Journal Description
Metrology
Metrology
is an international, peer-reviewed, open access journal on the science and technology of measurement and metrology, published quarterly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus and other databases.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 28.5 days after submission; acceptance to publication is undertaken in 7.3 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually in the journal.
Latest Articles
Plantar Load System Analysis Using FSR Sensors and Interpolation Methods
Metrology 2024, 4(4), 566-577; https://doi.org/10.3390/metrology4040035 (registering DOI) - 9 Oct 2024
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The foot is considered a wonder of biological engineering due to its structure, formed by bones, ligaments, and tendons that collaborate to ensure stability and mobility. A key area often examined by medical professionals in patients with diabetic feet is the plantar surface,
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The foot is considered a wonder of biological engineering due to its structure, formed by bones, ligaments, and tendons that collaborate to ensure stability and mobility. A key area often examined by medical professionals in patients with diabetic feet is the plantar surface, due to the risk of ulcer development. If left untreated, these ulcers can lead to severe complications, including amputation of the toe, foot, or even the limb. Interpolation methods are used to find areas with overloads in a system of sensor maps that are based on capacitive, load cells, or force-sensitive resistors (FSRs). This manuscript presents the assessment of linear, nearest neighbors, and bicubic methods in comparison with ground truth to calculate the root mean square error (RMSE) in two assessments using a dataset of eight healthy subjects, four men and four women, with an average age of 25 years, height of 1.63 m, and weight of 72 kg with shoe sizes from 7.3 USA using FSR map with 48 sensors. Additionally, this paper describes the conditioning circuit development to implement a plantar surface system that enables interpolating loads on the plantar surface. The proposed system’s results show that the first assessment indicates an RMSE of 0.089, 0.126, and 0.089 for linear, nearest neighbor, and bicubic methods, while the second assessment shows a mean RMSE for linear, nearest neighbor, and bicubic methods of 0.114, 0.159, and 0.112.
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Differential Hall Effect Metrology for Electrical Characterization of Advanced Semiconductor Layers
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Bulent M. Basol and Abhijeet Joshi
Metrology 2024, 4(4), 547-565; https://doi.org/10.3390/metrology4040034 - 2 Oct 2024
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Semiconductor layers employed in fabricating advanced node devices are becoming thinner and their electrical properties are diverging from those established for highly crystalline standards. Since these properties also change as a function of depth within the film, accurate carrier profiling solutions are required.
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Semiconductor layers employed in fabricating advanced node devices are becoming thinner and their electrical properties are diverging from those established for highly crystalline standards. Since these properties also change as a function of depth within the film, accurate carrier profiling solutions are required. The Differential Hall Effect (DHE) technique has the unique capability of measuring mobility and carrier concentration (active carriers) through the depth of a semiconductor film. It comprises making successive sheet resistance and sheet Hall coefficient measurements as the thickness of the electrically active layer at a test region is reduced through successive material removal steps. Difference equations are then used to process the data and plot the desired depth profiles. The fundamentals of DHE were established in 1960s. Recently, the adaption of electrochemical processing for the material removal steps, and the integration of all other functionalities in a Differential Hall Effect Metrology (DHEM) tool, has made this technique more practical and accurate and improved its depth resolution to a sub-nm range. In this contribution, we review the development history of this important technique and present data from recent characterization work carried out on Si, Ge and SiGe layers.
