Tytuł artykułu
Treść / Zawartość
Pełne teksty:
Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Contemporary mine exploitation requires information about the deposit itself and the impact of mining activities on the surrounding surface areas. In the past, this task was performed using classical seismic and geodetic measurements. Nowadays, the use of new technologies enables the determination of the necessary parameters in global coordinate systems. For this purpose, the relevant services create systems that integrate various methods of determining interesting quantities, e.g., seismometers / GNSS / PSInSAR. These systems allow detecting both terrain deformations and seismic events that occur as a result of exploitation. Additionally, they enable determining the quantity parameters that characterise and influence these events. However, such systems are expensive and cannot be set up for all existing mines. Therefore, other solutions are being sought that will also allow for similar research. In this article, the authors examined the possibilities of using the existing GNSS infrastructure to detect seismic events. For this purpose, an algorithm of automatic discontinuity detection in time series “Switching Edge Detector” was used. The reference data were the results of GNSS measurements from the integrated system (seismic / GNSS / PSInSAR) installed on the LGCB (Legnica-Głogów Copper Belt) area. The GNSS data from 2020 was examined, for which the integrated system registered seven seismic events. The switching Edge Detector algorithm proved to be an efficient tool in seismic event detection.
Wydawca
Czasopismo
Rocznik
Tom
Strony
317--332
Opis fizyczny
Bibliogr. 45 poz., rys., tab., wykr.
Twórcy
autor
- University of Warmia and Mazury in Olsztyn, Faculty of Geoengineering, Institute of Geodesy and Civil Engineering, 2 Oczapowskiego Str., Olsztyn, 10-900, Poland
autor
- University of Warmia and Mazury in Olsztyn, Faculty of Geoengineering, Institute of Geodesy and Civil Engineering, 2 Oczapowskiego Str., Olsztyn, 10-900, Poland
autor
- KGHM CUPRUM Sp. z.o.o. Research and Development Centre, gen. W. Sikorskiego Street 2-8, Wrocław, 53-659, Poland
autor
- University of Warmia and Mazury in Olsztyn, Faculty of Technical Sciences, Chair of Mechatronics, 2 Oczapowskiego Str., Olsztyn, 10-900, Poland
Bibliografia
- [1] A. Borghi, L. Cannizzaro, A. Vitti, Advanced techniques for discontinuity detection in GNSS coordinate timeseries. An Italian case study. Geodesy for Planet Earth, 627-634 (2012). DOI: https://doi.org/10.1007/978-3-642-20338-1_77.
- [2] A.H.M. Ng, L. Ge, K. Zhang, H.C. Chang, X. Li, C. Rizos, M. Omura, Deformation mapping in three dimensions for underground mining using InSAR-Southern highland coalfield in New South Wales, Australia. International Journal of Remote Sensing 32 (22), 7227-7256 (2011). DOI: https://doi.org/10.1080/01431161.2010.519741.
- [3] A. Leśniak, Z. Isakow, Space-time clustering of seismic events and hazard assessment in the Zabrze-Bielszowice coal mine, Poland. International Journal of Rock Mechanics and Mining Sciences 46 (5), 918-928 (2009). DOI: https://doi.org/10.1016/j.ijrmms.2008.12.003.
- [4] A. Nairac, N. Townsend, R. Carr, S. King, P. Cowley, L. Tarassenko, A system for the analysis of jet engine vibration data. Integrated Computer-Aided Engineering 6 (1), 53-66 (1999). DOI: https://doi.org/10.5555/1275794.1275800.
- [5] B. Antonielli, A. Sciortino, S. Scancella, F. Bozzano, P. Mazzanti. Tracking Deformation Processes at the Legnica Glogow Copper District (Poland) by Satellite InSAR – I: Room and Pillar Mine District. Land 10 (6), 653 (2021). DOI: https://doi.org/10.3390/land10060653.
- [6] C.M. Bishop, Novelty detection and neural network validation. IEEE Proceedings-Vision, Image and Signal Processing 141 (4), 217-222 (1994). DOI: https://doi.org/10.1049/ip-vis:19941330.
- [7] C. Volksen, J. Wassermann, Recent crustal deformation and seismicity in Southern Bavaria revealed by GNSS observations. Proceedings of the EUREF Symposium. 29-31 (2013).
- [8] D.A. Smith, A quantitative method for the detection of edges in noisy timeseries. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 353 (1378), 1969-1981 (1998). DOI: https://doi.org/10.1098/rstb.1998.0348.
- [9] D.B. Skalak, Prototype and feature selection by sampling and random mutation hill climbing algorithms. Machine Learning Proceedings 293-301 (1994). DOI: https://doi.org/10.5555/3091574.3091610.
- [10] D. Dasgupta, S. Forrest, Novelty detection in time series data using ideas from immunology. Proceedings of the international conference on intelligent systems 82-87 (1996).
