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1

The MEMS-based barometric altimeter inaccuracy and drift phenomenon

Matyja Tomasz, Kubik Andrzej, Stanik Zbigniew

Zeszyty Naukowe. Transport / Politechnika Śląska

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2022

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z. 116

141--162

EN

MEMS technology has made sensors for measuring barometric pressure and altitude above sea level very cheap and widely used in many consumer electronic devices. This paper presents a theoretical analysis of the sources and types of errors in the barometric altimeter using the standard atmosphere model (ISA). Methods for correcting principal errors caused by non-standard sea level conditions are described and compared. A method of correcting errors in the case of altimeter horizontal movement to the air column and total pressure measurement was proposed. It was compared with another method known from the literature. In the numerical experiment, data recorded by a bicycle computer equipped with a MEMS-based barometric altimeter was analyzed. As the GPS data of the route covered was also known, it was possible to compare the recorded altimeter data with the heights determined from the digital terrain model (DTM), which in this case were considered accurate. The error of the measured altitude calculated in this way was tried to be divided into the principal error, the external error caused by the sensor movement, and the barometer drift. Hence, a numerical experiment was carried out in which, based on the recorded data, an attempt was made to reconstruct non-standard sea level conditions and the impact of speed on the sensor measurements. Furthermore, a method of solving such a reverse problem was proposed. The results of the presented studies can be used in the design of systems correcting the indications of barometric altimeters. The accuracy of the altitude measurement is especially important for small controlled flying objects (UAH) and when recording the route of vehicles moving on the ground.

2

Validation of CHIRPS satellite based precipitation data against the in situ observations using the Copula method: a case study of Kosar Dam basin, Iran

Mokhtari Shirin, Sharafati Ahmad, Raziei Tayeb

Acta Geophysica

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2022

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Vol. 70, no 1

465--484

EN

The present study compares the daily and monthly precipitation estimates of the CHIRPS satellite data with the in situ measurements at four stations scattered over the Kosar Dam basin in southwestern Iran. The uncertainty of the satellite precipitation estimates was calculated through simulation with the Copula functions. For this purpose, 55% of the stations, daily and monthly rainfall data relative to the 1987–2012 period were used for training (simulation), and the other 45% were used for testing (validation) the performance of the Copula model. First, the daily, monthly, and annual satellite precipitation estimates were statistically compared with precipitation observed at the stations and the whole basin using the Pearson correlation coefficient (CC), root mean square error (RMSE), and Bias statistics. The computed CC between the areal average of observed and satellite precipitation estimation at the basin is 0.49, 0.82, and 0.33 for daily, monthly, and annual time scales, respectively. The difference (biases) between the satellite estimates and in situ measurements was then calculated for daily, monthly, and annual time scales over the training period. The obtained biases were subsequently fitted with the General Extreme Value distribution function coupled with the Gaussian Copula model to generate a series of similar random biases for all precipitation events. Then, the generated random biases were summed with the original satellite estimates to correct the associated biases. The bias-corrected precipitation for the training period was then compared to the original estimates of the satellite at the stations and the whole basin using the P-factor, R-factor, Bias, RMSE, and CC statistics. The statistics show that the random biases generated by the Copula method for the monthly CHIRPS satellite data relative to the 14-year training period have reduced the error rate of the satellite data by 74 to 95 percent when compared to observations. The satellite precipitation estimates of the 11-year test period were also corrected using the generated random biases in the training period. The results show that the bias correction considerably improved the monthly estimates and reduced the error rate of the satellite estimation by about 76 percent. In general, the simulation of the satellite precipitation with the Gaussian Copula model was performed satisfactorily at the monthly time scale, but it was less efficient at the daily time scale.

