response spectrum - time domain to frequency domain

Hi all, hope this message finds you well. I have been running tests on a model wind turbine using fast and have an example of the output data in the time domain as shown below.

Time RotSpeed

(s) (rpm)

0 12.10

0.0125 12.11

0.025 12.11

0.0375 12.11

0.05 12.09

0.0625 12.07

0.075 12.03

I need a response spectrum to find natural frequencies etc. If anyone could give me any advice it would be really appreciated.

Kind regards,

Tom

Answer 1

[Star Strider]

Here is some example code that you can adapt to your data:

t = linspace(0, 5, 1E+4);                                                           % Time Vector
s = sum(sin([100; 250; 300; 700]*2*pi*t));                                          % Signal Vector

figure
plot(t, s)
grid

L = numel(t);                                                                       % Signal Length
Ts = mean(diff(t));                                                                 % Sampling Interval
Fs = 1/Ts;                                                                          % Sampling Frequency
Fn = Fs/2;                                                                          % Nyquist Frequency
n = nextpow2(numel(t));                                                             % Zero-Pad So Length Is The Next Highest Power Of 2 (Not Required)
FTs = fft(s,2^n)/L;                                                                 % Discrete Fourier Transform
Fv = linspace(0, 1, fix(2^n/2)+1)*Fn;                                               % Frequency Vector
Iv = 1:numel(Fv);                                                                   % Index Vector

figure
plot(Fv, abs(FTs(Iv))*2)
grid

If you do not use nextpow2, the fft call becomes:

FTs = fft(s)/L;

and the frequency vector calculation becomes:

Fv = linspace(0, 1, fix(L/2)+1)*Fn;

The rest of the code is unchanged.