39 lines
998 B
Mathematica
39 lines
998 B
Mathematica
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%%
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clear; close all; clc;
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%%
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load('sim_data/data_sim.mat', 'Trec_start', 'Trec_dur', 'Ts');
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%% White Noise => Identification of the sensibility transfer function
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s = zpk('s');
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Rx_noise = generateShapedNoise('Ts', Ts, ...
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'V_mean', 0, ...
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't_start', Trec_start, ...
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'exc_duration', Trec_dur, ...
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'V_exc', 2e-6/(2*pi*0.2 + s));
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R_dist = timeseries(Rx_noise(2, :), Rx_noise(1, :));
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figure;
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tiledlayout(1, 2, 'TileSpacing', 'Normal', 'Padding', 'None');
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ax1 = nexttile;
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hold on;
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plot(R_dist.Time, squeeze(R_dist.Data(1, 1, :)));
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xlabel('Time [s]'); ylabel('Amplitude [m,rad]');
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ax2 = nexttile;
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hold on;
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win = hanning(floor(length(squeeze(R_dist.Data(1, 1, :)))/8));
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[pxx, f] = pwelch(squeeze(R_dist.Data(1, 1, :)), win, 0, [], 1/Ts);
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plot(f, sqrt(pxx))
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hold off;
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xlabel('Frequency [Hz]'); ylabel('Amplitude Spectral Density [$m/\sqrt{Hz}$]');
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set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log');
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xlim([1, 1e3]); ylim([1e-10, 1e0]);
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%%
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save('sim_data/ref_dist.mat', 'R_dist');
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