ANSI/ASTM D6122-2006 多变量过程红外分光光度计确认惯例

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                   【英文标准名称】:     Practice for Validation of Multivariate Process Infrared Spectrophotometers            【原文标准名称】:     多变量过程红外分光光度计确认惯例            【标准号】:     ANSI/ASTM D6122-2006            【标准状态】:     作废            【国别】:     美国            【发布日期】:     2006    【实施或试行日期】: 2006-07-18【发布单位】: 美国国家标准学会(US-ANSI)【起草单位】: ANSI【标准类型】: ()【标准水平】: ()【中文主题词】: 分光光度计;证实【英文主题词】: Control charts;Opticsrocess instruments;Spectrophotometers;Validation【摘要】: This practice covers requirements for the validation of measurements made by online, process near- or mid-infrared analyzers, or both, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification of equivalence between the result calculated from the infrared measurements and the result produced by the primary test method used for the development of the calibration model. When there is adequate variation in property level, the statistical methodology of Practice D 6708 is used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where there is inadequate property variation, methodology for level specific validation is used.  Performance Validation is conducted by calculating the precision and bias of the differences between results from the analyzer system (or subsystem) produced by application of the multivariate model, (such results are herein referred to as Predicted Primary Test Method Results (PPTMRs)), versus the Primary Test Method Results (PTMRs) for the same sample set. Results used in the calculation are for samples that are not used in the development of the multivariate model. The calculated precision and bias are statistically compared to user-specified requirements for the analyzer system application.  For analyzers used in product release or product quality certification applications, the precision and bias requirement for the degree of agreement are typically based on the site or published precision of the Primary Test Method. Note 1In most applications of this type, the PTM is the specification-cited test method.   This practice does not does not describe procedures for establishing precision and bias requirements for analyzer system applications. Such requirements must be based on the criticality of the results to the intended business application and on contractual and regulatory requirements. The user must establish precision and bias requirements prior to initiating the validation procedures described herein.  This practice does not cover procedures for establishing the calibration model (correlation) used by the analyzer. Calibration procedures are covered in Practices E 1655 and references therein.  This practice is intended as a review for experienced persons. For novices, this practice will serve as an overview of techniques used to verify instrument performance, to verify model applicability to the spectrum of the sample under test, and to verify equivalence between the parameters calculated from the infrared measurement and the results of the primary test method measurement.  This practice teaches and recommends appropriate statistical tools, outlier detection methods, for determining whether the spectrum of the sample under test is a member of the population of spectra used for the analyzer calibration. The statistical tools are used to determine if the infrared measurement results in a valid property or parameter estimate.  The outlier detection methods do not define criteria to determine whether the sample or the instrument is the cause of an outlier measurement. Thus, the operator who is measuring samples on a routine basis will find criteria to determine that a spectral measurement lies outside the calibration, but will not have specific information on the cause of the outlier. This practice does suggest methods by which instrument performance tests can be used to indicate if the outlier methods are responding to changes in the instrument response.【中国标准分类号】: N50【国际标准分类号】: 17_180_30【页数】: 【正文语种】: 英语         
         

albertpqr

我回复了，已经在这里跑了半天了，希望能下载此文档