Interpreting FFT Graph with Noise Floor

Question

Raidah Zaman 2021-5-10

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/826680-interpreting-fft-graph-with-noise-floor

评论： Star Strider 2021-5-11

Hello,

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 succesfully made a correct code and have proper results from it, however I need help interpeting the graphs.

Code:

X = importdata('tapedata.csv');
t = importdata('tapetimefix.csv');
subplot(2,1,1);
plot(t,X);
grid
xlabel('Time')
ylabel('Amplitude')
title('FSR Recording (Tape)');
L = numel(X);
Ts = mean(diff(t));
% Tsd = std(mean(diff(t)))
Fs = 1/Ts;
Fn = Fs/2;
xft=fft(X-mean(X),[],1)/L;
xabs = abs(xft);
subplot(2,1,2);
plot(t,xabs);
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]')
title('FFT Analysis Graph (Tape)');

I was wondering is that just a lot noise or if there are no deviances from -50db meaning the FSRs is constant?

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Star Strider 2021-5-10

It is not using whatever row or column that creates the yellow line to calculate the fft.

Since ‘tapedata.csv’ and ‘tapetimefix.csv’ are not provided, it is not possible to provide further details.

Raidah Zaman 2021-5-10

Here my apologies, I have attached it.

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Answer 1

Star Strider 2021-5-11

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/826680-interpreting-fft-graph-with-noise-floor#answer_696735

在 MATLAB Online 中打开

Try this —

X = readmatrix('https://www.mathworks.com/matlabcentral/answers/uploaded_files/613760/tapedata.csv');

t = readmatrix('https://www.mathworks.com/matlabcentral/answers/uploaded_files/613765/tapetimefix.csv');

SizeX = size(X)

SizeX = 1×2

1062 4

figure

for k = 1:size(X,2)

subplot(4,1,k)

plot(t, X(:,k))

title(sprintf('Column %d',k))

end

figure

subplot(3,1,1);

plot(t,X);

grid

xlabel('Time')

ylabel('Amplitude')

title('FSR Recording (Tape)');

L = size(X,1); % <= CHANGED

Ts = mean(diff(t));

% Tsd = std(mean(diff(t)))

Fs = 1/Ts;

Fn = Fs/2;

xft=fft(X-mean(X))/L;

xabs = abs(xft);

subplot(3,1,2);

plot(linspace(-Fn,Fn,numel(t)),mag2db(fftshift(xabs)*2));

grid

ylim([-75 50])

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

Iv = 1:numel(Fv);

xabs = abs(xft(:,3)); % <= CHANGED

subplot(3,1,3);

plot(Fv,mag2db(xabs(Iv)*2))

grid

ylim([-75 50])

xlabel('Freqency [units]')

ylabel('Power [dB]')

title('FFT Analysis Graph (Tape)');

This appears to be close to the desired result.

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Star Strider 2021-5-11

在 MATLAB Online 中打开

My pleasure!

That is the fft of all the signals in the file, using fftshift to centre them. That was part of the original code, so I left it in, although I added the last plot by re-numbering the subplots.

The code without it becomes —

X = readmatrix('https://www.mathworks.com/matlabcentral/answers/uploaded_files/613760/tapedata.csv');

t = readmatrix('https://www.mathworks.com/matlabcentral/answers/uploaded_files/613765/tapetimefix.csv');

SizeX = size(X)

SizeX = 1×2

1062 4

figure

for k = 1:size(X,2)

subplot(4,1,k)

plot(t, X(:,k))

title(sprintf('Column %d',k))

end

figure

subplot(2,1,1);

plot(t,X(:,3));

grid

xlabel('Time')

ylabel('Amplitude')

title('FSR Recording (Tape)');

L = size(X,1); % <= CHANGED

Ts = mean(diff(t));

% Tsd = std(mean(diff(t)))

Fs = 1/Ts;

Fn = Fs/2;

xft=fft(X-mean(X))/L;

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

Iv = 1:numel(Fv);

xabs = abs(xft(:,3)); % <= CHANGED

subplot(2,1,2);

plot(Fv,mag2db(xabs(Iv)*2))

grid

ylim([-75 50])

xlabel('Freqency [units]')

ylabel('Power [dB]')

title('FFT Analysis Graph (Tape)');

filtered_FSR = lowpass(X(:,3), 4.5, Fs, 'ImpulseResponse','iir');

figure

subplot(2,1,1);

plot(t,X(:,3));

grid

xlabel('Time')

ylabel('Amplitude')

title('Original Signal')

subplot(2,1,2);

plot(t,filtered_FSR);

grid

xlabel('Time')

ylabel('Amplitude')

title('Filtered Signal')

sgtitle('FSR Recording (Tape)');

I added the filter to remove some of the high-frequency noise. Experiment with it if you want to filter the signal

Raidah Zaman 2021-5-11

I see thank you, I was able to learn so much from this.

Star Strider 2021-5-11

As always, my pleasure!

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