modify scripts
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@ -9,28 +9,33 @@ addpath('./src/');
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% Test with one APA
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%% Load measurement data for APA number 1
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load(sprintf('mat/frf_data_%i.mat', 1), 't', 'Va', 'Vs', 'de', 'da');
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% Time domain data:
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figure;
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plot(t, de);
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load(sprintf('mat/frf_data_%i_sweep_lf.mat', 2), 't', 'Va', 'Vs', 'de', 'da');
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% Compute transfer functions:
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Ts = (t(end) - t(1))/(length(t)-1);
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Fs = 1/Ts;
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win = hanning(ceil(0.5*Fs)); % Hannning Windows
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win = hanning(ceil(1*Fs)); % Hannning Windows
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[G_dvf, f] = tfestimate(Va, de, win, [], [], 1/Ts);
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[G_d, ~] = tfestimate(Va, da, win, [], [], 1/Ts);
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[G_iff, ~] = tfestimate(Va, Vs, win, [], [], 1/Ts);
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[coh_dvf, ~] = mscohere(Va, de, win, [], [], 1/Ts);
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[coh_d, ~] = mscohere(Va, da, win, [], [], 1/Ts);
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[coh_iff, ~] = mscohere(Va, Vs, win, [], [], 1/Ts);
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%%
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figure;
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hold on;
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plot(f, coh_dvf);
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plot(f, coh_d);
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plot(f, coh_iff);
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hold off;
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set(gca, 'XScale', 'log');
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%%
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figure;
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tiledlayout(2, 1, 'TileSpacing', 'None', 'Padding', 'None');
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@ -42,7 +47,6 @@ hold off;
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set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log');
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ylabel('Amplitude $V_{out}/V_{in}$ [V/V]'); set(gca, 'XTickLabel',[]);
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hold off;
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ylim([10, 30]);
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ax2 = nexttile;
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hold on;
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@ -65,7 +69,6 @@ plot(f, abs(G_iff));
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set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log');
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ylabel('Amplitude $V_{out}/V_{in}$ [V/V]'); set(gca, 'XTickLabel',[]);
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hold off;
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ylim([10, 30]);
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ax2 = nexttile;
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plot(f, 180/pi*angle(G_iff));
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@ -75,7 +78,7 @@ hold off;
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yticks(-360:90:360);
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linkaxes([ax1,ax2],'x');
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xlim([5, 5e3]);
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xlim([0.1, 10]);
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% Comparison of all APA
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BIN
matlab/frf_data.mat
Normal file
BIN
matlab/frf_data.mat
Normal file
Binary file not shown.
Binary file not shown.
@ -26,7 +26,10 @@ t = data(:, end); % Time [s]
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% And we save this to a =mat= file:
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apa_number = 1;
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% leg_number = 4;
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save(sprintf('mat/frf_data_%i_huddle.mat', apa_number), 't', 'Va', 'Vs', 'de', 'da');
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save(sprintf('mat/frf_data_leg_coder_%i_noise.mat', apa_number), 't', 'Va', 'Vs', 'de', 'da');
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% save(sprintf('mat/frf_data_leg_coder_%i_sweep.mat', apa_number), 't', 'Va', 'Vs', 'de', 'da');
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% save(sprintf('mat/frf_data_leg_coder_%i_noise_hf.mat', apa_number), 't', 'Va', 'Vs', 'de', 'da');
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% save(sprintf('mat/frf_data_leg_coder_%i_add_mass_closed_circuit.mat', apa_number), 't', 'Va', 'Vs', 'de', 'da');
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@ -16,23 +16,6 @@ Trec_dur = 100; % Recording Duration [s]
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Tsim = 2*Trec_start + Trec_dur; % Simulation Time [s]
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%% Sweep Sine
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gc = 0.1;
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xi = 0.5;
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wn = 2*pi*94.3;
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% Notch filter at the resonance of the APA
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G_sweep = 0.2*(s^2 + 2*gc*xi*wn*s + wn^2)/(s^2 + 2*xi*wn*s + wn^2);
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V_sweep = generateSweepExc('Ts', Ts, ...
