1.1本规程涵盖了评估复合材料的化学成分、化学和物理性能以及复合和固化橡胶的测试，这些测试通常可以通过一种或多种测试方法进行。当有一种以上的测试方法可用时，会出现两个问题:哪种测试方法对所评估的基础基本特性有更好（或最好）的响应或区分？哪种测试方法误差最小？这两个特性共同决定了测试方法的一种技术优点，即测试灵敏度。 1.2尽管如本规程所述，需要对测试灵敏度进行全面和详细的处理，但此处可以给出一个简化的概念定义。测试灵敏度是评估的基本特性的判别能力与测量误差或不确定度的比率，表示为标准偏差。判别能力越大，测试误差越低，测试灵敏度越好。借用电子学中的术语，这个比率经常被称为信号- 噪声比；与鉴别功率相对应的信号和与测试测量误差相对应的噪声。因此，本规程描述了如何评估橡胶制造业中使用的测试方法的测试灵敏度（通常定义为信噪比），这些方法测量典型的物理和化学特性，但中所述的例外情况除外。 1.3本规程不涉及以下应用中阈值限或最小检测限（MDL）的灵敏度主题:( 1. )复合材料的有意变化对测量的化合物性能或( 2. )低或微量成分水平的评估。最低检测限是单独标准的主题。 本标准并非旨在解决与其使用相关的所有安全问题（如有）。本标准的用户有责任在使用前制定适当的安全和健康实践，并确定监管限制的适用性。 ====意义和用途====== 测试是为了对材料、过程和产品做出技术决策。随着用于评估科学和技术特性的可用测试方法的持续增长，需要一种定量方法来选择具有高（或最高）质量或技术优点的测试方法。本规程中定义的程序可用于此目的，以使测试尽可能具有成本效益。 过去经常使用的测试方法技术优点和隐含灵敏度的一个指标是测试方法精度。 精度通常表示为定义测试域的测试测量标准偏差的倍数。虽然精度是测试灵敏度所需的数量，但它是一个不完整的特征（仅为必要信息的一半），因为它没有考虑正在评估的FP（或成分）的判别能力。 任何基于测试测量标准偏差比或方差比评估两种不同测试方法的相对测试灵敏度的尝试，均构成无效的灵敏度定量基础或技术价值评估。 只有在比较的两种试验方法直接成比例或相互相关的特殊条件下，变异系数比（归一化为平均值）才可能构成有效的试验灵敏度评估。如果两种试验方法之间的关系是非线性的或具有非零截距的线性关系，则变异系数比不等于本规程中定义的真实试验灵敏度。请参阅中的示例讨论 X1.1.4 . 本规程引入的由测试灵敏度及其各种分类、类别和类型定义的优值允许真实的定量测试灵敏度评估。

1.1 This practice covers testing to evaluate chemical constituents, chemical and physical properties of compounding materials, and compounded and cured rubbers, which may frequently be conducted by one or more test methods. When more than one test method is available, two questions arise: Which test method has the better (or best) response to or discrimination for the underlying fundamental property being evaluated? and Which test method has the least error? These two characteristics collectively determine one type of technical merit of test methods that may be designated as test sensitivity. 1.2 Although a comprehensive and detailed treatment, as given by this practice, is required for a full appreciation of test sensitivity, a simplified conceptual definition may be given here. Test sensitivity is the ratio of discrimination power for the fundamental property evaluated to the measurement error or uncertainty, expressed as a standard deviation. The greater the discriminating power and the lower the test error, the better is the test sensitivity. Borrowing from the terminology in electronics, this ratio has frequently been called the signal-to-noise ratio; the signal corresponding to the discrimination power and the noise corresponding to the test measurement error. Therefore, this practice describes how test sensitivity, generically defined as the signal-to-noise ratio, may be evaluated for test methods used in the rubber manufacturing industry, which measure typical physical and chemical properties, with exceptions as noted in. 1.3 This practice does not address the topic of sensitivity for threshold limits or minimum detection limits (MDL) in such applications as ( 1 ) the effect of intentional variations of compounding materials on measured compound properties or ( 2 ) the evaluation of low or trace constituent levels. Minimum detection limits are the subject of separate standards. This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use. ====== Significance And Use ====== Testing is conducted to make technical decisions on materials, processes, and products. With the continued growth in the available test methods for evaluating scientific and technical properties, a quantitative approach is needed to select test methods that have high (or highest) quality or technical merit. The procedures as defined in this practice may be used for this purpose to make testing as cost effective as possible. One index of test method technical merit and implied sensitivity frequently used in the past has been test method precision. The precision is usually expressed as some multiple of the test measurement standard deviation for a defined testing domain. Although precision is a required quantity for test sensitivity, it is an incomplete characteristic (only one half of the necessary information) since it does not consider the discrimination power for the FP (or constituent) being evaluated. Any attempt to evaluate relative test sensitivity for two different test methods on the basis of test measurement standard deviation ratios or variance ratios, which lack any discrimination power information content, constitutes an invalid quantitative basis for sensitivity, or technical merit evaluation. Coefficient of variation ratios (which are normalized to the mean) may constitute a valid test sensitivity evaluation only under the special condition where the two test methods under comparison are directly proportional or reciprocally related to each other. If the relationship between two test methods is nonlinear or linear with a nonzero intercept, the coefficient of variation ratios are not equivalent to the true test sensitivity as defined in this practice. See discussion of example in X1.1.4 . The figure of merit defined by test sensitivity and its various classifications, categories, and types as introduced by this practice permits an authentic quantitative test sensitivity evaluation.