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The essential source of errors in machining on five-axis milling centres are errors caused by the improper calibration of a machine tool, setup errors and a process plan which is not designed optimally. For the multilateral machining of the complex, precise parts of machines, a process plan should include, before and during the process, coordinate measurements by means of a touch probe in order to verify previously made surfaces or to determine accurately the position and orientation of a local coordinate system. The uncertainty of these measurements is connected with the estimate precision of performing the manufactured parts. This paper presents a tool devised for determining the uncertainty of the results of coordinate measurements by a simulation method, which is also useful at the stage of machine tool calibration. A basis of this method is a bipartite graph with a tree structure. Transitions in the graph constitute a set of elementary measurement activities and analytical activities which determine the uncertainty of the position and orientation of respective geometric features and abstract objects. Based on the results of the conducted simulation tests it is possible to build analytical models for the rapid determination of measurement uncertainty. The tool devised is aimed at vector dimensioning and therefore it enables simple extension, including integration with geometric dimensioning and tolerancing. This paper includes an example of applying the method devised, which confirms its practicability. [ABSTRACT FROM AUTHOR]

Ultrasonic thickness measurement depends on the capability of the equipment and its operating characteristics, as well as on the auxiliary means used to adjust the system and analyse the obtained results. The characteristics of the ultrasonic device commonly used as a flaw detector are crucial for achieving accurate and precise results and are very important for the reliability of the results obtained in the measurement process, especially in production systems. This article aims to determine the quantitative variations in thickness caused by influencing parameters of the ultrasonic device and chosen ultrasonic probe, their quantification of interactions, and the significance of their influence on the accuracy and precision of the results. In the experimental part of the research, a factorial plan of the experiment was carried out to determine the influence of the ultrasonic device and the type of ultrasonic probe on the variability of the results of the ultrasonic thickness measurement. The parameters of the ultrasonic device and probes were analysed, and the experimental plan for developing the regression model was elaborated. The response surface methodology was applied, and the in-service measurement process was simulated using Monte Carlo simulation. [ABSTRACT FROM AUTHOR]

This article investigated the charge and discharge management structure of electric vehicles (EVs) in intelligent parking lots (IPLs). It seems that with the expansion of renewable energy sources (RESs) as clean energy and investigation of the effects of EVs on the operation and planning of future distribution networks around the way EVs exchange energy with each other and the upstream network operator, RESs such as solar and wind sources, along with hydrogen storage are essential. Therefore, a new stochastic multi‐scenario approach for charge/discharge management of EVs parked in IPL was proposed, in which a newly developed model for the IPL with a hydrogen storage system (HSS) consisting of a fuel cell, an electrolyzer, and a hydrogen storage tank was presented. In the proposed model, the constraints of upstream network and power balance constraints, with the operating constraints related to the IPL, including EVs, renewable energy sources, and the hydrogen storage system, were formulated as the most important objectives of the optimization problem. The optimization algorithm, Competitive Swarm Optimizer (CSO), was formulated for implementation, and its results were compared with those of the PSO and GWO algorithms. The CSO must handle a variety of practical, large‐scale optimization problems. Based on the obtained results, the excess energy purchased from the upstream network or renewable sources was used as hydrogen storage for consumption during peak hours. As expected, the technical constraints and financial goals of the system were met, and the proposed system was evaluated on a 33‐bus network. As the expected benefits will be the most beneficial with the presence of renewable sources, the final profit will be reduced by taking into account uncertainty for charge/discharge management in EVs such as the uncertainty of electric load, market price, wind turbine, and photovoltaic cell sources. Nonetheless, the profit obtained from renewable resources is preferable to losses resulting from the uncertainty of the system, and according to expectation, the performance of the system for managing the optimal charging and discharging of EVs in the IPL will be acceptable with the maximum profit for the grid. [ABSTRACT FROM AUTHOR]

This paper investigates the significant factors influencing the measurement uncertainty of 3D laser scanners, an essential tool in industrial contexts for swiftly and accurately analysing complex geometric objects. Through a designed experimental study, parameters such as object size, surface texture, scanner resolution, and ambient light intensity were systematically varied to assess their impact. The results demonstrate that nominal shaft diameter, ambient light intensity, surface finish of the shaft, scan resolution, and the interaction between surface finish and resolution significantly affect repeatability. An empirical model was developed to predict repeatability in shaft diameter measurements. Additionally, the exploration of developer coating revealed its pivotal role in minimising errors stemming from reflective surfaces, underscoring its importance in ensuring measurement reliability. The main contribution of the paper belongs to the knowledge and practice of 3D laser scanning by offering practical recommendations and guidelines. [ABSTRACT FROM AUTHOR]

Automated sorption balances are widely used for characterizing the interaction of water vapor with hygroscopic materials. These instruments provide an efficient way to collect sorption isotherm data and kinetic data. A typical method for defining equilibrium after a step change in relative humidity (RH) is using a particular threshold value for the rate of change in mass with time. Recent studies indicate that commonly used threshold values yield substantial errors and that further measurements are needed at extended hold times as a basis to assess the accuracy of abbreviated equilibration criteria. However, the mass measurement accuracy at extended times depends on the operational stability of the instrument. Published data on the stability of automated sorption balances are rare. An interlaboratory study was undertaken to investigate equilibration criteria for automated sorption balances. This paper focuses on the mass, temperature, and RH stability and includes data from 25 laboratories throughout the world. An initial target for instrument mass stability was met on the first attempt in many cases, but several instruments were found to have unexpectedly large instabilities. The sources of these instabilities were investigated and greatly reduced. This paper highlights the importance of verifying operational mass stability of automated sorption balances, gives a method to perform stability checks, and provides guidance on identifying and correcting common sources of mass instability. [ABSTRACT FROM AUTHOR]

