diff --git a/index.html b/index.html index 2da3714..bde09d9 100644 --- a/index.html +++ b/index.html @@ -3,7 +3,7 @@ "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"> - + Test Bench APA95ML @@ -35,42 +35,42 @@

Table of Contents

@@ -78,26 +78,26 @@
-
+

setup_picture.png

Figure 1: Picture of the Setup

-
+

setup_zoom.png

Figure 2: Zoom on the APA

-
-

1 Setup

+
+

1 Setup

-
-

1.1 Parameters

+
+

1.1 Parameters

Ts = 1e-4;
@@ -106,8 +106,8 @@
-
-

1.2 Filter White Noise

+
+

1.2 Filter White Noise

Glpf = 1/(1 + s/2/pi/500);
@@ -119,13 +119,13 @@ Gz = c2d(Glpf, Ts, 'tustin');
-
-

2 Run Experiment and Save Data

+
+

2 Run Experiment and Save Data

-
-

2.1 Load Data

+
+

2.1 Load Data

data = SimulinkRealTime.utils.getFileScopeData('data/apa95ml.dat').data;
@@ -134,8 +134,8 @@ Gz = c2d(Glpf, Ts, 'tustin');
-
-

2.2 Save Data

+
+

2.2 Save Data

u = data(:, 1); % Input Voltage [V]
@@ -152,16 +152,16 @@ t = data(:, 3); % Time [s]
-
-

3 Huddle Test

+
+

3 Huddle Test

-
-

3.1 Time Domain Data

+
+

3.1 Time Domain Data

-
+

huddle_test_time_domain.png

Figure 3: Measurement of the Mass displacement during Huddle Test

@@ -169,8 +169,8 @@ t = data(:, 3); % Time [s]
-
-

3.2 PSD of Measurement Noise

+
+

3.2 PSD of Measurement Noise

Ts = t(end)/(length(t)-1);
@@ -186,7 +186,7 @@ win = hanning(ceil(1*Fs));
-
+

huddle_test_pdf.png

Figure 4: Amplitude Spectral Density of the Displacement during Huddle Test

@@ -195,16 +195,16 @@ win = hanning(ceil(1*Fs));
-
-

4 Transfer Function Estimation with \(m=5kg\)

+
+

4 Transfer Function Estimation with \(m=5kg\)

-
-

4.1 Time Domain Data

+
+

4.1 Time Domain Data

-
+

apa95ml_5kg_10V_time_domain.png

Figure 5: Time domain signals during the test

@@ -212,8 +212,8 @@ win = hanning(ceil(1*Fs));
-
-

4.2 Comparison of the PSD with Huddle Test

+
+

4.2 Comparison of the PSD with Huddle Test

Ts = t(end)/(length(t)-1);
@@ -230,7 +230,7 @@ win = hanning(ceil(1*Fs));
-
+

apa95ml_5kg_10V_pdf_comp_huddle.png

Figure 6: Comparison of the ASD for the identification test and the huddle test

@@ -238,8 +238,8 @@ win = hanning(ceil(1*Fs));
-
-

4.3 Compute TF estimate and Coherence

+
+

4.3 Compute TF estimate and Coherence

Ts = t(end)/(length(t)-1);
@@ -256,14 +256,14 @@ Fs = 1/Ts;
-
+

apa95ml_5kg_10V_coh.png

Figure 7: Coherence

-
+

apa95ml_5kg_10V_tf.png

Figure 8: Estimation of the transfer function from input voltage to displacement

@@ -271,8 +271,8 @@ Fs = 1/Ts;
-
-

4.4 Comparison with the FEM model

+
+

4.4 Comparison with the FEM model

load('mat/fem_model_5kg.mat', 'Ghm');
@@ -280,7 +280,7 @@ Fs = 1/Ts;
-
+

apa95ml_5kg_comp_fem.png

Figure 9: Comparison of the identified transfer function and the one estimated from the FE model

@@ -299,12 +299,12 @@ In the next section, a current amplifier is used.
-
-

5 Transfer function of the PI Amplifier

+
+

5 Transfer function of the PI Amplifier

-
-

5.1 Compute TF estimate and Coherence

+
+

5.1 Compute TF estimate and Coherence

Ts = t(end)/(length(t)-1);
@@ -317,11 +317,11 @@ The coherence and the transfer function are estimate from the voltage input of t
 

 
 

-The coherence is very good as expected (Figure 10).
+The coherence is very good as expected (Figure 10).
 