- [11] D. Geudtner, R. Torres, P. Snoeij, M. Davidson, B. Rommen, Sentinel-1 System capabilities and applications. IEEE Geoscience and Remote Sensing Symposium 1457-1460 (2014). DOI: https://doi.org/10.1109/IGARSS.2014.6946711.
- [12] D. Massonnet, M. Rossi, C. Carmona et al. The displacement field of the Landers earthquake mapped by radar interferometry. Nature. 364, 138-142 (1993). DOI: https://doi.org/10.1038/364138a0.
- [13] F. Grigoli, S. Cesca, E. Priolo, A.P. Rinaldi, J.F. Clinton, T.A. Stabile, B. Dost, M. Garcia Fernandez, S. Wiemer, T. Dham, Current challenges in monitoring, discrimination and management of induced seismicity related to underground industrial activities: a European perspective. Reviews of Geophysics 55 (4), (2017). DOI: https://doi.org/10.1002/2016RG000542.
- [14] F. Ma, H. Zhao, Y. Zhang, J. Guo, A. Wei, Z. Wu, Y. Zhang, GPS monitoring and analysis of ground movement and deformation induced by transition from open-pit to underground mining. Journal of Rock Mechanics and Geotechnical Engineering 4 (1), 82-87 (2012). DOI: https://doi.org/10.3724/SP.J.1235.2012.00082.
- [15] F.E. Grubbs, Procedures for detecting outlying observations in Samples. Technometrics 11, 1-21 (1969). DOI: http://dx.doi.org/10.1080/00401706.1969.10490657.
- [16] G. Herrera, R. Tomás, F. Vicente, J.M. Lopez-Sanchez, J.J. Mallorquí, J. Mulas, Mapping ground movements in open pit mining areas using differential SAR interferometry. International Journal of Rock Mechanics and Mining Sciences 47 (7), 1114-1125 (2010). DOI: https://doi.org/10.1016/j.ijrmms.2010.07.006.
- [17] H.D. Fan, G. Wei, Q. Yong, J.Q. Xue, B.Q. Chen, A model for extracting large deformation mining subsidence using D-InSAR technique and probability integral method. Transactions of Nonferrous Metals Society of China 24 (4), 1242-1247 (2014). DOI: https://doi.org/10.1016/S1003-6326(14)63185-X.
- [18] I. Kudłacik, J. Kapłon, G. Lizurek, M. Crespi, G. Kurpiński. High-rate GPS positioning for tracing anthropogenic seismic activity: The 29 January 2019 mining tremor in Legnica-Głogów Copper District, Poland. Measurement 168 (2021). DOI: https://doi.org/10.1016/j.measurement.2020.108396.
- [19] J. Gazeaux, S. Williams, M. King, M. Bos, R. Dach, M. Deo, F.N. Teferle, Detecting offsets in GPS time series: First results from the detection of offsets in GPS experiment. Journal of Geophysical Research: Solid Earth 118 (5), 2397-2407 (2013). DOI: https://doi.org/10.1002/jgrb.50152.
- [20] J. Laurikkala, M. Juhola, E. Kentala, N. Lavrac, S. Miksch, B. Kavsek, Informal identification of outliers in medical data. Intelligent data analysis in medicine and pharmacology 1, 20-24 (2000).
- [21] J. Paziewski, G. Kurpinski, P. Wielgosz, L. Stolecki, R. Sieradzki, M. Seta, F. Martin-Porqueras, Towards Galileo+ GPS seismology: Validation of high-rate GNSS-based system for seismic events characterisation. Measurement 166, 108236 (2020). DOI: https://doi.org/10.1016/j.measurement.2020.108236.
- [22] J. Rapiński, K. Kowalczyk, Detection of discontinuities in the height component of GNSS time series. Acta Geodynamica et Geomaterialia 13 (3), 315-320 (2016). DOI: https://doi.org/10.13168/AGG.2016.0013.
- [23] K. Kowalczyk, J. Rapiński, Verification of a GNSS Time Series Discontinuity Detection Approach in Support of the Estimation of Vertical Crustal Movements. ISPRS Int. J. Geo-Inf. 7, 149 (2018). DOI: https://doi.org/10.3390/ijgi7040149.
- [24] K. Tretyak, S. Dosyn, Study of vertical movements of the European crust using tide gauge and GNSS observations. Reports on Geodesy and Geoinformatics 97 (1), 112-131 (2015). DOI: https://doi.org/10.2478/rgg-2014-0016.
- [25] L. Ge, C. Rizos, S. Han, H. Zebker, Mining subsidence monitoring using the combined InSAR and GPS approach. Proceedings of the 10th International Symposium on Deformation Measurements. 1-10 (2001).
- [26] L. Stolecki, Badania rozkładów parametrów drgań generowanych wstrząsami górniczymi w kopalniach LGOM. CUPRUM Czasopismo Naukowo-Techniczne Górnictwa Ród 3 (60), 29-37 (2011).
- [27] L. Stolecki, W. Grzebyk, The velocity of roof deflection as an indicator of underground workings stability – Case study from polish deep copper mines. International Journal of Rock Mechanics and Mining Sciences 143 (2021).
