Add analysis on the force sensor

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Thomas Dehaeze 2020-10-29 09:59:29 +01:00
parent 0f1c082b66
commit 2d6a2953cf
22 changed files with 884 additions and 55 deletions

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@ -3,7 +3,7 @@
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"> "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">
<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"> <html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en">
<head> <head>
<!-- 2020-10-25 dim. 09:06 --> <!-- 2020-10-29 jeu. 09:59 -->
<meta http-equiv="Content-Type" content="text/html;charset=utf-8" /> <meta http-equiv="Content-Type" content="text/html;charset=utf-8" />
<title>Encoder - Test Bench</title> <title>Encoder - Test Bench</title>
<meta name="generator" content="Org mode" /> <meta name="generator" content="Org mode" />
@ -31,37 +31,49 @@
<h2>Table of Contents</h2> <h2>Table of Contents</h2>
<div id="text-table-of-contents"> <div id="text-table-of-contents">
<ul> <ul>
<li><a href="#org62e3fd3">1. Experimental Setup</a></li> <li><a href="#org6fbc445">1. Experimental Setup</a></li>
<li><a href="#org12a748d">2. Huddle Test</a> <li><a href="#orgdbbcb08">2. Huddle Test</a>
<ul> <ul>
<li><a href="#orgcc6a5f5">2.1. Load Data</a></li> <li><a href="#orge0cae84">2.1. Load Data</a></li>
<li><a href="#org38dca56">2.2. Time Domain Results</a></li> <li><a href="#orgeb6de99">2.2. Time Domain Results</a></li>
<li><a href="#orgb3db033">2.3. Frequency Domain Noise</a></li> <li><a href="#orga9c316e">2.3. Frequency Domain Noise</a></li>
</ul> </ul>
</li> </li>
<li><a href="#org99db9f6">3. Comparison Interferometer / Encoder</a> <li><a href="#org3f480f8">3. Comparison Interferometer / Encoder</a>
<ul> <ul>
<li><a href="#org1d63b9a">3.1. Load Data</a></li> <li><a href="#org1144cae">3.1. Load Data</a></li>
<li><a href="#org185e20d">3.2. Time Domain Results</a></li> <li><a href="#org504ca00">3.2. Time Domain Results</a></li>
<li><a href="#org04cd372">3.3. Difference between Encoder and Interferometer as a function of time</a></li> <li><a href="#org0bb5487">3.3. Difference between Encoder and Interferometer as a function of time</a></li>
<li><a href="#org0271741">3.4. Difference between Encoder and Interferometer as a function of position</a></li> <li><a href="#org8ffe43b">3.4. Difference between Encoder and Interferometer as a function of position</a></li>
</ul> </ul>
</li> </li>
<li><a href="#orga08d704">4. Identification</a> <li><a href="#org8db94b6">4. Identification</a>
<ul> <ul>
<li><a href="#orgaa05248">4.1. Load Data</a></li> <li><a href="#org5dbc303">4.1. Load Data</a></li>
<li><a href="#org0d4f0cd">4.2. Identification</a></li> <li><a href="#org7e6c771">4.2. Identification</a></li>
</ul>
</li>
<li><a href="#org34f3a3e">5. Change of Stiffness due to Sensors stack being open/closed circuit</a>
<ul>
<li><a href="#org74a3435">5.1. Load Data</a></li>
<li><a href="#org3c7c26d">5.2. Transfer Functions</a></li>
</ul>
</li>
<li><a href="#org939e6d1">6. Generated Number of Charge / Voltage</a>
<ul>
<li><a href="#org24ebf58">6.1. Steps</a></li>
<li><a href="#orgd891bf7">6.2. Sinus</a></li>
</ul> </ul>
</li> </li>
</ul> </ul>
</div> </div>
</div> </div>
<div id="outline-container-org62e3fd3" class="outline-2"> <div id="outline-container-org6fbc445" class="outline-2">
<h2 id="org62e3fd3"><span class="section-number-2">1</span> Experimental Setup</h2> <h2 id="org6fbc445"><span class="section-number-2">1</span> Experimental Setup</h2>
<div class="outline-text-2" id="text-1"> <div class="outline-text-2" id="text-1">
<p> <p>
The experimental Setup is schematically represented in Figure <a href="#org4fd66dc">1</a>. The experimental Setup is schematically represented in Figure <a href="#orgd0e8875">1</a>.
</p> </p>
<p> <p>
@ -70,21 +82,21 @@ The displacement of the mass (relative to the mechanical frame) is measured both
</p> </p>
<div id="org4fd66dc" class="figure"> <div id="orgd0e8875" class="figure">
<p><img src="figs/exp_setup_schematic.png" alt="exp_setup_schematic.png" /> <p><img src="figs/exp_setup_schematic.png" alt="exp_setup_schematic.png" />
</p> </p>
<p><span class="figure-number">Figure 1: </span>Schematic of the Experiment</p> <p><span class="figure-number">Figure 1: </span>Schematic of the Experiment</p>
</div> </div>
<div id="orge37bdbc" class="figure"> <div id="orga0a129f" class="figure">
<p><img src="figs/IMG_20201023_153905.jpg" alt="IMG_20201023_153905.jpg" /> <p><img src="figs/IMG_20201023_153905.jpg" alt="IMG_20201023_153905.jpg" />
</p> </p>
<p><span class="figure-number">Figure 2: </span>Side View of the encoder</p> <p><span class="figure-number">Figure 2: </span>Side View of the encoder</p>
</div> </div>
<div id="org168fd7f" class="figure"> <div id="org3eb8621" class="figure">
<p><img src="figs/IMG_20201023_153914.jpg" alt="IMG_20201023_153914.jpg" /> <p><img src="figs/IMG_20201023_153914.jpg" alt="IMG_20201023_153914.jpg" />
</p> </p>
<p><span class="figure-number">Figure 3: </span>Front View of the encoder</p> <p><span class="figure-number">Figure 3: </span>Front View of the encoder</p>
@ -92,8 +104,8 @@ The displacement of the mass (relative to the mechanical frame) is measured both
</div> </div>
</div> </div>
<div id="outline-container-org12a748d" class="outline-2"> <div id="outline-container-orgdbbcb08" class="outline-2">
<h2 id="org12a748d"><span class="section-number-2">2</span> Huddle Test</h2> <h2 id="orgdbbcb08"><span class="section-number-2">2</span> Huddle Test</h2>
<div class="outline-text-2" id="text-2"> <div class="outline-text-2" id="text-2">
<p> <p>
The goal in this section is the estimate the noise of both the encoder and the intereferometer. The goal in this section is the estimate the noise of both the encoder and the intereferometer.
