create a matlab code which is able to determine the mode shapes of some measured data through a stabilisation chart analysis in matlab

To determine the mode shapes from measured data using stabilization chart analysis in MATLAB, you can follow these steps:

  1. Load your measured data into MATLAB.
  2. Preprocess the data if needed (filtering, removing noise, etc.).
  3. Perform a frequency domain analysis (such as Fast Fourier Transform) to identify the mode shapes corresponding to the natural frequencies.
  4. Create a stabilization chart by plotting the mode shapes against the corresponding natural frequencies.
  5. Analyze the stabilization chart to identify the dominant mode shapes.

Here is a simple example code snippet to get you started:

main.m
% Load the measured data
data = load('measured_data.mat');

% Preprocess the data if needed
% data = preprocess_data(data);

% Perform Fast Fourier Transform (FFT) to get the frequency content
Fs = 1000; % Sampling frequency
L = length(data);
Y = fft(data);
P2 = abs(Y/L);
P1 = P2(1:L/2+1);
f = Fs*(0:(L/2))/L;

% Find peaks in the frequency spectrum (natural frequencies)
[~, locs] = findpeaks(P1, 'MinPeakHeight', 0.1*max(P1));
frequencies = f(locs);

% Create the stabilization chart
mode_shapes = 1:length(frequencies);

figure;
plot(mode_shapes, frequencies, 'o-');
xlabel('Mode Shapes');
ylabel('Natural Frequencies (Hz)');
title('Stabilization Chart Analysis');

% Identify the dominant mode shapes
% You can set a threshold to determine the significance of the mode shapes

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Remember to replace 'measured_data.mat' with the actual file path to your measured data. This code provides a basic framework for performing stabilization chart analysis in MATLAB to determine mode shapes from measured data. Further customization and optimization may be needed based on the specifics of your data and analysis requirements.

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