Coordinate measuring machines are widely used in the industrial field due to their ease of automation. However, estimating the measurement uncertainty is a delicate task, especially when controlling for deviation, given the large number of factors that influence the measurement. A precise estimate of the uncertainty is crucial to avoid incorrect conformity assessments. The purpose of this study is to control geometrical-form tolerance specifications, taking into consideration their associated uncertainty. A surface fitting model based on the least squares criterion is proposed, allowing one to obtain the variance–covariance matrix by iterative calculation according to the Levenberg–Marquard optimization method. The form deviation is then evaluated following the Geometrical Product Specifications (GPS) Standard, and its associated uncertainty is estimated using the guide to the expression of uncertainty in measurement (GUM) propagation of the uncertainty law. Finally, the conformity assessment is performed based on the measured deviation and its associated uncertainty. Different results for the measurement of straightness, flatness, circularity, roundness, and cylindricity are presented and detailed. This model is thereafter validated by a Monte Carlo simulation, and interlaboratory comparisons of the obtained results were performed, which showed satisfactory outcome. This contribution is of great use to manufacturing companies and metrology laboratories, allowing them to meet the normative guidelines, which stipulates that each measurement result must be accompanied by its associated uncertainty. [ABSTRACT FROM AUTHOR]

The accurate measurement of spindle errors, especially quasi-static errors, is one of the key issues for the analysis and compensation of machine tool thermal errors in machining accuracy. To quantitatively analyze the influence of the measurement system's own drift on the measurement results, a drifted uncertainty evaluation method of the precision instrument considering the time drift coefficient is proposed. This study also produced a high-precision compact spindle error measurement device (with a displacement measurement error of less than ±1.33 μm and an angular measurement error of less than ±1.42 arcsecs) as the research object to verify the proposed drift uncertainty evaluation method. A method for evaluating the drift uncertainty of the measurement system is proposed to quantitatively evaluate the system error and drift uncertainty of the measurement device. Experiments show that the drift uncertainty evaluation method proposed in this paper is more suitable for evaluating the uncertainty changes in measurement instruments during long-term measurements compared to traditional methods. [ABSTRACT FROM AUTHOR]

A prerequisite for the recycling of mineral wool is information about the type of material, that is, whether it is glass wool or rock wool. As mineral wool produced before the year 2000 can be potentially carcinogenic, it is furthermore important to distinguish between “old” and “new” wool when handling the material. Based on VDI 3492, it is possible to determine the material and, in the case of rock wool, the age by analyzing the mass fractions of eight oxides, which are the main components of mineral wool. This study presents the X‐ray fluorescence (XRF) analyses of 141 man‐made mineral fibers collected in Germany. Only in a few cases it was not possible to clearly assign the material type. In contrast, the identification of “old” and “new” rock wool posed a challenge as there were many borderline samples. Based on the available data, a chemometric model was developed that can classify “old” and “new” RW with a sensitivity of 93% and 89% and with a specificity of 100% in both cases. However, care must be taken when oxide contents are close to the specification limits. The reason for this mainly lies in the overlapping intervals of key oxides as suggested by VDI 3492, and, to a lesser extent, in the uncertainties typically occurring in the XRF‐based analysis of oxides. With this study, a comprehensive collection and evaluation of XRF data on mineral wool is made available, which can serve as a reference database for future users. [ABSTRACT FROM AUTHOR]

Copyright of Technisches Messen is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Wu and Browne (Psychometrika 80(3):571–600, 2015. https://doi.org/10.1007/s11336-015-9451-3; henceforth W &B) introduced the notion of adventitious error to explicitly take into account approximate goodness of fit of covariance structure models (CSMs). Adventitious error supposes that observed covariance matrices are not directly sampled from a theoretical population covariance matrix but from an operational population covariance matrix. This operational matrix is randomly distorted from the theoretical matrix due to differences in study implementations. W &B showed how adventitious error is linked to the root mean square error of approximation (RMSEA) and how the standard errors (SEs) of parameter estimates are augmented. Our contribution is to consider adventitious error as a general phenomenon and to illustrate its consequences. Using simulations, we illustrate that its impact on SEs can be generalized to pairwise relations between variables beyond the CSM context. Using derivations, we conjecture that heterogeneity of effect sizes across studies and overestimation of statistical power can both be interpreted as stemming from adventitious error. We also show that adventitious error, if it occurs, has an impact on the uncertainty of composite measurement outcomes such as factor scores and summed scores. The results of a simulation study show that the impact on measurement uncertainty is rather small although larger for factor scores than for summed scores. Adventitious error is an assumption about the data generating mechanism; the notion offers a statistical framework for understanding a broad range of phenomena, including approximate fit, varying research findings, heterogeneity of effects, and overestimates of power. [ABSTRACT FROM AUTHOR]

This study reports the improvement and validation of a colorimetric method to quantify polysorbates (20, 60, 65, and 80) in food by measuring absorbance at 620 nm using ultraviolet–visible spectrophotometry. The method was validated for linearity, limit of detection (LOD), limit of quantitation (LOQ), precision, accuracy, and measurement uncertainty. The coefficient of determination was linear (r2 ≥ 0.9991) over the measured concentration range of 50–1000 mg/L. The LOD and LOQ were 2.3–4.9 and 7.0–15.0 mg/kg, respectively. Intra-day and inter-day accuracy and precision were 91.9–104.1% and 0.1–1.1% RSD, and 91.6–103.8% and 0.4–5.0% RSD, respectively. The result of inter-laboratory recovery was 90.9–99.8% and the measurement uncertainty was < 16% with the compliance of the CODEX recommendation. Sauce, bread, whipped cream, rice cake, ice cream, and various other polysorbate-labeled food products (n = 229, detection range; N.D.–16,442.3 mg/kg) distributed in Korea were analyzed to confirm the applicability of the analytical method. [ABSTRACT FROM AUTHOR]

The depth measurement scale of the hardness test must be verified with an accuracy of 0.0001 mm. A novel optical setup is designed and developed using a flat mirror interferometer and indigenously fabricated fixtures to calibrate a Rockwell tester. One needs to repeatedly move and position the indenter of the machine to the pre-decided scale markings for calibrating the displacement to achieve the recommended accuracy. Usually, the spindle of the Rockwell tester cannot be precisely moved to a desirable position. To avert this hurdle, the measurements are taken in the time-based mode of a commercial displacement measuring laser interferometer. A new algorithm is devised to remove the unwanted readings from these time-based measurements. The deviations of the depth measuring system of the Rockwell tester are determined by applying the proposed algorithm. Further, the uncertainty of measurement associated with the displacement of the Rockwell tester is estimated. [ABSTRACT FROM AUTHOR]