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Using a Multivariate Virtual Experiment for Uncertainty Evaluation with Unknown Variance
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Manuel Marschall, Finn Hughes, Gerd Wübbeler, Gertjan Kok, Marcel van Dijk and Clemens Elster
Metrology 2024, 4(4), 534-546; https://doi.org/10.3390/metrology4040033 - 1 Oct 2024
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Virtual experiments are a digital representation of a real measurement and play a crucial role in modern measurement sciences and metrology. Beyond their common usage as a modeling and validation tool, a virtual experiment may also be employed to perform a parameter sensitivity
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Virtual experiments are a digital representation of a real measurement and play a crucial role in modern measurement sciences and metrology. Beyond their common usage as a modeling and validation tool, a virtual experiment may also be employed to perform a parameter sensitivity analysis or to carry out a measurement uncertainty evaluation. For the latter to be compliant with statistical principles and metrological guidelines, the procedure to obtain an estimate and a corresponding measurement uncertainty requires careful consideration. We employ a Monte Carlo sampling procedure using a virtual experiment that allows one to perform a measurement uncertainty evaluation according to the Monte Carlo approach of JCGM-101 and JCGM-102, two widely applied guidelines for uncertainty evaluation in metrology. We extend and formalize a previously published approach for simple additive models to account for a large class of non-linear virtual experiments and measurement models for multidimensionality of the data and output quantities, and for the case of unknown variance of repeated measurements. With the algorithm developed here, a simple procedure for the evaluation of measurement uncertainty is provided that may be applied in various applications that admit a certain structure for their virtual experiment. Moreover, the measurement model commonly employed for uncertainty evaluation according to JCGM-101 and JCGM-102 is not required for this algorithm, and only evaluations of the virtual experiment are performed to obtain an estimate and an associated uncertainty of the measurand. We demonstrate the efficacy of the developed approach and the effect of the underlying assumptions for a generic polynomial regression example and an example of a simplified coordinate measuring machine and its virtual representation. The results of this work highlight that considerable effort, diligence, and statistical considerations need to be invested to make use of a virtual experiment for uncertainty evaluation in a way that ensures equivalence with the accepted guidelines.
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(This article belongs to the Collection Measurement Uncertainty)
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Navigating Safer Car Routes Based on Measured Car Accidents
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Nazir L. Gandur, Stephen Ekwaro-Osire, Jahan Rasty, Olin Parker and Guilherme Fernandes
Metrology 2024, 4(4), 517-533; https://doi.org/10.3390/metrology4040032 - 1 Oct 2024
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Car accidents, a major US public safety issue, demand precise analysis and predictive models for mitigation. This study asks the following question: Can the safest car routes across the US be determined? The paper analyzes historical data to forecast future accidents and calculates
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Car accidents, a major US public safety issue, demand precise analysis and predictive models for mitigation. This study asks the following question: Can the safest car routes across the US be determined? The paper analyzes historical data to forecast future accidents and calculates the safest route between two locations. The study builds a predictive model utilizing statistical analyses, data mining, and machine learning. A joint probability density function (PDF) is devised to calculate the safest route for risk modeling, factoring in latitude and longitude. The model quantifies accident probabilities in areas and travel routes. Additionally, the safest direction can be determined using the gradient of the joint PDF curve. The predictive model enables policymakers to allocate resources proactively. The safest route selection enables drivers to navigate safer areas and routes, which can reduce the number of accidents. Through its analysis and joint PDF model, this research enriches accident analysis and prevention engineering, potentially fostering safer US roads.
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Open AccessArticle
In Situ Visualization of Inhomogeneities in the Magnetic Properties of Permanent Magnets
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Maximilian Lanz, Gerhard Martinek, Gerhard Schneider and Dagmar Goll
Metrology 2024, 4(3), 506-516; https://doi.org/10.3390/metrology4030031 - 22 Sep 2024
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Irreversible demagnetization processes in high-performance Fe-Nd-B magnets were investigated using a novel test rig. Designed to capture local magnetic field distributions and integral average magnetization in situ, the rig operates under field and temperature conditions similar to those found in electric motors. Validation
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Irreversible demagnetization processes in high-performance Fe-Nd-B magnets were investigated using a novel test rig. Designed to capture local magnetic field distributions and integral average magnetization in situ, the rig operates under field and temperature conditions similar to those found in electric motors. Validation against established techniques such as the hysteresisgraph and Hall mapper confirmed its accuracy. Furthermore, we observed the ability to detect even small variations of less than 2.5% in coercive field strength across the sample volume using field scans. The system significantly reduces measurement times from days to hours, enabling efficient in situ detection of magnetic field distributions during the whole demagnetization process.
