Accuracy Characteristics of the Selected Diagnostics Methods and the Adjustment of Geodetic Observations

• Autorzy: Kulupa Martyna , Magda Paulina , Mrówczyńska Maria

Identyfikatory

DOI

10.2478/ceer-2021-0055

• Języki publikacji: EN

Abstrakty

EN

The article presents the results of the adjustment of the experimental horizontal geodetic network using the classical method and the estimation of strengths in identifying observations with gross error and analyzing the accuracy of the obtained results. The presented analyses were made considering the possibility of their use in implementation networks and measurement and control networks used for monitoring building structures. The paper's subject was a horizontal network established on the Morasko campus (Poznań). While creating it, the practical needs and economics of measurements were taken into account. The obtained results of numerical analyzes confirmed the benefits of using the methods of estimating strengths in the equalization process, which give satisfactory results in the case of outliers.

Słowa kluczowe

EN

geodetic observations; gross errors; robust estimation; horizontal network; accuracy analysis

PL

obserwacje geodezyjne; błędy; estymacja; osnowa pozioma; analiza dokładności

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: Civil and Environmental Engineering Reports
• Rocznik: 2021
• Tom: Vol. 31, no. 4
• Strony: 167--183
• Opis fizyczny: Bibliogr. 33 poz., fot., rys., tab., wykr.

Twórcy

autor

Kulupa Martyna

• Faculty of Geographical and Geological Sciences Adam Mickiewicz University, Poznań, Poland

autor

Magda Paulina

• Faculty of Geographical and Geological Sciences Adam Mickiewicz University, Poznań, Poland

autor

Mrówczyńska Maria

• Faculty of Civil Engineering, Architecture and Environmental Engineering, University of Zielona Góra, Poland