Abstract This article investigated the charge and discharge management structure of electric vehicles (EVs) in intelligent parking lots (IPLs). It seems that with the expansion of renewable energy sources (RESs) as clean energy and investigation of the effects of EVs on the operation and planning of future distribution networks around the way EVs exchange energy with each other and the upstream network operator, RESs such as solar and wind sources, along with hydrogen storage are essential. Therefore, a new stochastic multi‐scenario approach for charge/discharge management of EVs parked in IPL was proposed, in which a newly developed model for the IPL with a hydrogen storage system (HSS) consisting of a fuel cell, an electrolyzer, and a hydrogen storage tank was presented. In the proposed model, the constraints of upstream network and power balance constraints, with the operating constraints related to the IPL, including EVs, renewable energy sources, and the hydrogen storage system, were formulated as the most important objectives of the optimization problem. The optimization algorithm, Competitive Swarm Optimizer (CSO), was formulated for implementation, and its results were compared with those of the PSO and GWO algorithms. The CSO must handle a variety of practical, large‐scale optimization problems. Based on the obtained results, the excess energy purchased from the upstream network or renewable sources was used as hydrogen storage for consumption during peak hours. As expected, the technical constraints and financial goals of the system were met, and the proposed system was evaluated on a 33‐bus network. As the expected benefits will be the most beneficial with the presence of renewable sources, the final profit will be reduced by taking into account uncertainty for charge/discharge management in EVs such as the uncertainty of electric load, market price, wind turbine, and photovoltaic cell sources. Nonetheless, the profit obtained from renewable resources is preferable to losses resulting from the uncertainty of the system, and according to expectation, the performance of the system for managing the optimal charging and discharging of EVs in the IPL will be acceptable with the maximum profit for the grid.

The essential source of errors in machining on five-axis milling centres are errors caused by the improper calibration of a machine tool, setup errors and a process plan which is not designed optimally. For the multilateral machining of the complex, precise parts of machines, a process plan should include, before and during the process, coordinate measurements by means of a touch probe in order to verify previously made surfaces or to determine accurately the position and orientation of a local coordinate system. The uncertainty of these measurements is connected with the estimate precision of performing the manufactured parts. This paper presents a tool devised for determining the uncertainty of the results of coordinate measurements by a simulation method, which is also useful at the stage of machine tool calibration. A basis of this method is a bipartite graph with a tree structure. Transitions in the graph constitute a set of elementary measurement activities and analytical activities which determine the uncertainty of the position and orientation of respective geometric features and abstract objects. Based on the results of the conducted simulation tests it is possible to build analytical models for the rapid determination of measurement uncertainty. The tool devised is aimed at vector dimensioning and therefore it enables simple extension, including integration with geometric dimensioning and tolerancing. This paper includes an example of applying the method devised, which confirms its practicability.

The problem of increasing the reliability of uncertainty estimation of measurement results is considered. The purpose of this work was to justify the application of the process approach to the formation of the algorithm of uncertainty estimation on the basis of morphological analysis. It is theoretically substantiated that from the standpoint of the system approach to achieving an acceptable degree of reliability of measurement uncertainty estimates it is necessary to implement a process approach to the formation of the estimation method as an algorithm of actions. The main stages of the estimation process are defined. It is established that each stage of the estimation process can be realized by alternative methods. The morphological box method as a realization of morphological analysis is proposed as a basis for its solution. A morphological box design of the uncertainty estimation process with an open architecture is presented, based only on commonly accepted methods and approaches for realizing each step of the process. Two aspects of the application of the morphological box method are identified. On the one hand, the morphological box allows to form an algorithm of the uncertainty assessment process, maximally acceptable for the laboratory conditions, as a combination of process steps, based on the task at hand, combining different variants of realization of these steps. On the other hand, the morphological box acts as a tool for development of new methods of realization of various stages of the uncertainty assessment process. Examples of using the morphological box method to develop alternative algorithms of the uncertainty estimation process of the same measurement method and to develop new methods of realization of different stages of the estimation process are considered.

In this study, the uncertainty of measurement paths was estimated using selected statistical methods. Specifically, temperature measurements obtained from contact temperature sensors used in a heat transfer test section were investigated. The experiments utilized a drywell temperature calibrator, thermoelements (types K, J, N, and T), and a data acquisition station. Additionally, a certified Pt-100 resistance sensor connected to the temperature meter was considered during measurements. The temperature range for the selected measurement points was 0.3 to 100 °C, covering both increasing and decreasing temperatures. To calculate the expanded uncertainty, both the uncertainty propagation method and the Monte Carlo method were employed. The results were analyzed and found to be similar.

High-resolution multi-channel digitizers are used extensively for precision low voltage measurements in numerous applications and allow the simultaneous measurement of voltage magnitude ratio and phase difference between two different waveforms in power system applications. Delta–sigma-based analog-to-digital conversion enables the use of sampling frequencies in the range of megahertz, which provides accurate measurement bandwidths for transformed high-frequency, high-voltage signals. With the increased use of power electronic converters contributing to high-frequency harmonic emissions in power systems, there is a growing interest in developing calibration systems to measure voltage ratio and phase difference of distorted fundamental frequency waveforms consisting of superimposed, high-frequency harmonics. However, information regarding the accuracy of the high-resolution digitizers in the measurement of distorted voltage waveforms is limited as characterization is typically performed under sinusoidal voltage waveform conditions. This paper presents the details of the accuracy characterization of a 24-bit resolution digitizer under both sinusoidal and distorted waveform conditions for measuring complex voltage ratio and phase error for frequencies up to 10 kHz. The detailed experimental results and the measurement uncertainty evaluations show that increased voltage ratio and phase difference errors should be allocated when these high-resolution digitizers are used to measure distorted voltage waveforms. The estimated expanded uncertainties of complex voltage ratio measurement and phase error measurement for harmonic frequencies up to 10 kHz are ±260 ppm and ±100 µrad, respectively.