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(This article belongs to the Special Issue Advances in Magnetic Measurements)
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Heat Conduction Control Using Deep Q-Learning Approach with Physics-Informed Neural Networks
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Nelson D. Gonçalves and Jhonny de Sá Rodrigues
Metrology 2024, 4(3), 489-505; https://doi.org/10.3390/metrology4030030 - 16 Sep 2024
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As modern systems become more complex, their control strategy no longer relies only on measurement data from probes; it also requires information from mathematical models for non-measurable places. On the other hand, those mathematical models can lead to unbearable computation times due to
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As modern systems become more complex, their control strategy no longer relies only on measurement data from probes; it also requires information from mathematical models for non-measurable places. On the other hand, those mathematical models can lead to unbearable computation times due to their own complexity, making the control process non-viable. To overcome this problem, it is possible to implement any kind of surrogate model that enables the computation of such estimates within an acceptable time frame, which allows for making decisions. Using a Physics-Informed Neural Network as a surrogate model, it is possible to compute the temperature distribution at each time step, replacing the need for running direct numerical simulations. This approach enables the use of a Deep Reinforcement Learning algorithm to train a control strategy. On this work, we considered a one-dimensional heat conduction problem, in which temperature distribution feeds a control system. Such control system has the objective of reacing and maintaining constant temperature value at a specific location of the 1D problem by activating a heat source; the desired location somehow cannot be directly measured so, the PINN approach allows to estimate its temperature with a minimum computational workload. With this approach, the control training becomes much faster without the need of performing numerical simulations or laboratory measurements.
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Comparative Studies of the Measurement Accuracy of Basic Gear Wheel Parameters
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Agata Świerek, Paweł Nowakowski, Lidia Marciniak-Podsadna and Piotr Góral
Metrology 2024, 4(3), 469-488; https://doi.org/10.3390/metrology4030029 - 15 Sep 2024
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This article presents the results of comparative tests of gear wheels based on the contactless and contact measurement methods. Measurements of gear wheels in accuracy classes containing deviations within the range of measurement capabilities of the GOM ATOS II optical scanner are proposed.
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This article presents the results of comparative tests of gear wheels based on the contactless and contact measurement methods. Measurements of gear wheels in accuracy classes containing deviations within the range of measurement capabilities of the GOM ATOS II optical scanner are proposed. Elementary deviations of teeth related to the involute profile were analyzed. In undertaking a non-contact gear measurement using the GOM ATOS II scanner, a new method was developed to extract parameters from the point cloud, which were then used to determine the total deviation of the profile. The results of the measurements obtained using the non-contact method were compared with the results obtained with the contact method using the Wenzel WGT 600 four-axis machine specialized for measuring gear wheels. Measurement uncertainty was also compared. The result of the conducted tests is the comparability of results for gear wheels made in accuracy class 10 according to DIN 3961/62. The proposed non-contact method shows the possibility of using it to measure gear wheels commonly used in agricultural and construction machines. The information obtained from comparing the measurement model and the nominal wheel model provides additional information about surface defects of the part which result from the production and operation process.
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Practical Approaches for Determining the Structural Resolution Capability of X-ray Computed Tomography Measurement Tasks
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Matthias Busch and Tino Hausotte
Metrology 2024, 4(3), 457-468; https://doi.org/10.3390/metrology4030028 - 12 Sep 2024
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The structural resolution describes the ability of a measuring device to detect small structures on the surface of a component or test specimen by means of a quantitative value. However, the structural resolution in the computer tomograph depends on the object and must
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The structural resolution describes the ability of a measuring device to detect small structures on the surface of a component or test specimen by means of a quantitative value. However, the structural resolution in the computer tomograph depends on the object and must therefore be determined separately for each measurement task. The previous approaches to structural resolution determination are only related to test specimens. In this paper, less discrete approaches based on a circular pattern are presented, which can be integrated into the measured component. A voxel-based methodology as well as two surface-based methodologies are described. The investigation results regarding the effect of the component position on the structural resolution are obtained on the basis of real CT measurements. A comparison is also completed with the well-known hourglass method. The results show that the resolution depends on the object being measured, with similar values being obtained for the same object using different methods.
