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 Wysłany: Czw 22:06, 17 Lut 2011 Temat postu: Track irregularity stochastic process simulation _ |
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Track irregularity Numerical simulation of random process
Operation is more complex, there is a certain difficulty. World Earthquake Engineering Volume 24,moncler milano, 1O8 O5l52O253O35 time,tory burch outlet, B: Head § Figure 1 Secondary Filter and power spectrum of the sample (= 100km / h) [urgent 05lOl52O253O35 time, sl00lOlO. 1o. IE a 3 orders O1'lE a 4IE a 5: ? 1E-6lE a 7lE-8lE-9lE-lOlOl00 frequency / Hz Figure 2 samples of the original trigonometric series and power spectrum (= 100km / h) 05lOl52O253O35 time, B100101 ∞ o. 1o. 011E-3 41E Island 1E A one of a 51E 71E 61E a 8lOl00 a frequency / Hz Figure 3, samples and power spectrum inversion (= 100km / h) O5lOl52O253O time,p90x workout calendar, B35100101 ∞ o. 1o. 011E-3 island 1E_41E one of a 51E 61E 71E a 810 100 a frequency, IIz Figure 4,supra for sale, a new sample of trigonometric series and power spectrum (= 100km / h) lOl00 frequency, IIz00 ● ● ● 34S678902345678 Ⅲ. m ¨ ¨ 864204E Head, Xin m8642om, Xin 8642o JC, Xin 642O4, Xin 1 Li-Wei Zhang et al: track irregularity stochastic process simulation 1O95 Conclusion In this paper, stochastic theory, derived from the theoretical track irregularity spectral density of random process space, the conversion between time domain, and the vertical track irregularity spectrum of the United States,tory burch shoes, for example, given its space and time domain comparison of spectral density formula. This paper describes the commonly used at home and abroad of the simulation track irregularity and its principles. Through the power of the principle of FFT algorithm for the analysis, constructed a new trigonometric series. According to the text for the different simulation methods of numerical example, you can obtain the following conclusions: (1) New method for trigonometric series with the inverse Fourier transform method has the equivalence of the two simulated samples of both the time-amplitude, or spectral structure are consistent; both the high degree of consistency, also shows that two methods are fitting a random sample of GAUSS 0 mean random process; (2) white noise filter and secondary filter for different needs power spectrum filter design, the method does not have the versatility, the analog samples and accuracy of fitting the power spectrum depends on the filter parameter; (3) new trigonometric series, inverse Fourier transform method to simulate random samples to schedule and the power spectrum is superior to the original both in terms of trigonometric series and white noise rate method. (4) from the sample simulation rate, slower trigonometric series, inverse Fourier transform method has great advantages in speed. |
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