IEEE 101-1987 pdf free.IEEE Guide for the Statistical Analysis of Thermal Life Test Data.
This revision of IEEE Std 101-1972 describes statistical analyses for data from thermally accelerated aging tests Itexplains the basis and use of statistical calculations for an engineer or scientist. Statistical methods discussed in [2] ‘through [6] provide more information. Life test data analysis is dealt with more specifically in [7] through [13J.Thesubject of this guide is treated extensively in [11] and [12].
ANSIIEEE Std 1-1986 (see Annex 1) discusses the principles for temperature rating of electrical insulation.Theseprinciples are carried forward in ANSIEEE Std 98-1972 and ANSIIEEE Std 99-1980 (see Annex 1) whichrespectively outline test procedures for the experimental estimation of the life of insulating materials and systems.Lifetest procedures for specific insulating materials and systems are outlined in other IEEE publications (see Annex 1)Insulation life test procedures are also described in ASTM (American Society for Testing and Materials),NEMA(National Electrical Manufacturers Association), and lEC(International Electrotechnical Commission) standards (seeAnnex 1).Also, proposed life test procedures continue to appear in the literature.All such publications assume that thelife of insulation with organic materials is a decreasing function of temperature.
Accelerated test procedures usually call for a number of specimens to be aged at each of several temperaturesappreciably above normal operating temperatures.High temperatures are chosen to produce specimen failures(according to specified failure criteria) in typically one week to one year. The test objective is to determine thedependence of median life on temperature from the data and to estimate, by extrapolation, the median life to beexpected at service temperature.This guide presents methods for analyzing such data and for comparing test data ondifferent materials.
The Arrhenius equation gives the rate of a chemical reaction as a function of temperature. Ilt has been adapted [1] toapproximate the relationship between insulation life and temperature as follows.
The coefficients A and B are estimated by fitting the above equation to experimental data. This fitting can be donegraphically or,more precisely, by the method of least squares. These methods are presented in sections 2 and 3.Section 3 gives confidence limits that indicate the uncertainty in estimates from data.Throughout, population valuesare denoted by capital letters (A,B,M(X), etc), and their sample estimates based on experimental data by lower-caseletters (a,b, m(X), etc) to distinguish them.
Theoretically,Eq 3 is valid only if a single chemical reaction and failure mode control the insulation failuremechanism. Other reactions may occur, but if they are not dominant, application of the Arrhenius equation may still bevalid. The Arrhenius equation application is often valid in practice. Sometimes one reaction and failure modedominates over a temperature range, but another reaction with a different temperature coefficient and/or failure modedominates at lower or higher temperatures. Deviations from the simple Arrhenius relation may be caused by differentfailure modes dominant at different temperatures or by variations in mechanical stress,with temperature, that affectthe life. Therefore, while the Arrhenius relation will often fit insulation life-temperature data, it will not always apply.Presented in [8] are valid analyses of such data with two or more failure modes identified by examination of failedspecimens.IEEE 101 pdf download.