Calibration of a modular trap detector system towards a new realisation of the luminous intensity unit

A modular photometric trap detector system has recently been developed at Physikalisch-Technische Bundesanstalt (PTB). All parts of the detector are now completely calibrated. The new planned traceability chain for the realisation of luminous intensity unit can therefore be established for the first time. This contribution shows the results of the individual calibration steps including the associated measurement uncertainties and correlations. A major part of the calibrations along the traceability chain is done at the upgraded measurement setup TULIP (TUnable Lasers In Photometry). The improvements of the TULIP setup are presented and the effects on the measurement uncertainty are shown. The result of the first complete calibration according to the new traceability chain is compared to previous calibration results both in terms of spectral irradiance responsivity and luminous responsivity. The further steps required towards implementing the new traceability chain and the possible implications are discussed.

Application of systems thinking to the establishment of metrological traceability chains

International agreements in the field of metrology and accreditation of calibration laboratories are the basis for establishing global metrological traceability. Important elements of metrological traceability are calibration of measurement standards and measuring instruments, assessment of measurement uncertainty. The International Laboratory Accreditation Cooperation has a specific policy regarding on traceability of measurement results and estimation of measurement uncertainty in calibration. The partial concept diagram around metrological traceability in accordance with the International Vocabulary of Metrology is proposed. This diagram contains a total of nine metrological concepts, which have most of the associative relations. There are associative relations between the concept of metrological traceability chain and concepts of metrological traceability, measurement standard, calibration and calibration hierarchy, and through the concept of measurement standard with the concept of measurement uncertainty. Systems thinking to the analysis of state of proposed terminological system around metrological traceability was applied. For construction of generalized metrological traceability chain, all the established properties of the system elements around the terminology system of metrological traceability were taken into account. Generalized metrological traceability chain for different levels of the calibration hierarchy was proposed. The proposed chain can be used to develop appropriate chains for specific areas of measurement. To achieve this, it is necessary to determine the specific measured value, the required measurement uncertainty for different levels of the calibration hierarchy and select the necessary measurement standards. Such schemes should be used in national metrology institutes and calibration laboratories.

HANDLING OF CORRELATIONS OF SPECTRAL QUANTITIES IN TRACEABILITY CHAIN – BASICS FOR A PYTHON-BASED ANALYSIS FRAMEWORKE

In this contribution a framework is presented that aims to help for handling correlations within measurement uncertainty calculations for spectral quantities. Taking correlations for spectral quantities into account is necessary as they directly influence the measurement uncertainties especially for integral quantities. Therefore, determination of correlations within traceability chains at national metrology institutes (NMIs) and disseminations of correlated data to test laboratory level is encouraged and a major goal of the EMPIR project 19NRM02 “Revision and extension of standards for test methods for LED lamps, luminaires and modules” (RevStdLED). The presented python-based analysis framework is used in photometry and spectroradiometry at PTB to calculate the results and associated measurement uncertainty for spectral irradiance, spectral irradiance responsivity and luminous responsivity based on spectral calibrations.

Digital Representation of Measurement Uncertainty: A Case Study Linking an RMO Key Comparison with a CIPM Key Comparison

This paper considers a future scenario in which digital reporting of measurement results is ubiquitous and digital calibration certificates (DCCs) contain information about the components of uncertainty in a measurement result. The task of linking international measurement comparisons is used as a case study to look at the benefits of digitalization. Comparison linking provides a context in which correlations are important, so the benefit of passing a digital record of contributions to uncertainty along a traceability chain can be examined. The International Committee for Weights and Measures (CIPM) uses a program of international “key comparisons” to establish the extent to which measurements of a particular quantity may be considered equivalent when made in different economies. To obtain good international coverage, the results of the comparisons may be linked together: a number of regional metrology organization (RMO) key comparisons can be linked back to an initial CIPM key comparison. Specific information about systematic effects in participants’ results must be available during linking to allow correct treatment of the correlations. However, the conventional calibration certificate formats used today do not provide this: participants must submit additional data, and the report of an initial comparison must anticipate the requirements for future linking. Special handling of additional data can be laborious and prone to error. An uncertain-number digital reporting format was considered in this case study, which caters to all the information required and would simplify the comparison analysis, reporting, and linking; the format would also enable a more informative presentation of comparison results. The uncertain-number format would be useful more generally, in measurement scenarios where correlations arise, so its incorporation into DCCs should be considered. A full dataset supported by open-source software is available.