@ -105,8 +117,8 @@ Ideally, a mechanical part would clamp the two together, we here suppose that th
</p> </p>
</div> </div>
<div id="outline-container-orgcc6a5f5" class="outline-3"> <div id="outline-container-orge0cae84" class="outline-3">
<h3 id="orgcc6a5f5"><span class="section-number-3">2.1</span> Load Data</h3> <h3 id="orge0cae84"><span class="section-number-3">2.1</span> Load Data</h3>
<div class="outline-text-3" id="text-2-1"> <div class="outline-text-3" id="text-2-1">
<div class="org-src-container"> <div class="org-src-container">
<pre class="src src-matlab">load(<span class="org-string">'mat/int_enc_huddle_test.mat'</span>, <span class="org-string">'interferometer'</span>, <span class="org-string">'encoder'</span>, <span class="org-string">'t'</span>); <pre class="src src-matlab">load(<span class="org-string">'mat/int_enc_huddle_test.mat'</span>, <span class="org-string">'interferometer'</span>, <span class="org-string">'encoder'</span>, <span class="org-string">'t'</span>);
@ -121,11 +133,11 @@ encoder = detrend(encoder, 0);
</div> </div>
</div> </div>
<div id="outline-container-org38dca56" class="outline-3"> <div id="outline-container-orgeb6de99" class="outline-3">
<h3 id="org38dca56"><span class="section-number-3">2.2</span> Time Domain Results</h3> <h3 id="orgeb6de99"><span class="section-number-3">2.2</span> Time Domain Results</h3>
<div class="outline-text-3" id="text-2-2"> <div class="outline-text-3" id="text-2-2">
<div id="org1e8928d" class="figure"> <div id="org686e97a" class="figure">
<p><img src="figs/huddle_test_time_domain.png" alt="huddle_test_time_domain.png" /> <p><img src="figs/huddle_test_time_domain.png" alt="huddle_test_time_domain.png" />
</p> </p>
<p><span class="figure-number">Figure 4: </span>Huddle test - Time domain signals</p> <p><span class="figure-number">Figure 4: </span>Huddle test - Time domain signals</p>
@ -137,7 +149,7 @@ encoder = detrend(encoder, 0);
</div> </div>
<div id="org831d12c" class="figure"> <div id="orgb481e1f" class="figure">
<p><img src="figs/huddle_test_time_domain_filtered.png" alt="huddle_test_time_domain_filtered.png" /> <p><img src="figs/huddle_test_time_domain_filtered.png" alt="huddle_test_time_domain_filtered.png" />
</p> </p>
<p><span class="figure-number">Figure 5: </span>Huddle test - Time domain signals filtered with a LPF at 10Hz</p> <p><span class="figure-number">Figure 5: </span>Huddle test - Time domain signals filtered with a LPF at 10Hz</p>
@ -145,8 +157,8 @@ encoder = detrend(encoder, 0);
</div> </div>
</div> </div>
<div id="outline-container-orgb3db033" class="outline-3"> <div id="outline-container-orga9c316e" class="outline-3">
<h3 id="orgb3db033"><span class="section-number-3">2.3</span> Frequency Domain Noise</h3> <h3 id="orga9c316e"><span class="section-number-3">2.3</span> Frequency Domain Noise</h3>
<div class="outline-text-3" id="text-2-3"> <div class="outline-text-3" id="text-2-3">
<div class="org-src-container"> <div class="org-src-container">
<pre class="src src-matlab">Ts = 1e<span class="org-type">-</span>4; <pre class="src src-matlab">Ts = 1e<span class="org-type">-</span>4;
@ -158,7 +170,7 @@ win = hann(ceil(10<span class="org-type">/</span>Ts));
</div> </div>
<div id="orgd4d1e96" class="figure"> <div id="org8d5409d" class="figure">
<p><img src="figs/huddle_test_asd.png" alt="huddle_test_asd.png" /> <p><img src="figs/huddle_test_asd.png" alt="huddle_test_asd.png" />
</p> </p>
<p><span class="figure-number">Figure 6: </span>Amplitude Spectral Density of the signals during the Huddle test</p> <p><span class="figure-number">Figure 6: </span>Amplitude Spectral Density of the signals during the Huddle test</p>
@ -167,8 +179,8 @@ win = hann(ceil(10<span class="org-type">/</span>Ts));
</div> </div>
</div> </div>
<div id="outline-container-org99db9f6" class="outline-2"> <div id="outline-container-org3f480f8" class="outline-2">
<h2 id="org99db9f6"><span class="section-number-2">3</span> Comparison Interferometer / Encoder</h2> <h2 id="org3f480f8"><span class="section-number-2">3</span> Comparison Interferometer / Encoder</h2>
<div class="outline-text-2" id="text-3"> <div class="outline-text-2" id="text-3">
<p> <p>
The goal here is to make sure that the interferometer and encoder measurements are coherent. The goal here is to make sure that the interferometer and encoder measurements are coherent.
@ -176,8 +188,8 @@ We may see non-linearity in the interferometric measurement.
