diff --git a/matlab/frf_analyze.m b/matlab/frf_analyze.m index bf6904e..c757ff2 100644 --- a/matlab/frf_analyze.m +++ b/matlab/frf_analyze.m @@ -9,28 +9,33 @@ addpath('./src/'); % Test with one APA %% Load measurement data for APA number 1 -load(sprintf('mat/frf_data_%i.mat', 1), 't', 'Va', 'Vs', 'de', 'da'); - - - -% Time domain data: - -figure; -plot(t, de); - - +load(sprintf('mat/frf_data_%i_sweep_lf.mat', 2), 't', 'Va', 'Vs', 'de', 'da'); % Compute transfer functions: Ts = (t(end) - t(1))/(length(t)-1); Fs = 1/Ts; -win = hanning(ceil(0.5*Fs)); % Hannning Windows +win = hanning(ceil(1*Fs)); % Hannning Windows [G_dvf, f] = tfestimate(Va, de, win, [], [], 1/Ts); [G_d, ~] = tfestimate(Va, da, win, [], [], 1/Ts); [G_iff, ~] = tfestimate(Va, Vs, win, [], [], 1/Ts); +[coh_dvf, ~] = mscohere(Va, de, win, [], [], 1/Ts); +[coh_d, ~] = mscohere(Va, da, win, [], [], 1/Ts); +[coh_iff, ~] = mscohere(Va, Vs, win, [], [], 1/Ts); + +%% +figure; +hold on; +plot(f, coh_dvf); +plot(f, coh_d); +plot(f, coh_iff); +hold off; +set(gca, 'XScale', 'log'); + +%% figure; tiledlayout(2, 1, 'TileSpacing', 'None', 'Padding', 'None'); @@ -42,7 +47,6 @@ hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); ylabel('Amplitude $V_{out}/V_{in}$ [V/V]'); set(gca, 'XTickLabel',[]); hold off; -ylim([10, 30]); ax2 = nexttile; hold on; @@ -65,7 +69,6 @@ plot(f, abs(G_iff)); set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); ylabel('Amplitude $V_{out}/V_{in}$ [V/V]'); set(gca, 'XTickLabel',[]); hold off; -ylim([10, 30]); ax2 = nexttile; plot(f, 180/pi*angle(G_iff)); @@ -75,7 +78,7 @@ hold off; yticks(-360:90:360); linkaxes([ax1,ax2],'x'); -xlim([5, 5e3]); +xlim([0.1, 10]); % Comparison of all APA diff --git a/matlab/frf_data.mat b/matlab/frf_data.mat new file mode 100644 index 0000000..6641245 Binary files /dev/null and b/matlab/frf_data.mat differ diff --git a/matlab/frf_measure.slx b/matlab/frf_measure.slx index 7d1b7ec..0ccd370 100644 Binary files a/matlab/frf_measure.slx and b/matlab/frf_measure.slx differ diff --git a/matlab/frf_save.m b/matlab/frf_save.m index 33498a1..08c4083 100644 --- a/matlab/frf_save.m +++ b/matlab/frf_save.m @@ -26,7 +26,10 @@ t = data(:, end); % Time [s] % And we save this to a =mat= file: - apa_number = 1; +% leg_number = 4; -save(sprintf('mat/frf_data_%i_huddle.mat', apa_number), 't', 'Va', 'Vs', 'de', 'da'); +save(sprintf('mat/frf_data_leg_coder_%i_noise.mat', apa_number), 't', 'Va', 'Vs', 'de', 'da'); +% save(sprintf('mat/frf_data_leg_coder_%i_sweep.mat', apa_number), 't', 'Va', 'Vs', 'de', 'da'); +% save(sprintf('mat/frf_data_leg_coder_%i_noise_hf.mat', apa_number), 't', 'Va', 'Vs', 'de', 'da'); +% save(sprintf('mat/frf_data_leg_coder_%i_add_mass_closed_circuit.mat', apa_number), 't', 'Va', 'Vs', 'de', 'da'); diff --git a/matlab/frf_setup.m b/matlab/frf_setup.m index f0e8046..ab4d014 100644 --- a/matlab/frf_setup.m +++ b/matlab/frf_setup.m @@ -16,23 +16,6 @@ Trec_dur = 100; % Recording Duration [s] Tsim = 2*Trec_start + Trec_dur; % Simulation Time [s] -%% Sweep Sine -gc = 0.1; -xi = 0.5; -wn = 2*pi*94.3; - -% Notch filter at the resonance of the APA -G_sweep = 0.2*(s^2 + 2*gc*xi*wn*s + wn^2)/(s^2 + 2*xi*wn*s + wn^2); - -V_sweep = generateSweepExc('Ts', Ts, ... - 'f_start', 10, ... - 'f_end', 1e3, ... - 'V_mean', 3.25, ... - 't_start', Trec_start, ... - 'exc_duration', Trec_dur, ... - 'sweep_type', 'log', ... - 'V_exc', G_sweep*1/(1 + s/2/pi/500)); - %% Shaped Noise V_noise = generateShapedNoise('Ts', 1/Fs, ... 