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(This article belongs to the Special Issue Next-Level Surface Metrology—Advances in Sensors, Data Analysis and Simulation)
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Neural Network Approach for Modelling and Compensation of Local Surface-Tilting-Dependent Topography Measurement Errors in Coherence Scanning Interferometry
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Sai Gao, Zhi Li and Uwe Brand
Metrology 2024, 4(3), 446-456; https://doi.org/10.3390/metrology4030027 - 9 Sep 2024
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The topography measurement accuracy of coherence scanning interferometry (CSI) suffers from the local characteristic of micro-structured surfaces, such as local surface slopes. A cylindrical reference artefact made of single-mode fiber with high roundness and low roughness has been proposed in this manuscript to
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The topography measurement accuracy of coherence scanning interferometry (CSI) suffers from the local characteristic of micro-structured surfaces, such as local surface slopes. A cylindrical reference artefact made of single-mode fiber with high roundness and low roughness has been proposed in this manuscript to traceably investigate the surface tilting induced measurement deviations using coherence scanning interferometry with high NA objectives. A feed-forward neural network (FF-NN) is designed and trained to model and thereafter compensate the systematic measurement deviations due to local surface tilting. Experimental results have verified that the FF-NN approach can well enhance the accuracy of the CSI for radius measurement of cylindrical samples up to 0.3%. Further development of the FF-NN for modelling of the measurement errors in CSI due to the optical properties of surfaces including areal roughness is outlined.
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Economical Experimental Device for Evaluating Thermal Conductivity in Construction Materials under Limited Research Funding
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Damien Ali Hamada Fakra, Rijalalaina Rakotosaona, Marie Hanitriniaina Ratsimba, Mino Patricia Randrianarison and Riad Benelmir
Metrology 2024, 4(3), 430-445; https://doi.org/10.3390/metrology4030026 - 30 Aug 2024
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African scientific research faces formidable challenges, particularly with limited access to state-of-the-art measurement instruments. The high cost associated with these devices presents a significant barrier for regional research laboratories, impeding their ability to conduct sophisticated experiments and gather precise data. This predicament not
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African scientific research faces formidable challenges, particularly with limited access to state-of-the-art measurement instruments. The high cost associated with these devices presents a significant barrier for regional research laboratories, impeding their ability to conduct sophisticated experiments and gather precise data. This predicament not only hampers the individual laboratories but also has broader implications for the African scientific community and the advancement of knowledge in developing nations—the financial cost barrier considerably impacts the research quality of these laboratories. Reflection on technical and economical solutions needs to be quickly found to help these countries advance their research. In civil engineering, the thermal conductivity property is the most important measurement for characterizing heat transfer in construction materials. Existing devices (i.e., conductometers) in a laboratory are expensive (approximately EUR 30,000) and unavailable for some African laboratories. This study proposes a new and affordable device to evaluate thermal conductivity in construction materials. The method involves establishing a thermal flux between a heat source (from the Joule effect provided by steel wool where a current is circulating) and a cold source (generated by ice cubes) under steady-state conditions. The development of the cylindrical prototype is based on the comparative flux-meter method outlined in the measuring protocol of the ASTM E1225 standard document. Experiments were conducted on four distinct materials (polystyrene, wood, agglomerated wood, and rigid foam). The results indicate a correct correlation between the experimental values obtained from the newly developed prototype and the reference values found in the literature. For example, concerning the experimental polystyrene study, the detailed case analysis reveals a good correlation, with a deviation of only 4.88%. The percent error found falls within the acceptable range indicated by the standard recommendations of the ASTM E1225 standard, i.e., within 5% acceptable error.