</p> </p>
</div> </div>
<div id="outline-container-org1d63b9a" class="outline-3"> <div id="outline-container-org1144cae" class="outline-3">
<h3 id="org1d63b9a"><span class="section-number-3">3.1</span> Load Data</h3> <h3 id="org1144cae"><span class="section-number-3">3.1</span> Load Data</h3>
<div class="outline-text-3" id="text-3-1"> <div class="outline-text-3" id="text-3-1">
<div class="org-src-container"> <div class="org-src-container">
<pre class="src src-matlab">load(<span class="org-string">'mat/int_enc_comp.mat'</span>, <span class="org-string">'interferometer'</span>, <span class="org-string">'encoder'</span>, <span class="org-string">'u'</span>, <span class="org-string">'t'</span>); <pre class="src src-matlab">load(<span class="org-string">'mat/int_enc_comp.mat'</span>, <span class="org-string">'interferometer'</span>, <span class="org-string">'encoder'</span>, <span class="org-string">'u'</span>, <span class="org-string">'t'</span>);
@ -193,18 +205,18 @@ u = detrend(u, 0);
</div> </div>
</div> </div>
<div id="outline-container-org185e20d" class="outline-3"> <div id="outline-container-org504ca00" class="outline-3">
<h3 id="org185e20d"><span class="section-number-3">3.2</span> Time Domain Results</h3> <h3 id="org504ca00"><span class="section-number-3">3.2</span> Time Domain Results</h3>
<div class="outline-text-3" id="text-3-2"> <div class="outline-text-3" id="text-3-2">
<div id="orgf56a137" class="figure"> <div id="org5e28133" class="figure">
<p><img src="figs/int_enc_one_cycle.png" alt="int_enc_one_cycle.png" /> <p><img src="figs/int_enc_one_cycle.png" alt="int_enc_one_cycle.png" />
</p> </p>
<p><span class="figure-number">Figure 7: </span>One cycle measurement</p> <p><span class="figure-number">Figure 7: </span>One cycle measurement</p>
</div> </div>
<div id="org3adb535" class="figure"> <div id="org1d42180" class="figure">
<p><img src="figs/int_enc_one_cycle_error.png" alt="int_enc_one_cycle_error.png" /> <p><img src="figs/int_enc_one_cycle_error.png" alt="int_enc_one_cycle_error.png" />
</p> </p>
<p><span class="figure-number">Figure 8: </span>Difference between the Encoder and the interferometer during one cycle</p> <p><span class="figure-number">Figure 8: </span>Difference between the Encoder and the interferometer during one cycle</p>
@ -212,8 +224,8 @@ u = detrend(u, 0);
</div> </div>
</div> </div>
<div id="outline-container-org04cd372" class="outline-3"> <div id="outline-container-org0bb5487" class="outline-3">
<h3 id="org04cd372"><span class="section-number-3">3.3</span> Difference between Encoder and Interferometer as a function of time</h3> <h3 id="org0bb5487"><span class="section-number-3">3.3</span> Difference between Encoder and Interferometer as a function of time</h3>
<div class="outline-text-3" id="text-3-3"> <div class="outline-text-3" id="text-3-3">
<div class="org-src-container"> <div class="org-src-container">
<pre class="src src-matlab">Ts = 1e<span class="org-type">-</span>4; <pre class="src src-matlab">Ts = 1e<span class="org-type">-</span>4;
@ -234,7 +246,7 @@ d_err_mean = d_err_mean <span class="org-type">-</span> mean(d_err_mean);
</div> </div>
<div id="orgd16ecc5" class="figure"> <div id="org8fda1bf" class="figure">
<p><img src="figs/int_enc_error_mean_time.png" alt="int_enc_error_mean_time.png" /> <p><img src="figs/int_enc_error_mean_time.png" alt="int_enc_error_mean_time.png" />
</p> </p>
<p><span class="figure-number">Figure 9: </span>Difference between the two measurement in the time domain, averaged for all the cycles</p> <p><span class="figure-number">Figure 9: </span>Difference between the two measurement in the time domain, averaged for all the cycles</p>
@ -242,8 +254,8 @@ d_err_mean = d_err_mean <span class="org-type">-</span> mean(d_err_mean);
</div> </div>
</div> </div>
<div id="outline-container-org0271741" class="outline-3"> <div id="outline-container-org8ffe43b" class="outline-3">
<h3 id="org0271741"><span class="section-number-3">3.4</span> Difference between Encoder and Interferometer as a function of position</h3> <h3 id="org8ffe43b"><span class="section-number-3">3.4</span> Difference between Encoder and Interferometer as a function of position</h3>
<div class="outline-text-3" id="text-3-4"> <div class="outline-text-3" id="text-3-4">
<p> <p>
Compute the mean of the interferometer measurement corresponding to each of the encoder measurement. Compute the mean of the interferometer measurement corresponding to each of the encoder measurement.
@ -262,7 +274,7 @@ i_mean_error = (i_mean <span class="org-type">-</span> e_sorted);
</div> </div>
<div id="org81096af" class="figure"> <div id="org3b4facc" class="figure">
<p><img src="figs/int_enc_error_mean_position.png" alt="int_enc_error_mean_position.png" /> <p><img src="figs/int_enc_error_mean_position.png" alt="int_enc_error_mean_position.png" />
</p> </p>
<p><span class="figure-number">Figure 10: </span>Difference between the two measurement as a function of the measured position by the encoder, averaged for all the cycles</p> <p><span class="figure-number">Figure 10: </span>Difference between the two measurement as a function of the measured position by the encoder, averaged for all the cycles</p>
@ -283,7 +295,7 @@ e_sorted_mean_over_period = mean(reshape(i_mean_error(i_init<span class="org-typ
</div> </div>
<div id="orgd460333" class="figure"> <div id="org8f808d8" class="figure">
<p><img src="figs/int_non_linearity_period_wavelength.png" alt="int_non_linearity_period_wavelength.png" /> <p><img src="figs/int_non_linearity_period_wavelength.png" alt="int_non_linearity_period_wavelength.png" />
</p> </p>
<p><span class="figure-number">Figure 11: </span>Non-Linearity of the Interferometer over the period of the wavelength</p> <p><span class="figure-number">Figure 11: </span>Non-Linearity of the Interferometer over the period of the wavelength</p>
@ -292,12 +304,12 @@ e_sorted_mean_over_period = mean(reshape(i_mean_error(i_init<span class="org-typ
</div> </div>
</div> </div>
<div id="outline-container-orga08d704" class="outline-2"> <div id="outline-container-org8db94b6" class="outline-2">
<h2 id="orga08d704"><span class="section-number-2">4</span> Identification</h2> <h2 id="org8db94b6"><span class="section-number-2">4</span> Identification</h2>
<div class="outline-text-2" id="text-4"> <div class="outline-text-2" id="text-4">
</div> </div>
<div id="outline-container-orgaa05248" class="outline-3"> <div id="outline-container-org5dbc303" class="outline-3">
<h3 id="orgaa05248"><span class="section-number-3">4.1</span> Load Data</h3> <h3 id="org5dbc303"><span class="section-number-3">4.1</span> Load Data</h3>
<div class="outline-text-3" id="text-4-1"> <div class="outline-text-3" id="text-4-1">