Optical current sensors have been developed and improved over the past few decades, and they have been increasingly employed in power systems, including smart and high-voltage grids. This is due to their many advantages over conventional electromagnetic current sensors, such as reduced size and weight, greater operational safety, and electromagnetic immunity. Like any measuring instrument or system, their quality and reliability are associated with measurement uncertainty, which quantifies their precision. This measurement uncertainty depends on a series of influencing quantities, such as the wavelength of light used in the sensor, the birefringence of the optical material used in the construction of the sensor, and environmental conditions, such as temperature and vibration. This article presents a review of the main influences that affect the quality and performance of optical current sensors and how these influences can be used to estimate measurement uncertainty. The main objective is to serve as a guide or reference for the identification and evaluation of uncertainty sources in optical current sensors used in power systems. [ABSTRACT FROM AUTHOR]

Classification systems based on machine learning (ML) models, critical in predictive maintenance and fault diagnosis, are subject to an error rate that can pose significant risks, such as unnecessary downtime due to false alarms. Propagating the uncertainty of input data through the model can define confidence bands to determine whether an input is classifiable, preferring to indicate a result of unclassifiability rather than misclassification. This study presents an electrical fault diagnosis system on asynchronous motors using an artificial neural network (ANN) model trained with vibration measurements. It is shown how vibration analysis can be effectively employed to detect and locate motor malfunctions, helping reduce downtime, improve process control and lower maintenance costs. In addition, measurement uncertainty information is introduced to increase the reliability of the diagnosis system, ensuring more accurate and preventive decisions. [ABSTRACT FROM AUTHOR]

Micro-Computed Tomography (µCT) systems are used for examining the internal structures of various objects, such as material samples, manufactured parts, and natural objects. Resolving fine details or performing accurate geometric measurements in the voxel data critically depends on the precise calibration of the µCT systems geometry. This paper presents a calibration method for µCT systems using projections of a calibration phantom, where the coordinates of the phantom are initially unknown. The approach involves detecting and tracking steel ball bearings and adjusting the unknown system geometry parameters using non-linear least squares optimization. Multiple geometric models are tested to verify their suitability for a self-calibration approach. The implementation is tested using a calibration phantom captured at different magnifications. The results demonstrate the system's capability to determine the geometry model parameters with a remaining error on the detector between 0.27 px and 0.18 px. Systematic errors that remain after calibration, as well as changing parameters due to system instabilities, are investigated. The source code of this work is published to enable further research. [ABSTRACT FROM AUTHOR]

The usage of liquefied hydrogen (LH 2) is growing fast as the EU aims to be climate-neutral by 2050. Therefore, reliable and consistent measurements of LH 2 amounts (as determined by flow meters) will become increasingly important for custody transfers. Reliability and consistency of measurements is established from calibration. Due to the lack of facilities being able to calibrate flow meters directly with LH 2 as calibration fluid, the question arises whether the measurement error of the calibration performed on a different fluid and different process conditions are representative for the errors when measuring LH 2. An on-site calibration of two turbine meters measuring LH 2 flow was performed. A Coriolis mass flow meter calibrated on water was used as a reference in conjunction with a dedicated flow meter model, which was validated by a directly SI-traceable calibration on liquefied natural gas. LH 2 flow rates were within 1000 kg/h and 3000 kg/h, which are relevant to hydrogen transport by LH 2 trailers. The analysis of the measurement data reveal errors on totalized mass ranging from 2.0 % to 2.9 % with a total calibration uncertainty of 1.3 % (k = 2), where the main uncertainty source was identified as the on-site density estimate necessary to convert the volume flow measurements into mass flow measurements. The results indicate the need for reliable and accurate temperature measurements (the latter allowing for an accurate density estimate), so that volume based and mass based amount measurements can be compared with smaller uncertainties. • Reliable measurements of liquefied hydrogen amounts will be crucial for custody transfer. • Direct calibration of flow meters on liquefied hydrogen is currently not possible. • Novel results of liquefied hydrogen flow measurement of an on-site calibration are presented. • The analysis reveals errors between 2.0 % and 2.9 % with an uncertainty of 1.3 % (coverage factor = 2). • The main uncertainty source was identified as the on-site density estimate. [ABSTRACT FROM AUTHOR]

Most wet-type multi-path ultrasonic flowmeters have their measurement accuracy rate deteriorate as the flow rate is decreased. Curve-fitting on the characteristics of ultrasonic flowmeters is essential to improve their measurement accuracy rate. This hinders their use as transfer standards in inter-laboratory comparisons for water flow metrology. A breakthrough to enhance the measurement accuracy rate of ultrasonic flowmeters is needed. This study suggests that the concept of near-wall flow velocity should enhance the characteristics of ultrasonic flowmeters. As a result, repeatability can be improved as low as ±0.02 %, which should be suitable to be used as transfer standards. Two main points of using the near-wall flow velocity for ultrasonic flowmeters are emphasized. One is a formula to describe the near-wall flow velocity as a function of both Reynolds number and surface roughness. The other is the results of comparison calibrations between two national metrology institutes, which can support measurement equivalence. In particular, the number of equivalence is less than one (∣En∣ ≤ 1), and the inconclusiveness parameter is less than two (ucomp/ubase ≤ 2) if the near-wall flow velocity is applied for ultrasonic flowmeters. This implies that the ultrasonic flowmeters could be used as transfer standards for the forthcoming inter-laboratory comparisons. [ABSTRACT FROM AUTHOR]

To improve the accuracy of in situ measurement of the standard volumes of pipe provers and to shorten the traceability chain, a new method of in situ pipe prover volume measurement was developed alongside a supporting measurement device. This method is based on the geometric dimension approach, which measures the inner diameter and length of a pipe prover to calculate its volume. For inner diameter measurement, a three-probe inner-diameter algorithm model was established. This model was calibrated using a standard ring gauge of Φ313 mm, with the parameters calculated through fitting. Another standard ring gauge of Φ320 mm was used to verify the inner diameters determined by the algorithmic model. A laser interferometer was employed for the segmented measurement of the pipe prover length. The comprehensive measurement system was then used for in situ measurement of the standard pipe prover. The newly developed system achieved an expanded uncertainty of 0.012% (k = 2) in volume measurement, with the deviation between the measured and nominal pipe prover volumes being merely 0.007%. These results demonstrate that the proposed in situ measurement method offers ultra-high-precision measurement capabilities. [ABSTRACT FROM AUTHOR]

