I want to do fft analysis of the input signal but I am getting the following error

%Clear command window, variables and close all open figures (if any)
clc;
clear all;
% close all;

%Import the CSV file
filename = '2DOF_11a.csv';
opts = detectImportOptions(filename,'NumHeaderLines',0); % number of header lines which are to be ignored
opts.VariableNamesLine = 0; % row number which has variable names
opts.DataLine = 1; % row number from which the actual data starts
tbl = readtable(filename,opts);


% Time (numerical)
time = table2array(tbl(:,1));
Fs = 1/time(2); % Sampling frequency

%x1 (numerical)
x1_num = table2array(tbl(:,2));
%x2 (numerical)
% x2_num = table2array(tbl(:,5));
% 
% %x1 (analytical)
% x1_ana = table2array(tbl(:,8));
% %x2 (analytical)
% x2_ana = table2array(tbl(:,11));
% % x2_ana = str2double(x2_ana); %x2_ana was coming as a cell in the line before, so had to add this line
% 
L = length(x1_num); %Length of all the signals
% % 
% % % PSD of x1 (numerical) using Hanning window
% % % F is the set of actual frequencies (will be same for all signals)
[PSD_x1_num,F] = periodogram(x1_num, hanning(L), L, Fs, 'power');
% 
% % PSD of x2 (numerical) using Hanning window
% PSD_x2_num = periodogram(x2_num, hanning(L), L, Fs, 'power');
% 
% % PSD of x1 (analytical) using Hanning window
% PSD_x1_ana = periodogram(x1_ana, hanning(L), L, Fs, 'power');
% 
% % PSD of x2 (analtical) using Hanning window
% PSD_x2_ana = periodogram(x2_ana, hanning(L), L, Fs, 'power');
% 
f_index = find(F >= 10);
F_set = 1:f_index(1); %Frequency index to plot is between 0 to 10 Hz 
% % 
figure(1);
clf;
% % Plot x1 PSDs
plot(F(F_set),PSD_x1_num(F_set),'b','linewidth',2.0);
hold on;
plot(F(F_set),PSD_x1_ana(F_set),'r--','linewidth',2.0);
xlabel('Frequency (Hz)')
ylabel('PSD')
% 
% figure(2);
% clf;
% % Plot x2 PSDs
% % plot(F(F_set),PSD_x2_num(F_set),'b','linewidth',2.0);
% hold on;
% plot(F(F_set),PSD_x2_ana(F_set),'r--','linewidth',2.0);
% xlabel('Frequency (Hz)')
% ylabel('PSD')
% % 
freq = [F(F_set) PSD_x1_num(F_set)]; %PSD_x1_ana(F_set) PSD_x2_num(F_set) PSD_x2_ana(F_set)];

I am getting the following error

Error in periodogram (line 215)

[Sxx,w2,RSxx,wc] = computeperiodogram(x,win,nfft,esttype,Fs,options);

Error in fft_SV (line 34)

[PSD_x1_num,F] = periodogram(x1_num, hanning(L), L, Fs, 'power');

[Mathieu NOE]

hello

can you share the data file as well ?

tx

[Karthik B K]

PFA

Answer 1

[Karthik B K]

PFA

Answer 2

[Mathieu NOE]

hello

I had to tweak a bit my code because your data file does not have same amount of rows depending at which column we look at

now, I don't know which of the data is interesting for you, but basically I found only 2 could be of some interest

select the channel you want to process using this line

selected_channel = 2; % 2,4 or 5 , 3 is empty

full code :

clc
clearvars
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% load signal
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%% data
% data has 2 columns (time / signal)

data = table2array(readtable('2DOF_1a.csv'));

time = data(:,1);
signal = data(:,2:end);

[samples,channels] = size(signal);

% select one channel and remove NaN if needed
selected_channel = 2; % 2,4 or 5 , 3 is empty
signal = data(:,selected_channel);
ind = find(~isnan(signal));
signal = signal(ind);
time = time(ind);

Fs = 1/mean(diff(time));


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% FFT parameters
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
NFFT = 256;    % 
OVERLAP = 0.95;

% spectrogram dB scale
spectrogram_dB_scale = 80;  % dB range scale (means , the lowest displayed level is XX dB below the max level)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% options 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% if you are dealing with acoustics, you may wish to have A weighted
% spectrums 

% option_w = 0 : linear spectrum (no weighting dB (L) )
% option_w = 1 : A weighted spectrum (dB (A) )
option_w = 0;

%% decimate (if needed)
% NB : decim = 1 will do nothing (output = input)
decim = 1;
if decim>1
    for ck = 1:channels
    newsignal(:,ck) = decimate(signal(:,ck),decim);
    Fs = Fs/decim;
    end
   signal = newsignal;
end
samples = length(signal);
time = (0:samples-1)*1/Fs;

%%%%%% legend structure %%%%%%%%
for ck = 1:channels
    leg_str{ck} = ['Channel ' num2str(ck) ];
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% display 1 : time domain plot
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
figure(1),plot(time,signal);grid on
title(['Time plot  / Fs = ' num2str(Fs) ' Hz ']);
xlabel('Time (s)');ylabel('Amplitude');
legend(leg_str);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% display 2 : averaged FFT spectrum
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