<div class="org-src-container"> <div class="org-src-container">
<pre class="src src-matlab">load(<span class="org-string">'mat/int_enc_id_noise_bis.mat'</span>, <span class="org-string">'interferometer'</span>, <span class="org-string">'encoder'</span>, <span class="org-string">'u'</span>, <span class="org-string">'t'</span>); <pre class="src src-matlab">load(<span class="org-string">'mat/int_enc_id_noise_bis.mat'</span>, <span class="org-string">'interferometer'</span>, <span class="org-string">'encoder'</span>, <span class="org-string">'u'</span>, <span class="org-string">'t'</span>);
@ -313,8 +325,8 @@ u = detrend(u, 0);
</div> </div>
</div> </div>
<div id="outline-container-org0d4f0cd" class="outline-3"> <div id="outline-container-org7e6c771" class="outline-3">
<h3 id="org0d4f0cd"><span class="section-number-3">4.2</span> Identification</h3> <h3 id="org7e6c771"><span class="section-number-3">4.2</span> Identification</h3>
<div class="outline-text-3" id="text-4-2"> <div class="outline-text-3" id="text-4-2">
<div class="org-src-container"> <div class="org-src-container">
<pre class="src src-matlab">Ts = 1e<span class="org-type">-</span>4; <span class="org-comment">% Sampling Time [s]</span> <pre class="src src-matlab">Ts = 1e<span class="org-type">-</span>4; <span class="org-comment">% Sampling Time [s]</span>
@ -332,24 +344,436 @@ win = hann(ceil(10<span class="org-type">/</span>Ts));
</div> </div>
<div id="org0157819" class="figure"> <div id="org002dcef" class="figure">
<p><img src="figs/identification_dynamics_coherence.png" alt="identification_dynamics_coherence.png" /> <p><img src="figs/identification_dynamics_coherence.png" alt="identification_dynamics_coherence.png" />
</p> </p>
</div> </div>
<div id="org4b89965" class="figure"> <div id="orgdbdd6e0" class="figure">
<p><img src="figs/identification_dynamics_bode.png" alt="identification_dynamics_bode.png" /> <p><img src="figs/identification_dynamics_bode.png" alt="identification_dynamics_bode.png" />
</p> </p>
</div> </div>
</div> </div>
</div> </div>
</div> </div>
<div id="outline-container-org34f3a3e" class="outline-2">
<h2 id="org34f3a3e"><span class="section-number-2">5</span> Change of Stiffness due to Sensors stack being open/closed circuit</h2>
<div class="outline-text-2" id="text-5">
</div>
<div id="outline-container-org74a3435" class="outline-3">
<h3 id="org74a3435"><span class="section-number-3">5.1</span> Load Data</h3>
<div class="outline-text-3" id="text-5-1">
<div class="org-src-container">
<pre class="src src-matlab">oc = load(<span class="org-string">'./mat/identification_open_circuit.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'encoder'</span>, <span class="org-string">'u'</span>);
sc = load(<span class="org-string">'./mat/identification_short_circuit.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'encoder'</span>, <span class="org-string">'u'</span>);
</pre>
</div>
</div>
</div>
<div id="outline-container-org3c7c26d" class="outline-3">
<h3 id="org3c7c26d"><span class="section-number-3">5.2</span> Transfer Functions</h3>
<div class="outline-text-3" id="text-5-2">
<div class="org-src-container">
<pre class="src src-matlab">Ts = 1e<span class="org-type">-</span>4; <span class="org-comment">% Sampling Time [s]</span>
win = hann(ceil(10<span class="org-type">/</span>Ts));
</pre>
</div>
<div class="org-src-container">
<pre class="src src-matlab">[tf_oc_est, f] = tfestimate(oc.u, oc.encoder, win, [], [], 1<span class="org-type">/</span>Ts);
[co_oc_est, <span class="org-type">~</span>] = mscohere( oc.u, oc.encoder, win, [], [], 1<span class="org-type">/</span>Ts);
[tf_sc_est, <span class="org-type">~</span>] = tfestimate(sc.u, sc.encoder, win, [], [], 1<span class="org-type">/</span>Ts);
[co_sc_est, <span class="org-type">~</span>] = mscohere( sc.u, sc.encoder, win, [], [], 1<span class="org-type">/</span>Ts);
</pre>
</div>
<div id="org3137b17" class="figure">
<p><img src="figs/stiffness_force_sensor_coherence.png" alt="stiffness_force_sensor_coherence.png" />
</p>
</div>
<div id="org0b7ba5b" class="figure">
<p><img src="figs/stiffness_force_sensor_bode.png" alt="stiffness_force_sensor_bode.png" />
</p>
</div>
<div id="org8bfdbdd" class="figure">
<p><img src="figs/stiffness_force_sensor_bode_zoom.png" alt="stiffness_force_sensor_bode_zoom.png" />
</p>
<p><span class="figure-number">Figure 16: </span>Zoom on the change of resonance</p>
</div>
<div class="important" id="org98481c9">
<p>
The change of resonance frequency / stiffness is very small and is not important here.
</p>
</div>
</div>
</div>
</div>
<div id="outline-container-org939e6d1" class="outline-2">
<h2 id="org939e6d1"><span class="section-number-2">6</span> Generated Number of Charge / Voltage</h2>
<div class="outline-text-2" id="text-6">
<p>
Two stacks are used as actuator (in parallel) and one stack is used as sensor.
</p>
<p>
The amplifier gain is 20V/V (Cedrat LA75B).
</p>
</div>
<div id="outline-container-org24ebf58" class="outline-3">
<h3 id="org24ebf58"><span class="section-number-3">6.1</span> Steps</h3>
<div class="outline-text-3" id="text-6-1">
<div class="org-src-container">
<pre class="src src-matlab">load(<span class="org-string">'./mat/force_sensor_steps.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'encoder'</span>, <span class="org-string">'u'</span>, <span class="org-string">'v'</span>);
</pre>
</div>
<div class="org-src-container">
<pre class="src src-matlab"><span class="org-type">figure</span>;
tiledlayout(2, 1, <span class="org-string">'TileSpacing'</span>, <span class="org-string">'None'</span>, <span class="org-string">'Padding'</span>, <span class="org-string">'None'</span>);
nexttile;
plot(t, v);
xlabel(<span class="org-string">'Time [s]'</span>); ylabel(<span class="org-string">'Measured voltage [V]'</span>);
nexttile;
plot(t, u);
xlabel(<span class="org-string">'Time [s]'</span>); ylabel(<span class="org-string">'Actuator Voltage [V]'</span>);
</pre>
</div>
<div id="org487995c" class="figure">
<p><img src="figs/force_sen_steps_time_domain.png" alt="force_sen_steps_time_domain.png" />
</p>
<p><span class="figure-number">Figure 17: </span>Time domain signal during the 3 actuator voltage steps</p>
</div>
<p>
Three steps are performed at the following time intervals:
</p>
<ul class="org-ul">
<li>2.5, 23</li>
<li>23.8, 35</li>
<li>35.8, 50</li>
</ul>
<p>
Fit function:
</p>
<div class="org-src-container">
<pre class="src src-matlab">f = @(b,x) b(1)<span class="org-type">.*</span>exp(b(2)<span class="org-type">.*</span>x) <span class="org-type">+</span> b(3);
</pre>
</div>
<p>
We are interested by the <code>b(2)</code> term, which is the time constant of the exponential.
