PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Preliminary assessment of ADIS16470AMLZ sensor for monitoring of seismic activity in mining area

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Seismic activity monitoring in the mining exploitation area is an important factor, that has an effect on safety and infrastructure management. The introduction sections presents the outline of mining interference into rock mass structure and selected parameters and methods of observation related to its effects. Further in the article an alternative to currently seismic measurement devices was proposed, and an preliminary research of its metrological quality was carried out based on experimental data. Assessment was based on short time Fourier transform (STFT) and Pearson cross-correlation coefficient.
Czasopismo
Rocznik
Strony
art. no. 2022404
Opis fizyczny
Bibliogr. 17 poz., rys., tab.
Twórcy
  • University of Warmia and Mazury in Olsztyn, Faculty of Technical Sciences, Oczapowskiego 11, 10-957 Olsztyn, Poland
autor
  • University of Warmia and Mazury in Olsztyn, Faculty of Technical Sciences, Oczapowskiego 11, 10-957 Olsztyn, Poland
  • Geotronics Dystrybucja Sp. z o.o., Centralna 36, 31-586 Kraków, Poland
  • University of Warmia and Mazury in Olsztyn, Faculty of Geoengineering, Institute of Geodesy and Civil Engineering, Oczapowskiego 1, 10-719 Olsztyn, Poland
Bibliografia
  • 1. Albarbar A, Badri A, Jyoti KS, Starr A. Performance evaluation of MEMS accelerometers. Measurement. 2009;42(5):790-795. https://doi.org/10.1016/j.measurement.2008.12.002.
  • 2. Caijun X, Zheng G, Jieming N. Recent developments in seismological geodesy. Geodesy and Geodynamics. 2016;(3):157-164. https://doi.org/10.1016/j.geog.2016.04.009.
  • 3. Cochran ES, Lawrence JF, Christensen C, Jakka RS. the Quake-catcher network: citizen science expanding seismic Horizons. Seismological Research Letters. 2009;80(1):26-30. http://dx.doi.org/10.1785/gssrl.80.1.26.
  • 4. Douglas J. Earthquake ground motion estimation using strong-motion records: a review of equations for the estimation of peak ground acceleration and response spectral ordinates. Earth-Science Reviews. 2003;61:43-104. https://doi.org/10.1016/S0012-8252(02)00112-5.
  • 5. Górnicza skala intensywności sejsmicznej GSI2004/18 dla wstrząsów górniczych w LGOM”. KGHM Cuprum. 2019.
  • 6. Jin S, Occhipinti G, Jin R. GNSS ionospheric seismology: Recent observation evidences and characteristics. Earth-Science Reviews. 2015; 147: 54-64. https://doi.org/10.1016/j.earscirev.2015.05.003.
  • 7. López Gayarre F, Álvarez-Fernández MI, GonzálezNicieza C, Álvarez-Vigil AE, Herrera García G. Forensic analysis of buildings affected by mining subsidence. Engineering Failure Analysis. 2010; 17(1):270-285. https://doi.org/10.1016/j.engfailanal.2009.06.008.
  • 8. Milligan DJ, Homeijer BD Walmsley RG. An ultralow noise MEMS accelerometer for seismic imaging. Sensors. 2011:1281-1284. http://dx.doi.org/10.1109/ICSENS.2011.6127185.
  • 9. Pisarenko VF, Lyubushin AA. Statistical estimation of maximum peak ground acceleration at a given point of a seismic region. Journal of Seismology. 1997;1:395-405. https://doi.org/10.1023/A:1009795503733.
  • 10. Snieder R, Miyazawa M, Slob E, et al. A Comparison of Strategies for Seismic Interferometry. Surveys in Geophysics. 2009;30:503-523. https://doi.org/10.1007/s10712-009-9069-z.
  • 11. Tronin AA. Satellite remote sensing in seismology. A review. Remote Sensing 2010; 2(1): 124-150. https://doi.org/10.3390/rs2010124.
  • 12. Varanis M, Silva A, Mereles A et al. MEMS accelerometers for mechanical vibrations analysis: a comprehensive review with applications. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 2018;40:527. https://doi.org/10.1007/s40430-018-1445-5.
  • 13. Yuanming S, Yun S, Peiliang X, Xiaoji N, Jingnan L. Error analysis of high-rate GNSS precise point positioning for seismic wave measurement. Advances in Space Research. 2017; 59(11): 2691-2713. https://doi.org/10.1016/j.asr.2017.02.006.
  • 14. Zhang L , Ren Y, Lin R, Song Z, Zeng X. Distributed acoustic sensing system and its application for seismological studies. Progress in Geophysics. 2020; 35(1):65-71. http://dx.doi.org/10.3997/1365-2397.2013034.
  • 15. Zhupeng Z, Hao Q, Zhichao W, Sujuan L, Ying L. Data fusion based multi-rate Kalman filtering with unknown input for on-line estimation of dynamic displacements. Measurement. 2019; 131: 211-218. https://doi.org/10.1016/j.measurement.2018.08.057.
  • 16. Salhi MS, Barhoumi El M, Lachiri Z. Effectiveness of RSOM neural model in detecting industrial anomalies. Diagnostyka. 2022;23(1):2022106. https://doi.org/10.29354/diag/146213.
  • 17. Maciuk K. Aging of ground Global Navigation Satellite System oscillators. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2022; 24(2):371-376. http://doi.org/10.17531/ein.2022.2.18.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-652ccae6-9f9d-4b58-a6b7-01212678e985
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.