Traditionally, for indoor radon testing, predominantly passive measurements have been used, typically applying the solid-state alpha track-etch method for long-term and the charcoal method for short-term measurements. However, increasingly, affordable consumer-grade active monitors have become available in the last few years, which can generate a concentration time series of an almost arbitrary duration. Firstly, we argue that consumer-grade monitors can well be used for quality-assured indoor radon assessment and consequent reliable decisions. Secondly, we discuss the requirements of quality assurance, which actually allow for reliable decision-making. In particular, as part of a rational strategy, we discuss how to interpret measurement results from low-cost active monitors with high and low sensitivity with respect to deciding on conformity with reference levels that are the annual average concentration of indoor radon. Rigorous analysis shows that temporal variations in radon are a major component of the uncertainty in decision-making, the reliability of which is practically independent of monitor sensitivity. Manufacturers of low-cost radon monitors already provide sufficient reliability and quality of calibration for their devices, which can be used by both professional inspectors and the general public. Therefore, within the suggested measurement strategy and metrologically assured criteria, we only propose to clarify the set and values of the key metrological characteristics of radon monitors as well as to upgrade user-friendly online tools. By implementing clear metrological requirements as well as the rational measurement strategy for the reliable conformity assessment of a room (building) with radon safety requirements, we anticipate significant reductions in testing costs, increased accessibility, and enhanced quality assurance and control (QA/QC) in indoor radon measurements. [ABSTRACT FROM AUTHOR]

The upcoming Euro 7 vehicle exhaust emissions regulation includes particle number (PN) limits for all vehicles, not only those with direct fuel injection. It also sets the lower detection particle size of the PN methodology to 10 nm from 23 nm. Recently, a commercial diffusion charger-based PEMS added the possibility of switching the lower size between 23 nm and 10 nm. In this study, we assessed the dual PEMS in the calibration laboratory using diffusion flame soot or spark discharge graphite particles following the regulated procedures. Furthermore, we compared the dual PEMS with a laboratory grade system (LABS) using soot, graphite, and vehicle exhaust particles. To put the results into perspective, we added comparisons (validations) of two additional 23 nm PEMSs with LABSs over a three-year period. The results showed that the differences of the 23 nm PEMSs remained the same (around 35% underestimation) over the years and were similar to the dual PEMS. This difference is still well within the permissible tolerance from the regulation (50%). We argued that the reason is the calibration material used by the manufacturer (spark discharge graphite). We demonstrated that calibrating with combustion soot could reduce the differences. The 10 nm PEMS gave similar results but with much smaller differences, indicating that the calibration material is of less importance for the Euro 7 step. The results showed that the measurement uncertainty has not increased but rather decreased for the specific PEMS switching from 23 nm to 10 nm. [ABSTRACT FROM AUTHOR]

Psychometrics is historically grounded in the study of individual differences. Consequently, common metrics such as quantitative validity and reliability require between-person variance in a psychological variable to be meaningful. Experimental psychology, in contrast, deals with variance between treatments, and experiments often strive to minimise within-group person variance. In this article, I ask whether and how psychometric evaluation can be performed in experimental psychology. A commonly used strategy is to harness between-person variance in the treatment effect. Using simulated data, I show that this approach can be misleading when between-person variance is low, and in the face of methods variance. I argue that this situation is common in experimental psychology, because low between-person variance is desirable, and because methods variance is no more problematic in experimental settings than any other source of between-person variance. By relating validity and reliability with the corresponding concepts in measurement science outside psychology, I show how experiment-based calibration can serve to compare the psychometric quality of different measurement methods in experimental psychology. [ABSTRACT FROM AUTHOR]

Copyright of Nuclear Safety is the property of Nuclear & Radiation Safety Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The concept of uncertainty in an isotopic analysis is not uniform in the scientific community worldwide and can compromise the risk of false compliance assessment applied to carbon isotopic analyses in natural gas exploratory evaluation. In this work, we demonstrated a way to calculate one of the main sources of this uncertainty, which is underestimated in most studies focusing on gas analysis: the δ13C calculation itself is primarily based on the raw analytical data. The carbon isotopic composition of methane, ethane, propane, and CO2 was measured. After a detailed mathematical treatment, the corresponding expanded uncertainties for each analyte were calculated. Next, for the systematic isotopic characterization of the two gas standards, we calculated the standard uncertainty, intermediary precision, combined standard uncertainty, and finally, the expanded uncertainty for methane, ethane, propane, and CO2. We have found an expanded uncertainty value of 1.8‰ for all compounds, except for propane, where a value of 1.6‰ was obtained. The expanded uncertainty values calculated with the approach shown in this study reveal that the error arising from the application of delta calculation algorithms cannot be neglected, and the obtained values are higher than 0.5‰, usually considered as the accepted uncertainty associated with the GC-IRMS analyses. Finally, based on the use of uncertainty information to evaluate the risk of false compliance, the lower and upper acceptance limits for the carbon isotopic analysis of methane in natural gas are calculated, considering the exploratory limits between −55‰ and −50‰: (i) for the underestimated current uncertainty of 0.5‰, the lower and upper acceptance limits, respectively, are −54.6‰ and −50.4‰; and (ii) for the proposed realistic uncertainty of 1.8‰, the lower and upper acceptance limits would be more restrictive; i.e., −53.5‰ and −51.5‰, respectively. [ABSTRACT FROM AUTHOR]

Metrology is the science of measurement and its applications, whereas biometrology is the science of biological measurement and its applications. Biometrology aims to achieve accuracy and consistency of biological measurements by focusing on the development of metrological traceability, biological reference measurement procedures, and reference materials. Irreproducibility of biological and multi-omics research results from different laboratories, platforms, and analysis methods is hampering the translation of research into clinical uses and can often be attributed to the lack of biologists' attention to the general principles of metrology. In this paper, the progresses of biometrology including metrology on nucleic acid, protein, and cell measurements and its impacts on the improvement of reliability and comparability in biological research are reviewed. Challenges in obtaining more reliable biological and multi-omics measurements due to the lack of primary reference measurement procedures and new standards for biological reference materials faced by biometrology are discussed. In the future, in addition to establishing reliable reference measurement procedures, developing reference materials from single or multiple parameters to multi-omics scale should be emphasized. Thinking in way of biometrology is warranted for facilitating the translation of high-throughput omics research into clinical practices. [ABSTRACT FROM AUTHOR]

