diff --git a/figs/PI_E505_coh.pdf b/figs/PI_E505_coh.pdf new file mode 100644 index 0000000..587aad8 Binary files /dev/null and b/figs/PI_E505_coh.pdf differ diff --git a/figs/PI_E505_coh.png b/figs/PI_E505_coh.png new file mode 100644 index 0000000..0f53bfc Binary files /dev/null and b/figs/PI_E505_coh.png differ diff --git a/figs/PI_E505_tf.pdf b/figs/PI_E505_tf.pdf new file mode 100644 index 0000000..a9c5246 Binary files /dev/null and b/figs/PI_E505_tf.pdf differ diff --git a/figs/PI_E505_tf.png b/figs/PI_E505_tf.png new file mode 100644 index 0000000..f9231b2 Binary files /dev/null and b/figs/PI_E505_tf.png differ diff --git a/index.html b/index.html index b01409a..2da3714 100644 --- a/index.html +++ b/index.html @@ -3,7 +3,7 @@ "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">
- +
Figure 1: Picture of the Setup
Figure 2: Zoom on the APA
Ts = 1e-4; @@ -101,8 +106,8 @@
Glpf = 1/(1 + s/2/pi/500); @@ -114,13 +119,13 @@ Gz = c2d(Glpf, Ts, 'tustin');
data = SimulinkRealTime.utils.getFileScopeData('data/apa95ml.dat').data; @@ -129,8 +134,8 @@ Gz = c2d(Glpf, Ts, 'tustin');
u = data(:, 1); % Input Voltage [V] @@ -147,16 +152,16 @@ t = data(:, 3); % Time [s]
Figure 3: Measurement of the Mass displacement during Huddle Test
@@ -164,8 +169,8 @@ t = data(:, 3); % Time [s]Ts = t(end)/(length(t)-1); @@ -181,7 +186,7 @@ win = hanning(ceil(1*Fs));
Figure 4: Amplitude Spectral Density of the Displacement during Huddle Test
@@ -190,16 +195,16 @@ win = hanning(ceil(1*Fs));
Figure 5: Time domain signals during the test
@@ -207,8 +212,8 @@ win = hanning(ceil(1*Fs));Ts = t(end)/(length(t)-1); @@ -225,7 +230,7 @@ win = hanning(ceil(1*Fs));
Figure 6: Comparison of the ASD for the identification test and the huddle test
@@ -233,8 +238,8 @@ win = hanning(ceil(1*Fs));Ts = t(end)/(length(t)-1); @@ -251,14 +256,14 @@ Fs = 1/Ts;
Figure 7: Coherence
Figure 8: Estimation of the transfer function from input voltage to displacement
@@ -266,8 +271,8 @@ Fs = 1/Ts;load('mat/fem_model_5kg.mat', 'Ghm'); @@ -275,25 +280,85 @@ Fs = 1/Ts;
Figure 9: Comparison of the identified transfer function and the one estimated from the FE model
+The problem comes from the fact that the piezo is driven directly by the DAC that cannot deliver enought current. +In the next section, a current amplifier is used. +
+Ts = t(end)/(length(t)-1); Fs = 1/Ts; ++
+The coherence and the transfer function are estimate from the voltage input of the PI amplifier to its voltage inputs. +
+ ++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). +
+ +win = hann(ceil(10/Ts)); + +[tf_est, f] = tfestimate(u, um, win, [], [], 1/Ts); +[co_est, ~] = mscohere( u, um, win, [], [], 1/Ts); ++
+
+Figure 10: Coherence
++
+Figure 11: Estimation of the transfer function from input voltage to displacement
+Ts = t(end)/(length(t)-1); +Fs = 1/Ts; win = hanning(ceil(1*Fs));@@ -306,17 +371,17 @@ win = hanning(ceil(1*Fs));
-
Figure 10: Comparison of the ASD for the identification test and the huddle test
+Figure 12: Comparison of the ASD for the identification test and the huddle test
Ts = t(end)/(length(t)-1); Fs = 1/Ts; @@ -332,34 +397,34 @@ Fs = 1/Ts;
-
Figure 11: Coherence
+Figure 13: Coherence
-
Figure 12: Estimation of the transfer function from input voltage to displacement
+Figure 14: Estimation of the transfer function from input voltage to displacement
load('mat/fem_model_5kg.mat', 'Ghm');
-
Figure 13: Comparison of the identified transfer function and the one estimated from the FE model
+Figure 15: Comparison of the identified transfer function and the one estimated from the FE model
Created: 2020-07-23 jeu. 09:33
+Created: 2020-07-24 ven. 11:34