Metrology, Volume 3, Issue 1 (March 2023) – 6 articles

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