</p>
<div class="org-src-container">
<pre class="src src-matlab">tau = zeros(3,1);
V0 = zeros(3,1);
</pre>
</div>
<div class="org-src-container">
<pre class="src src-matlab">t_cur = t(2.5 <span class="org-type">&lt;</span> t <span class="org-type">&amp;</span> t <span class="org-type">&lt;</span> 23);
t_cur = t_cur <span class="org-type">-</span> t_cur(1);
y_cur = v(2.5 <span class="org-type">&lt;</span> t <span class="org-type">&amp;</span> t <span class="org-type">&lt;</span> 23);
nrmrsd = @(b) norm(y_cur <span class="org-type">-</span> f(b,t_cur)); <span class="org-comment">% Residual Norm Cost Function</span>
B0 = [0.5, <span class="org-type">-</span>0.15, 2.2]; <span class="org-comment">% Choose Appropriate Initial Estimates</span>
[B,rnrm] = fminsearch(nrmrsd, B0); <span class="org-comment">% Estimate Parameters &#8216;B&#8217;</span>
tau<span class="org-type">(1) </span>= 1<span class="org-type">/</span>B(2);
V0<span class="org-type">(1) </span>= B(3);
</pre>
</div>
<div class="org-src-container">
<pre class="src src-matlab">t_cur = t(23.8 <span class="org-type">&lt;</span> t <span class="org-type">&amp;</span> t <span class="org-type">&lt;</span> 35);
t_cur = t_cur <span class="org-type">-</span> t_cur(1);
y_cur = v(23.8 <span class="org-type">&lt;</span> t <span class="org-type">&amp;</span> t <span class="org-type">&lt;</span> 35);
nrmrsd = @(b) norm(y_cur <span class="org-type">-</span> f(b,t_cur)); <span class="org-comment">% Residual Norm Cost Function</span>
B0 = [0.5, <span class="org-type">-</span>0.15, 2.2]; <span class="org-comment">% Choose Appropriate Initial Estimates</span>
[B,rnrm] = fminsearch(nrmrsd, B0); <span class="org-comment">% Estimate Parameters &#8216;B&#8217;</span>
tau<span class="org-type">(2) </span>= 1<span class="org-type">/</span>B(2);
V0<span class="org-type">(2) </span>= B(3);
</pre>
</div>
<div class="org-src-container">
<pre class="src src-matlab">t_cur = t(35.8 <span class="org-type">&lt;</span> t);
t_cur = t_cur <span class="org-type">-</span> t_cur(1);
y_cur = v(35.8 <span class="org-type">&lt;</span> t);
nrmrsd = @(b) norm(y_cur <span class="org-type">-</span> f(b,t_cur)); <span class="org-comment">% Residual Norm Cost Function</span>
B0 = [0.5, <span class="org-type">-</span>0.15, 2.2]; <span class="org-comment">% Choose Appropriate Initial Estimates</span>
[B,rnrm] = fminsearch(nrmrsd, B0); <span class="org-comment">% Estimate Parameters &#8216;B&#8217;</span>
tau<span class="org-type">(3) </span>= 1<span class="org-type">/</span>B(2);
V0<span class="org-type">(3) </span>= B(3);
</pre>
</div>
<table border="2" cellspacing="0" cellpadding="6" rules="groups" frame="hsides">
<colgroup>
<col class="org-right" />
<col class="org-right" />
</colgroup>
<thead>
<tr>
<th scope="col" class="org-right">\(tau\) [s]</th>
<th scope="col" class="org-right">\(V_0\) [V]</th>
</tr>
</thead>
<tbody>
<tr>
<td class="org-right">6.47</td>
<td class="org-right">2.26</td>
</tr>
<tr>
<td class="org-right">6.76</td>
<td class="org-right">2.26</td>
</tr>
<tr>
<td class="org-right">6.49</td>
<td class="org-right">2.25</td>
</tr>
</tbody>
</table>
<p>
With the capacitance being \(C = 4.4 \mu F\), the internal impedance of the Speedgoat ADC can be computed as follows:
</p>
<div class="org-src-container">
<pre class="src src-matlab">Cp = 4.4e<span class="org-type">-</span>6; <span class="org-comment">% [F]</span>
Rin = abs(mean(tau))<span class="org-type">/</span>Cp;
</pre>
</div>
<pre class="example">
1494100.0
</pre>
<p>
The input impedance of the Speedgoat&rsquo;s ADC should then be close to \(1.5\,M\Omega\) (specified at \(1\,M\Omega\)).
</p>
<div class="important" id="org3005c4e">
<p>
How can we explain the voltage offset?
</p>
</div>
<p>
As shown in Figure <a href="#org63387ea">18</a> (taken from (<a href="#citeproc_bib_item_1">Reza and Andrew 2006</a>)), an input voltage offset is due to the input bias current \(i_n\).
</p>
<div id="org63387ea" class="figure">
<p><img src="figs/piezo_sensor_model_instrumentation.png" alt="piezo_sensor_model_instrumentation.png" />
</p>
<p><span class="figure-number">Figure 18: </span>Model of a piezoelectric transducer (left) and instrumentation amplifier (right)</p>
</div>
<p>
The estimated input bias current is then:
</p>
<div class="org-src-container">
<pre class="src src-matlab">in = mean(V0)<span class="org-type">/</span>Rin;
</pre>
</div>
<pre class="example">
1.5119e-06
</pre>
<p>
An additional resistor in parallel with \(R_{in}\) would have two effects:
</p>
<ul class="org-ul">
<li>reduce the input voltage offset
\[ V_{off} = \frac{R_a R_{in}}{R_a + R_{in}} i_n \]</li>
<li>increase the high pass corner frequency \(f_c\)
\[ C_p \frac{R_{in}R_a}{R_{in} + R_a} = \tau_c = \frac{1}{f_c} \]
\[ R_a = \frac{R_i}{f_c C_p R_i - 1} \]</li>
</ul>
<p>
If we allow the high pass corner frequency to be equals to 3Hz:
</p>
<div class="org-src-container">
<pre class="src src-matlab">fc = 3;
Ra = Rin<span class="org-type">/</span>(fc<span class="org-type">*</span>C<span class="org-type">*</span>Rin <span class="org-type">-</span> 1);
</pre>
</div>
<pre class="example">
79804
</pre>
<p>
With this parallel resistance value, the voltage offset would be:
</p>
<div class="org-src-container">
<pre class="src src-matlab">V_offset = Ra<span class="org-type">*</span>Rin<span class="org-type">/</span>(Ra <span class="org-type">+</span> Rin) <span class="org-type">*</span> in;
</pre>
</div>
<pre class="example">
0.11454
</pre>
<p>
Which is much more acceptable.
