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Type A Standard Uncertainty of Long-Term Noise Indicators

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The problem of estimation of the long-term environmental noise hazard indicators and their uncer- tainty is presented in the present paper. The type A standard uncertainty is defined by the standard deviation of the mean. The rules given in the ISO/IEC Guide 98 are used in the calculations. It is usually determined by means of the classic variance estimators, under the following assumptions: the normality of measurements results, adequate sample size, lack of correlation between elements of the sample and observation equivalence. However, such assumptions in relation to the acoustic measurements are rather questionable. This is the reason why the authors indicated the necessity of implementation of non-classical statistical solutions. An estimation idea of seeking density function of long-term noise indicators distri- bution by the kernel density estimation, bootstrap method and Bayesian inference have been formulated. These methods do not generate limitations for form and properties of analyzed statistics. The theoretical basis of the proposed methods is presented in this paper as well as an example of calculation process of expected value and variance of long-term noise indicators LDEN and LN. The illustration of indicated solutions and their usefulness analysis were constant due to monitoring results of traffic noise recorded in Cracow, Poland.
Rocznik
Strony
25--36
Opis fizyczny
Bibliogr. 30 poz., rys., tab., wykr.
Twórcy
autor
  • AGH University of Science and Technology al. Mickiewicza 30, 30-059 Kraków, Poland
autor
  • AGH University of Science and Technology al. Mickiewicza 30, 30-059 Kraków, Poland
Bibliografia
  • 1. Batko W., Pawlik P. (2012), New approach to the uncertainty assessment of acoustic effects in the environment, Archives of Acoustics, 37, 1, 57–61.
  • 2. Batko W., Przysucha B. (2010), Determination of the probability distribution of the mean sound level, Archives of Acoustics, 35, 4, 543–550.
  • 3. Batko W., Przysucha B. (2011), Random distribution of long-term indicators of variable emission conditions, Acta Physica Polonica A, 119, 6-A, 1086–1090.
  • 4. Batko W., Stępień B. (2007), Analysis of traffic noise probability distribution [in Polish], Proceedings of 35th Winter School on Vibroacoustical Hazards Suppressions, pp. 5–16.
  • 5. Batko W., Stępień B. (2009), Non-parametric methods of estimation of type A uncertainty of the environmental noise hazards indices, Archives of Acoustics, 34, 3, 295–303.
  • 6. Batko W., Stępień B. (2010), Application of the bootstrap estimator for uncertainty analysis of the longterm noise indicators, Acta Physica Polonica A, 118, 1, 11–16.
  • 7. Batko W., Stępień B. (2011), Application of the Bayesian inference for estimation of the long-term noise indicators and their uncertainty, Acta Physica Polonica A, 119, 6-A, 916–920.
  • 8. Bowman A.W., Azzalini A. (1997), Applied smoothing techniques for data analysis: the kernel approach with S-plus illustrations, Oxford University Press, Inc., New York.
  • 9. Candy J.V. (2009), Bayesian signal processing: classical, modern, and particle filtering methods, John Wiley & Sons, Inc., Hoboken.
  • 10. Directive 2002/49/EC of the European Parliament and of the Council of 25 June 2002 relating to the assessment and management of environmental noise.
  • 11. Don C.G., Rees I.G. (1985), Road traffic sound level distributions, Journal of Sound and Vibration, 100, 1, 41–53.
  • 12. Efron B., Tibshirani R.J. (1993), An introduction to the bootstrap, Chapman & Hall/CRC, New York.
  • 13. Gaja E., Gimenez A., Sancho S., Reig A. (2003), Sampling techniques for the estimation of the annual equivalent noise level under urban traffic conditions, Applied Acoustics, 64, 1, 43–53.
  • 14. Gałuszka M. (2010), Statistical distributions of levels and energy of traffic noise [in Polish], Proceedings of Monitoring of environment, abstract p. 36 (full text on CD-ROM).
  • 15. Gamerman D., Lopes H.F. (2006), Markov chain Monte Carlo: stochastic simulation for Bayesian inference, Chapman & Hall/CRC, Boca Raton.
  • 16. Gimenez A., Gonzalez M. (2009), A stochastic model for the noise levels, Journal of the Acoustical Society of America, 125, 5, 3030–3037.
  • 17. Hastings W.K. (1970), Monte Carlo sampling methods using Markov chains and their application, Biometrika, 57, 1, 97–109.
  • 18. ISO/IEC Guide 98-3:2008, Uncertainty of measurement – Guide to the expression of uncertainty in measurement, International Organization for Standardization.
  • 19. Kulczycki P. (2005), Kernel estimators for analysis of systems [in Polish], Scientific and Technical Publishers, Warszawa.
  • 20. Makarewicz R., Gałuszka M. (2011), Empirical revision of noise mapping, Applied Acoustic, 72, 8, 578–581.
  • 21. Makarewicz R., Żołtowski M. (2008), Variations of road traffic noise in residental areas, Journal of the Acoustical Society of America, 124, 6, 3568–3575.
  • 22. Metropolis N., Rosenbluth A.W., Rosenbluth M.N., Teller A.H., Teller E. (1953), Equations of state calculations by fast computing machines, Journal of Chemical Physics, 21, 6, 1087–1092.
  • 23. Metropolis N., Ulam S. (1949), The Monte Carlomethod, Journal of the American Statistical Association, 44, 247, 335–341.
  • 24. Osiewalski J. (2001), Applications of Bayesian econometrics [in Polish], Cracow Academy of Economics Publishers, Krakow.
  • 25. Parzen E. (1962), On estimation of a probability density function and mode, Annals of Mathematical Statistics, 33, 3, 1065–1076.
  • 26. Romeu J., Jimenez S., Genesca M., Pamies T., Capdevila R. (2006), Spatial sampling for night levels estimation in urban environments, Journal of the Acoustical Society of America, 120, 2, 791–800.
  • 27. Rosenblatt M. (1956), Remarks on some nonparametric estimates of a density function, Annals of Mathematical Statistics, 27, 3, 832–837.
  • 28. Schomer P.D., DeVor R.E. (1981), Temporal sampling requirements for estimation of long-term average sound levels in the vicinity of airports, Journal of the Acoustical Society of America, 69, 3, 713–719.
  • 29. Tang S.K., Au W.H. (1999), Statistical structures of indoor traffic noise in a high-rise city, Journal of the Acoustical Society of America, 106, 6, 3415–3423.
  • 30. Wszołek T., Kłaczyński M. (2006), Effect of traffic noise statistical distribution on LAeq;T measurement uncertainty, Archives of Acoustics, 31, 4 (Supplement), 311–318.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-acd188de-c54c-4c1a-ad7d-1d66e936b4fb
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