'V_mean', 3.25, ... @@ -41,28 +24,79 @@ V_noise = generateShapedNoise('Ts', 1/Fs, ... 'smooth_ends', true, ... 'V_exc', 0.05/(1 + s/2/pi/10)); +%% Sweep Sine +gc = 0.1; +xi = 0.5; +wn = 2*pi*92.7; + +% Notch filter at the resonance of the APA +G_sweep = 0.2*(s^2 + 2*gc*xi*wn*s + wn^2)/(s^2 + 2*xi*wn*s + wn^2); + +V_sweep = generateSweepExc('Ts', Ts, ... + 'f_start', 10, ... + 'f_end', 400, ... + 'V_mean', 3.25, ... + 't_start', Trec_start, ... + 'exc_duration', Trec_dur, ... + 'sweep_type', 'log', ... + 'V_exc', G_sweep*1/(1 + s/2/pi/500)); + +V_sweep_lf = generateSweepExc('Ts', Ts, ... + 'f_start', 0.1, ... + 'f_end', 10, ... + 'V_mean', 3.25, ... + 't_start', Trec_start, ... + 'exc_duration', Trec_dur, ... + 'sweep_type', 'log', ... + 'V_exc', 0.2); + +%% High Frequency Shaped Noise +[b,a] = cheby1(10, 2, 2*pi*[300 2e3], 'bandpass', 's'); +wL = 0.005*tf(b, a); + +V_noise_hf = generateShapedNoise('Ts', 1/Fs, ... + 'V_mean', 3.25, ... + 't_start', Trec_start, ... + 'exc_duration', Trec_dur, ... + 'smooth_ends', true, ... + 'V_exc', wL); + %% Sinus excitation with increasing amplitude V_sin = generateSinIncreasingAmpl('Ts', 1/Fs, ... - 'V_mean', 3.25, ... - 'sin_ampls', [0.1, 0.2, 0.4, 1, 2, 4], ... - 'sin_period', 1, ... - 'sin_num', 5, ... - 't_start', 10, ... - 'smooth_ends', true); + 'V_mean', 3.25, ... + 'sin_ampls', [0.1, 0.2, 0.4, 1, 2, 4], ... + 'sin_period', 1, ... + 'sin_num', 5, ... + 't_start', Trec_start, ... + 'smooth_ends', true); + +%% Zero Excitation +% Trec_start = 10; % Start time for Recording [s] +% Trec_dur = 40; % Recording Duration [s] +% +% Tsim = 2*Trec_start + Trec_dur; % Simulation Time [s] + +V_zero = generateShapedNoise('Ts', 1/Fs, ... + 'V_mean', 3.25, ... + 't_start', Trec_start, ... + 'exc_duration', Trec_dur, ... + 'smooth_ends', true, ... + 'V_exc', tf(0)); %% Select the excitation signal V_exc = timeseries(V_noise(2,:), V_noise(1,:)); +%% Plot figure; tiledlayout(1, 2, 'TileSpacing', 'Normal', 'Padding', 'None'); ax1 = nexttile; -plot(V_exc(1,:), V_exc(2,:)); +plot(V_exc.Time, squeeze(V_exc.Data)); xlabel('Time [s]'); ylabel('Amplitude [V]'); ax2 = nexttile; -win = hanning(floor(length(V_exc)/8)); -[pxx, f] = pwelch(V_exc(2,:), win, 0, [], Fs); +win = hanning(floor(length(squeeze(V_exc.Data))/8)); +[pxx, f] = pwelch(squeeze(V_exc.Data), win, 0, [], Fs); plot(f, pxx) xlabel('Frequency [Hz]'); ylabel('Power Spectral Density [$V^2/Hz$]'); set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log'); diff --git a/matlab/notes.txt b/matlab/notes.txt new file mode 100644 index 0000000..b46d770 --- /dev/null +++ b/matlab/notes.txt @@ -0,0 +1 @@ +6.39 kg \ No newline at end of file