3

Satellite-based streamflow simulation using CHIRPS satellite precipitation product in Shah Bahram Basin, Iran

Shirin Mokhtari, Ahmad Sharafati, Tayeb Raziei

Acta Geophysica

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2022

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Vol. 70, no 1

385--398

EN

Precipitation is the most important climate variable in hydrological practices, so accurate estimation of its intensity and volume is very crucial for hydrological applications. Remote sensing precipitation estimations have recently been widely employed in water resources management due to the lack of observed precipitation measurements in remote areas. However, remote sensing precipitation estimations are not free from systematic errors. This study aims to bias-correct the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) satellite precipitation estimations using the Gaussian-Copula approach and illustrates how it improves the simulated flow characteristics in the Shah Bahram basin in Kohgiluyeh and Boyer-Ahmad Province, southwestern Iran. The Nash-Sutclif Efciency (NSE) calculated between the original CHIRPS precipitation estimation and observation in the Shah Bahram basin equals −0.14; however, when bias-corrected CHIRPS data was compared to observation, the NSE increased to 0.23, suggesting about 158% improvement in the CHIRPS precipitation estimation when bias-corrected with the Gaussian-Copula approach. Next, the bias-corrected precipitation time series were utilized as the hydrologic modeling system inputs to simulate flow specifications such as discharge and peak value. Then, the simulation of the flow parameters was carried out with both original and bias-corrected CHIRPS satellite precipitation estimations and the ground-based precipitation. Though the NSE statistic of the simulation for the testing period has not changed significantly, the Pbias statistic has considerably improved. The result of the study indicates the good performance of the proposed bias correction approach in reducing the CHIRPS satellite estimations errors, concluding that it is a suitable approach for bias correction of the other satellite precipitation estimations in areas that suffer from the lack of ground-based observations necessary for food forecasting and other hydrological practices.

4

Performance of bias corrected monthly CMIP6 climate projections with diferent reference period data in Turkey

Oruc Sertac

Acta Geophysica

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2022

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Vol. 70, no 2

777--789

EN

Decisions that are based on the future climate data, and its consequences are significantly important for many sectors such as water, agriculture, built environment, however, the performance of model outputs have direct influence on the accuracy of these decisions. This study has focused on the performance of three bias correction methods, Delta, Quantile Mapping (QM) and Empirical Quantile Mapping (EQM) with two reference data sets (ERA and station-based observations) of precipitation for 5 single CMIP6 GCM models (ACCESS-CM2, CNRM-CM6-1-HR, GFDL-ESM4, MIROC6, MRI-ESM2-0) and ensemble mean approach over Turkey. Performance of model-bias correction method-reference data set combinations was assessed on monthly basis for every single station and regionally. It was shown that performance of GCM models mostly affected by the region and the reference data set. Bias correction methods were not detected as effective as the reference data set over the performance. Moreover, Delta method outperformed among the other bias correction techniques for the computation that used observation as reference data while the difference between bias correction methods was not significant for the ERA based computations. Besides ensemble approach, MIROC6 and MRI-ESM2-0 models were selected as the best performing models over the region. In addition, selection of the reference data sets also found to be a dominant factor for the prediction accuracy, 65% of the consistent performance at the stations achieved by the ERA reference used bias correction approaches.

5

Stanowisko do badań przepływu za elementami armatury hydraulicznej, zaburzającymi przepływ

Synowiec P., Piechota P., Wędrychowicz W., Andruszkiewicz A.

Elektronika : konstrukcje, technologie, zastosowania

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2018

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Vol. 59, nr 10

53--55

PL

Tematyka artykułu dotyczy stanowiska przeznaczonego do badań przepływu za elementami armatury hydraulicznej zaburzającymi przepływ. Badania wykonywane są na specjalnym stanowisku, przystosowanym do wykonania przepływu przy pomocy różnego rodzaju przepływomierzy. Wszystkie zastosowane na stanowisku rodzaje przepływomierzy mają zastosowanie w przemyśle, ale do tej pory nie określono błędu jakim są obarczone przy niezastosowaniu zaleceń montażowych. Celem aktualnych badań jest określenie błędu pomiarowego przepływomierzy ultradźwiękowych z głowicami nakładanymi na rurociąg, kiedy pomiar wykonywany w różnych płaszczyznach rurociągu jest za łukiem hamburskim o promieniu równym dwóm średnicom nominalnym rurociągu. Wykonano pomiar w różnych odległościach od łuku hamburskiego oraz w różnych położeniach głowic ultradźwiękowych na obwodzie rurociągu. Głowice zostały usytuowane na rurociągu co 30 stopni, tzn. pod kątem 0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300 i 330 stopni.

