Assume a random process x(
t). In the following,
T denotes a time span which is ‘long’ compared to any frequencies of interest.
The mean value is defined using the expectancy value operator
E[] as
It can be seen from the definition that the autocorrelation is an even function of the time difference τ. An interpretation of the autocorrelation is that it compares how similar the signal is to itself after a certain time has elapsed.
For two different processes x(
t) and
y(
t), the cross-correlation is similarly defined as
The power spectral density (PSD) of a signal x is defined through the Fourier transform (denoted by
F[]) of the autocorrelation,
The term PSD comes from the fact that the physical dimension of Gx is (input signal)
2 / frequency. Thus,
Gx(
f)
Δf represents the power of the signal contained in the small frequency interval
Δf.
Since the autocorrelation is a real-valued and even function of τ,
Gx is also real-valued. Because of this property,
Gx can also be written as
It is possible to compute the mean square of x (the power) for only a certain frequency range
where H is the complex-valued transfer function. It can then be shown that the corresponding spectral densities have the relation
SX is a square matrix having the size of number of inputs,
N, while the size of the square matrix
SU is the number of outputs,
M.
where the vector yk contains eigenmode
k, and the mode matrix
Y has the eigenmodes
yk as columns. The modal coordinates (amplitudes of each mode) are collected in the vector
q.
Using the common notation that M is the mass matrix,
C is the damping matrix and
K is the stiffness matrix, the full set equations of motion is
In frequency domain, any quantity a can be written using a complex notation as
where â is a complex-valued amplitude. With an assumption about harmonic excitation,
If the applied load is given in terms of its cross-correlation spectra, SL(
Ω), then it can be shown that the corresponding cross correlation for the modal loads,
Sl(
Ω), is obtained by a similar projection into modal space,