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'f_start', 10, ...
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'f_end', 1e3, ...
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'V_mean', 3.25, ...
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't_start', Trec_start, ...
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'exc_duration', Trec_dur, ...
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'sweep_type', 'log', ...
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'V_exc', G_sweep*1/(1 + s/2/pi/500));
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%% Shaped Noise
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V_noise = generateShapedNoise('Ts', 1/Fs, ...
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'V_mean', 3.25, ...
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@ -41,28 +24,79 @@ V_noise = generateShapedNoise('Ts', 1/Fs, ...
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'smooth_ends', true, ...
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'V_exc', 0.05/(1 + s/2/pi/10));
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%% Sweep Sine
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gc = 0.1;
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xi = 0.5;
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wn = 2*pi*92.7;
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% Notch filter at the resonance of the APA
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G_sweep = 0.2*(s^2 + 2*gc*xi*wn*s + wn^2)/(s^2 + 2*xi*wn*s + wn^2);
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V_sweep = generateSweepExc('Ts', Ts, ...
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'f_start', 10, ...
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'f_end', 400, ...
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'V_mean', 3.25, ...
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't_start', Trec_start, ...
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'exc_duration', Trec_dur, ...
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'sweep_type', 'log', ...
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'V_exc', G_sweep*1/(1 + s/2/pi/500));
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V_sweep_lf = generateSweepExc('Ts', Ts, ...
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'f_start', 0.1, ...
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'f_end', 10, ...
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'V_mean', 3.25, ...
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't_start', Trec_start, ...
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'exc_duration', Trec_dur, ...
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'sweep_type', 'log', ...
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'V_exc', 0.2);
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%% High Frequency Shaped Noise
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[b,a] = cheby1(10, 2, 2*pi*[300 2e3], 'bandpass', 's');
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wL = 0.005*tf(b, a);
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V_noise_hf = generateShapedNoise('Ts', 1/Fs, ...
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'V_mean', 3.25, ...
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't_start', Trec_start, ...
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'exc_duration', Trec_dur, ...
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'smooth_ends', true, ...
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'V_exc', wL);
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%% Sinus excitation with increasing amplitude
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V_sin = generateSinIncreasingAmpl('Ts', 1/Fs, ...
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'V_mean', 3.25, ...
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'sin_ampls', [0.1, 0.2, 0.4, 1, 2, 4], ...
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'sin_period', 1, ...
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'sin_num', 5, ...
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't_start', 10, ...
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't_start', Trec_start, ...
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'smooth_ends', true);
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%% Zero Excitation
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% Trec_start = 10; % Start time for Recording [s]
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% Trec_dur = 40; % Recording Duration [s]
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%
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% Tsim = 2*Trec_start + Trec_dur; % Simulation Time [s]
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V_zero = generateShapedNoise('Ts', 1/Fs, ...
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'V_mean', 3.25, ...
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't_start', Trec_start, ...
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'exc_duration', Trec_dur, ...
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'smooth_ends', true, ...
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'V_exc', tf(0));
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%% Select the excitation signal
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V_exc = timeseries(V_noise(2,:), V_noise(1,:));
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%% Plot
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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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plot(V_exc(1,:), V_exc(2,:));
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plot(V_exc.Time, squeeze(V_exc.Data));
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xlabel('Time [s]'); ylabel('Amplitude [V]');
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ax2 = nexttile;
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win = hanning(floor(length(V_exc)/8));
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[pxx, f] = pwelch(V_exc(2,:), win, 0, [], Fs);
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win = hanning(floor(length(squeeze(V_exc.Data))/8));
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[pxx, f] = pwelch(squeeze(V_exc.Data), win, 0, [], Fs);
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plot(f, pxx)
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xlabel('Frequency [Hz]'); ylabel('Power Spectral Density [$V^2/Hz$]');
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set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log');
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1
matlab/notes.txt
Normal file
1
matlab/notes.txt
Normal file
@ -0,0 +1 @@
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6.39 kg
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