Encoder - Test Bench
Table of Contents
-
-
- 1. Experimental Setup -
- 2. Huddle Test +
- 1. Experimental Setup +
- 2. Huddle Test -
- 3. Comparison Interferometer / Encoder +
- 3. Comparison Interferometer / Encoder
-
-
- 3.1. Load Data -
- 3.2. Time Domain Results -
- 3.3. Difference between Encoder and Interferometer as a function of time -
- 3.4. Difference between Encoder and Interferometer as a function of position +
- 3.1. Load Data +
- 3.2. Time Domain Results +
- 3.3. Difference between Encoder and Interferometer as a function of time +
- 3.4. Difference between Encoder and Interferometer as a function of position
- - 4. Identification +
- 4. Identification -
- 5. Change of Stiffness due to Sensors stack being open/closed circuit +
- 5. Change of Stiffness due to Sensors stack being open/closed circuit -
- 6. Generated Number of Charge / Voltage +
- 6. Generated Number of Charge / Voltage
1 Experimental Setup
+1 Experimental Setup
-The experimental Setup is schematically represented in Figure 1. +The experimental Setup is schematically represented in Figure 1.
@@ -82,21 +86,21 @@ The displacement of the mass (relative to the mechanical frame) is measured both
-
Figure 1: Schematic of the Experiment
Figure 2: Side View of the encoder
Figure 3: Front View of the encoder
@@ -104,8 +108,8 @@ The displacement of the mass (relative to the mechanical frame) is measured both2 Huddle Test
+2 Huddle Test
The goal in this section is the estimate the noise of both the encoder and the intereferometer. @@ -117,8 +121,8 @@ Ideally, a mechanical part would clamp the two together, we here suppose that th
2.1 Load Data
+2.1 Load Data
load('mat/int_enc_huddle_test.mat', 'interferometer', 'encoder', 't'); @@ -133,11 +137,11 @@ encoder = detrend(encoder, 0);
2.2 Time Domain Results
+2.2 Time Domain Results
Figure 4: Huddle test - Time domain signals
@@ -149,7 +153,7 @@ encoder = detrend(encoder, 0);
Figure 5: Huddle test - Time domain signals filtered with a LPF at 10Hz
@@ -157,8 +161,8 @@ encoder = detrend(encoder, 0);2.3 Frequency Domain Noise
+2.3 Frequency Domain Noise
Ts = 1e-4; @@ -170,7 +174,7 @@ win = hann(ceil(10/Ts));
Figure 6: Amplitude Spectral Density of the signals during the Huddle test
@@ -179,8 +183,8 @@ win = hann(ceil(10/Ts));3 Comparison Interferometer / Encoder
+3 Comparison Interferometer / Encoder
The goal here is to make sure that the interferometer and encoder measurements are coherent. @@ -188,8 +192,8 @@ We may see non-linearity in the interferometric measurement.
3.1 Load Data
+3.1 Load Data
load('mat/int_enc_comp.mat', 'interferometer', 'encoder', 'u', 't'); @@ -205,18 +209,18 @@ u = detrend(u, 0);
3.2 Time Domain Results
+3.2 Time Domain Results
Figure 7: One cycle measurement
Figure 8: Difference between the Encoder and the interferometer during one cycle
@@ -224,8 +228,8 @@ u = detrend(u, 0);3.3 Difference between Encoder and Interferometer as a function of time
+3.3 Difference between Encoder and Interferometer as a function of time
Ts = 1e-4; @@ -246,7 +250,7 @@ d_err_mean = d_err_mean - mean(d_err_mean);
Figure 9: Difference between the two measurement in the time domain, averaged for all the cycles
@@ -254,8 +258,8 @@ d_err_mean = d_err_mean - mean(d_err_mean);3.4 Difference between Encoder and Interferometer as a function of position
+3.4 Difference between Encoder and Interferometer as a function of position
Compute the mean of the interferometer measurement corresponding to each of the encoder measurement. @@ -274,7 +278,7 @@ i_mean_error = (i_mean - e_sorted);
Figure 10: Difference between the two measurement as a function of the measured position by the encoder, averaged for all the cycles
@@ -295,7 +299,7 @@ e_sorted_mean_over_period = mean(reshape(i_mean_error(i_init +
Figure 11: Non-Linearity of the Interferometer over the period of the wavelength
@@ -304,12 +308,12 @@ e_sorted_mean_over_period = mean(reshape(i_mean_error(i_init -4 Identification
+4 Identification
4.1 Load Data
+4.1 Load Data
load('mat/int_enc_id_noise_bis.mat', 'interferometer', 'encoder', 'u', 't'); @@ -325,8 +329,8 @@ u = detrend(u, 0);
4.2 Identification
+4.2 Identification
Ts = 1e-4; % Sampling Time [s] @@ -344,14 +348,14 @@ win = hann(ceil(10/Ts));
5 Change of Stiffness due to Sensors stack being open/closed circuit
+5 Change of Stiffness due to Sensors stack being open/closed circuit
5.1 Load Data
+5.1 Load Data
oc = load('./mat/identification_open_circuit.mat', 't', 'encoder', 'u'); @@ -374,8 +378,8 @@ sc = load('./mat/identification_short_circuit.mat'
5.2 Transfer Functions
+5.2 Transfer Functions
Ts = 1e-4; % Sampling Time [s] @@ -393,26 +397,26 @@ win = hann(ceil(10/Ts));
Figure 16: Zoom on the change of resonance
The change of resonance frequency / stiffness is very small and is not important here.
