Metrology

Modern power systems are rapidly transitioning towards a fully digital substation paradigm. Based on the IEC 61850, a common communication protocol between the different intelligent electronic devices (IEDs) promises a significant enhancement in terms of efficiency and interoperability. In this context, synchronization represents a crucial aspect as it allows us to rigorously compare measurements taken at the same time in different locations. In this paper, we consider a measurement chain for synchrophasor estimation based on digital inputs: an instrument transformer, a stand-alone merging unit (SAMU) and a phasor measurement unit (PMU). Both the SAMU and the PMU are equipped with independent synchronization sources. In case the SAMU loses its synchronization, the final measurement result would be considered invalid until a complete restoration of the SAMU synchronization status. In view of a longer continuity of operation, this paper proposes an alternative approach to evaluate the PMU Time Quality in real-time. This approach allows for continuing crucial monitoring and control operations, such as state estimation and fault detection, even in the presence of temporary loss of synchronization. A characterization, in both simulated and experimental conditions, proves the potential and reliability of the proposed approach. In the considered test case, the come-back within a sufficient time quality is correctly detected in less than 200 s, while waiting for the full restoration of the SAMU time reference would cost several minutes. Full article

This paper presents a novel low-speed measuring method using analog sine and square waves of Hall effect speed sensors coupled with correlative digital signal processing algorithms packaged on a signal processing unit. The frequency of the initial signal is estimated by a square wave period measuring method (SWPM). On the basis of the initially measured frequency, a recursive self-correction (RSC) algorithm is used to perform the low-frequency measurement using the discrete sinusoid wave. The low-speed signal frequency can be derived continuously from the phase difference of the discrete sine wave, where the RSC algorithm is used to achieve high measuring accuracy. Compared to the method using only the SWPM algorithm, this novel low-speed measuring method enables faster measuring speed to achieve sufficient real-time performance. Simulation analyses and experiments verified the effectiveness of the proposed low-speed measuring method. Full article

Achieving the highest levels of compliance with the FAIR (findable, accessible, interoperable, reusable) principles for scientific data management and stewardship requires machine-actionable semantic representations of data and metadata. Human and machine interpretation and reuse of measurement datasets rely on metrological information that is often specified inconsistently or cannot be inferred automatically, while several ontologies to capture the metrological information are available, practical implementation examples are few. This work aims to close this gap by discussing how standardised measurement data and metadata could be presented using semantic web technologies. The examples provided in this paper are machine-actionable descriptions of Earth observation and bathymetry measurement datasets, based on two ontologies of quantities and units of measurement selected for their prominence in the semantic web. The selected ontologies demonstrated a good coverage of the concepts related to quantities, dimensions, and individual units as well as systems of units, but showed variations and gaps in the coverage, completeness and traceability of other metrology concept representations such as standard uncertainty, expanded uncertainty, combined uncertainty, coverage factor, probability distribution, etc. These results highlight the need for both (I) user-friendly tools for semantic representations of measurement datasets and (II) the establishment of good practices within each scientific community. Further work will consequently investigate how to support ontology modelling for measurement uncertainty and associated concepts. Full article

New automated laser radar measurement systems at the Saab Inc. West Lafayette, USA, facility will make airframe assembly of the aft body for the new eT7-A aircraft a quicker, more cost-efficient process. Digital twin concepts realized through simulation and off-line programming show advantageous results when studying future state scenarios or investigating how a current large-volume dimensional metrology system acts and behaves. The aim of this exploration has been to examine how to facilitate the design and programming of automated laser radar concepts by means of novel simulation-based software. High-speed computing algorithms efficiently solve tasks and sequence problems related to many statistical combinatorial possibilities in calculations. However, this approach requires accurate and reliable models and digital twins that are continuously updated with real world data and information. In this paper, the main contributions are to create procedures to define the dimensional metrology workflow at Saab and to model and simulate the laser radar process, enhancing and tailoring existing offline programming software by specific new functionalities. A case study conducted at Saab Aeronautics premises in Linköping acted as a clinical laboratory to generate our research findings. The exploratory work indicates that a reliable simulation-based development method can be used advantageously in the early-stage design layout of automated dimensional metrology systems to verify and guarantee the line-of-sight of, e.g., a laser light path and its allowed inclinations to a specific geometrical feature to be measured, extracted, and evaluated. Full article