- [28] Ł. Rudziński, S. Lasocki, B. Orlecka‐Sikora, J. Wiszniowski, D. Olszewska, J. Kokowski, J. Mirek, Integrating Data under the European Plate Observing System from the Regional and Selected Local Seismic Networks in Poland. Seismological Research Letters 92 (3), 1717-1725 (2021). DOI: https://doi.org/10.1785/0220200354.
- [29] M.C. Cuenca, A.J. Hooper, R.F. Hanssen, Surface deformation induced by water influx in the abandoned coal mines in Limburg, The Netherlands observed by satellite radar interferometry. Journal of Applied Geophysics 88, 1-11 (2013). DOI: https://doi.org/10.1016/j.jappgeo.2012.10.003.
- [30] M.D.G. Salamon, G.A. Wiebols, Digital location of seismic events by an underground network of seismometers using the arrival times of compressional waves. Rock Mechanics 6 (3), 141-166 (1974). DOI: https://doi.org/10.1007/BF01238422.
- [31] M. Ester, H.P. Kriegel, J. Sander, X. Xu, A density-based algorithm for discovering clusters in large spatial databases with noise. Kdd. 96, 226-231 (1996). DOI: https://doi.org/10.5555/3001460.3001507.
- [32] M. Ilieva, P. Polanin, A. Borkowski, P. Gruchlik, K. Smolak, A. Kowalski, W. Rohm, Mining deformation life cycle in the light of InSAR and deformation models. Remote Sensing 11 (7), 745 (2019). DOI: https://doi.org/10.3390/rs11070745.
- [33] N. Perfetti, Detection of station coordinate discontinuities within the Italian GPS Fiducial Network. Journal of Geodesy 80 (7), 381-396 (2006). DOI: https://doi.org/10.1007/s00190-006-0080-6.
- [34] P. Datta, D. Kibler, Learning prototypical concept descriptions. Machine Learning Proceedings 158-166 (1995). DOI: https://doi.org/10.1016/b978-1-55860-377-6.50028-1.
- [35] P.J. Rousseeuw, A.M. Leroy, Robust regression and outlier detection 589, 2005 John Wiley & Sons.
- [36] R. Baryła, J. Paziewski, P. Wielgosz, K. Stepniak, M. Krukowska, Accuracy assessment of the ground deformation monitoring with the use of GPS local network: open pit mine Koźmin case study. Acta Geodynamica et Geomaterialia 11 (4), (2014). DOI: https://doi.org/10.13168/AGG.2014.0013.
- [37] S.H. Chung, R.A. Kennedy, Forward-backward non-linear filtering technique for extracting small biological signals from noise. Journal of Neuroscience Methods 40 (1), 71-86 (1991). DOI: https://doi.org/10.1016/0165-0270(91)90118-j.
- [38] S. Roberts, L. Tarassenko, A probabilistic resource allocating network for novelty detection. Neural Computation 6 (2), 270-284 (1994). DOI: https://doi.org/10.1162/neco.1994.6.2.270.
- [39] T. Kohonen, Exploration of very large databases by self-organizing maps. Proceedings of international conference on neural networks 1, (1997). DOI: https://doi.org/10.1109/ICNN.1997.611622.
- [40] V. Barnett, T. Lewis, Outliers in statistical data. 1984 John Wiley & Sons, Singapore. DOI: https://doi.org/10.1002/bimj.4710300725.
- [41] W. Milczarek, J. Blachowski, P. Grzempowski, Application of PSInSAR for assessment of surface deformations in post-mining area – case study of the former Walbrzych hard coal basin (SW Poland). Acta Geodynamica et Geomaterialia 14 (1), 41-52 (2017). DOI: https://doi.org/10.13168/AGG.2016.0026.
- [42] W. Stefansky, Rejecting outliers in factorial designs. Technometrics 14, 469-479 (1972).
- [43] Y. Guéguen, B. Deffontaines, B. Fruneau, M. Al Heib, M. de Michele, D. Raucoules, J. Planchenaul, Monitoring residual mining subsidence of Nord/Pas-de-Calais coal basin from differential and Persistent Scatterer Interferometry (Northern France). Journal of Applied Geophysics 69 (1), 24-34 (2009). DOI: https://doi.org/.1016/j.appgeo.2009.02.008.
- [44] T. Veikkolainen, J. Kortström, T. Vuorinen, I. Salmenperä, T. Luhta, P. Mäntyniemi,T. Tiira. The Finnish national seismic network: Toward fully automated analysis of low‐magnitude seismic events. Seismological Research Letters 92 (3), 1581-1591 (2021).
- [45] Z. Szczerbowski, J. Jura, Mining induced seismic events and surface deformations monitored by GPS permanent stations. Acta Geodynamica et Geomaterialia 12 (3), 237-248 (2015). DOI: https://doi.org/10.13168/AGG.2015.0023.
Uwagi
PL
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-dbc83bb1-f387-406a-8ade-d4be4310dff0