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Geometrical and Dimensional Deviations of Fused Deposition Modelling (FDM) Additive-Manufactured Parts
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Radu Emanuil Petruse, Carmen Simion and Ioan Bondrea
Metrology 2024, 4(3), 411-429; https://doi.org/10.3390/metrology4030025 - 9 Aug 2024
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This research investigates the influence of printing parameters and different materials on the geometrical and dimensional deviations of Fused Deposition Modelling (FDM) additive manufacturing. Using the Taguchi method, experiments with four factors are designed: print layer height, printing material, printing speed, and nozzle
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This research investigates the influence of printing parameters and different materials on the geometrical and dimensional deviations of Fused Deposition Modelling (FDM) additive manufacturing. Using the Taguchi method, experiments with four factors are designed: print layer height, printing material, printing speed, and nozzle size, employing an L9 orthogonal array. Deviations in flatness, perpendicularity, parallelism, cylindricity, spherical form, and surface roughness of 3D-printed parts are evaluated. The results reveal that print speed and nozzle size significantly affect flatness and surface roughness, while layer height and material influence perpendicularity and parallelism deviations. Notably, nozzle size critically impacts cylindricity and spherical form deviations. Our study demonstrates that lower printing speed, smaller nozzle diameter, and reduced layer height are not universally optimal; instead, parameter adjustments based on specific geometrical requirements and part orientation are necessary. These findings are essential for improving the accuracy and quality of FDM-printed parts, supporting their broader application in precision manufacturing industries.
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(This article belongs to the Special Issue Novel Dynamic Measurement Methods and Systems)
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Metrological Analysis with Covariance Features of Micro-Channels Fabricated with a Femtosecond Laser
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Matteo Verdi, Federico Bassi, Luigi Calabrese, Martina Azzolini, Salim Malek, Roberto Battisti, Eleonora Grilli, Fabio Menna, Enrico Gallus and Fabio Remondino
Metrology 2024, 4(3), 398-410; https://doi.org/10.3390/metrology4030024 - 1 Aug 2024
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This study presents an automated methodology for evaluating micro-channels fabricated using a femtosecond laser on stainless steel substrates. We utilize 3D surface topography and metrological analyses to extract geometric features and detect fabrication defects. Standardized samples were analyzed using a light interferometer, and
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This study presents an automated methodology for evaluating micro-channels fabricated using a femtosecond laser on stainless steel substrates. We utilize 3D surface topography and metrological analyses to extract geometric features and detect fabrication defects. Standardized samples were analyzed using a light interferometer, and the resulting data were processed with Principal Component Analysis (PCA) and RANSAC algorithms to derive channel characteristics, such as depth, wall taper, and surface roughness. The proposed method identifies common defects, including bumps and V-defects, which can compromise the functionality of micro-channels. The effectiveness of the approach is validated by comparisons with commercial solutions. This automated procedure aims to enhance the reliability and precision of femtosecond laser micro-milling for industrial applications. The detected defects, combined with fabrication parameters, could be ingested in an AI-based process to optimize fabrication processes.
