GB/T 22394.2-2021 English PDF

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GB/T 22394.2-2021: Condition monitoring and diagnostics of machines - Data interpretation and diagnostics techniques - Part 2: Data-driven applications
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Similar standards

GB/T 23901.1   GB/T 23901.2   GB/T 22393   GB/T 19799.3   GB/T 22394.1   

Basic data

Standard ID: GB/T 22394.2-2021 (GB/T22394.2-2021)
Description (Translated English): Condition monitoring and diagnostics of machines - Data interpretation and diagnostics techniques - Part 2: Data-driven applications
Sector / Industry: National Standard (Recommended)
Classification of Chinese Standard: J04
Word Count Estimation: 14,178
Issuing agency(ies): State Administration for Market Regulation, China National Standardization Administration

GB/T 22394.2-2021: Condition monitoring and diagnostics of machines - Data interpretation and diagnostics techniques - Part 2: Data-driven applications

---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.
Condition monitoring and diagnostics of machines-Data interpretation and diagnostics techniques-Part 2.Data-driven applications ICS 17.160 J04 National Standards of People's Republic of China Machine condition monitoring and diagnosis data interpretation and diagnosis Technology Part 2.Data Driven Applications (ISO 13379-2.2015, IDT) Released on 2021-05-21 2021-12-01 implementation State Administration of Market Supervision and Administration Issued by the National Standardization Management Committee

Table of contents

Foreword Ⅰ Introduction Ⅱ 1 Scope 1 2 Normative references 1 3 Terms and definitions 1 4 The process of implementing data-driven monitoring 2 4.1 Principle of data-driven monitoring method 2 4.2 Asset critical failure and process parameter selection 2 4.3 Data cleaning and resampling 3 4.3.1 General 3 4.3.2 Interpolation error 3 4.3.3 Data quality issues 3 4.3.4 Data resampling 3 4.4 Model development 3 4.4.1 General 3 4.4.2 Definition of the model and selection of related inputs 4 4.4.3 Selection of relevant working conditions and data 4 4.4.4 Model test preparation 4 4.5 Model performance evaluation 4 4.6 Alarm setting 5 5 The process of implementing data-driven diagnostics 5 5.1 General 5 5.2 Automatic mode classification method 5 5.3 Simplified automatic feature classification method 6 6 General recommendations for implementing data-driven monitoring methods 7 Appendix A (informative appendix) Data-driven monitoring application example 8 Appendix B (informative appendix) Data-driven diagnostic application example 10 Reference 11

Foreword

GB/T 22394 "Machine Condition Monitoring and Diagnosis Data Interpretation and Diagnosis Technology" is divided into the following 3 parts. ---Part 1.General Provisions; ---Part 2.Data-driven applications; ---Part 3.Application based on knowledge. This part is Part 2 of GB/T 22394. This section was drafted in accordance with the rules given in GB/T 1.1-2009. The translation method used in this part is equivalent to the ISO 13379-2.2015 "Machine Condition Monitoring and Diagnosis Data Interpretation and Diagnosis Technology No. Part 2.Data Driven Applications. The Chinese documents that have a consistent correspondence with the international documents cited in this section are as follows. ---GB/T 20921-2007 Machine Condition Monitoring and Diagnosis Vocabulary (ISO 13372.2004, IDT). ---GB/T 22394.1-2005 Machine condition monitoring and diagnosis data interpretation and diagnosis technology Part 1.General (ISO 13379-1.2012, IDT). This part is proposed and managed by the National Mechanical Vibration, Shock and Condition Monitoring Standardization Technical Committee (SAC/TC53). Drafting organizations of this section. North China Electric Power University, Xi'an Thermal Power Research Institute Co., Ltd., Zhengzhou Machinery Research Institute Co., Ltd. The main drafters of this section. Fu Zhongguang, Zhang Xueyan, Ma Weiping.

Introduction

This part of GB/T 22394 gives a general process that can be used to determine the state of the machine relative to a series of baseline parameters. Relative to baseline Value changes and comparison with alarm conditions are used to indicate abnormal conditions and generate alarms. Such a process is usually called condition monitoring. In addition, To help determine the appropriate treatment measures, the process of identifying the cause of the abnormal state is usually called diagnosis. Machine condition monitoring and diagnosis data interpretation and diagnosis Technology Part 2.Data Driven Applications

1 Scope

This part of GB/T 22394 gives the process of implementing data-driven monitoring and diagnostic methods to help professionals, especially monitoring The professional staff of the center conduct analysis work. Although some steps have been embedded in the existing tools, in order to better use it, it is still necessary to pay attention to the following steps. ---The selection of assets, critical failures and available process parameters; ---Data cleaning and resampling; ---Model development; ---Model initialization and adjustment; ---Model performance evaluation; ---Diagnostic process. The implementation of these steps does not require comprehensive knowledge of statistical methods, but requires the ability to first establish a training model and apply the model to monitoring And the ability of the diagnostic process. Implement data-driven monitoring model training on machines in normal working conditions. The principle of fault monitoring is to combine the observed data with the estimated data According to comparison. The difference between the observed value of the parameter and the expected value (called residual) indicates that there is an abnormality, which may be related to the equipment or instrument. related. Implement data-driven diagnostic model training on machines in normal working and faulty states. The principle of the diagnostic method is not to detect The deviation of the parameters is to identify the fault by comparing the observed conditions with the faults learned in the training phase. Commonly used techniques The technique is pattern recognition and pattern classification. The data can be taken from the historical data of the distributed control system (DCS), or from a specific monitoring system.

2 Normative references

The following documents are indispensable for the application of this document. For dated reference documents, only the dated version applies to this article Pieces. For undated reference documents, the latest version (including all amendments) is applicable to this document. ISO 13372 Machine Condition Monitoring and Diagnostic Vocabulary (Conditionmonitoringanddiagnosticsofmachines-Vo- cabulary) ISO 13379-1 Machine Condition Monitoring and Diagnosis Data Interpretation and Diagnosis Technology Part 1.General (Condition monitoringanddiagnosticsofmachine-Datainterpretationanddiagnosticstechniques-Part 1.Gen- eralguidelines)

3 Terms and definitions

The terms and definitions defined by ISO 13372 and ISO 13379-1 apply to this document. ......

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