[freq, sensor_spectrum] = myfft_peak(signal,Fs,NFFT,OVERLAP);

% convert to dB scale (ref = 1)
sensor_spectrum_dB = 20*log10(sensor_spectrum);

% apply A weigthing if needed
if option_w == 1
    pondA_dB = pondA_function(freq);
    sensor_spectrum_dB = sensor_spectrum_dB+pondA_dB;
    my_ylabel = ('Amplitude (dB (A))');
else
    my_ylabel = ('Amplitude (dB (L))');
end


figure(2),plot(freq,sensor_spectrum_dB);grid on
df = freq(2)-freq(1); % frequency resolution 
title(['Averaged FFT Spectrum  / Fs = ' num2str(Fs) ' Hz / Delta f = ' num2str(df,3) ' Hz ']);
xlabel('Frequency (Hz)');ylabel(my_ylabel);
legend(leg_str);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% display 3 : time / frequency analysis : spectrogram demo
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for ck = 1:channels
    [sg,fsg,tsg] = specgram(signal(:,ck),NFFT,Fs,hanning(NFFT),floor(NFFT*OVERLAP));  

    % FFT normalisation and conversion amplitude from linear to dB (peak)
    sg_dBpeak = 20*log10(abs(sg))+20*log10(2/length(fsg));     % NB : X=fft(x.*hanning(N))*4/N; % hanning only

    % apply A weigthing if needed
    if option_w == 1
        pondA_dB = pondA_function(fsg);
        sg_dBpeak = sg_dBpeak+(pondA_dB*ones(1,size(sg_dBpeak,2)));
        my_title = ('Spectrogram (dB (A))');
    else
        my_title = ('Spectrogram (dB (L))');
    end

    % saturation of the dB range : 
    % saturation_dB = 60;  % dB range scale (means , the lowest displayed level is XX dB below the max level)
    min_disp_dB = round(max(max(sg_dBpeak))) - spectrogram_dB_scale;
    sg_dBpeak(sg_dBpeak<min_disp_dB) = min_disp_dB;

    % plots spectrogram
    figure(2+ck);
    imagesc(tsg,fsg,sg_dBpeak);colormap('jet');
    axis('xy');colorbar('vert');grid on
    df = fsg(2)-fsg(1); % freq resolution 
    title([my_title ' / Fs = ' num2str(Fs) ' Hz / Delta f = ' num2str(df,3) ' Hz / Channel : ' num2str(ck)]);
    xlabel('Time (s)');ylabel('Frequency (Hz)');

end

function pondA_dB = pondA_function(f)
	% dB (A) weighting curve
	n = ((12200^2*f.^4)./((f.^2+20.6^2).*(f.^2+12200^2).*sqrt(f.^2+107.7^2).*sqrt(f.^2+737.9^2)));
	r = ((12200^2*1000.^4)./((1000.^2+20.6^2).*(1000.^2+12200^2).*sqrt(1000.^2+107.7^2).*sqrt(1000.^2+737.9^2))) * ones(size(f));
	pondA = n./r;
	pondA_dB = 20*log10(pondA(:));
end


function  [freq_vector,fft_spectrum] = myfft_peak(signal, Fs, nfft, Overlap)
% FFT peak spectrum of signal  (example sinus amplitude 1   = 0 dB after fft).
% Linear averaging
%   signal - input signal, 
%   Fs - Sampling frequency (Hz).
%   nfft - FFT window size
%   Overlap - buffer percentage of overlap % (between 0 and 0.95)

[samples,channels] = size(signal);

% fill signal with zeros if its length is lower than nfft
if samples<nfft
    s_tmp = zeros(nfft,channels);
    s_tmp((1:samples),:) = signal;
    signal = s_tmp;
    samples = nfft;
end

% window : hanning
window = hanning(nfft);
window = window(:);

%    compute fft with overlap 
 offset = fix((1-Overlap)*nfft);
 spectnum = 1+ fix((samples-nfft)/offset); % Number of windows
%     % for info is equivalent to : 
%     noverlap = Overlap*nfft;
%     spectnum = fix((samples-noverlap)/(nfft-noverlap));	% Number of windows

    % main loop
    fft_spectrum = 0;
    for i=1:spectnum
        start = (i-1)*offset;
        sw = signal((1+start):(start+nfft),:).*(window*ones(1,channels));
        fft_spectrum = fft_spectrum + (abs(fft(sw))*4/nfft);     % X=fft(x.*hanning(N))*4/N; % hanning only 
    end
    fft_spectrum = fft_spectrum/spectnum; % to do linear averaging scaling

% one sidded fft spectrum  % Select first half 
    if rem(nfft,2)    % nfft odd
        select = (1:(nfft+1)/2)';
    else
        select = (1:nfft/2+1)';
    end
fft_spectrum = fft_spectrum(select,:);
freq_vector = (select - 1)*Fs/nfft;
end

[Karthik B K]

Firstly, thank you for helping.

Actually I need to do FFT analysis for the input signal which is in second(Column B) column. The first column indicates time span of the complete signal. In the code, I have commented for the remaining column. The same code is used for the different problem which had number of input signal. But if I use the same code for this probem I am getting the above mentioned errors.