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(This article belongs to the Special Issue Advances in Optical 3D Metrology)
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An Advanced Synchronized Time Digital Grid Twin Testbed for Relay Misoperation Analysis of Electrical Fault Type Detection Algorithms
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Emilio C. Piesciorovsky, Mathew J. Reno, Maximiliano Ferrari Maglia and Adam K. Summers
Metrology 2024, 4(3), 374-397; https://doi.org/10.3390/metrology4030023 - 28 Jul 2024
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Distributed energy resources and the number of relays are expected to rise in modern electrical grids; consequently, relay misoperations are also expected to grow. Relays can detect electrical fault types using an internal algorithm and can display the result using light indicators on
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Distributed energy resources and the number of relays are expected to rise in modern electrical grids; consequently, relay misoperations are also expected to grow. Relays can detect electrical fault types using an internal algorithm and can display the result using light indicators on the front of the relay. However, some relays’ internal algorithms for predicting types of electrical faults could be improved. This study assesses a relay’s external and internal algorithms with an Advanced Synchronized Time Digital Grid Twin (ASTDGT) testbed with paired relays. A misoperation relay analysis focused on measuring the accuracy of using the boundary admittance (the external algorithm) versus the set-default (the internal algorithm) relay method to determine the electrical fault types was performed. In this study, the internal and external relay algorithms were assessed with a synchronized time digital grid twin testbed using a real-time simulator. This testbed evaluated two sets of logic at the same time with the digital grid twin and paired relays in the loop. Different types of electrical faults were simulated, and the relays’ recorded events and electrical fault light indicator states were collected from the human–machine interfaces. This ASTDGT testbed with paired relays successfully evaluated the relay algorithm misoperations. The boundary admittance method had an accuracy of 100% for line-to-line, line-to-ground, and line-to-line ground faults.
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(This article belongs to the Special Issue Power and Electronic Measurement Systems)
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Are Unitary Accounts of Quantum Measurements in Relativistic Wigner’s Friend Setups Compatible in Different Reference Frames?
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Jawad Allam and Alex Matzkin
Metrology 2024, 4(3), 364-373; https://doi.org/10.3390/metrology4030022 - 26 Jul 2024
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Wigner’s friend scenarios—in which external agents describe a closed laboratory containing a friend making a measurement—highlight the difficulties of quantum theory when accounting for measurements. The problem is to accommodate for unitary evolution from the point of view of the external agent with
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Wigner’s friend scenarios—in which external agents describe a closed laboratory containing a friend making a measurement—highlight the difficulties of quantum theory when accounting for measurements. The problem is to accommodate for unitary evolution from the point of view of the external agent with the measurements or other operations carried out by the friend. Here, we show in the context of a relativistic thought experiment that an operation that may be accounted for unitarily in a given reference frame cannot be described unitarily in a different reference frame. This result, based on the frame dependence of the state update in relativistic contexts, could point to some fundamental inadequacy when attempting to model actions taken by a complex agent as unitary operations.
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A Shared Metrological Framework for Trustworthy Virtual Experiments and Digital Twins
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Giacomo Maculotti, Manuel Marschall, Gertjan Kok, Brahim Ahmed Chekh, Marcel van Dijk, Jon Flores, Gianfranco Genta, Pablo Puerto, Maurizio Galetto and Sonja Schmelter
Metrology 2024, 4(3), 337-363; https://doi.org/10.3390/metrology4030021 - 17 Jul 2024
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Virtual experiments (VEs) and digital twins (DTs), pivotal for realizing European strategic policies on sustainability and digitalization within Industry 4.0 and the European Green Deal, simulate physical systems and characteristics in a virtual environment, with DTs incorporating dynamic inputs from and outputs to
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Virtual experiments (VEs) and digital twins (DTs), pivotal for realizing European strategic policies on sustainability and digitalization within Industry 4.0 and the European Green Deal, simulate physical systems and characteristics in a virtual environment, with DTs incorporating dynamic inputs from and outputs to the real-world counterpart. To ensure confidence in their use and outcomes, traceability and methods to evaluate measurement uncertainty are needed, topics that are hardly covered by the literature so far. This paper provides a harmonized definition of VEs and DTs and introduces a framework for evaluating measurement uncertainty. Furthermore, it discusses how to propagate the uncertainty of the contributions coming from the different parts of the DT. For the core part of the DT, the framework derived for VEs can be used. For the physical-to-virtual (P2V) connection and the virtual-to-physical (V2P) connection, additional sources of uncertainty need to be considered. This paper provides a metrological framework for taking all these uncertainty contributions into account while describing a framework to establish traceability for DTs. Two case studies are presented to demonstrate the proposed methodology considering industrially relevant measuring instruments and devices, namely, a coordinate measuring machine (CMM) and a collaborative robot arm (cobot).
