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<title>Test Bench APA95ML</title>
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2020-07-20 11:27:55 +02:00
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<a accesskey="H" href="../index.html"> HOME </a>
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</div><div id="content">
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<h1 class="title">Test Bench APA95ML</h1>
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<div id="table-of-contents">
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<h2>Table of Contents</h2>
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<div id="text-table-of-contents">
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<ul>
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<li><a href="#orgdca5c97">1. Setup</a>
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<ul>
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<li><a href="#org0d12d9d">1.1. Parameters</a></li>
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<li><a href="#org15a3975">1.2. Filter White Noise</a></li>
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</ul>
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</li>
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<li><a href="#org4392a0d">2. Run Experiment and Save Data</a>
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<ul>
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<li><a href="#orge9621ee">2.1. Load Data</a></li>
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<li><a href="#org1da78b3">2.2. Save Data</a></li>
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</ul>
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</li>
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<li><a href="#orgf5ba24e">3. Huddle Test</a>
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<ul>
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<li><a href="#org36326ca">3.1. Time Domain Data</a></li>
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<li><a href="#orge6edd66">3.2. PSD of Measurement Noise</a></li>
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</ul>
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</li>
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<li><a href="#org788fd72">4. Transfer Function Estimation with m=5kg</a>
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<ul>
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<li><a href="#org47e2de6">4.1. Time Domain Data</a></li>
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<li><a href="#org6544479">4.2. Comparison of the PSD with Huddle Test</a></li>
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<li><a href="#orgc4644a8">4.3. Compute TF estimate and Coherence</a></li>
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</ul>
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</li>
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</ul>
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</div>
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</div>
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<div id="org8e3aae2" class="figure">
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<p><img src="figs/setup_picture.png" alt="setup_picture.png" />
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</p>
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<p><span class="figure-number">Figure 1: </span>Picture of the Setup</p>
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</div>
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<div id="org9f02ad0" class="figure">
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<p><img src="figs/setup_zoom.png" alt="setup_zoom.png" />
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</p>
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<p><span class="figure-number">Figure 2: </span>Zoom on the APA</p>
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</div>
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<div id="outline-container-orgdca5c97" class="outline-2">
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<h2 id="orgdca5c97"><span class="section-number-2">1</span> Setup</h2>
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<div class="outline-text-2" id="text-1">
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</div>
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<div id="outline-container-org0d12d9d" class="outline-3">
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<h3 id="org0d12d9d"><span class="section-number-3">1.1</span> Parameters</h3>
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<div class="outline-text-3" id="text-1-1">
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<div class="org-src-container">
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<pre class="src src-matlab">Ts = 1e-4;
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</pre>
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</div>
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</div>
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<div id="outline-container-org15a3975" class="outline-3">
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<h3 id="org15a3975"><span class="section-number-3">1.2</span> Filter White Noise</h3>
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<div class="outline-text-3" id="text-1-2">
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<div class="org-src-container">
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<pre class="src src-matlab">Glpf = 1/(1 + s/2/pi/500);
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Gz = c2d(Glpf, Ts, 'tustin');
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</pre>
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</div>
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</div>
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</div>
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</div>
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<div id="outline-container-org4392a0d" class="outline-2">
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<h2 id="org4392a0d"><span class="section-number-2">2</span> Run Experiment and Save Data</h2>
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<div class="outline-text-2" id="text-2">
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</div>
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2020-07-20 13:17:34 +02:00
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<div id="outline-container-orge9621ee" class="outline-3">
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<h3 id="orge9621ee"><span class="section-number-3">2.1</span> Load Data</h3>
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<div class="outline-text-3" id="text-2-1">
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<div class="org-src-container">
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<pre class="src src-matlab">data = SimulinkRealTime.utils.getFileScopeData('data/apa95ml.dat').data;
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</pre>
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</div>
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</div>
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</div>
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<div id="outline-container-org1da78b3" class="outline-3">
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<h3 id="org1da78b3"><span class="section-number-3">2.2</span> Save Data</h3>
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<div class="outline-text-3" id="text-2-2">
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<div class="org-src-container">
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<pre class="src src-matlab">u = data(:, 1); % Input Voltage [V]
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y = data(:, 2); % Output Displacement [m]
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t = data(:, 3); % Time [s]
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</pre>
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</div>
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<div class="org-src-container">
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<pre class="src src-matlab">save('./mat/huddle_test.mat', 't', 'u', 'y', 'Glpf');
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</pre>
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</div>
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</div>
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</div>
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</div>
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<div id="outline-container-orgf5ba24e" class="outline-2">
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<h2 id="orgf5ba24e"><span class="section-number-2">3</span> Huddle Test</h2>
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<div class="outline-text-2" id="text-3">
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</div>
