Metrology and Measurement Systems

Verification of electrical safety in low-voltage power systems includes the measurement of earth fault loop impedance. This measurement is performed to verify the effectiveness of protection against indirect contact. The widespread classic methods and meters use a relatively high value of the measuring current (5÷20) A, so that they are a source of nuisance tripping of residual current devices (RCDs). The meters dedicated to circuits with RCDs usually use an extremely low value of current (lower than 15 mA), which in many cases it is not acceptable in terms of the measurement accuracy. This paper presents a method of earth fault loop impedance measurement in 3-phase circuits, without nuisance tripping of RCDs – the concept of measurement, the meter structure and the experimental validation. The nuisance tripping is avoided in spite of the use of measuring current value many times higher than that of the rated residual current of RCDs. The main advantage of the proposed method is the possibility of creating values of measuring current in a very wide range, what is very important with regard to accuracy of the measurement.

Electroencephalogram (EEG) is one of biomedical signals measured during all-night polysomnography to diagnose sleep disorders, including sleep apnoea. Usually two central EEG channels (C3-A2 and C4- A1) are recorded, but typically only one of them are used. The purpose of this work was to compare discriminative features characterizing normal breathing, as well as obstructive and central sleep apnoeas derived from these central EEG channels. The same methodology of feature extraction and selection was applied separately for the both synchronous signals. The features were extracted by combined discrete wavelet and Hilbert transforms. Afterwards, the statistical indexes were calculated and the features were selected using the analysis of variance and multivariate regression. According to the obtained results, there is a partial difference in information contained in the EEG signals carried by C3-A2 and C4-A1 EEG channels, so data from the both channels should be preferably used together for automatic sleep apnoea detection and differentiation.

To find effective and practical methods to distinguish gas-liquid two-phase flow patterns, new flow pattern maps are established using the differential pressure through a classical Venturi tube. The differential pressure signal was first decomposed adaptively into a series of intrinsic mode functions (IMFs) by the ensemble empirical mode decomposition. Hilbert marginal spectra of the IMFs showed that the flow patterns are related to the amplitude of the pressure fluctuation. The cross-correlation method was employed to sift the characteristic IMF, and then the energy ratio of the characteristic IMF to the raw signal was proposed to construct flow pattern maps with the volumetric void fraction and with the two-phase Reynolds number, respectively. The identification rates of these two maps are verified to be 91.18% and 92.65%. This approach provides a cost-effective solution to the difficult problem of identifying gas-liquid flow patterns in the industrial field.

New measurement technologies, e.g. Light Detection And Ranging (LiDAR), generate very large datasets. In many cases, it is reasonable to reduce the number of measuring points, but in such a way that the datasets after reduction satisfy specific optimization criteria. For this purpose the Optimum Dataset (OptD) method proposed in [1] and [2] can be applied. The OptD method with the use of several optimization criteria is called OptD-multi and it gives several acceptable solutions. The paper presents methods of selecting one best solution based on the assumptions of two selected numerical optimization methods: the weighted sum method and the "-constraint method. The research was carried out on two measurement datasets from Airborne Laser Scanning (ALS) and Mobile Laser Scanning (MLS). The analysis have shown that it is possible to use numerical optimization methods (often used in construction) to obtain the LiDAR data. Both methods gave different results, they are determined by initially adopted assumptions and – in relation to early made findings, these results can be used instead of the original dataset for various studies.

The accuracy and reliability of Kalman filter are easily affected by the gross errors in observations. Although robust Kalman filter based on equivalent weight function models can reduce the impact of gross errors on filtering results, the conventional equivalent weight function models are more suitable for the observations with the same noise level. For Precise Point Positioning (PPP) with multiple types of observations that have different measuring accuracy and noise levels, the filtering results obtained with conventional robust equivalent weight function models are not the best ones. For this problem, a classification robust equivalent weight function model based on the t-inspection statistics is proposed, which has better performance than the conventional equivalent weight function models in the case of no more than one gross error in a certain type of observations. However, in the case of multiple gross errors in a certain type of observations, the performance of the conventional robust Kalman filter based on the two kinds of equivalent weight function models are barely satisfactory due to the interaction between gross errors. To address this problem, an improved classification robust Kalman filtering method is further proposed in this paper. To verify and evaluate the performance of the proposed method, simulation tests were carried out based on the GPS/BDS data and their results were compared with those obtained with the conventional robust Kalman filtering method. The results show that the improved classification robust Kalman filtering method can effectively reduce the impact of multiple gross errors on the positioning results and significantly improve the positioning accuracy and reliability of PPP.

