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GB/T 40796-2021 English PDF

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GB/T 40796-2021: Corrosion of metals and alloys - Guidelines for applying statistics to analysis of corrosion data
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Basic data

Standard ID GB/T 40796-2021 (GB/T40796-2021)
Description (Translated English) Corrosion of metals and alloys - Guidelines for applying statistics to analysis of corrosion data
Sector / Industry National Standard (Recommended)
Classification of Chinese Standard H25
Word Count Estimation 69,644
Issuing agency(ies) State Administration for Market Regulation, China National Standardization Administration

GB/T 40796-2021: Corrosion of metals and alloys - Guidelines for applying statistics to analysis of corrosion 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.
Corrosion of metals and alloys - Guidelines for applying statistics to analysis of corrosion data ICS 77.060 CCSH25 National Standards of People's Republic of China Corrosion of metals and alloys A Guide to Applied Statistics for Corrosion Data Analysis (ISO 14802.2012,MOD) Released on 2021-10-11 2022-05-01 implementation State Administration for Market Regulation 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 Significance and use 1 5 Scattered data 1 5.1 Distribution 1 5.2 Histogram 1 5.3 Normal distribution 2 5.4 Normal Probability Paper 2 5.5 Other probability paper 2 5.6 Unknown distribution 3 5.7 Extreme Value Analysis 3 5.8 Significant number of digits 3 5.9 Propagation of variance 3 5.10 Error 3 6 Main metric 3 6.1 Average 3 6.2 Median 4 6.3 Note 4 7 Measures of variability 4 7.1 Overview 4 7.2 Variance 4 7.3 Standard deviation 5 7.4 Coefficient of variation 5 7.5 Very Poor 5 7.6 Precision 5 7.7 Bias 6 8 Statistical Test 6 8.1 Null hypothesis 6 8.2 Degrees of freedom 6 8.3 t test 6 8.4 F inspection 8 8.5 Correlation coefficient 8 8.6 Sign check 8 8.7 External enumeration inspection 9 9 Curve fitting---least squares method 9 9.1 Minimizing variance 9 9.2 Linear regression - 2 variables 9 9.3 Polynomial regression 10 9.4 Multiple regression 10 10 Analysis of Variance 10 10.1 Impact comparison 10 10.2 Two-level factorial design 10 11 Extreme value statistics 10 11.1 Extremum statistical range 10 11.2 The Gumbel distribution and its probability paper 11 11.3 Estimation of distribution parameters 12 11.3.1 Data collection 12 11.3.2 Estimation of distribution parameters 12 11.3.3 The probability distribution of xmax and the probability of perforation 13 11.3.4 Estimate the deviation of xmax from the distribution 14 11.4 Report 14 11.5 Other content 15 11.5.1 Sample size 15 11.5.2 Censored samples 15 11.5.3 Other methods of estimating distribution parameters 15 Appendix A (informative) Structural changes of this document compared with ISO 14802.2012 47 Appendix B (informative) Technical differences, editorial changes and reasons between this document and ISO 14802.2012 48 Appendix C (informative) Calculation example 50 Reference 65

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. This document uses the redrafting method to amend and adopt ISO 14802.2012 "Corrosion and Corrosion Data Analysis of Metals and Alloys and Applied Statistics guide". Compared with ISO 14802.2012, this document has many structural adjustments. Appendix A lists this document and ISO 14802.2012. The structural adjustment control checklist. Compared with ISO 14802.2012, this document has technical differences. The set vertical single line (|) is marked, and Appendix B gives a list of corresponding technical differences, editorial changes and their reasons. 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 the China Iron and Steel Association. This document is under the jurisdiction of the National Steel Standardization Technical Committee (SAC/TC183). Drafting organizations of this document. University of Science and Technology Beijing, Metallurgical Industry Information Standards Institute. The main drafters of this document. Li Xiaogang, Hou Jie, Xiao Kui, Sun Menghan, Tian Zijian, Dong Chaofang, Du Cuiwei. Corrosion of metals and alloys A Guide to Applied Statistics for Corrosion Data Analysis

1 Scope

This document provides guidance on certain generally accepted statistical analysis methods that can be used to interpret corrosion test results. This document applies to statistical methods that are widely accepted in corrosion testing. This document does not include detailed calculations and methods, but considers a series of methods that have been used in corrosion tests. Note. Appendix C gives a calculation example of the statistical analysis methods involved in the article.

2 Normative references

There are no normative references in this document.

3 Terms and definitions

There are no terms and definitions that need to be defined in this document.

4 Significance and use

Due to the influence of various factors, the corrosion test results are usually more dispersive than other types of tests, for example, a small amount of impurities can significantly affect Affect the corrosion rate. Statistical analysis can help researchers interpret these results, especially when it is necessary to determine whether the two sets of test results are significant. In the case of sexual differences. When the test involves multiple materials, the difficulty of the test will increase, but statistical methods can provide a reasonable solution to this problem. Deciding method. The combination of modern data reduction programs and computers can make it easier for people to perform complex statistical analysis on data sets. because Therefore, statistical analysis can make it easier for researchers to determine whether there is an association between different variables, and if so, then further develop Develop quantitative expressions related to variables. In analyzing various quantitative results, statistical evaluation is a necessary step. This analysis can estimate the confidence interval from the measurement results.

5 Data fragmentation

5.1 Distribution When the measured value is related to metal corrosion, various factors will cause the actual measured value to deviate from the expected value. Generally speaking, the measured value is scattered The factor of more or less acts in a random manner, and the average of several measured values is closer to the expected value than a single measured value. Data dispersion model The formula is called distribution, and various distributions are observed in corrosion, such as normal distribution, lognormal distribution, binomial distribution, Poisson distribution, and extreme value points. Cloth (including Gumbel and Weibull distributions). 5.2 Histogram Bar graphs (called histograms) can be used to show data dispersion. Construction of histogram. divide the range of data values into phases on the abscissa Equal intervals, and then place bars with a height equal to the number of samples in the interval in each interval. The formula for calculating the number of groups k is shown in formula (1).

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