EN

This Article applies stand for flow tests after hydraulic fittings, that disturb flow. The tests are carried out on special stand, adapted to use various types of flowmeter. All types of flowmeters used to on these stand are generaly use in industry, but to this time the measurement error is not specify when the mounting recommendations were not use. The aim of actually research is determine of measurement error of ultrasonic flowmeters with clamp-on sensor on pipeline, when measure in different after short radius bend 90° with radius is two nominal dimension. The measurement made at different distances after diffuser at different positions of ultrasonic sensors around the circumference on the pipe. The heads are arranged on pipeline at 30 degrees, for example at 0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300 and 330 degrees.

6

Influence of climate change on flood magnitude and seasonality in the Arga River catchment in Spain

Garijo C., Mediero L.

Acta Geophysica

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2018

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Vol. 66, no. 4

769--790

EN

Climate change projections suggest that extremes, such as floods, will modify their behaviour in the future. Detailed catchment-scale studies are needed to implement the European Union Floods Directive and give recommendations for flood management and design of hydraulic infrastructure. In this study, a methodology to quantify changes in future flood magnitude and seasonality due to climate change at a catchment scale is proposed. Projections of 24 global climate models are used, with 10 being downscaled by the Spanish Meteorological Agency (Agencia Estatal de Meteorologı´a, AEMET) and 14 from the EURO-CORDEX project, under two representative concentration pathways (RCPs) 4.5 and 8.5, from the Fifth Assessment Report provided by the Intergovernmental Panel on Climate Change. Downscaled climate models provided by the AEMET were corrected in terms of bias. The HBV rainfall-runoff model was selected to simulate the catchment hydrological behaviour. Simulations were analysed through both annual maximum and peaks-over-threshold (POT) series. The results show a decrease in the magnitude of extreme floods for the climate model projections downscaled by the AEMET. However, results for the climate model projections downscaled by EURO-CORDEX show differing trends, depending on the RCP. A small decrease in the flood magnitude was noticed for the RCP 4.5, while an increase was found for the RCP 8.5. Regarding the monthly seasonality analysis performed by using the POT series, a delay in the flood timing from late-autumn to late-winter is identified supporting the findings of recent studies performed with observed data in recent decades.

7

Wielopłaszczyznowy pomiar strumienia objętości cieczy jednofazowej za dyfuzorem w badaniach bilansowych instalacji hydraulicznych : pierwsza ćwiartka rurociągu

Synowiec P., Wędrychowicz W., Andruszkiewicz A.

Elektronika : konstrukcje, technologie, zastosowania

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2016

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Vol. 57, nr 10

91--93

PL

Tematyka artykułu dotyczy ultradźwiękowych pomiarów strumienia objętości w badaniach bilansowych instalacji hydraulicznych. Rozpatrywanym problemem jest wykonanie pomiaru za dyfuzorem w różnych płaszczyznach rurociągu poziomego. Wykonano pomiar w różnych odległościach od dyfuzora oraz w różnych położeniach głowic ultradźwiękowych na obwodzie rurociągu. Głowice zostały usytuowane w pierwszej ćwiartce rurociągu co 30 stopni, tzn. pod kątem 0, 30, 60 i 90 stopni. Wykonano obliczenia odchylenia standardowego oraz współczynnika poprawkowego eliminującego błędy wskazania przepływomierza, związane z występującymi zaburzeniami.

EN

This Article applies ultrasonic measurement of the flow rate in the study of balance sheet hydraulic system. Considered problem is to measure the diffuser in different planes of horizontal pipeline. The measurement made at different distances after diffuser at different positions of ultrasonic probes around the circumference on the pipe. The heads are arranged in the first quadrant of the pipeline at 30 degrees, for example at 0, 30, 60 and 90 degrees. Taken calculate the standard deviation and coefficient of correction to eliminate errors indicate flowmeter related from occurring disorders.