Analytical performance specifications (APS) are typically established through one of three models: (i) outcome studies, (ii) biological variation (BV), or (iii) state-of-the-art. Presently, The APS can, for most measurands that have a stable concentration, be based on BV. BV based APS, defined for imprecision, bias, total allowable error and allowable measurement uncertainty, are applied to many different processes in the laboratory. When calculating APS, it is important to consider the different APS formulae, for what setting they are to be applied and if they are suitable for the intended purpose. In this opinion paper, we elucidate the background, limitations, strengths, and potential intended applications of the different BV based APS formulas. When using BV data to set APS, it is important to consider that all formulae are contingent on accurate and relevant BV estimates. During the last decade, efficient procedures have been established to obtain reliable BV estimates that are presented in the EFLM biological variation database. The database publishes detailed BV data for numerous measurands, global BV estimates derived from meta-analysis of quality-assured studies of similar study design and automatic calculation of BV based APS. [ABSTRACT FROM AUTHOR]

This document discusses the concept of analytical performance specifications (APS) in laboratory medicine. It provides an overview of previous conferences and consensus documents on setting APS, including the 2014 EFLM Strategic Conference. The 2023 CELME conference aimed to explore the three models from the Milan conference and offer practical recommendations for their application. The document emphasizes the importance of APS in ensuring harmonized medical laboratory results for patient care. It also discusses the challenges in determining measurement uncertainty and the need for education on APS usage. The document concludes by highlighting important questions for further consideration, such as the creation of a single database for APS and the intended use and aspirational nature of APS. [Extracted from the article]

In addition to the correct implementation of calibration traceability, the definition and fulfillment of maximum allowable measurement uncertainty (MAU) are essential in assuring that laboratory measurements are clinically usable. Across the entire calibration hierarchy, three major contributors to the measurement uncertainty (MU) budget are identified, starting with the higher-order reference providers, extending through the in vitro diagnostic (IVD) manufacturers and their processes for assigning calibrator values, and ending with medical laboratories generating the random variability of results reported to clinicians. To understand if it is possible to achieve MAU and, consequently, to fix the possible drawbacks, the definition of combined MU budget limits across the entire calibration hierarchy has a central role. In particular, quality specifications for MU of reference and commercial calibrator materials should be defined according to the MAU on clinical samples. All involved stakeholders (i.e., higher-order reference providers, IVD manufacturers, medical laboratories) should be prepared to improve their performance whenever the clinical application of the test is made questionable by the failure to achieve MAU. [ABSTRACT FROM AUTHOR]

To be accurate and equivalent among assays, laboratory results should be traceable to higher-order references and their quality should fulfill maximum allowable measurement uncertainty (MU) as defined to fit the intended clinical use. Accordingly, laboratory professionals should estimate and validate MU of performed tests using appropriate analytical performance specifications (APS). Current consensus supports the derivation of APS by using one of the three models established by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Strategic Conference held in Milan in 2014. It is recognized that some models are better suited for certain measurands than for others and the attention should be primarily directed towards their biological and clinical characteristics. Among others, model 3 should reflect the state of the art of the measurements that can be defined as the best analytical performance that is technically achievable. Taking serum C-reactive protein and ferritin as examples, here we describe the theoretical premises and the experimental protocol to be used to derive APS for MU when a measurand is allocated to this model. Although the model lacks a direct relationship with clinical outcomes, useful information about the in vitro diagnostic medical device performance and the average quality of provided results may be obtained. [ABSTRACT FROM AUTHOR]

ISO 15189 requires laboratories to estimate the uncertainty of their quantitative measurements and to maintain them within relevant performance specifications. Furthermore, it refers to ISO TS 20914 for instructions on how to estimate the uncertainty and what to take into consideration when communicating uncertainty of measurement with requesting clinicians. These instructions include the responsibility of laboratories to verify that bias is not larger than medically significant. If estimated to be larger than acceptable, such bias first needs to be eliminated or (temporarily) corrected for. In the latter case, the uncertainty of such correction becomes part of the estimation of the total measurement uncertainty. If small enough to be acceptable, bias becomes part of the long term within laboratory random variation. Sources of possible bias are (not limited to) changes in reagent or calibrator lot variation or calibration itself. In this paper we clarify how the rationale and mathematics from an EFLM WG ISO/A position paper on allowable between reagent lot variation can be applied to calculate whether bias can be accepted to become part of long-term imprecision. The central point of this rationale is to prevent the risk that requesting clinicians confuse changes in bias with changes in the steady state of their patients. [ABSTRACT FROM AUTHOR]

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In this paper, novel fuzzy observers are designed for a class of nonlinear systems with sampled outputs and unknown measurement noises. Firstly, sufficient conditions are given to ensure that a sampled‐data nonlinear system is ultimately uniformly bounded (UUB). Secondly, an output filtering transformation is taken. Then, an augmented nonlinear system is obtained. The sampled output and the measurement noise are transformed into the state equation of the augmented nonlinear system. Thirdly, an augmented observer is constructed by applying a fuzzy logic system (FLS) to approximate the unknown measurement noise. Sufficient conditions are derived by using a suitable Lyapunov–Krasovskii generalized function, such that the observation error is UUB. Finally, the effectiveness of the proposed method is verified by a numerical simulation example. [ABSTRACT FROM AUTHOR]

Emotion recognition is a critical component of affective computing. Training accurate machine learning models for emotion recognition typically requires a large amount of labeled data. Due to the subtleness and complexity of emotions, multiple evaluators are usually needed for each affective sample to obtain its ground-truth label, which is expensive. To save the labeling cost, this paper proposes an inconsistency-based active learning approach for cross-task transfer between emotion classification and estimation. Affective norms are utilized as prior knowledge to connect the label spaces of categorical and dimensional emotions. Then, the prediction inconsistency on the two tasks for the unlabeled samples is used to guide sample selection in active learning for the target task. Experiments on within-corpus and cross-corpus transfers demonstrated that cross-task inconsistency could be a very valuable metric in active learning. To our knowledge, this is the first work that utilizes prior knowledge on affective norms and data in a different task to facilitate active learning for a new task, even the two tasks are from different datasets. [ABSTRACT FROM AUTHOR]