A metrological verification of a high precision digital multimeter was made by the laboratory of calibration of programmable electrical multifunction instruments of the National Institute of Metrological Research (INRIM) in order to verify its accuracy and stability. The instrument had been tested for a period of six months for five low-frequency electrical quantities (DC and AC Voltage and Current and DC Resistance). Its stability and precision were compared with the accuracy specifications of the manufacturer. As a new approach, a performance index of the DMM was introduced and evaluated for each examined measurement point. The DMM showed a satisfactory agreement with its specifications to be considered at the level of other top-class DMMs and even better in some measurements points.

The paper provides statistical analysis of the photographs of four various granular materials (peas, pellets, triticale, wood chips). For analysis, the (parametric) ANOVA and the (nonparametric) Kruskal-Wallis tests were applied. Additionally, the (parametric) two-sample t-test and (non-parametric) Wilcoxon Rank-Sum Test for pairwise comparisons were performed. In each case, the Bonferroni correction was used. The analysis shows a statistical evidence of the presence of differences between the respective average discrete pixel intensity distributions (PID), induced by the histograms in each group of photos, which cannot be explained only by the existing differences among single granules of different materials. The proposed approach may contribute to the development of a fast inspection method for comparison and discrimination of granular materials differing from the reference material, in the production process.

The paper presents the campaigns of mobile satellite measurements, carried out in 2009–2015 on the railway and tram lines. The accuracy of the measurement method has been analysed on the basis of the results obtained in both horizontal and vertical planes. The track axis deviation from the defined geometric shape has been analysed in the areas clearly defined in terms of geometry, i.e. on the straight sections and sections with constant longitudinal inclination. The values of measurement errors have been estimated on the basis of signals subjected to appropriate processes of filtration. The paper attempts to evaluate the changing possibilities of using the GNSS techniques to determine the shape of the railway track axis from 2009 to 2015. The determined average value of the measurement error now equals a few millimetres. This achievement is very promising for the prospects of mobile satellite measurements in railway engineering.

Combining surface measurement data from individual measurements of surface fragments is an issue that has been recognized for flat surfaces. The connection takes place on the principle of making ‘overlap’ measurements according to a specific measurement strategy, and then the algorithm synthesizes the measurement data for the common part (data fusion). This paper presents a method of combining partial data into one larger set using image processing methods. The purpose of the analysis is to combine surface data of a more complex shape in terms of surface roughness and waviness. A successful attempt was made to combine surface measurement data located on a cylindrical surface – convex surface. A rotated table was designed and used for surface data acquisition. The datasets were acquired with the use of CCI 6000 (366 μm – 366 μm) with the assumed overlapping of at least 20%. The measurement datasets were first pre-processed: filling in non-measured points, levelling and form re- moving were applied. For such processed datasets, the common part was identified (data registration) and then the data fusion was performed. An example of stitching the surface datasets shows usefulness of the presented methodology.

The Hopkinson pressure bar has been developed to calibrate and assess high g accelerometers’ capacity. The extreme caution is indispensable for performing calibration of severe characteristics, like the bearable super-high overload peak and wide duration of stress. In the paper, the Hopkinson bar calibrating system is being critically appraised. A limiting formula is deduced based on the stress wave theory. It indicates that the overload peak and duration of stress are limited by the elastic limit and wave speed of Hopkinson bar material. Both stress wave configurations in the form of linear ramp and cosine functions were designed theoretically to meet typical calibrating requirements. They were confirmed experimentally with the aid of the pulse shaping technique. Their corresponding calibration characteristics were analysed critically, and it was found that the cosine stress wave can achieve the values of acceleration peak or duration by π/2 times greater than those obtained with the linear stress wave. Finally, some suggestions are proposed for more extreme calibration requirements.

This paper presents a geomagnetic detection method for pipeline defects using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and wavelet energy product (WEP) – Teager energy operator (TEO), which improves detection accuracy and defect identification ability as encountering strong inference noise. The measured signal is first subtly decomposed via CEEMDAN into a series of intrinsic mode functions (IMFs), which are then distinguished by the Hurst exponent to reconstruct the filtered signal. Subsequently, the scale signals are obtained by using gradient calculation and discrete wavelet transform and are then fused by using WEP. Finally, TEO is implemented to enhance defect signal amplitude, completing geomagnetic detection of pipeline defects. The simulation results created by magnetic dipole in a noisy environment, indoor experiment results and field testing results certify that the proposed method outperforms ensemble empirical mode decomposition (EEMD)-gradient, EEMD-WEP-TEO, CEEMDAN-gradient in terms of detection deviation, peak side-lobe ratio (PSLR) and integrated side-lobe ratio (ISLR).