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<div id="outline-container-org36326ca" class="outline-3">
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<h3 id="org36326ca"><span class="section-number-3">3.1</span> Time Domain Data</h3>
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<div class="outline-text-3" id="text-3-1">
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<div id="org513762b" class="figure">
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<p><img src="figs/huddle_test_time_domain.png" alt="huddle_test_time_domain.png" />
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</p>
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<p><span class="figure-number">Figure 3: </span>Measurement of the Mass displacement during Huddle Test</p>
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</div>
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</div>
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</div>
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<div id="outline-container-orge6edd66" class="outline-3">
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<h3 id="orge6edd66"><span class="section-number-3">3.2</span> PSD of Measurement Noise</h3>
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<div class="outline-text-3" id="text-3-2">
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<div class="org-src-container">
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<pre class="src src-matlab">Ts = t(end)/(length(t)-1);
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Fs = 1/Ts;
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win = hanning(ceil(1*Fs));
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</pre>
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</div>
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<div class="org-src-container">
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<pre class="src src-matlab">[pxx, f] = pwelch(y, win, [], [], Fs);
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</pre>
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</div>
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<div id="orgc707f3e" class="figure">
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<p><img src="figs/huddle_test_pdf.png" alt="huddle_test_pdf.png" />
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</p>
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<p><span class="figure-number">Figure 4: </span>Amplitude Spectral Density of the Displacement during Huddle Test</p>
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</div>
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</div>
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</div>
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</div>
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<div id="outline-container-org788fd72" class="outline-2">
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<h2 id="org788fd72"><span class="section-number-2">4</span> Transfer Function Estimation with m=5kg</h2>
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<div class="outline-text-2" id="text-4">
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</div>
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<div id="outline-container-org47e2de6" class="outline-3">
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<h3 id="org47e2de6"><span class="section-number-3">4.1</span> Time Domain Data</h3>
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<div class="outline-text-3" id="text-4-1">
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<div id="orgf20885a" class="figure">
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<p><img src="figs/apa95ml_5kg_10V_time_domain.png" alt="apa95ml_5kg_10V_time_domain.png" />
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</p>
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<p><span class="figure-number">Figure 5: </span>Time domain signals during the test</p>
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</div>
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</div>
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</div>
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<div id="outline-container-org6544479" class="outline-3">
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<h3 id="org6544479"><span class="section-number-3">4.2</span> Comparison of the PSD with Huddle Test</h3>
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<div class="outline-text-3" id="text-4-2">
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<div class="org-src-container">
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<pre class="src src-matlab">Ts = t(end)/(length(t)-1);
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Fs = 1/Ts;
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win = hanning(ceil(1*Fs));
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</pre>
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</div>
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<div class="org-src-container">
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<pre class="src src-matlab">[pxx, f] = pwelch(y, win, [], [], Fs);
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[pht, ~] = pwelch(ht.y, win, [], [], Fs);
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</pre>
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</div>
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<div id="org2052faa" class="figure">
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<p><img src="figs/apa95ml_5kg_10V_pdf_comp_huddle.png" alt="apa95ml_5kg_10V_pdf_comp_huddle.png" />
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</p>
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<p><span class="figure-number">Figure 6: </span>Comparison of the ASD for the identification test and the huddle test</p>
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<div id="outline-container-orgc4644a8" class="outline-3">
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<h3 id="orgc4644a8"><span class="section-number-3">4.3</span> Compute TF estimate and Coherence</h3>
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<div class="outline-text-3" id="text-4-3">
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<div class="org-src-container">
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<pre class="src src-matlab">win = hann(ceil(1/Ts));
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[tf_est, f] = tfestimate(u, -y, win, [], [], 1/Ts);
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[co_est, ~] = mscohere( u, -y, win, [], [], 1/Ts);
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</pre>
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</div>
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<div id="orgb885b51" class="figure">
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<p><img src="figs/apa95ml_5kg_10V_coh.png" alt="apa95ml_5kg_10V_coh.png" />
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</p>
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<p><span class="figure-number">Figure 7: </span>Coherence</p>
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</div>
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<div id="org1871e4a" class="figure">
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<p><img src="figs/apa95ml_5kg_10V_tf.png" alt="apa95ml_5kg_10V_tf.png" />
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</p>
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2020-07-20 13:17:34 +02:00
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<p><span class="figure-number">Figure 8: </span>Estimation of the transfer function from input voltage to displacement</p>
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</div>
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<div class="org-src-container">
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<pre class="src src-matlab">Glpf = 1/(1 + s/2/pi/500);
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</pre>
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2020-07-20 11:27:55 +02:00
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</div>
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</div>
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2020-07-17 11:56:08 +02:00
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</div>
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</div>
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</div>
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<div id="postamble" class="status">
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<p class="author">Author: Dehaeze Thomas</p>
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2020-07-20 13:17:34 +02:00
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<p class="date">Created: 2020-07-20 lun. 13:17</p>
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2020-07-17 11:56:08 +02:00
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