An Introduction to Random Vibrations and Spectral Analysis |
Contents
Joint probability distributions ensemble averages | 12 |
Correlation | 30 |
Fourier analysis | 41 |
Copyright | |
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Common terms and phrases
aliased amplitude analysis approximately array assume autocorrelation function average value bandwidth beam binary signal calculated Chapter complex consider constant correlation coefficients correlation function corresponding cross-spectral density defined degree-of-freedom delta functions DFT's dimensional discrete Fourier transform E[y² ensemble average equation ergodic example filter Fourier series frequency response function Gaussian given gives H₁(w input integral linear system mean-square velocity measured N₁ N₂ narrow band process noise Nyquist frequency obtain one-dimensional output probability density function probability distribution problem r₁ rad/s random binary random excitation random variable random vibration Rayleigh distribution result s₁ sample functions sampling interval sequence shown in Fig spectral coefficients spectral density spectral estimates spectral window spectrum square stationary process stationary random process substituting summation surface t₁ two-dimensional DFT uncorrelated w₁ w₂ wavenumber x₁ x₁(t X₂ y₁ zero Δω Σ Σ