Bibliografia

• 1. Błaszczak-Bak, W et al. 2020. Automatic threat detection for historic buildings in dark places based on the modified OPTD method. ISPRS International Journal of Geo-Information 9, 123.
• 2. Borkowski, A and Jóźków, G 2006. Filtering of airborne laser scanning data using a moving polynomial surface model [in polish], Archiwum Fotogrametrii, Kartografii i Teledetekcji 16, 63-73.
• 3. Ćmielewski, K et al. 2021. Detection of crane track geometric parameters using UAS. Automation in Construction 128, 103751.
• 4. Duchnowski, R and Wiśniewski, Z 2011. Shift-Msplit estimation. Geodes and cartography 60(2), 79-97.
• 5. Gawronek, P et al. 2019. Measurements of the vertical displacements of a railway bridge using TLS technology in the context of the upgrade of the polish railway transport. Sensors 19(191), 4275.
• 6. Janicka, J. et al. 2020. Application of the Msplit Estimation Method in the Detection and Dimensioning of the Displacement of Adjacent Planes. Remote Sensing 12(19), 3203.
• 7. Juszczyk, M et al. 2014. Errors in the preparation of design documentation in public procurement in Poland. Procedia Engineering 85, 283-292.
• 8. Kadaj, R 1988. Eine verallgemeinerte Klasse von Schatzverfahren mit praktischen Anwendungen. Zeitschrift für Vermessungswesen 113(4), 157-166.
• 9. Kampczyk, A and Dybeł, K 2021. Integrating surveying railway special grid pins with terrestrial laser scanning targets for monitoring rail transport infrastructure. Measurement 170, 108729.
• 10. Kovanič, L et al. 2010. Geodetic surveying of crane trail space relations. Acta Montanistica Slovaca 15(3), 188-199.
• 11. Kulupa, M. 2021. Measurement and alignment of the implementation network established on the Morasko campus with diagnostics of gross errors in observations [in polish]. Praca dyplomowa, Uniwersytet im. Adama Mickiewicza w Poznaniu.
• 12. Kurnatowski, M 2020. Test of vibrations influence on the measurement accuracy in the precise digital leveller TRIMBLE DINI 03 and comparison of its vibration sensitivity with leveller NI 002. Civil and Environmental Engineering Reports 4(30), 111-124.
• 13. Leń, P et al. 2017. Methodology for Asessing the Size and Liquidation of the Outer Patchwork of Land. IOP Conference Series: Earth and Environmental Science Open Access 95(3), 032020.
• 14. Lv, S et al. 2021. Geometric algebra based least mean m-estimate robust adaptive filtering algorithm and its transient performance analysis. Signal Processing 189, 108235.
• 15. Magda, P 2021. Analysis of the accuracy of determining the coordinates of the points of the experimental geodetic network established on the Morasko campus [in polish]. Praca dyplomowa, Uniwersytet im. Adama Mickiewicza w Poznaniu.
• 16. Mrówczyńska, M 2011. Neural networks and neuro-fuzzy systems applied to the analysis of selected problems of geodesy. Computer Assisted Mechanics and Engineering Sciences 8(3), 161-173.
• 17. Mrówczyńska, M et al. 2020. Compression of results of geodetic displacement measurements using the PCA method and neural networks. Measurement: Journal of the International Measurement Confederation 158, 107693.
• 18. Mrówczyńska, M et al. 2021. Scenarios as a tool supporting decisions in urban energy policy: The analysis using fuzzy logic, multi-criteria analysis and GIS tools. Renewable and Sustainable Energy 137, 110598.
• 19. Mrówczyńska, M and Sztubecki J 2021. The network structure evolutionary optimization to geodetic monitoring in the aspect of information entropy. Measurement: Journal of the International Measurement Confederation 179, 109369.
• 20. Oleniacz, G et al. 2017. Survey of the Urban Bell in the Belfry of St. Trinity Church in Krosno. Reports on Geodesy and Geoinformatics 103(1), 38-45.
• 21. Rofatto, VF et al. 2020. A Monte Carlo-based outlier diagnosis method for sensitivity analysis. Remote Sensing 12(5), 860.
• 22. Skrzypczak, I et al. 2021. Interlaboratory Comparative Tests in Ready-Mixed Concrete Quality Assessment. Materials 14, 3475.
• 23. Smaczyński, M et al. 2020. The land use mapping techniques (Including the areas used by pedestrians) based on low-level aerial imagery. ISPRS International Journal of Geo-Information 9(12), 754.
• 24. Sztubecki, J et al. 2018. A hybrid method of determining deformations of engineering structures with a laser station and a 3D scanner. Civil and Environmental Engineering Reports 28(2), 177-185.
• 25. Sztubecki, J et al. 2020. Displacement and deformation study of engineering structures with the use of modern laser technologies. Open Geosciences (Central European Journal of Geosciences - CEJG) 12(1), 354-362.
• 26. Vasundhara 2021. Sparsity aware affine-projection-like filtering integrated with robust set membership and M-estimate approach for acoustic feedback cancellation in hearing aids. Applied Acoustics 175, 107778.
• 27. Wiśniewski, Z 2005. Adjustment calculus in geodesy (with examples) [in Polish]. Wydawnictwo Uniwersytetu Warmińsko-Mazurskiego w Olsztynie, Olsztyn.
• 28. Wiśniewski, Z 2017. MP estimation applied to platykurtic sets of geodetic observations. Geodesy and Cartography 66(1), 117-135.
• 29. Wittwer, T 2018. Automatisierte Gleisvermessung in Punktwolken vom mobilen Laserscanning. ZFV Zeitschrift für Geodäsie, Geoinformation und Landmanagement, 143, 109-113.
• 30. Wyszkowska, P and Duchnowski, R 2020. Performance of M split estimates in the context of vertical displacement analysis. Journal of Applied Geodesy 14(20), 149-158.
• 31. Wyszkowska, P and Duchnowski, R 2020. Iterative Process of M split (q) Estimation. Journal of Surveying Engineering 146(3), 06020002.
• 32. Zaczek-Peplinska, J and Osińska-Skotak, K 2018. Concrete surface evaluation based on the reflected TLS laser beam's intensity image classification. Studia Geotechnica et Mechanica 40(1), 56-64.
• 33. Zięba, Z et al. 2020. Built environment challenges due to climate change. IOP Conference Series: Earth and Environmental 609(115), 165782.