Discussion on the Classification Criteria of Measurement System Level

According to the definition of metrological traceability in ISO/IEC Guide 99:2007(VIM 3)[1], people in the metrology field can know the level of the measurement system in the metrological traceability chain by drawing the metrological traceability diagram on the measurement results. However, if someone want to further determine which level the measurement system belongs to, it should be classified as primary measurement system, secondary measurement system, or even other measurement systems. Because the definitions of terms such as primary measurement system, secondary measurement system and other measurement systems are not included in VIM 3[1], there’s no clear classification basis for the measurement system level. Therefore, this article will discuss the definitions of terms in VIM 3[1] that are more relevant to the classification of measurement system levels, then try to formulate the classification criteria, supplemented by case studies, and hope to serve as a reference for people in the metrology field when reviewing the measurement system and judging its system level.

Quantifying Metrology’s Real Value

Where practicable, the total end-to-end test-and-calibration program cost would serve as the ultimate measurement quality metric (MQM). Total cost includes both the capitalization and ongoing costs that support product quality (sometimes called cost of quality) and the consequence costs (sometimes called cost of poor quality) that result from imperfect measurement and products. End-to-end means capturing costs from the entire traceability chain: from measurement standards to end products. Minimizing this MQM, total end-toend cost (TETEC), equates to optimizing measurement quality assurance (MQA). Lacking easily available measurement and performance data automatically fed to modeling software, organizations have found cost metrics unimaginable or impracticable, so their measurement programs instead target more easily computed MQMs, such as false-accept risk or simpler proxies thereof, setting minimum, but sub-optimal, quality levels. However, modern computing systems and software, such as laboratory management systems with testpoint- level traceability, rapidly approach the point at which the TETEC MQM will become practicable. Preparing for this eventuality, the NCSLI 173 Metrology Practices Committee has developed models that relate costs to measurement program information such as product specifications, test and measurement uncertainties, calibration intervals and reliability targets. Applications include optimizing overall program MQA, but also estimating the value of metrology and return on equipment investments, selecting instruments, designing test and calibration processes, designing products. This paper applies the cost models to case studies and examples to illustrate some applications.

Sandia’s Uncertainty Calculator: A Case Study in the Graded Approach to Software Quality Assurance

Where practicable, the total end-to-end test-and-calibration program cost would serve as the ultimate measurement quality metric (MQM). Total cost includes both the capitalization and ongoing costs that support product quality (sometimes called cost of quality) and the consequence costs (sometimes called cost of poor quality) that result from imperfect measurement and products. End-to-end means capturing costs from the entire traceability chain: from measurement standards to end products. Minimizing this MQM, total end-toend cost (TETEC), equates to optimizing measurement quality assurance (MQA). Lacking easily available measurement and performance data automatically fed to modeling software, organizations have found cost metrics unimaginable or impracticable, so their measurement programs instead target more easily computed MQMs, such as false-accept risk or simpler proxies thereof, setting minimum, but sub-optimal, quality levels. However, modern computing systems and software, such as laboratory management systems with testpoint- level traceability, rapidly approach the point at which the TETEC MQM will become practicable. Preparing for this eventuality, the NCSLI 173 Metrology Practices Committee has developed models that relate costs to measurement program information such as product specifications, test and measurement uncertainties, calibration intervals and reliability targets. Applications include optimizing overall program MQA, but also estimating the value of metrology and return on equipment investments, selecting instruments, designing test and calibration processes, designing products. This paper applies the cost models to case studies and examples to illustrate some applications.

ANALYSIS OF A PROJECT THE NATIONAL TRACEABILITY CHAIN FOR INSTRUMENTS MEASURING MASS AND VOLUME OF LIQUID IN A FLOW

The article provides a comparative analysis of the canceled, current and draft new version of the state verification scheme for measuring the mass and volume of liquid in the flow. The prerequisites and reasons for making changes are considered, as well as the estimated consequences of the changes made for the metrological services using standards and instruments for measuring the mass and volume of liquid in the flow.

Traceability of the Sentinel-3 SLSTR Level-1 Infrared Radiometric Processing

Providing uncertainties in satellite datasets used for Earth observation can be a daunting prospect because of the many processing stages and input data required to convert raw detector counts to calibrated radiances. The Sea and Land Surface Temperature Radiometer (SLSTR) was designed to provide measurements of the Earth’s surface for operational and climate applications. In this paper the authors describe the traceability chain and derivation of uncertainty estimates for the thermal infrared channel radiometry. Starting from the instrument model, the contributing input quantities are identified to build up an uncertainty effects tree. The characterisation of each input effect is described, and uncertainty estimates provided which are used to derive the combined uncertainties as a function of scene temperature. The SLSTR Level-1 data products provide uncertainty estimates for fully random effects (noise) and systematic effects that can be mapped for each image pixel, examples of which are shown.