</p>
</div>
</div>
<div id="outline-container-orgd891bf7" class="outline-3">
<h3 id="orgd891bf7"><span class="section-number-3">6.2</span> Sinus</h3>
<div class="outline-text-3" id="text-6-2">
<div class="org-src-container">
<pre class="src src-matlab">load(<span class="org-string">'./mat/force_sensor_sin.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'encoder'</span>, <span class="org-string">'u'</span>, <span class="org-string">'v'</span>);
u = u(t<span class="org-type">&gt;</span>25);
v = v(t<span class="org-type">&gt;</span>25);
encoder = encoder(t<span class="org-type">&gt;</span>25) <span class="org-type">-</span> mean(encoder(t<span class="org-type">&gt;</span>25));
t = t(t<span class="org-type">&gt;</span>25);
</pre>
</div>
<p>
The driving voltage is a sinus at 0.5Hz centered on 3V and with an amplitude of 3V (Figure <a href="#orgf11f3a7">19</a>).
</p>
<div id="orgf11f3a7" class="figure">
<p><img src="figs/force_sensor_sin_u.png" alt="force_sensor_sin_u.png" />
</p>
<p><span class="figure-number">Figure 19: </span>Driving Voltage</p>
</div>
<p>
The full stroke as measured by the encoder is:
</p>
<div class="org-src-container">
<pre class="src src-matlab">max(encoder)<span class="org-type">-</span>min(encoder)
</pre>
</div>
<pre class="example">
5.005e-05
</pre>
<p>
Its signal is shown in Figure <a href="#org3cc6daf">20</a>.
</p>
<div id="org3cc6daf" class="figure">
<p><img src="figs/force_sensor_sin_encoder.png" alt="force_sensor_sin_encoder.png" />
</p>
<p><span class="figure-number">Figure 20: </span>Encoder measurement</p>
</div>
<p>
The generated voltage by the stack is shown in Figure
</p>
<div id="orgd2cbe17" class="figure">
<p><img src="figs/force_sensor_sin_stack.png" alt="force_sensor_sin_stack.png" />
</p>
<p><span class="figure-number">Figure 21: </span>Voltage measured on the stack used as a sensor</p>
</div>
<p>
The capacitance of the stack is
</p>
<div class="org-src-container">
<pre class="src src-matlab">Cp = 4.4e<span class="org-type">-</span>6; <span class="org-comment">% [F]</span>
</pre>
</div>
<p>
The corresponding generated charge is then shown in Figure <a href="#org5b6dc79">22</a>.
</p>
<div id="org5b6dc79" class="figure">
<p><img src="figs/force_sensor_sin_charge.png" alt="force_sensor_sin_charge.png" />
</p>
<p><span class="figure-number">Figure 22: </span>Generated Charge</p>
</div>
<p>
The relation between the generated voltage and the measured displacement is almost linear as shown in Figure <a href="#org9b9ea94">23</a>.
</p>
<div class="org-src-container">
<pre class="src src-matlab">b1 = encoder<span class="org-type">\</span>(v<span class="org-type">-</span>mean(v));
</pre>
</div>
<div id="org9b9ea94" class="figure">
<p><img src="figs/force_sensor_linear_relation.png" alt="force_sensor_linear_relation.png" />
</p>
<p><span class="figure-number">Figure 23: </span>Almost linear relation between the relative displacement and the generated voltage</p>
</div>
<p>
With a 16bits ADC, the resolution will then be equals to (in [nm]):
</p>
<div class="org-src-container">
<pre class="src src-matlab">abs((20<span class="org-type">/</span>2<span class="org-type">^</span>16)<span class="org-type">/</span>(b1<span class="org-type">/</span>1e9))
</pre>
</div>
<pre class="example">
3.9838
</pre>
<style>.csl-entry{text-indent: -1.5em; margin-left: 1.5em;}</style><h2 class='citeproc-org-bib-h2'>Bibliography</h2>
<div class="csl-bib-body">
<div class="csl-entry"><a name="citeproc_bib_item_1"></a>Reza, Moheimani, and Fleming Andrew. 2006. <i>Piezoelectric Transducers for Vibration Control and Damping</i>. London: Springer.</div>
</div>
</div>
</div>
</div>
</div> </div>
<div id="postamble" class="status"> <div id="postamble" class="status">
<p class="author">Author: Dehaeze Thomas</p> <p class="author">Author: Dehaeze Thomas</p>
<p class="date">Created: 2020-10-25 dim. 09:06</p> <p class="date">Created: 2020-10-29 jeu. 09:59</p>
</div> </div>
</body> </body>
</html> </html>

405
index.org
View File

@ -404,3 +404,408 @@ The period of the non-linearity seems to be $1.53 \mu m$ which corresponds to th
#+caption: #+caption:
#+RESULTS: #+RESULTS:
[[file:figs/identification_dynamics_bode.png]] [[file:figs/identification_dynamics_bode.png]]
* Change of Stiffness due to Sensors stack being open/closed circuit
** Matlab Init :noexport:ignore:
#+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name)
<<matlab-dir>>
#+end_src
#+begin_src matlab :exports none :results silent :noweb yes
<<matlab-init>>
#+end_src
** Load Data
#+begin_src matlab
oc = load('./mat/identification_open_circuit.mat', 't', 'encoder', 'u');
sc = load('./mat/identification_short_circuit.mat', 't', 'encoder', 'u');
#+end_src
** Transfer Functions
#+begin_src matlab
Ts = 1e-4; % Sampling Time [s]
win = hann(ceil(10/Ts));
#+end_src
#+begin_src matlab
[tf_oc_est, f] = tfestimate(oc.u, oc.encoder, win, [], [], 1/Ts);
[co_oc_est, ~] = mscohere( oc.u, oc.encoder, win, [], [], 1/Ts);
[tf_sc_est, ~] = tfestimate(sc.u, sc.encoder, win, [], [], 1/Ts);
[co_sc_est, ~] = mscohere( sc.u, sc.encoder, win, [], [], 1/Ts);
