is the FFT right?

6 views (last 30 days)
Raidah Zaman
Raidah Zaman on 3 May 2021
Answered: Star Strider on 3 May 2021
I am trying to analyze data that I recorded from the Force Sensitive Resistors (FSRs) coded on Arduino through data streamer on excel. I used four FSRs, so there are 4 columns of data over a set of time (1200 rows, about 15 seconds). I seperated time from the FSR data so that I can graph the FFT of the FSR data against the time.
I have made a different question which has been answered, but I was wondering if this method works as well.
Here is the code:
X = importdata('botdata.csv');
t = importdata('botdatatime.csv');
subplot(2,1,1);
plot(t,X);
xft=fft(X,[],1);
xabs = abs(xft);
subplot(2,1,2);
plot(t,xabs);
This is what was displayed.
Now I don't know if it makes sense or not.
What is the meaning of the y axis?
Is this correct?

Accepted Answer

Star Strider
Star Strider on 3 May 2021
‘What is the meaning of the y axis?’
It is necessary to normalise the fft result by the length of the vector it uses as an argument. (This is nin the fft documentation.) Once that is done, the y-axis units make sense.
Is this correct?
Almost. I made a few changes to eliminate the constant offset from the fft result, normalise it, and plot a one-sided Fourier transform. The multiplication-by-2 corrects the one-sided Fourier transform amplitude, since the energy at each frequency is divided evenly betweek the ‘positive’ and ‘negativeÄ fft frequencies.
X = readmatrix('https://www.mathworks.com/matlabcentral/answers/uploaded_files/606440/botdata.csv');
t = readmatrix('https://www.mathworks.com/matlabcentral/answers/uploaded_files/606445/botdatatime.csv');
subplot(2,1,1);
plot(t,X);
grid
xlabel('Time')
ylabel('Amplitude')
L = numel(X);
Ts = mean(diff(t))
Ts = 0.0128
% Tsd = std(mean(diff(t)))
Fs = 1/Ts;
Fn = Fs/2
Fn = 39.1012
xft=fft(X-mean(X),[],1)/L;
Fv = linspace(0, 1, fix(L/2)+1)*Fn;
Iv = 1:numel(Fv);
xabs = abs(xft);
subplot(2,1,2);
plot(Fv,mag2db(xabs(Iv)*2))
grid
ylim([-75 50])
xlabel('Freqency [units]')
ylabel('Power [dB]')
.

More Answers (0)

Categories

Find more on Fourier Analysis and Filtering in Help Center and File Exchange

Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!