Different outputs from spectrogram and pwelch

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Louise Wilson
Louise Wilson 2023-8-11
回答： Louise Wilson 2023-8-14
When analysing an acoustic signal, I would expect to get the same results presented in a spectrogram or a PSD analysis, when using the same input variables.
However, this is not the case with my example data (xbit.mat), attached.
%Read audio file
load('xbit.mat');
Fs=96000; %sample rate
xbit=detrend(xbit);
cal=-163.287; %calibration value
% FFT inputs
window=Fs;
nfft=Fs;
overlap=Fs/2;
% Spectrogram
Calibration=10^((abs(cal))/20); % calibration value for specific device used to record data
xbit_cal=xbit*Calibration;
figure(1)
subplot(2,1,1)
[S,F,T,P] = spectrogram(xbit_cal,window,overlap,nfft,Fs,'yaxis');
surf(T,F,10*log10(P),'edgecolor','none');
colorbar;
view(0,90);
ylim([50 24000])
set(gca,'YScale','log','TickDir','out');
clim([0 120]);
ylabel('Frequency');
xlabel('Time')
ylabel(colorbar,'Intensity','VerticalAlignment','bottom','Rotation',270,'FontSize',12)
% PSD analysis
[pxx,f]=pwelch(xbit,window,overlap,nfft,fs); %perform PSD analysis
%signal, window/segment length, overlap, nfft
pxx_dB=10*log10(pxx)-cal; %convert to dB re 1µPa and calibrate
subplot(2,1,2)
semilogx(f,pxx_dB)
ylabel('Intensity')
xlabel('Frequency')

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采纳的回答

Louise Wilson
Louise Wilson 2023-8-14
There was a mistake in my code which I have now rectified. The results for the spectrogram and spectra now match.

更多回答（1 个）

Mrutyunjaya Hiremath
  1. Spectrogram Scaling: In your spectrogram analysis, you are converting the spectrogram power values to dB and applying calibration (cal) using P=((10*log10(P))-cal);. This could lead to the differences in the value ranges between the spectrogram and PSD.
  2. PSD Scaling: In your PSD analysis, you are calculating the PSD values using pwelch, which already provides the power spectral density values in dB. However, you are applying an additional calibration (pxx_dB=10*log10(pxx)-cal;) to the PSD values. This might be causing the PSD values to be shifted.
To maintain consistency and facilitate a direct comparison between the spectrogram and PSD, you should avoid applying additional calibrations and dB conversions to both the spectrogram and PSD values. Here's how you can modify your code:
% ... (previous code)
% Spectrogram
figure(1)
subplot(2,1,1)
[S,F,T,P] = spectrogram(xbit,window,overlap,nfft,Fs,'yaxis');
surf(T,F,P,'edgecolor','none');
colorbar;
view(0,90);
ylim([50 24000])
set(gca,'YScale','log','TickDir','out');
clim([0 120]);
ylabel('Frequency');
xlabel('Time')
ylabel(colorbar,'Intensity','VerticalAlignment','bottom','Rotation',270,'FontSize',12)
% PSD analysis
pxx=pwelch(xbit,window,overlap,nfft); %perform PSD analysis
pxx_dB=10*log10(pxx); % convert to dB re 1µPa
subplot(2,1,2)
plot(pxx_dB)
ylabel('Intensity')
xlabel('Frequency')
By removing the cal calibration and dB conversions from both the spectrogram and PSD calculations, you should get a more accurate representation of the value ranges between the two analyses. This will allow you to compare the spectrogram and PSD more directly.
  1 个评论
Louise Wilson
Louise Wilson 2023-8-11
Thanks for your answer!
This does not help me though because I need to apply the calibration value for the values to be valid?
Surely there is a solution to apply it consistently to both outputs, which should be done once they are converted to dB? (since the calibration value is in dB)

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