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首页> 外文会议>STP 1465; Symposium on Bearing Steel Technology-Advances and State of the Art in Bearing Steel Quality Assurance; 20050517-19; Reno,NV(US) >A Statistical Method to Assess the Reliability of Cleanness Measurements for High Quality Bearing Steels
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A Statistical Method to Assess the Reliability of Cleanness Measurements for High Quality Bearing Steels

机译：一种评估高质量轴承钢清洁度可靠性的统计方法

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摘要

During the past decade, greatly increased in-service demands on finished products such as gears, bearings, and springs have inspired a wish by steel makers to guarantee the highest level of cleanness in their steels. In order to achieve this, it has been necessary to develop methods of characterization of cleanness which can describe all the nonmetallic inclusion populations endogenous and exogenous contained in the steel. These methods are essentially based on quantitative metallography and ultrasonic tests. Statistical tools have also been developed to maximize the accuracy of measurements in relation to the time taken to make them, and to answer the key question: What is the minimum analyzed volume for which a measurement can be expected to yield a reliable estimate of a specific in-service property? For quantitative metallographic methods, smaller inclusion densities necessitate an increase in the surface area analyzed, and the study of a larger surface is time consuming. Extreme value analysis is a further method for prediction of the expected size of the largest inclusion in a volume. Often, however, the amount of material examined is not sufficient to assess the quality of the heat with complete certainty. Other tools that have been developed utilize high frequency ultrasonic tests over a frequency range from 10 to 100 MHz , which make it possible to detect inclusions with diameters ranging from 15 urn to 1 mm. In all cases, in order to obtain accurate estimates of the densities of nonmetallic inclusions, it is important to know the appropriate settings for the measurement method. In particular, it is very important to estimate the diagnosis error when we rate a product on the basis of measurements. For each of these inspection techniques, statistical models have been developed to assess the main statistical properties of the methods. The results are reported here. They give a basis for comparison of steel heats that takes account of knowledge of the confidence level of the various measurement methods.
机译：在过去的十年中，对齿轮，轴承和弹簧等成品的使用要求大大提高，这激发了钢铁制造商的愿望，即要保证其钢的最高清洁度。为了实现这一目标，有必要开发一种清洁度表征方法，该方法可以描述钢中所有内源性和外源性的非金属夹杂物群。这些方法主要基于定量金相学和超声测试。还开发了统计工具，以最大程度地提高与进行测量有关的时间的准确性，并回答以下关键问题：可以期望对某项测量产生可靠的特定估计值的最小分析量是多少？服务中的财产？对于定量金相方法，较小的夹杂物密度需要增加所分析的表面积，而研究较大的表面积非常耗时。极值分析是用于预测体积中最大夹杂物的预期大小的另一种方法。但是，通常所检查的材料量不足以完全确定地评估热量的质量。已开发的其他工具利用10至100 MHz频率范围内的高频超声测试，从而可以检测直径范围为15微米至1毫米的夹杂物。在所有情况下，为了获得对非金属夹杂物密度的准确估计，了解测量方法的适当设置非常重要。特别是，当我们根据测量结果对产品进行评估时，估计诊断误差非常重要。对于每种检查技术，已经开发了统计模型来评估方法的主要统计属性。结果报告在这里。它们为比较钢热提供了基础，并考虑了各种测量方法的置信度。

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