#+end_src
#+begin_src matlab :exports none
figure;
hold on;
plot(f, co_oc_est, '-')
plot(f, co_sc_est, '-')
set(gca, 'Xscale', 'log'); set(gca, 'Yscale', 'lin');
ylabel('Coherence'); xlabel('Frequency [Hz]');
hold off;
xlim([0.5, 5e3]);
#+end_src
#+begin_src matlab :tangle no :exports results :results file replace
exportFig('figs/stiffness_force_sensor_coherence.pdf', 'width', 'wide', 'height', 'normal');
#+end_src
#+name: fig:stiffness_force_sensor_coherence
#+caption:
#+RESULTS:
[[file:figs/stiffness_force_sensor_coherence.png]]
#+begin_src matlab :exports none
figure;
tiledlayout(2, 1, 'TileSpacing', 'None', 'Padding', 'None');
ax1 = nexttile;
hold on;
plot(f, abs(tf_oc_est), '-', 'DisplayName', 'Open-Circuit')
plot(f, abs(tf_sc_est), '-', 'DisplayName', 'Short-Circuit')
set(gca, 'Xscale', 'log'); set(gca, 'Yscale', 'log');
ylabel('Amplitude'); set(gca, 'XTickLabel',[]);
hold off;
ylim([1e-7, 3e-4]);
legend('location', 'southwest');
ax2 = nexttile;
hold on;
plot(f, 180/pi*angle(tf_oc_est), '-')
plot(f, 180/pi*angle(tf_sc_est), '-')
set(gca, 'Xscale', 'log'); set(gca, 'Yscale', 'lin');
ylabel('Phase'); xlabel('Frequency [Hz]');
hold off;
yticks(-360:90:360);
axis padded 'auto x'
linkaxes([ax1,ax2], 'x');
xlim([0.5, 5e3]);
#+end_src
#+begin_src matlab :tangle no :exports results :results file replace
exportFig('figs/stiffness_force_sensor_bode.pdf', 'width', 'wide', 'height', 'tall');
#+end_src
#+name: fig:stiffness_force_sensor_bode
#+caption:
#+RESULTS:
[[file:figs/stiffness_force_sensor_bode.png]]
#+begin_src matlab :tangle no :exports results :results file replace
xlim([180, 280]);
exportFig('figs/stiffness_force_sensor_bode_zoom.pdf', 'width', 'small', 'height', 'tall');
#+end_src
#+name: fig:stiffness_force_sensor_bode_zoom
#+caption: Zoom on the change of resonance
#+RESULTS:
[[file:figs/stiffness_force_sensor_bode_zoom.png]]
#+begin_important
The change of resonance frequency / stiffness is very small and is not important here.
#+end_important
* Generated Number of Charge / Voltage
** Introduction :ignore:
Two stacks are used as actuator (in parallel) and one stack is used as sensor.
The amplifier gain is 20V/V (Cedrat LA75B).
** Matlab Init :noexport:ignore:
#+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name)
<<matlab-dir>>
#+end_src
#+begin_src matlab :exports none :results silent :noweb yes
<<matlab-init>>
#+end_src
** Steps
#+begin_src matlab
load('./mat/force_sensor_steps.mat', 't', 'encoder', 'u', 'v');
#+end_src
#+begin_src matlab
figure;
tiledlayout(2, 1, 'TileSpacing', 'None', 'Padding', 'None');
nexttile;
plot(t, v);
xlabel('Time [s]'); ylabel('Measured voltage [V]');
nexttile;
plot(t, u);
xlabel('Time [s]'); ylabel('Actuator Voltage [V]');
#+end_src
#+begin_src matlab :tangle no :exports results :results file replace
exportFig('figs/force_sen_steps_time_domain.pdf', 'width', 'wide', 'height', 'tall');
#+end_src
#+name: fig:force_sen_steps_time_domain
#+caption: Time domain signal during the 3 actuator voltage steps
#+RESULTS:
[[file:figs/force_sen_steps_time_domain.png]]
Three steps are performed at the following time intervals:
- 2.5, 23
- 23.8, 35
- 35.8, 50
Fit function:
#+begin_src matlab
f = @(b,x) b(1).*exp(b(2).*x) + b(3);
#+end_src
We are interested by the =b(2)= term, which is the time constant of the exponential.
#+begin_src matlab
tau = zeros(3,1);
V0 = zeros(3,1);
#+end_src
#+begin_src matlab
t_cur = t(2.5 < t & t < 23);
t_cur = t_cur - t_cur(1);
y_cur = v(2.5 < t & t < 23);
nrmrsd = @(b) norm(y_cur - f(b,t_cur)); % Residual Norm Cost Function
B0 = [0.5, -0.15, 2.2]; % Choose Appropriate Initial Estimates
[B,rnrm] = fminsearch(nrmrsd, B0); % Estimate Parameters B
tau(1) = 1/B(2);
V0(1) = B(3);
#+end_src
#+begin_src matlab
t_cur = t(23.8 < t & t < 35);
t_cur = t_cur - t_cur(1);
y_cur = v(23.8 < t & t < 35);
nrmrsd = @(b) norm(y_cur - f(b,t_cur)); % Residual Norm Cost Function
B0 = [0.5, -0.15, 2.2]; % Choose Appropriate Initial Estimates
[B,rnrm] = fminsearch(nrmrsd, B0); % Estimate Parameters B
tau(2) = 1/B(2);
V0(2) = B(3);
#+end_src
#+begin_src matlab
t_cur = t(35.8 < t);
t_cur = t_cur - t_cur(1);
y_cur = v(35.8 < t);
nrmrsd = @(b) norm(y_cur - f(b,t_cur)); % Residual Norm Cost Function
B0 = [0.5, -0.15, 2.2]; % Choose Appropriate Initial Estimates
[B,rnrm] = fminsearch(nrmrsd, B0); % Estimate Parameters B
tau(3) = 1/B(2);
V0(3) = B(3);
#+end_src
#+begin_src matlab :exports results :results value table replace :tangle no :post addhdr(*this*)
data2orgtable([abs(tau), V0], {}, {'$tau$ [s]', '$V_0$ [V]'}, ' %.2f ');
#+end_src
#+RESULTS:
| $tau$ [s] | $V_0$ [V] |
|-----------+-----------|
| 6.47 | 2.26 |
| 6.76 | 2.26 |
| 6.49 | 2.25 |
With the capacitance being $C = 4.4 \mu F$, the internal impedance of the Speedgoat ADC can be computed as follows:
#+begin_src matlab
Cp = 4.4e-6; % [F]
Rin = abs(mean(tau))/Cp;
#+end_src
#+begin_src matlab :results value replace :exports results
ans = Rin
#+end_src
#+RESULTS:
: 1494100.0
The input impedance of the Speedgoat's ADC should then be close to $1.5\,M\Omega$ (specified at $1\,M\Omega$).