The numerical modeling of cardiac electrophysiology has reached a mature and advanced state that allows for quantitative modeling of many clinically relevant processes. As a result, complex computational tasks such as the creation of a variety of electrocardiograms (ECGs) from virtual cohorts of models representing biological variation are within reach. This requires a correct representation of the variability of a population by suitable distributions of a number of input parameters. Hence, the assessment of the dependence and variation of model outputs by sensitivity analysis and uncertainty quantification become crucial. Since the standard metrological approach of using Monte–Carlo simulations is computationally prohibitive, we use a nonintrusive polynomial chaos-based approximation of the forward model used for obtaining the atrial contribution to a realistic electrocardiogram. The surrogate increases the speed of computations for varying parameters by orders of magnitude and thereby greatly enhances the versatility of uncertainty quantification. It further allows for the quantification of parameter influences via Sobol indices for the time series of 12 lead ECGs and provides bounds for the accuracy of the obtained sensitivities derived from an estimation of the surrogate approximation error. Thus, it is capable of supporting and improving the creation of synthetic databases of ECGs from a virtual cohort mapping a representative sample of the human population based on physiologically and anatomically realistic three-dimensional models. Full article

This study proposes an algorithm to autonomously generate the scan path for a laser line scanner mounted on a coordinate measuring machine. The scan path is determined based on task-specific measurement uncertainty in order to prove conformance to specified tolerances. The novelty of the algorithm is the integration of measurement uncertainty. This development is made possible by recent developments for digital twins of optical measurement systems. Furthermore, the algorithm takes all the constraints of this optical measurement system into account. The proposed algorithm is validated on different objects with different surface characteristics. The validation is performed experimentally by a physical measurement system and virtually by an in-house developed digital twin. The validation proves that theoretical coverable areas are measured properly, and the method applied to the equipment used leads to adequate measurement paths that give measurements results with sufficient measurement uncertainty to prove conformance to specifications. Full article

High-accuracy source standards preparation in radionuclide metrology is based on a properly described and reliable weighing procedure able to achieve relative standard uncertainties below 0.1%. However, the results of uncertainty budget comparison CCRI(II)-S7 put in check the ability of the former pycnometer and substitution weighing methods to attain this goal. As a result, a question arises about the validation of mass measurements performed from the elimination weighing method when appropriate uncertainties are required. In order to address this problem, a comprehensive in situ validation methodology is proposed for the results of the pycnometer, substitution, elimination and modified elimination (MEM) methods. Mass comparisons are applied to evaluate the compatibility between weighing methods’ results. It is possible due to a developed weighing sequence, which allows for the performing of all methods by only one drop deposition in the range of mass from 10 mg to 200 mg. As a result, the high degree of compatibility between the MEM and elimination method for uncertainties below 0.1% has been achieved, as well as for higher uncertainties to pycnometer and substitution methods. Numerical simulations indicate that the validation results remain valid on improved technical implementations for these last two methods. Full article

Major aircraft manufacturers are expecting the commercial aircraft market to overcome the pre-COVID levels by 2025, which demands an increase in the production rate. However, aeronautical product assembly processes are still mainly manually performed with a low level of automation. Moreover, the current industry digitalization trend offers the possibility to develop faster, smarter and more flexible manufacturing processes, aiming at a higher production rate and product customization. Here, the integration of metrology within the manufacturing processes offers the possibility to supply reliable data to constantly adjust the assembly process parameters aiming at zero-defect, more digital and a higher level of automation manufacturing processes. In this context, this article introduces the virtual metrology as an assistant of the assembly process of the Advanced Rear-End fuselage component. It describes how the assembly process CADmodel is used by simulation tools to design, set up and perform the virtual commissioning of the new metrology-driven assembly methods, moving from a dedicated tooling approach to a more flexible and reconfigurable metrology-aided design. Preliminary results show that portable metrology solutions are fit-to-purpose even for hardly accessible geometries and fulfil the current accuracy demands. Moreover, the simulation environment ensures a user-friendly assembly process interaction providing further set-up time reduction. Full article

Reverse transcription polymerase chain reaction (RT-PCR) targeting select genes of the SARS-CoV-2 RNA has been the main diagnostic tool in the global response to the COVID-19 pandemic. It took several months after the development of these molecular tests to assess their diagnostic performance in the population. The objective of this study is to demonstrate that it was possible to measure the diagnostic accuracy of the RT-PCR test at an early stage of the pandemic despite the absence of a gold standard. The study design is a secondary analysis of published data on 1014 patients in Wuhan, China, of whom 59.3% tested positive for COVID-19 in RT-PCR tests and 87.6% tested positive in chest computerized tomography (CT) exams. Previously ignored expert opinions in the form of verbal probability classifications of patients with conflicting test results have been utilized here to derive the informative prior distribution of the infected proportion. A Bayesian implementation of the Dawid-Skene model, typically used in the context of crowd-sourced data, was used to reconstruct the sensitivity and specificity of the diagnostic tests without the need for specifying a gold standard. The sensitivity of the RT-PCR diagnostic test developed by China CDC was estimated to be 0.707 (95% Cr I: 0.664, 0.753), while the specificity was 0.861 (95% Cr I: 0.781, 0.956). In contrast, chest CT was found to have high sensitivity (95% Cr I: 0.969, 1.000) but low specificity (95% Cr I: 0.477, 0.742). This estimate is similar to estimates that were found later in studies designed specifically for measuring the diagnostic performance of the RT-PCR test. The developed methods could be applied to assess diagnostic accuracy of new variants of SARS-CoV-2 in the future. Full article