In the paper, the variation of the intensity of the geomagnetic field force is analysed in time and space. For the research, the data from measurements of the intensity of the geomagnetic field force at four airports (Kaunas, Klaip˙eda, Palanga andVilnius) and 6 geomagnetic field repeat stations aswell as the data from Belsk Magnetometric Observatory (Poland) were used. For the data analysis, the theory of covariance functions was applied. The estimates of the cross-covariance functions of the measured intensity of the geomagnetic field force or the estimates of auto-covariance functions of single data were calculated according to the random functions created from the force intensity measurement data arrays. The estimates of covariance functions were calculated upon varying the quantization interval on the time scale and applying the software created using Matlab package of procedures. The impact of radars of airports on the intensity of geomagnetic field variation and on changes of their covariance functions was established.

The paper presents verification of a peak detection method cooperating with infrared radiation detector module applications. The work has been divided into parts including SPICE simulations and presentation of results obtained with the constructed prototype. The design of the peak detector dedicated to applications with very short pulses requires a different approach than that for standard solutions. It is mainly caused due to the ratio of pulse width and time period. In the described application this ratio is less than 10%. The paper shows testing of an analogue circuit which is capable to be inserted in these applications.

The paper presents the possibilities of quantitative analysis of results obtained from CT examination of organs and anatomical structures of the upper respiratory tract. The presented results of the analysis were obtained using proprietary software developed in the MATLAB 2018b environment (Image Processing toolbox). The software enables to visualize the original results of CT scan and, after evaluating the visible structures, enables to select the area to be subjected to quantitative analysis. After the initial identification of an area of interest requiring detailed diagnostics, its volume and the surface areas of individual cross-sections are calculated in the area separated for examinations. A graphical presentation of the analysis results – the surface areas of selected cross-sections possible to visualize in two- and three-dimensional space – enables quick analysis of changes in the examined region.

A computer measurement system, designed and built by authors, dedicated to location and description of partial discharges (PD) in oil power transformers examined by means of the acoustic emission (AE) method is presented. The measurement system is equipped with 8 measurement channels and ensures: monitoring of signals, registration of data in real time within a band of 25–1000 kHz in laboratory and real conditions, basic and advanced analysis of recorded signals. The basic analysis carried out in the time, frequency and time-frequency domains deals with general properties of the AE signals coming from PDs. The advanced analysis, performed in the discrimination threshold domain, results in identification of signals coming from different acoustic sources as well as location of these sources in the examined transformers in terms of defined by authors descriptors and maps of these descriptors on the side walls of the tested transformer tank. Examples of typical results of laboratory tests carried out with the use of the built-in measurement system are presented.

The objective of the paper is to analyse traceability issues in real-life gas flow measurements in complex distribution systems. The initial aim is to provide complete and traceable measurement results and calibration certificates of gas-flow meters, which correspond to specific installation conditions. Extensive work has been done to enable a more credible decision on how to deal in particular situations with the measurement uncertainty which is always subject of a flow meter’s calibration as a quantitative parameter value obtained in laboratory, and with the qualitative statement about the error of an outdoor meter. The laboratory simulation of a complex, real-life distributed system has been designed to achieve the initial aim. As an extension of standardized procedures that refer to the laboratory conditions, the proposed methods introduce additional “installation-specific” error sources. These sources could be either corrected (if identified) or considered as an additional “installation-specific” uncertainty contribution otherwise. The analysis and the results of the experimental work will contribute to more precise and accurate measurement results, thus assuring proper measurements with a known/estimated uncertainty for a specific gas flow installation. Also, the analysis will improve the existing normative documents by here presented findings, as well as fair trade in one of the most important and growing energy consumption areas regarding the legal metrology aspects. These facts will enable comparing the entire quantity of gas at the input of a complex distributed system with the cumulative sum of all individual gas meters in a specific installation.

The paper is focused on the main problems of modern metrology in the context of the Fourth Industrial Revolution “Industry 4.0”, particularly in the field of qualimetry. The dominant issues of the methodology of qualimetrical measurement, as the interrelation between metrology and qualimetry, are considered. The following questions are raised and analysed: determination of the measurand in the qualimetrical measurement, creation of the virtual product quality pattern, determination of the product quality level by using the theory of multidimensional scaling, assurance of the metrological traceability of the qualimetrical measurement results. A procedure of performing the qualimetrical measurement is described.