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Test Bench APA

Table of Contents

1 Setup

1.1 Parameters

Ts = 1e-4;

1.2 Filter White Noise

Glpf = 1/(1 + s/2/pi/500);

Gz = c2d(Glpf, Ts, 'tustin');

2 Run Experiment and Save Data

2.1 Load Data

data = SimulinkRealTime.utils.getFileScopeData('data/apa95ml.dat').data;

2.2 Save Data

u = data(:, 1); % Input Voltage [V]
y = data(:, 2); % Output Displacement [m]
t = data(:, 3); % Time [s]
save('./mat/huddle_test.mat', 't', 'u', 'y', 'Glpf');

3 Huddle Test

3.1 Time Domain Data

huddle_test_time_domain.png

Figure 1: Measurement of the Mass displacement during Huddle Test

3.2 PSD of Measurement Noise

Ts = t(end)/(length(t)-1);
Fs = 1/Ts;

win = hanning(ceil(1*Fs));
[pxx, f] = pwelch(y, win, [], [], Fs);

huddle_test_pdf.png

Figure 2: Amplitude Spectral Density of the Displacement during Huddle Test

4 Transfer Function Estimation with m=5kg

4.1 Time Domain Data

apa95ml_5kg_10V_time_domain.png

Figure 3: Time domain signals during the test

4.2 Comparison of the PSD with Huddle Test

Ts = t(end)/(length(t)-1);
Fs = 1/Ts;

win = hanning(ceil(1*Fs));
[pxx, f] = pwelch(y, win, [], [], Fs);
[pht, ~] = pwelch(ht.y, win, [], [], Fs);

apa95ml_5kg_10V_pdf_comp_huddle.png

Figure 4: Comparison of the ASD for the identification test and the huddle test

4.3 Compute TF estimate and Coherence

win = hann(ceil(1/Ts));

[tf_est, f] = tfestimate(u, -y, win, [], [], 1/Ts);
[co_est, ~] = mscohere(  u, -y, win, [], [], 1/Ts);

apa95ml_5kg_10V_coh.png

Figure 5: Coherence

apa95ml_5kg_10V_tf.png

Figure 6: Estimation of the transfer function from input voltage to displacement

Author: Dehaeze Thomas

Created: 2020-07-20 lun. 11:27