Spectrometer Signal processing question

36 Ansichten (letzte 30 Tage)
Daniel
Daniel am 3 Dez. 2024 um 12:21
Kommentiert: Yukthi S am 4 Dez. 2024 um 9:32
Hi guys. I need to normalise the signal and perform polynomial fitting, as shown in the image below. I attempted to use the Signal Analyzer app and the Signal Multiresolution Analyzer but was unsuccessful. My signal code is below and picture with example how my signal processing should looks like.
My full code:
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  1 Kommentar
Star Strider
Star Strider am 3 Dez. 2024 um 17:17
Please see: Spectrometer signal processing.
I need to know how you want to normalise it. One problem (for me) is that your data don’t look anything like the plot in the image. (The provided image is of a critically-camped impulse function response.)

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Antworten (3)

Daniel
Daniel am 3 Dez. 2024 um 12:23
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T1 = cell2table(Data);
Time = datetime(T1{:,2}, InputFormat='HH:mm:ss.SSS', Format='HH:mm:ss.SSS');
ElapsedTime = seconds(Time - Time(1));
T1 = removevars(T1,2);
T1 = addvars(T1, ElapsedTime, 'Before',2)
figure
plot(T1{:,2}, T1{:,3})
grid
title('Spectrometer Plot')
Yukthi S
Yukthi S am 3 Dez. 2024 um 14:32
Hi Daniel,
For data normalization and to perform polynomial fitting on the raw data, the in-built MATLAB functions “normalize” and “polyfit” can be used.
You can refer to the following documentation links for more insights:
The given code can be modified as below:
Data ={....}; %give the raw data here
% Convert to table
T1 = cell2table(Data, 'VariableNames', {'Timestamp', 'TimeStr', 'Value'});
% Convert time strings to datetime and calculate elapsed time
Time = datetime(T1{:, 'TimeStr'}, 'InputFormat', 'HH:mm:ss.SSS', 'Format', 'HH:mm:ss.SSS');
ElapsedTime = seconds(Time - Time(1));
% Update table
T1 = removevars(T1, 'TimeStr');
T1 = addvars(T1, ElapsedTime, 'Before', 'Value');
% Normalize the data using the normalize function
normalizedValues = normalize(T1.Value, 'range');
% Perform polynomial fitting
degree = 3; % Degree of polynomial
p = polyfit(T1.ElapsedTime, normalizedValues, degree);
fittedValues = polyval(p, T1.ElapsedTime);
% Plotting
figure;
plot(T1.ElapsedTime, normalizedValues, 'b', 'DisplayName', 'Normalized Data');
hold on;
plot(T1.ElapsedTime, fittedValues, 'r--', 'DisplayName', ['Polynomial Fit (Degree ' num2str(degree) ')']);
grid on;
title('Spectrometer Plot');
xlabel('Elapsed Time (s)');
ylabel('Normalized Value');
legend('show');
Hope this will help you get started!
Daniel
Daniel am 4 Dez. 2024 um 9:25
Hi Yukthi S
Thank you. I really appreciated!

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