@@ -422,8 +426,8 @@ The change of resonance frequency / stiffness is very small and is not important6 Generated Number of Charge / Voltage
+6 Generated Number of Charge / Voltage
Two stacks are used as actuator (in parallel) and one stack is used as sensor. @@ -434,8 +438,8 @@ The amplifier gain is 20V/V (Cedrat LA75B).
6.1 Steps
+6.1 Steps
load('./mat/force_sensor_steps.mat', 't', 'encoder', 'u', 'v'); @@ -455,7 +459,7 @@ xlabel('Time [s]'); ylabel( +
Figure 17: Time domain signal during the 3 actuator voltage steps
@@ -580,7 +584,7 @@ Rin = abs(mean(tau))/Cp; The input impedance of the Speedgoat’s ADC should then be close to \(1.5\,M\Omega\) (specified at \(1\,M\Omega\)). -+How can we explain the voltage offset?
@@ -588,11 +592,11 @@ How can we explain the voltage offset?-As shown in Figure 18 (taken from (Reza and Andrew 2006)), an input voltage offset is due to the input bias current \(i_n\). +As shown in Figure 18 (taken from (Reza and Andrew 2006)), an input voltage offset is due to the input bias current \(i_n\).
-+-
Figure 18: Model of a piezoelectric transducer (left) and instrumentation amplifier (right)
@@ -656,8 +660,8 @@ Which is much more acceptable.-6.2 Sinus
++6.2 Sinus
load('./mat/force_sensor_sin.mat', 't', 'encoder', 'u', 'v'); @@ -670,11 +674,11 @@ t = t(t>25);-The driving voltage is a sinus at 0.5Hz centered on 3V and with an amplitude of 3V (Figure 19). +The driving voltage is a sinus at 0.5Hz centered on 3V and with an amplitude of 3V (Figure 19).
-+
Figure 19: Driving Voltage
@@ -694,11 +698,11 @@ The full stroke as measured by the encoder is:-Its signal is shown in Figure 20. +Its signal is shown in Figure 20.
-+
Figure 20: Encoder measurement
@@ -709,7 +713,7 @@ The generated voltage by the stack is shown in Figure -+
Figure 21: Voltage measured on the stack used as a sensor
@@ -724,10 +728,10 @@ The capacitance of the stack is-The corresponding generated charge is then shown in Figure 22. +The corresponding generated charge is then shown in Figure 22.
-+
Figure 22: Generated Charge
@@ -735,7 +739,7 @@ The corresponding generated charge is then shown in Figure -The relation between the generated voltage and the measured displacement is almost linear as shown in Figure 23. +The relation between the generated voltage and the measured displacement is almost linear as shown in Figure 23.@@ -744,7 +748,7 @@ The relation between the generated voltage and the measured displacement is almo-+
Figure 23: Almost linear relation between the relative displacement and the generated voltage
@@ -773,7 +777,7 @@ With a 16bits ADC, the resolution will then be equals to (in [nm]):diff --git a/index.org b/index.org index 647de5c..a3426e7 100644 --- a/index.org +++ b/index.org @@ -4,6 +4,9 @@ #+EMAIL: dehaeze.thomas@gmail.com #+AUTHOR: Dehaeze Thomas +#+HTML_LINK_HOME: ../index.html +#+HTML_LINK_UP: ../index.html + #+HTML_HEAD: #+HTML_HEAD: #+HTML_HEAD: -Created: 2020-10-29 jeu. 09:59
+Created: 2020-10-29 jeu. 10:08