Data-driven manufacturing in Industry 4.0 demands digital metrology not only to drive the in-process quality assurance of manufactured products but also to supply reliable data to constantly adjust the manufacturing process parameters for zero-defect manufacturing processes. Better quality, improved productivity, and increased flexibility of manufacturing processes are obtained by combining intelligent production systems and advanced information technologies where in-process metrology plays a significant role. While traditional coordinate measurement machines offer strengths in performance, accuracy, and precision, they are not the most appropriate in-process measurement solutions when fast, non-contact and fully automated metrology is needed. In this way, non-contact optical 3D metrology tackles these limitations and offers some additional key advantages to deploying fully integrated 3D metrology capability to collect reliable data for their use in intelligent decision-making. However, the full adoption of 3D optical metrology in the manufacturing process depends on the establishment of metrological traceability. Thus, this article presents a practical approach to the task-specific uncertainty assessment realisation of a dense point cloud data type of measurement. Finally, it introduces an experimental exercise in which data-driven 3D point cloud automatic data acquisition and evaluation are performed through a model-based definition measurement strategy. Full article

Understanding the length and subdivisions of ancient length units is necessary for Archaeology, Architecture, and engineering, among other fields. These metrological units derive from anthropocentric concepts (fathom, cubit, foot, finger, etc.) and hence their metrological characteristics are variable and unknown for various ancient civilizations. The Roman length units are well determined, but the ancient Greek units are not. A rule sculpted in a metrological relief recently permitted the recognition of the Doric foot as having a length of 327 mm, but the broader use and divisions of this length unit remain unknown. In this article we present evidence of use of the Doric foot from the modeling of an ancient, atypical small theatre of the 4th–3rd century B.C., at Makyneia, on the western Greece mainland. It was found that this structure was designed using the Doric foot and its division in 24 (or even 12) digits. This result from a small provincial town indicates that the Doric foot was in broad use in architectural and engineering works of the ancient Greek World, and this result may be used to solve various problems of that era. Full article

Arterial simulators are a useful tool to simulate the cardiovascular system in many different fields of application and to carry out in vitro tests that would constitute a danger when performed in in vivo conditions. In the literature, a thriving series of in vitro experimental set-up examples can be found. Nevertheless, in the current scientific panorama on this topic, it seems that organic research from a metrological and functional perspective is still lacking. In this regard, the present review study aims to make a contribution by analyzing and classifying the main concerns for the cardiovascular simulators proposed in the literature from a metrological and functional point of view, according to their field of application, as well as for the transducers in the arterial experimental set-ups, measuring the main hemodynamic quantities in order to study their trends in specific testing conditions and to estimate some parameters or indicators of interest for the scientific community. Full article

Ultrasonic clamp-on meters have become an established technology for non-invasive flow measurements. Under disturbed flow conditions, their measurement values must be adjusted with corresponding fluid mechanical calibration factors. Due to the variety of flow disturbances and installation positions, the experimental determination of these factors often needs to be complemented by computational fluid dynamics (CFD) simulations. From a metrological perspective, substituting experiments with simulation results raises the question of how confidence in a so-called virtual measurement can be ensured. While there are well-established methods to estimate errors in CFD predictions in general, strategies to meet metrological requirements for CFD-based virtual meters have yet to be developed. In this paper, a framework for assessing the overall uncertainty of a virtual flow meter is proposed. In analogy to the evaluation of measurement uncertainty, the approach is based on the utilization of an expanded simulation uncertainty representing the entirety of the computational domain. The study was conducted using the example of an ultrasonic clamp-on meter downstream of a double bend out-of-plane. Nevertheless, the proposed method applies to other flow disturbances and different types of virtual meters. The comparison between laboratory experiments and simulation results with different turbulence modeling approaches demonstrates a clear superiority of hybrid RANS-LES models over the industry standard RANS. With an expanded simulation uncertainty of 1.44 × 10⁻², the virtual measurement obtained with a hybrid model allows for a continuous determination of calibration factors applicable to the relevant mounting positions of a real meter at a satisfactory level of confidence. Full article