#+begin_important
How can we explain the voltage offset?
#+end_important
As shown in Figure [[fig:piezo_sensor_model_instrumentation]] (taken from cite:reza06_piezoel_trans_vibrat_contr_dampin), an input voltage offset is due to the input bias current $i_n$.
#+name: fig:piezo_sensor_model_instrumentation
#+caption: Model of a piezoelectric transducer (left) and instrumentation amplifier (right)
[[file:figs/piezo_sensor_model_instrumentation.png]]
The estimated input bias current is then:
#+begin_src matlab
in = mean(V0)/Rin;
#+end_src
#+begin_src matlab :results value replace :exports results
ans = in
#+end_src
#+RESULTS:
: 1.5119e-06
An additional resistor in parallel with $R_{in}$ would have two effects:
- reduce the input voltage offset
\[ V_{off} = \frac{R_a R_{in}}{R_a + R_{in}} i_n \]
- increase the high pass corner frequency $f_c$
\[ C_p \frac{R_{in}R_a}{R_{in} + R_a} = \tau_c = \frac{1}{f_c} \]
\[ R_a = \frac{R_i}{f_c C_p R_i - 1} \]
If we allow the high pass corner frequency to be equals to 3Hz:
#+begin_src matlab
fc = 3;
Ra = Rin/(fc*C*Rin - 1);
#+end_src
#+begin_src matlab :results value replace :exports results
ans = Ra
#+end_src
#+RESULTS:
: 79804
With this parallel resistance value, the voltage offset would be:
#+begin_src matlab
V_offset = Ra*Rin/(Ra + Rin) * in;
#+end_src
#+begin_src matlab :results value replace :exports results
ans = V_offset
#+end_src
#+RESULTS:
: 0.11454
Which is much more acceptable.
** Sinus
#+begin_src matlab
load('./mat/force_sensor_sin.mat', 't', 'encoder', 'u', 'v');
u = u(t>25);
v = v(t>25);
encoder = encoder(t>25) - mean(encoder(t>25));
t = t(t>25);
#+end_src
The driving voltage is a sinus at 0.5Hz centered on 3V and with an amplitude of 3V (Figure [[fig:force_sensor_sin_u]]).
#+begin_src matlab :exports none
figure;
plot(t, u)
xlabel('Time [s]'); ylabel('Control Voltage [V]');
#+end_src
#+begin_src matlab :tangle no :exports results :results file replace
exportFig('figs/force_sensor_sin_u.pdf', 'width', 'normal', 'height', 'small');
#+end_src
#+name: fig:force_sensor_sin_u
#+caption: Driving Voltage
#+RESULTS:
[[file:figs/force_sensor_sin_u.png]]
The full stroke as measured by the encoder is:
#+begin_src matlab :results value replace
max(encoder)-min(encoder)
#+end_src
#+RESULTS:
: 5.005e-05
Its signal is shown in Figure [[fig:force_sensor_sin_encoder]].
#+begin_src matlab :exports none
figure;
plot(t, encoder)
xlabel('Time [s]'); ylabel('Encoder [m]');
#+end_src
#+begin_src matlab :tangle no :exports results :results file replace
exportFig('figs/force_sensor_sin_encoder.pdf', 'width', 'normal', 'height', 'small');
#+end_src
#+name: fig:force_sensor_sin_encoder
#+caption: Encoder measurement
#+RESULTS:
[[file:figs/force_sensor_sin_encoder.png]]
The generated voltage by the stack is shown in Figure
#+begin_src matlab :exports none
figure;
plot(t, v)
xlabel('Time [s]'); ylabel('Force Sensor Output [V]');
#+end_src
#+begin_src matlab :tangle no :exports results :results file replace
exportFig('figs/force_sensor_sin_stack.pdf', 'width', 'normal', 'height', 'small');
#+end_src
#+name: fig:force_sensor_sin_stack
#+caption: Voltage measured on the stack used as a sensor
#+RESULTS:
[[file:figs/force_sensor_sin_stack.png]]
The capacitance of the stack is
#+begin_src matlab
Cp = 4.4e-6; % [F]
#+end_src
The corresponding generated charge is then shown in Figure [[fig:force_sensor_sin_charge]].
#+begin_src matlab :exports none
figure;
plot(t, 1e6*Cp*(v-mean(v)))
xlabel('Time [s]'); ylabel('Generated Charge [$\mu C$]');
#+end_src
#+begin_src matlab :tangle no :exports results :results file replace
exportFig('figs/force_sensor_sin_charge.pdf', 'width', 'normal', 'height', 'small');
#+end_src
#+name: fig:force_sensor_sin_charge
#+caption: Generated Charge
#+RESULTS:
[[file:figs/force_sensor_sin_charge.png]]
The relation between the generated voltage and the measured displacement is almost linear as shown in Figure [[fig:force_sensor_linear_relation]].
#+begin_src matlab
b1 = encoder\(v-mean(v));
#+end_src
#+begin_src matlab :exports none
figure;
hold on;
plot(encoder, v-mean(v), 'DisplayName', 'Measured Voltage');
plot(encoder, encoder*b1, 'DisplayName', sprintf('Linear Fit: $U_s \\approx %.3f [V/\\mu m] \\cdot d$', 1e-6*abs(b1)));
hold off;
xlabel('Measured Displacement [m]'); ylabel('Generated Voltage [V]');
legend();
#+end_src
#+begin_src matlab :tangle no :exports results :results file replace
exportFig('figs/force_sensor_linear_relation.pdf', 'width', 'normal', 'height', 'small');
#+end_src
#+name: fig:force_sensor_linear_relation
#+caption: Almost linear relation between the relative displacement and the generated voltage
#+RESULTS:
[[file:figs/force_sensor_linear_relation.png]]
With a 16bits ADC, the resolution will then be equals to (in [nm]):
#+begin_src matlab :results value replace
abs((20/2^16)/(b1/1e9))
#+end_src
#+RESULTS:
: 3.9838