Water distribution network (WDN) models are a common decision support tool for understanding the behavior and performance of WDNs, aiding in the planning and management of WDN systems. The increasing availability of real-time data has recently promoted the exploration of Data Assimilation (DA) techniques to improve these models. However, flow, pressure and demand data are uncertain, particularly due to sensor characteristics such as precision and noise. An open question is to what extent DA can still improve hydraulic models when the data used to this end is uncertain. This paper proposes a three-step Ensemble Kalman Filter based DA approach for WDNs (3-EnKF-WDN), building on previous approaches, and advancing in two main fronts: the use of extended period simulation, and the use of pressure-dependent demand (PDD) analysis. Different scenarios considering uncertain sensor data, with varied precision and noise, are applied to two networks of different sizes, representative of real-world WDNs. The computational demand of the 3-EnKF-WDN method is also assessed. Results show that increasing sensor's precision and decreasing the noise in state measurements reduce model error, as expected. However, we also found that model errors: 1) are reduced more effectively by using 3-EnKF-WDN than by increasing sensors' precision; 2) are not reduced if certain noise thresholds are surpassed; 3) can be reduced without assimilating demand data if the WDNs are fully monitored with head sensors in all the nodes and flow sensors in all the links. [ABSTRACT FROM AUTHOR]

Copyright of Technisches Messen is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Technisches Messen is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Technisches Messen is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Accurate knowledge of solar radiation data or its estimation is crucial to maximize the benefits derived from the Sun. In this context, many sectors are re-evaluating their investments and plans to increase profit margins in line with sustainable development based on knowledge and estimation of solar radiation. This scenario has drawn the attention of researchers to the estimation and measurement of solar radiation with a low level of error. Various types of models, such as empirical models, time series, artificial intelligence algorithms and hybrid models, for estimating and measuring solar radiation have been continuously developed in the literature. In general, these models require atmospheric, geographical, climatic and historical solar radiation data from a specific region for accurate estimation. Each analysis model has its advantages and disadvantages when it comes to estimating solar radiation and, depending on the model, the results for one region may be better or worse than for another. Furthermore, it has been observed that an input parameter that significantly improves the model's performance in one region can make it difficult to succeed in another. The research gaps, challenges and future directions in terms of solar radiation estimation have substantial impacts, but regardless of the model, in situ measurements and commercially available equipment consistently influence solar radiation calculations and, subsequently, simulations or estimates. This article aims to exemplify, through a case study in a multi-family residential building located in Viana do Castelo, a city in the north of Portugal, the difficulties of capturing the spectrum of radiations that make up the total radiation that reaches the measuring equipment or site. Three pieces of equipment are used—a silicon pyranometer, a thermopile pyranometer and a solar meter—on the same day, in the same place, under the same meteorological conditions and with the same measurement method. It is found that the thermopile pyranometer has superior behavior, as it does not oscillate as much with external factors such as the ambient temperature, which influence the other two pieces of equipment. However, due to the different assumptions of the measurement models, the various components of the measurement site make it difficult to obtain the most accurate and reliable results in most studies. Despite the advantages of each model, measurement models have gained prominence in terms of the ease of use and low operating costs rather than the rigor of their results. [ABSTRACT FROM AUTHOR]

Just a few years after the inception of quantum mechanics, there has been a research program using the nonclassical values of some quasiprobability distributions to delineate the nonclassical aspects of quantum phenomena. In particular, in Kirkwood–Dirac (KD) quasiprobability distribution, the distinctive quantum mechanical feature of noncommutativity which underlies many nonclassical phenomena, manifests in the nonreal values and/or the negative values of the real part. Here, we develop a faithful quantifier of quantum coherence based on the KD nonclassicality which captures simultaneously the nonreality and the negativity of the KD quasiprobability. The KD-nonclassicality coherence thus defined, is upper bounded by the uncertainty of the outcomes of measurement described by a rank-1 orthogonal projection-valued measure (PVM) corresponding to the incoherent orthonormal basis which is quantified by the Tsallis 1 2 -entropy. Moreover, they are identical for pure states so that the KD-nonclassicality coherence for pure state admits a simple closed expression in terms of measurement probabilities. We then use the Maassen–Uffink uncertainty relation for min-entropy and max-entropy to obtain a lower bound for the KD-nonclassicality coherence of a pure state in terms of optimal guessing probability in measurement described by a PVM noncommuting with the incoherent orthonormal basis. We also derive a trade-off relation for the KD-nonclassicality coherences of a pure state relative to a pair of noncommuting orthonormal bases with a state-independent lower bound. Finally, we sketch a variational scheme for a direct estimation of the KD-nonclassicality coherence based on weak value measurement and thereby discuss its relation with quantum contextuality. [ABSTRACT FROM AUTHOR]

The object of research is a three-phase electricity metering unit, which includes a digital meter and measuring current transformers. The reduction of non-technological energy losses is restrained due to the insufficient accuracy of the accounting of electric energy in distribution power networks under a reduced load current of the metering unit. The possibility of representing the dependence of the relative error of electricity measurement on current values by a fuzzy function at reduced load has been confirmed. The boundaries of such a function are approximated with sufficient accuracy by the sum of two exponents, which is explained by its significant nonlinearity in the range of reduced current. The proposed EMRL software allows to estimate the real consumption and the most possible level of underaccounting based on the array of electricity meter readings. The accuracy of estimating by the EMRL the amount of electricity consumed with a probability of 0.7 can be estimated with a relative error not exceeding 2 %. The probability of psychophysical assessments of the accuracy of EMRL «very good» and «good» is at least 0.833. The trend of a significant decrease in the relative value of underaccounting with an increase in the level of electricity consumption was revealed. With a daily consumption of up to 10 kW·h, the amount of underaccounting can reach 18 %, and with a consumption of more than 20 kW·h, it does not exceed 6 %. The adequacy of the results of estimating the amount of consumed electricity at reduced load using the EMRL was confirmed by experimental data at a significance level of 0.05. The software capabilities allow to increase the accuracy of the accounting of electrical energy in distribution networks with a reduced load current of the metering unit. The program can be used as part of automated systems of commercial electricity metering or advanced metering infrastructure to determine the most possible underaccounting due to the operation of metering units at a reduced load [ABSTRACT FROM AUTHOR]

