Converting xlsx files to frequency domains using the fft algorithm
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The above graph is a graph using Var1_Time and Hammer (input) data Var2_1 through Var2_5, the time data of the referenced file 120mm.xlsx.
>> plot(Var1_Time,Var2_1)
>> hold on
>> plot(Var1_Time,Var2_2)
>> plot(Var1_Time,Var2_3)
>> plot(Var1_Time,Var2_4)
>> plot(Var1_Time,Var2_5)
But I want to make a graph about Hammer (input) data by changing Var1_Time, which is time data, to frequency domain using the fft algorithm, but I don't know how. I'd really appreciate your help.
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Try this —
T1 = readtable('120mm.xlsx')
VN = T1.Properties.VariableNames([1 4:end]);
t = T1{:,1};
s = T1{:,4:end};
Ts = mean(diff(t))
Tsd = std(diff(t))
Fs = 1/Ts
[sr, tr] = resample(s, t, Fs);
[FTs1,Fv] = FFT1(sr,tr);
figure
plot(Fv, mag2db(abs(FTs1)*2))
grid
xlim([0 max(Fv)])
xlabel('Frequency')
ylabel('Magnitude (dB)')
legend(strrep(VN(2:end),'_','\_'), 'Location','NE', 'NumColumns',2)
idx = reshape([1:5; 6:10], [],1);
figure
tiledlayout(5,2)
for k = 1:size(FTs1,2)
nexttile
plot(Fv, mag2db(abs(FTs1(:,idx(k)))*2))
title(strrep(VN{idx(k)+1},'_','\_'))
grid
axis([0 max(Fv) -100 10])
end
function [FTs1,Fv] = FFT1(s,t)
t = t(:);
L = numel(t);
if size(s,2) == L
s = s.';
end
Fs = 1/mean(diff(t));
Fn = Fs/2;
NFFT = 2^nextpow2(L);
FTs = fft((s - mean(s)) .* hann(L).*ones(1,size(s,2)), NFFT)/sum(hann(L));
Fv = linspace(0, 1, NFFT/2+1)*Fn;
Iv = 1:numel(Fv);
FTs1 = FTs(Iv,:);
end
Your data are not regularly sampled, so it is necessary to use the resample function here to produce reliable results, since fft and nearly every other signal processing function require regularly-sampled data.
I created the ‘FFT1’ function for my convenience. Feel free to use it.
.
댓글 수: 6
호태 강
2024년 3월 20일
As always, my pleasure!
I will be happy to help you, however I am not certain what you want. What do you intend by ‘... I need to divide the Var2_1~Var2_5 and Var3_1~Var3_5 graphs in order to organize the experimental data ...’? How do you want to divide them?
Perhaps this —
T1 = readtable('120mm.xlsx');
VN = T1.Properties.VariableNames([1 4:end]);
t = T1{:,1};
s = T1{:,4:end};
Ts = mean(diff(t));
Tsd = std(diff(t));
Fs = fix(1/Ts)
[sr, tr] = resample(s, t, Fs);
[FTs1,Fv] = FFT1(sr,tr);
figure
tiledlayout(5,1)
for k = 1:5
nexttile
plot(Fv, mag2db(abs(FTs1(:,k))*2))
title(strrep(VN{k+1},'_','\_'))
grid
axis([0 max(Fv) -100 10])
end
figure
tiledlayout(5,1)
for k = 1:5
nexttile
plot(Fv, mag2db(abs(FTs1(:,k+5))*2))
title(strrep(VN{k+6},'_','\_'))
grid
axis([0 max(Fv) -100 10])
end
function [FTs1,Fv] = FFT1(s,t)
t = t(:);
L = numel(t);
if size(s,2) == L
s = s.';
end
Fs = 1/mean(diff(t));
Fn = Fs/2;
NFFT = 2^nextpow2(L);
FTs = fft((s - mean(s)) .* hann(L).*ones(1,size(s,2)), NFFT)/sum(hann(L));
Fv = linspace(0, 1, NFFT/2+1)*Fn;
Iv = 1:numel(Fv);
FTs1 = FTs(Iv,:);
end
.
호태 강
2024년 3월 20일
As always, my pleasure!
O.K.
Try this —
T1 = readtable('120mm.xlsx');
VN = T1.Properties.VariableNames([1 4:end]);
t = T1{:,1};
s = T1{:,4:end};
Ts = mean(diff(t))
Tsd = std(diff(t))
Fs = 1/Ts
[sr, tr] = resample(s, t, Fs);
[FTs1,Fv] = FFT1(sr,tr);
figure
plot(Fv, mag2db(abs(FTs1(:,1:5))*2))
grid
xlim([0 max(Fv)])
xlabel('Frequency')
ylabel('Magnitude (dB)')
legend(strrep(VN(2:6),'_','\_'), 'Location','best')
figure
plot(Fv, mag2db(abs(FTs1(:,6:end))*2))
grid
xlim([0 max(Fv)])
xlabel('Frequency')
ylabel('Magnitude (dB)')
legend(strrep(VN(7:end),'_','\_'), 'Location','best')
function [FTs1,Fv] = FFT1(s,t)
t = t(:);
L = numel(t);
if size(s,2) == L
s = s.';
end
Fs = 1/mean(diff(t));
Fn = Fs/2;
NFFT = 2^nextpow2(L);
FTs = fft((s - mean(s)) .* hann(L).*ones(1,size(s,2)), NFFT)/sum(hann(L));
Fv = linspace(0, 1, NFFT/2+1)*Fn;
Iv = 1:numel(Fv);
FTs1 = FTs(Iv,:);
end
.
호태 강
2024년 3월 20일
Star Strider
2024년 3월 20일
As always, my pleasure!
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