IEEE 930 1987
$37.38
IEEE Guide for the Statistical Analysis of Electrical Insulation Voltage Endurance Data
Published By | Publication Date | Number of Pages |
IEEE | 1987 | 36 |
New IEEE Standard – Inactive – Superseded. Replaced by 930-2004 (SH/SS95269) This guide describes, with examples, statistical methods to analyze the data for time-to-failure from constant-stress voltage endurance tests or breakdown voltage from progressive-stress tests on specimens or systems of electrical insulation. Methods to compare test data are also given. The methods are principally applied to data from tests on solid insulation, but may also apply to the analyses of data from tests on gas, liquid, and composite systems. The statistical methods discussed here do not take into consideration the physical mechanism of voltage aging. The methods assume that the only aging stress is alternating voltage of constant frequency. The methods may not apply if there is more than one aging stress. Methods to ascertain the short time withstand voltage or operating voltage of an insulation system are not presented in this guide. The mathematical techniques contained in this guide may not directly apply to the estimation of equipment life.
PDF Catalog
PDF Pages | PDF Title |
---|---|
1 | Title Page |
3 | Introduction Participants |
4 | CONTENTS |
5 | 1. Scope and References 1.1 Scope 1.2 References |
6 | 2. Introduction 2.1 Steps Required to Analyze Voltage-Aging Data |
7 | 3. Data Analysis 3.1 Extreme-Value Distributions |
8 | 3.2 The Lognormal Distribution |
9 | 3.3 Censored Data 3.4 Probability Graph Papers |
13 | 4. Estimation of Distribution Parameters 4.1 Graphical Parameter Estimates |
16 | 4.2 Accurate Parameter Estimates |
18 | 4.3 Confidence Intervals for Parameters |
25 | 4.4 Confidence Intervals for Percentage Failed |
27 | 5. Comparison Tests 5.1 Rigorous Hypothesis Tests 5.2 Simplified Method to Compare Percentiles of Extreme Value Distributions |
29 | 6. Failure Models |
30 | 6.1 Inverse Power Model 6.2 Exponential Model 6.3 Fitting Data to Failure Models |
33 | Annex A—Program to Estimate Weibull and Gumbel Parameters |
35 | Annex B—Examples |