The object of this study is the process of optimizing measurement uncertainty on a coordinate measuring machine (CMM) when inspecting complex geometric surfaces. The problem addressed was insufficient accuracy and efficiency of measurements of complex parts on CMMs under production conditions. A method for optimizing measurement uncertainty has been devised, which includes a mathematical model of the measurement process and an adaptive algorithm for optimizing the control strategy, based on the Monte Carlo method. The model takes into account the geometry of surfaces and CMM characteristics, while the algorithm dynamically adjusts measurement parameters. The results demonstrate a reduction in measurement uncertainty by 15–20 % and a reduction in inspection time by 10–12 % compared to conventional methods. This is achieved by taking into account the specificity of complex surface geometry and an adaptive approach. The uniqueness of the developed method is the ability to automatically adapt to different types of CMMs and measured objects, optimizing the number and location of measurement points, the speed of probe movement, and its contact force with the surface. The method takes into account not only the geometric parameters of objects but also the characteristics of the CMM itself, which allows for high accuracy. The method is particularly effective for parts with complex geometry, in which conventional methods often lead to significant errors. Practical application is possible at machine-building enterprises for quality control of complex parts, especially in serial production. The implementation of the developed method allows for improving product quality and reducing production costs by 8–10 % due to optimization of the control process and reduction of defects. [ABSTRACT FROM AUTHOR]

S-parameters are widely used to detail the scattering parameters of radio frequency (RF) components and microwave circuit modules. The vector network analyzer (VNA) is the most commonly used device for measuring S-parameters. Given the multiple frequency points, complex values, and intricate uncertainty propagation involved, accurately assessing the uncertainty of S-parameter measurements is difficult. In this study, we proposed a new method for assessing S-parameter uncertainty based on the covariance matrices, tracing back to the nominal uncertainty of calibration standards. First, we analyzed the relevant theory of uncertainty assessment using covariance matrices and subsequently deduced the mechanism of Type B uncertainty propagating from calibration standards to error model coefficients and S-parameter measurements to evaluate Type B measurement uncertainty. In this study, a novel measurement system was constructed for measuring grounded coplanar waveguides by using a VNA and calibration standards with 8- and 12-error models. Initially, the model assessed the Type B uncertainty of measuring four S-parameters of a grounded coplanar waveguide. Next, the VNA calibrated with the 12-error model was used to conduct multiple repeated measurements to assess the Type A uncertainty of the grounded coplanar waveguide. Finally, the composite uncertainty was constructed, which demonstrated that the proposed method can be used for assessing the uncertainty of S-parameters. [ABSTRACT FROM AUTHOR]

3D scanners have great potential to boost the efficiency of geometric inspection if their traceability is established by identifying measurement bias and uncertainty. This article introduces a digital twin for a structured-light 3D scanner that provides these two essential measures in a real-time manner. The error quantification starts from iterated scans taken from a CMM-calibrated ball-plate artifact at eight different configurations. The differences between the erroneous scan readings of the artifact's distance features and the corresponding calibrated values in the CMM set give a spatial distribution of the scanner's error. Then, three polynomial functions map the Cartesian coordinates of the scan set onto their counterparts from the CMM set. In this error model, a least-square approach determines the polynomial coefficients. Evaluating the error model for a given point cloud returns a vector field of volumetric errors, which is then followed by error corrections and then GD&T calculations. The uncertainty propagation is pursued through the three steps of model development, error map evaluation, and GD&T analysis. The Monte-Carlo estimations benchmark and validate the GUM framework for the uncertainty associated with the outputs of each step. Experimental verifications of the proposed methodology suggest that the error correction improves the mean and the standard deviation of measurement bias by 50% and 27%, respectively. The uncertainty map provides the coverage probabilities of 62%, 88%, and 96% for the coverage factors of 1, 2, and 3, while the expected theoretical levels of confidence are 68%, 95%, and 100%. • The digital twin provides error maps for scan data as a field of error vectors. • Corrections reduced the error average from −10 to −5 μm and error dispersion by 27%. • Ellipsoidal uncertainty regions grant coverage probabilities close to expected levels. • GUM framework reliably estimates the uncertainty of digital twin outputs. • Fast uncertainty analysis allows using digital twin in real-time in-process metrology. [ABSTRACT FROM AUTHOR]

High-resolution multi-channel digitizers are used extensively for precision low voltage measurements in numerous applications and allow the simultaneous measurement of voltage magnitude ratio and phase difference between two different waveforms in power system applications. Delta–sigma-based analog-to-digital conversion enables the use of sampling frequencies in the range of megahertz, which provides accurate measurement bandwidths for transformed high-frequency, high-voltage signals. With the increased use of power electronic converters contributing to high-frequency harmonic emissions in power systems, there is a growing interest in developing calibration systems to measure voltage ratio and phase difference of distorted fundamental frequency waveforms consisting of superimposed, high-frequency harmonics. However, information regarding the accuracy of the high-resolution digitizers in the measurement of distorted voltage waveforms is limited as characterization is typically performed under sinusoidal voltage waveform conditions. This paper presents the details of the accuracy characterization of a 24-bit resolution digitizer under both sinusoidal and distorted waveform conditions for measuring complex voltage ratio and phase error for frequencies up to 10 kHz. The detailed experimental results and the measurement uncertainty evaluations show that increased voltage ratio and phase difference errors should be allocated when these high-resolution digitizers are used to measure distorted voltage waveforms. The estimated expanded uncertainties of complex voltage ratio measurement and phase error measurement for harmonic frequencies up to 10 kHz are ±260 ppm and ±100 µrad, respectively. [ABSTRACT FROM AUTHOR]

The imperative need to advance the development of more efficient electric motors requires the meticulous measurement of small increments while minimizing the associated uncertainty in dynamometer tests. One of the key variables in such tests is the angular speed, which is typically obtained based on encoder measurements. This paper proposes a systematic measurement uncertainty assessment method based on the Guide to the Expression of Uncertainty for the two most widely used methods for angular speed measurement, namely, the frequency and period methods. In addition, the impact of the angular speed calculation method on the efficiency test uncertainty is assessed using an automatic test rig for electric motors. Our experimental results consider both steady-state and dynamic analyses. The results show that the period measurement method provides measurements with lower uncertainty for the encoders typically used in such test rigs, about 30 times less than the uncertainty determined for the frequency measurement method. Based on these results, the choice of a proper method can drastically decrease the angular speed uncertainty, and consequently the motor efficiency uncertainty, without increasing instrumentation cost. [ABSTRACT FROM AUTHOR]