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Open AccessArticle
Experiments on High-Resolution Digitizer Accuracy in Measuring Voltage Ratio and Phase Difference of Distorted Harmonic Waveforms above 2 kHz
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Imanka Dewayalage, Duane A. Robinson, Sean Elphick and Sarath Perera
Metrology 2024, 4(2), 323-336; https://doi.org/10.3390/metrology4020020 - 19 Jun 2024
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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
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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.
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Open AccessArticle
An Artificial Neural Network-Based Approach to Improve Non-Destructive Asphalt Pavement Density Measurement with an Electrical Density Gauge
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Muyang Li and Loulin Huang
Metrology 2024, 4(2), 304-322; https://doi.org/10.3390/metrology4020019 - 12 Jun 2024
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Asphalt pavement density can be measured using either a destructive or a non-destructive method. The destructive method offers high measurement accuracy but causes damage to the pavement and is inefficient. In contrast, the non-destructive method is highly efficient without damaging the pavement, but
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Asphalt pavement density can be measured using either a destructive or a non-destructive method. The destructive method offers high measurement accuracy but causes damage to the pavement and is inefficient. In contrast, the non-destructive method is highly efficient without damaging the pavement, but its accuracy is not as good as that of the destructive method. Among the devices for non-destructive measurement, the nuclear density gauge (NDG) is the most accurate, but radiation in the device is a serious hazard. The electrical density gauge (EDG), while safer and more convenient to use, is affected by the factors other than density, such as temperature and moisture of the environment. To enhance its accuracy by minimizing or eliminating those non-density factors, an original approach based on artificial neural networks (ANNs) is proposed. Density readings, temperature, and moisture obtained by the EDG are the inputs, and the corresponding densities obtained by the NDG are the outputs to train the ANN models through Levenberg-Marquardt, Bayesian regularization, and Scaled Conjugate Gradient algorithms. Results indicate that the ANN models trained greatly improve the measurement accuracy of the electrical density gauge.
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(This article belongs to the Special Issue Novel Dynamic Measurement Methods and Systems)
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Chromogenic Approach for Oxygen Sensing Using Tapered Coreless Optical Fibre Coated with Methylene Blue
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Rahul Kumar and Neil Wight
Metrology 2024, 4(2), 295-303; https://doi.org/10.3390/metrology4020018 - 12 Jun 2024
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In this paper, a Methylene Blue (MB)-coated tapered coreless (TCL) optical fibre sensor is proposed and experimentally investigated for oxygen sensing in the near-infrared (NIR) wavelength range of 993.5 nm. The effect of TCL diameter and MB sol–gel coating thickness on the sensitivity
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In this paper, a Methylene Blue (MB)-coated tapered coreless (TCL) optical fibre sensor is proposed and experimentally investigated for oxygen sensing in the near-infrared (NIR) wavelength range of 993.5 nm. The effect of TCL diameter and MB sol–gel coating thickness on the sensitivity of the sensor was also investigated. A maximum sensitivity of 0.19 dB/O2% in the oxygen concentration range of 0–37.5% was achieved for a TCL fibre sensor with a 2 µm taper waist diameter and a 0.86 µm MB sol–gel coating thickness, with a response time of 4 min. The sensor provides reproducible results even after 7 days and is shown to be highly selective to oxygen compared to argon and ethanol at the same concentration.
