ASTM G172 加速运行的寿命数据的统计分析指南

ASTM G172-19发行信息

标准号ASTM G172-19

中文名加速运行的寿命数据的统计分析指南

英文名 Standard Guide for Statistical Analysis of Accelerated Service Life Data

发布日期2019

实施日期

废止日期无

中国标准分类号A41

国际标准分类号03.120.30

发布单位US-ASTM

ASTM G172-19适用范围

The nature of accelerated service life estimation normally requires that stresses higher than those experienced during service conditions are applied to the material being evaluated. For non-constant use stress, such as experienced by time varying weather outdoors, it may in fact be useful to choose an accelerated stress fixed at a level slightly lower than (say 90 % of) the maximum experienced outdoors. By controlling all variables other than the one used for accelerating degradation, one may model the expected effect of that variable at normal, or usage conditions. If laboratory accelerated test devices are used, it is essential to provide precise control of the variables used in order to obtain useful information for service life prediction. It is assumed that the same failure mechanism operating at the higher stress is also the life determining mechanism at the usage stress. It must be noted that the validity of this assumption is crucial to the validity of the final estimate.

Accelerated service life test data often show different distribution shapes than many other types of data. This is due to the effects of measurement error (typically normally distributed), combined with those unique effects which skew service life data towards early failure time (infant mortality failures) or late failure times (aging or wear-out failures). Applications of the principles in this guide can be helpful in allowing investigators to interpret such data.

The choice and use of a particular acceleration model and life distribution model should be based primarily on how well it fits the data and whether it leads to reasonable projections when extrapolating beyond the range of data. Further justification for selecting models should be based on theoretical considerations.

Note 28212;Accelerated service life or reliability data analysis packages are becoming more readily available in common computer software packages. This makes data reduction and analyses more directly accessible to a growing number of investigators. This is not necessarily a good thing as the ability to perform the mathematical calculation, without the fundamental understanding of the mechanics may produce some serious errors. See Ref (1).

1.1 This guide describes general statistical methods for analyses of accelerated service life data. It provides a common terminology and a common methodology for calculating a quantitative estimate of functional service life.

1.2 This guide covers the application of two general models for determining service life distribution at usage condition. The Arrhenius model serves as a general model where a single stress variable, specifically temperature, affects the service life. It also covers the Eyring Model for applications where multiple stress variables act simultaneously to affect the service life.

1.3 This guide emphasizes the use of the Weibull life distribution and is written to be used in combination with Guide G166.

1.4 The uncertainty and reliability of every accelerated service life model becomes more critical as the number of stress variables increases and the extent of extrapolation from the accelerated stress levels to the usage level increases, or both. The models and methodology used in this guide are to provide examples of data analysis techniques only. The fundamental requirements of proper variable selection and measurement must still be met by the users for a meaningful model to result.

1.5 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

1.1本指南描述了加速使用寿命数据分析的一般统计方法。它为计算功能使用寿命的定量估计提供了通用术语和通用方法。

1.2本指南涵盖了确定使用条件下使用寿命分布的两种通用模型的应用。Arrhenius模型作为一般模型，其中单个应力变量，特别是温度，影响使用寿命。它还涵盖了Eyring模型，适用于多个应力变量同时作用以影响使用寿命的应用。

1.3本指南强调使用威布尔寿命分布，并与指南G166结合使用。

1.4随着应力变量数量的增加以及从加速应力水平到使用水平的外推范围的增加，或两者同时增加，每个加速使用寿命模型的不确定性和可靠性变得更加关键。本指南中使用的模型和方法仅提供数据分析技术的示例。用户仍然必须满足适当变量选择和测量的基本要求，才能得到有意义的模型。

1.5本国际标准是根据世界贸易组织技术性贸易壁垒（TBT）委员会发布的《关于制定国际标准、指南和建议的原则的决定》中确立的国际公认标准化原则制定的。