 
 

-The transfer function show a low pass filter behavior with a lot of phase drop (Figure 11).
+The transfer function show a low pass filter behavior with a lot of phase drop (Figure 11).
 

 
 

@@ -333,28 +333,40 @@ The transfer function show a low pass filter behavior with a lot of phase drop (
 

 
 
-

+

 
PI_E505_coh.png
 

 
Figure 10: Coherence

 

 
 
-

+

 
PI_E505_tf.png
 

 
Figure 11: Estimation of the transfer function from input voltage to displacement

 

+
+

+The delay can be estimated as follow:
+

+

+
finddelay(u, um)*Ts
+

+

+
+
+0.0004
+
-
-

6 PI Amplifier

+
+

6 PI Amplifier

-
-

6.1 Comparison of the PSD with Huddle Test

+
+

6.1 Comparison of the PSD with Huddle Test

Ts = t(end)/(length(t)-1);
@@ -371,7 +383,7 @@ win = hanning(ceil(1*Fs));
-
+

apa95ml_5kg_PI_pdf_comp_huddle.png

Figure 12: Comparison of the ASD for the identification test and the huddle test

@@ -379,8 +391,8 @@ win = hanning(ceil(1*Fs));
-
-

6.2 Compute TF estimate and Coherence

+
+

6.2 Compute TF estimate and Coherence

Ts = t(end)/(length(t)-1);
@@ -397,14 +409,14 @@ Fs = 1/Ts;
-
+

apa95ml_5kg_PI_coh.png

Figure 13: Coherence

-
+

apa95ml_5kg_PI_tf.png

Figure 14: Estimation of the transfer function from input voltage to displacement

@@ -412,8 +424,8 @@ Fs = 1/Ts;
-
-

6.3 Comparison with the FEM model

+
+

6.3 Comparison with the FEM model

load('mat/fem_model_5kg.mat', 'Ghm');
@@ -421,7 +433,7 @@ Fs = 1/Ts;
-
+

apa95ml_5kg_pi_comp_fem.png

Figure 15: Comparison of the identified transfer function and the one estimated from the FE model

@@ -432,7 +444,7 @@ Fs = 1/Ts;

Author: Dehaeze Thomas

-

Created: 2020-07-24 ven. 11:34

+

Created: 2020-07-24 ven. 13:06

diff --git a/index.org b/index.org index 924b16c..08e0fd3 100644 --- a/index.org +++ b/index.org @@ -405,7 +405,7 @@ The transfer function show a low pass filter behavior with a lot of phase drop ( ax2 = subplot(2, 1, 2); hold on; plot(f, 180/pi*angle(tf_est), 'k-') - set(gca, 'Xscale', 'log'); set(gca, 'Yscale', 'lin'); + set(gca, 'Xscale', 'lin'); set(gca, 'Yscale', 'lin'); ylabel('Phase'); xlabel('Frequency [Hz]'); hold off; ylim([-180, 180]); @@ -424,6 +424,14 @@ The transfer function show a low pass filter behavior with a lot of phase drop ( #+RESULTS: [[file:figs/PI_E505_tf.png]] +The delay can be estimated as follow: +#+begin_src matlab :results replace value + finddelay(u, um)*Ts +#+end_src + +#+RESULTS: +: 0.0004 + * PI Amplifier ** Matlab Init :noexport:ignore: #+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name)