8

Short Term Load Forecasting Based on WLS-SVR and TGARCH Error Correction Model in Smart Grid

Hou L., Yang S., Wang X., Shen J.

Przegląd Elektrotechniczny

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2013

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R. 89, nr 3b

170--175

EN

Smart grid is the main development goal of future power grid while the short-term load forecasting is the significant premise of making management, power supply and trading plan in market circumstance. The forecasting accuracy directly determined the safety and economy of electric system. Support Vector Machines (SVM), as the new machine learning method, has applied successfully to short-termed load forecasting. However, research finds out that the singular points of the initial data have impact on forecasting accuracy. So in this paper, firstly, based on the analysis of SVM, we render Weighted Least Square and Support Vector Regression (WLS-SVR) applying to short-termed load forecasting, which overcomes the disadvantage of singular points. Secondly, we offer Threshold Generalized Autoregressive Conditional Heteroskedasticity (TGARCH) model to construct error prediction model to modify the initial predicted value. Finally, according to the PJM historical data, we get the results showing that the accuracy is greatly improving by implementing our methods which makes our methods founded.

PL

W artykule przedstawiono model przewidywania krótkookresowego obciążenia sieci elektroenergetycznej. W proponowanym rozwiązaniu wykorzystano metodę SVM (ang. Support Vector Machine). W celu eliminacji istniejącego wpływu wartości syngularnych na dokładność wyniku, zastosowano regresję ze średnią ważoną. Dodatkowo wykorzystano model TGARCH w określaniu błędów predykcji. Przedstawiono wyniki badań weryfikacyjnych, przeprowadzonych na rzeczywistych danych.

9

Korekcja funkcji przetwarzania czujnika stosowanego w tomografii pojemnościowej

Rząsa R. M.

Pomiary Automatyka Kontrola

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2010

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R. 56, nr 8

851-854

PL

Tomografia procesowa coraz częściej znajduje zastosowanie w badaniach eksperymentalnych różnych procesów przemysłowych. Jednym z rozwiązań jest tomograf pojemnościowy. Niejednokrotnie jest on wykorzystywany do badania przepływów dwufazowych. Początkowo tomografy były stosowane do wyznaczania obrazu struktury przepływu. Obecnie tomograf może być przyrządem pomiarowym który poza wyświetleniem obrazu struktury może wyznaczyć podstawowe parametry opisujące proces. Aby było możliwe dokonanie pomiarów konieczne jest odpowiednie wzorco-wanie urządzenia. Na wynik pomiaru ma wpływ szereg pojemności, pochodzących od elementów znajdujących się w bezpośrednim sąsiedztwie elektrod pomiarowych. Ze względu na budowę tomografu pewne błędy są nieuniknione. W celu zredukowania ich wpływu zaproponowano metodę korekcji funkcji przetwarzania dla typowego czujnika tomografu pojemnościowego. W pracy przedstawiono podstawy teoretyczne i wyniki badań eksperymentalnych. Niniejsze opracowanie może mieć również zastosowanie w innych urządzeniach pomiarowych, których zasada działania oparta jest na pomiarze małych zmian pojemności.

EN

Processing tomography is more and more often applied to tests of various industrial processes. The capacitance tomograph is one of measuring systems often used for tests of two-phase flows. Tomographs were previously used for determination of the flow structure images. At present they can be measuring devices which not only express the structure image but can be used for calculations of the basic parameters describing the process. In order to take measurements, it is necessary to calibrate the tomograph. Capacitances of elements being close to the measurement electrodes influence the measurement results. Some errors cannot be avoided. Thus, the correction method was proposed for measurements with the capacitance tomograph. The paper presents the theoretical basis and the test results obtained with this method. This method can also be used in other measuring devices for measurements of small capacitance changes.