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Open AccessArticle
Interlaboratory Comparison of Power Measurements at Millimetre- and Sub-Millimetre-Wave Frequencies
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Murat Celep, Daniel Stokes, Erkan Danacı, François Ziadé, Przemysław Zagrajek, Marcin Wojciechowski, Gia Ngoc Phung, Karsten Kuhlmann, Alireza Kazemipour, Steven Durant, Jeffrey Hesler, Ian Instone, Handan Sakarya, Djamel Allal, Jürgen Rühaak, James Skinner and Daniel Stalder
Metrology 2024, 4(2), 279-294; https://doi.org/10.3390/metrology4020017 - 24 May 2024
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The aim of this paper is to compare the power measurement capabilities in millimetre- and sub-millimetre-wave frequency bands of several national metrology institutes and one research institute. The first comparison, in WR-6.5 waveguide (110 GHz to 170 GHz), involved NPL, TUBITAK UME and
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The aim of this paper is to compare the power measurement capabilities in millimetre- and sub-millimetre-wave frequency bands of several national metrology institutes and one research institute. The first comparison, in WR-6.5 waveguide (110 GHz to 170 GHz), involved NPL, TUBITAK UME and PTB. The second comparison, in WR-1.5 waveguide (500 GHz to 750 GHz), involved NPL, METAS, TUBITAK UME, LNE, WAT, GUM and VDI. Two types of travelling standards were used for these comparisons: a thermoelectric power sensor in the WR-6.5 band and a calorimetric power sensor in the WR-6.5 and WR-1.5 bands. The thermoelectric power sensor was characterised by the participants against their own standards and a generalised effective efficiency was calculated. The calorimetric power sensor operating in the WR-6.5 band was measured to observe its behaviour during the comparison and was also measured in the WR-1.5 band after being fitted with a suitable waveguide taper and used in conjunction with a frequency multiplier. The participants measured the output of the calorimetric power sensor and their own power sensor standard. A normalised power ratio method was used as a comparison parameter for the WR-1.5 band measurements. In addition, a pyroelectric power standard was used by METAS to measure absolute power, and a frequency of 650 GHz was used as a link between the absolute power and the power ratios. Finally, all but two of the measurement points compared between the participants achieved agreement in terms of scores less than 1. For the first time, an interlaboratory comparison of power measurements at sub-millimetre frequencies has been performed and, overall, good agreement was achieved between the different laboratories.
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Open AccessArticle
Lightweight Convolutional Network with Integrated Attention Mechanism for Missing Bolt Detection in Railways
by
Mujadded Al Rabbani Alif and Muhammad Hussain
Metrology 2024, 4(2), 254-278; https://doi.org/10.3390/metrology4020016 - 10 May 2024
Cited by 2
Abstract
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Railway infrastructure safety is a paramount concern, with bolt integrity being a critical component. In the realm of railway maintenance, the detection of missing bolts is a vital task that ensures the stability and safety of tracks. Traditionally, this task has been approached
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Railway infrastructure safety is a paramount concern, with bolt integrity being a critical component. In the realm of railway maintenance, the detection of missing bolts is a vital task that ensures the stability and safety of tracks. Traditionally, this task has been approached through manual inspections or conventional automated methods, which are often time-consuming, costly, and prone to human error. Addressing these challenges, this paper presents a state-of-the-art solution with the development of a lightweight convolutional neural network (CNN) featuring an integrated attention mechanism. This novel model is engineered to be computationally efficient while maintaining high accuracy, making it particularly suitable for real-time analysis in resource-constrained environments commonly found in railway inspections. The proposed CNN utilises a distinctive architecture that synergises the speed of lightweight networks with the precision of attention-based mechanisms. By integrating an attention mechanism, the network selectively concentrates on regions of interest within the image, effectively enhancing the model’s capability to identify missing bolts with remarkable accuracy. Comprehensive testing showcases a remarkable 96.43% accuracy and an impressive 96 F1-score, substantially outperforming existing deep learning frameworks in the context of missing bolt detection. Key contributions of this research include the model’s innovative attention-integrated approach, which significantly reduces the model complexity without compromising detection performance. Additionally, the model offers scalability and adaptability to various railway settings, proving its efficacy not just in controlled environments but also in diverse real-world scenarios. Extensive experiments, rigorous evaluations, and real-time deployment results collectively underscore the transformative potential of the presented CNN model in advancing the domain of railway safety maintenance.
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