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The article focuses on the possibility of using a new method based on predicting the hydrogen maser frequency drift to control the Polish Time Scale UTC(PL). Controlling the national UTC(k) time scale is very important due to the fact that the scale is also the basis for determining the official time in a given country, and is also used in scientific research and the economy. The article describes in detail the new UTC(PL) steering method based on predicting the hydrogen maser frequency drift, and a number of research that has been carried out. The obtained preliminary results of the research on the use of the new UTC(PL) predicting method clearly showed the great potential of the presented method. The obtained residuals are within the range of ±0.73 ns, which indicates a very good quality of predicting as compared with type A uncertainties of UTC(PL) input points. It may allow UTC(PL) to be classified as one of the best time scales. Nevertheless, the method has its imperfections, which the authors plan to eliminate as part of further work on improving the method.
Czasopismo
Rocznik
Tom
Strony
1--12
Opis fizyczny
Bibliogr. 24 poz., rys., tab., wykr., wzory
Twórcy
autor
- University of Zielona Gora, Institute of Metrology, Electronics and Computer Science, Szafrana 2 Str., 65-516 Zielona Gora, Poland
autor
- University of Zielona Gora, Institute of Metrology, Electronics and Computer Science, Szafrana 2 Str., 65-516 Zielona Gora, Poland
autor
- Central Office of Measures, Time and Length Department, Elektoralna 2 Str., 00-139 Warsaw, Poland
autor
- Central Office of Measures, Time and Length Department, Elektoralna 2 Str., 00-139 Warsaw, Poland
autor
- Central Office of Measures, Time and Length Department, Elektoralna 2 Str., 00-139 Warsaw, Poland
Bibliografia
- [1] Bureau International des Poids et Mesures (2020). BIPM Annual Report on Time Activities, 15.
- [2] Bureau International des Poids et Mesures. BIPM Circular T. https://webtai.bipm.org/ftp/pub/tai/Circular-T/cirt/ (access 21.08.2024)
- [3] Marszalec, M., Lusawa, M. & Osuch, T. (2021). Efficient frequency jumps detection algorithm for atomic clock comparisons. Metrology and Measurement Systems, 28(1), pp. 107-121. https://doi.org/10.24425/mms.2021.135996
- [4] Czubla, A., Konopka, J. & Nawrocki, J. (2006). Realization of atomic SI second definition in context UTC(PL) and TA(PL). Metrology and Measurement Systems, 13(2), pp. 149-159. http://www.metrology.pg.gda.pl/full/2006/M&MS_2006_149.pdf
- [5] Panfilo, G., & Tavella, P. (2008). Atomic clock prediction based on stochastic differential equations. Metrologia, 45(5). https://doi.org/10.1088/0026-1394/45/6/S16
- [6] Bernier, L. G. (2003). Use of the Allan Deviation and Linear Prediction for the Determination of the Uncertainty on Time Calibrations Against Predicted Timescales. IEEE Transactions on Instrumentation and Measurement, 52(2), 483-486. https://doi.org/10.1109/TIM.2003.810015
- [7] Kaczmarek J., Miczulski W., KoziołM., and Czubla A. (2013). Integrated system for monitoring and control of the national time and frequency standard. IEEE Transactions on Instrumentation and Measurement, 62(10), 2828-2838. https://doi.org/10.1109/TIM.2013.2259751
- [8] Miczulski, W., & Sobolewski, Ł. (2012). Influence of the GMDH Neural Network Data Preparation Method on UTC(PL) correction prediction results. Metrology and Measurement Systems, 19(1). https://doi.org/10.2478/v10178-012-0011-1
- [9] Bureau International des Poids et Mesures. BIPM UTC Rapid. https://webtai.bipm.org/ftp/pub/tai/Rapid-UTC/utcr/ (access 21.08.2024)
- [10] Miczulski, W., & Sobolewski, Ł. (2017). Algorithm for predicting [UTC–UTC(k)] by means of neural networks. IEEE Transactions on Instrumentation and Measurement, 66(7), 2136-2142. https://doi.org/10.1109/TIM.2017.2674778
- [11] Sobolewski, Ł., & Miczulski, W. (2021). Methods of Constructing Time Series for Predicting Local Time Scales by Means of a GMDH-Type Neural Network. Applied Sciences, 11(12). https://doi.org/10.3390/app11125615
- [12] Sobolewski, Ł., Miczulski, W., & Czubla, A. (2021). Experimental Verification of the Neural Network Predicting Procedure Applied for UTC(PL). IEEE Transactions on Instrumentation and Measurement, 70(7), 1-9. https://doi.org/10.1109/TIM.2021.3116297
- [13] Johnson, E. H., & McGunigal, T. E. (1966). Hydrogen maser frequency comparison with a cesium beam standard, National Aeronautics and Space Administration, Washington D.C.
- [14] Peters, H. E., Holloway, J., Bagley, A. S., & Cutler, L. S. (1965). Hydrogen maser and cesium beam tube frequency standards comparison. Applied Physics Letters, 6(2), 34-35.
- [15] Major, F. G. (2013). The Quantum Beat - The Physical Principles of Atomic Clocks. Springer, New York.
- [16] Haibo, Y., Lili, Q., Shaowu, D., Wei L., & Hong, Z. (2009). The hydrogen maser and cesium clocks in time keeping at NTSC. Proc. 2009 IEEE International Frequency Control Symposium Joint with the 22nd European Frequency and Time forum, Apr. 2009, pp. 42-46.
- [17] Kamas, G., & Lombardi, M. (1990). Time and Frequency User’s Manual, NIST Special Publication.
- [18] Sobolewski, Ł. (2017). Application of GMDH type neural network for predicting UTC(k) timescales realized on the basis of hydrogen masers. Proc. Joint IEEE (FCS EFTF), Jul. 2017, pp. 42-46.
- [19] Barnes, J. A. (1983, December). The measurement of linear frequency drift in oscillators. In Proceedings of the 15th Annual Precise Time and Time Interval Systems and Applications Meeting.
- [20] Kartaschoff, P. (1985). Częstotliwość i czas, Wydawnictwo Komunikacji i Łączności (in Polish).
- [21] Panfilo G., Harmegnies A. and Tisserand L. (2012). A new prediction algorithm for the generation of International Atomic Time. Metrologia 49, https://doi.org/10.1088/0026-1394/49/1/008
- [22] Bureau International des Poids et Mesures. CCTF WGMRA Guideline 4 (201209) Uncertainty in frequency https://www.bipm.org/documents/20126/30132341/cc-publication-ID-310/f15432f2-cfa7-ac71-bd9d-a6f3168affb4 (access 10.01.2025)
- [23] Pindyck, R. S., Rubinfeld, D. C. (1998). Econometric Models and Economic Forecasts. Boston, MA, USA: McGraw-Hill, 1998.
- [24] Caldwell, R. B. (1995). Performance metrics for neural network-based trading system development. NeuroVestJournal, 3(2), 22-26.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8270b887-b5da-48f1-a2c2-3e9b312c8706
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