The increased relevance of large-volume metrology (LVM) in industrial applications entails certain challenges: measurements must be cost-efficient and the technologies must be easy to use while ensuring accuracy and reliability. Portable photogrammetry shows great potential to overcome such challenges, but industrial users do not yet rely on its accuracy for large scenarios (3 to 64 m), especially when mass-market cameras are not conceived of as industrial metrology instruments. Furthermore, the measurement results might also depend on the operator’s skills and knowledge of the key process variables. In this work, a methodology was designed so that the measurement uncertainty of portable photogrammetry can be evaluated under controlled conditions for LVM. To do so, PTB’s reference wall, which was designed to assess laser-based methods applied to large volumes, was used as a reference artefact to study the measurement performance under different conditions, enabling an analysis of the relative influence of two process variables: the spatial arrangement of the optical instruments on the scene, and the relative camera poses for an accurate triangulation. According to these variables, different measuring conditions were designed (Monte Carlo analysis), and experimentally evaluated and reported (LME, length measuring errors), analysing the performance figures expected from both unskilled and expert users. Full article

The usage of virtual instruments (VIs) to analyze measurements and calculate uncertainties is increasing. Well-known examples are virtual coordinate measurement machines (VCMMs) which are often used and even commercially offered to assess measurement uncertainties of CMMs. A more recent usage of the VI concept is posed by the modeling of scatterometers. These VIs can be used to assess the measurement uncertainty after the measurement has been performed based on the real measurement data or prior to the measurement to predict the measurement uncertainty using a type of simulated measurement data. The research question addressed in this paper is to assess if this predicted uncertainty will be similar in magnitude to the calculated uncertainty based on the measurement data. It turns out that this is not necessarily the case. The main observation of this paper was that the uncertainty predicted by a VI can be highly sensitive to the chosen way of operating the VI. To amend this situation, a simple procedure was proposed that can be used prior to performing the real measurement and that is believed to produce a conservative prediction of the measurement uncertainty in most cases. This was verified in a case study involving the measurement of the asphericity of an imperfect sphere using a CMM, with the uncertainty calculated by means of a VCMM. Full article

Accurate frequency measurement plays an important role in many industrial and robotic systems. However, different influences from the application’s environment cause signal noises, which complicate frequency measurement. In rough environments, small signals are intensively disturbed by noises. Thus, even negative Signal-to-Noise Ratios (SNR) are possible in practice. Thus, frequency measuring methods, which can be used for low SNR signals, are in great demand. In previous work, the method of cross-correlation spectrum has been developed as an alternative to Fast Fourier-Transformation or Continuous Wavelet Transformation. It is able to determine the frequencies of a signal under strong noise and is not affected by Heisenberg’s uncertainty principle. However, in its current version, its creation is computationally very intensive. Thus, its application to real-time operations is limited. In this article, a new way to create the cross-correlation spectrum is presented. It is capable of reducing the calculation time by 89% without significant accuracy loss. In simulations, it achieves an average deviation of less than 0.1% on sinusoidal signals with an SNR of −14 dB and a signal length of 2000 data points. When applied to “self-mixing”-interferometry signals, the method can reach a normalized root-mean-square error of 0.21% with the aid of an estimation method and an averaging algorithm. Therefore, further research of the method is recommended. Full article

Modern manufacturing processes are characterized by growing product diversities and complexities alike. As a result, the demand for fast and flexible process automation is ever increasing. However, higher individuality and smaller batch sizes hamper the use of standard robotic automation systems, which are well suited for repetitive tasks but struggle in unknown environments. Modern manipulators, such as collaborative industrial robots, provide extended capabilities for flexible automation. In this paper, an adaptive ROS-based end-to-end toolchain for vision-guided robotic process automation is presented. The processing steps comprise several consecutive tasks: CAD-based object registration, pose generation for sensor-guided applications, trajectory generation for the robotic manipulator, the execution of sensor-guided robotic processes, test and the evaluation of the results. The main benefits of the ROS framework are readily applicable tools for digital twin functionalities and established interfaces for various manipulator systems. To prove the validity of this approach, an application example for surface reconstruction was implemented with a 3D vision system. In this example, feature extraction is the basis for viewpoint generation, which, in turn, defines robotic trajectories to perform the inspection task. Two different feature point extraction algorithms using neural networks and Voronoi covariance measures, respectively, are implemented and evaluated to demonstrate the versatility of the proposed toolchain. The results showed that complex geometries can be automatically reconstructed, and they outperformed a standard method used as a reference. Hence, extensions to other vision-controlled applications seem to be feasible. Full article