghai Airlines
Digital Intelligence Technology Co., Ltd., Accenture (China) Co., Ltd., Beijing Longdingyuan Technology Co., Ltd., Zhenkunxing Industrial Supermarket (Shanghai)
Co., Ltd., Ifm Electronics (Shanghai) Co., Ltd., Fujian Agu Electric Data Technology Co., Ltd., the Fifth Research Institute of Electronics of the Ministry of Industry and Information Technology
Research Institute, Beijing Bichuang Technology Co., Ltd., Shandong Academy of Sciences Computing Center, Beijing Guangli Nuclear System Engineering Co., Ltd., China Nuclear Power Engineering
Engineering Co., Ltd., Guangdong Liyuanheng Intelligent Equipment Co., Ltd., Shanxi Clean Energy Research Institute of Tsinghua University, Shanghai Enai Instrument Co., Ltd.
Division (NI), Pipeline Technology Research Center of PetroChina North Pipeline Co., Ltd., Space Application Engineering and Technology Center of Chinese Academy of Sciences, Beijing
All-road Communication Signal Research and Design Institute Group Co., Ltd., Shuocheng (Xiamen) Technology Co., Ltd., Zhejiang Zheneng Technology Research Institute Co., Ltd.,
Rockwell Automation Control Integration (Shanghai) Co., Ltd., Chongqing Huashu Robot Co., Ltd., North China Electric Power Research Institute Co., Ltd.
Company, Wuhan Zhongyun Kang Chong Technology Co., Ltd., Suzhou Tuokang Automation Technology Co., Ltd., Chongqing Intelligent Robot Research Institute, Xiyin Technology (Hangzhou)
State) Co., Ltd., Beijing Yizong Testing Technology Development Co., Ltd.
The main drafters of this document. Wang Chengcheng, Wang Chunxi, Zhang Laibin, Wang Kai, Song Yan, You Heping, Wang Jinjiang, Yang Ming, Wang Zhongfeng, Jiang Zhinong,
Huang Qingqing, Huang Yi, Dong Zhisheng, Zhu Guoliang, Gao Shanqing, Fu Zhenduo, Liu Wen, Zhou Chunrong, Zhao Dongfang, Guo Dongdong, Yang Zuye, Xu Wei, Zhang Guijun,
Li Yiwen, Chen Jing, Luo Chuanxian, Qian Xiaozhong, Jia Weiyin, Zhao Dali, Li Hongkun, Ren Zhigang, Xiong Guanchu, Tao Jianquan, Zeng Li, Wang Lihui, Hao Yan,
Shi Guilian, Li Yun, Chen Fang, Guo Yun, Tan Hongzhi, Wang Kai, Yang Yang, Guo Qiong, Xu Xiaolu, Li Peng, Wang Min, Liu Zhuo, Wei Kunlun, Yang Xiliang, Wang Yuanhang,
Li Yurong, Chen Zhicong, Lin Legan, Huang Shengda, Guo Qiao, Wang Yue, Zhu Zhifeng, Ma Xiangyang, Ning Guoyun, Zhang Qingjun, Yang Baojun, Chen Demin, Chang Jingbin,
Yang Zhenyong, Qu Qianshang, Xing Yousheng, Shen Yang, Wang Xianfu, Lin Juan.
General requirements for predictive maintenance of intelligent services
1 Scope
This document specifies the general rules of predictive maintenance of intelligent services, equipment and function identification, failure mode impact analysis function, feasibility analysis
Function, condition monitoring function, fault diagnosis function, life prediction function, maintenance management function, etc.
This document applies to the design, development, use, and maintenance of predictive maintenance systems.
2 Normative references
The contents of the following documents constitute the indispensable clauses of this document through normative references in the text. Among them, the dated reference documents, only
The version corresponding to this date is applicable to this document; for undated references, the latest version (including all amendments) is applicable to this document.
GB/T 2298 Mechanical vibration, shock and condition monitoring vocabulary
GB/T 7826 System Reliability Analysis Technology Failure Mode and Effect Analysis (FMEA) Program
GB/T 20921 Machine Condition Monitoring and Diagnosis Vocabulary
GB/T 27921 Risk Management Risk Assessment Technology
3 Terms and definitions
The following terms and definitions defined in GB/T 2298 and GB/T 20921 apply to this document.
3.1
Edgecalculation
On the edge of the network close to the source of things or data, an open platform that integrates network, computing, storage, and application core capabilities, provides edge intelligence nearby
Services to meet the key needs of industry digitalization in agile connection, real-time business, data optimization, application intelligence, security and privacy protection.
3.2
Fault
An abnormal condition that may result in a reduction or loss of the ability of the functional unit to perform the required function.
[Source. GB/T 15969.6-2015, 3.24]
3.3
Intelligent service
A service that can automatically identify the explicit and implicit needs of users, and actively, efficiently, safely and greenly meet their needs.
Note. Predictive maintenance is a typical intelligent service model.
3.4
Monitoringterminal
A device that collects and processes physical quantities (such as flow, pressure, vibration, temperature, humidity, etc.) information, and can interact with centralized or interactive terminals.
[Source. GB/T 31960.1-2015, 3.4, with modification]
3.5
Predictivemaintenance
Continuous or intermittent maintenance based on observed conditions to monitor, diagnose or predict the condition of structures, systems or components
Piece indicators.
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