nass-micro-station-measurem.../disturbance-measurement/index.org

197 lines
6.1 KiB
Org Mode
Raw Normal View History

2019-05-02 08:45:08 +02:00
#+TITLE:Measurement of the sample vibrations when rotating the Spindle
:DRAWER:
#+STARTUP: overview
#+HTML_HEAD: <link rel="stylesheet" type="text/css" href="../css/htmlize.css"/>
#+HTML_HEAD: <link rel="stylesheet" type="text/css" href="../css/readtheorg.css"/>
#+HTML_HEAD: <link rel="stylesheet" type="text/css" href="../css/zenburn.css"/>
#+HTML_HEAD: <script type="text/javascript" src="../js/jquery.min.js"></script>
#+HTML_HEAD: <script type="text/javascript" src="../js/bootstrap.min.js"></script>
#+HTML_HEAD: <script type="text/javascript" src="../js/jquery.stickytableheaders.min.js"></script>
#+HTML_HEAD: <script type="text/javascript" src="../js/readtheorg.js"></script>
#+PROPERTY: header-args:matlab :session *MATLAB*
#+PROPERTY: header-args:matlab+ :comments org
#+PROPERTY: header-args:matlab+ :results output
#+PROPERTY: header-args:matlab+ :exports both
#+PROPERTY: header-args:matlab+ :eval no-export
#+PROPERTY: header-args:matlab+ :output-dir figs
:END:
2019-05-03 17:33:15 +02:00
* Experimental Setup
2019-05-02 08:45:08 +02:00
* Signal Processing
** Matlab Init :noexport:ignore:
#+begin_src matlab :exports none :results silent :noweb yes
<<matlab-init>>
#+end_src
** Load Data
Measurement =data_001.mat= corresponds to a measurement where the spindle is not turning and =data_002.mat= where the spindle is turning at 1rpm.
=x1= is the signal coming from the geophone located on the marble and =x2= is the signal from the geophone located on the sample station.
#+begin_src matlab :results none
data1 = load('mat/data_001.mat', 't', 'x1', 'x2');
data2 = load('mat/data_002.mat', 't', 'x1', 'x2');
#+end_src
** Time domain Data
#+begin_src matlab :results none
figure;
hold on;
plot(data1.t, data1.x1);
plot(data2.t, data2.x1);
hold off;
#+end_src
#+begin_src matlab :results none
figure;
hold on;
plot(data1.t, data1.x2);
plot(data2.t, data2.x2)
hold off;
#+end_src
** ASD and Frequency domain data
#+begin_src matlab :results none
dt = data1.t(2) - data1.t(1);
Fs = 1/dt;
2019-05-03 17:33:15 +02:00
windows_psd = hanning(ceil(10*Fs));
2019-05-02 08:45:08 +02:00
#+end_src
#+begin_src matlab :results none
2019-05-03 17:33:15 +02:00
[pxx1m, f] = pwelch(data1.x1, windows_psd, [], [], Fs); f(1) = []; pxx1m(1) = [];
[pxx1h, ~] = pwelch(data1.x2, windows_psd, [], [], Fs); pxx1h(1) = [];
2019-05-02 08:45:08 +02:00
2019-05-03 17:33:15 +02:00
[pxx2m, ~] = pwelch(data2.x1, windows_psd, [], [], Fs); pxx2m(1) = [];
[pxx2h, ~] = pwelch(data2.x2, windows_psd, [], [], Fs); pxx2h(1) = [];
2019-05-02 08:45:08 +02:00
#+end_src
2019-05-03 17:33:15 +02:00
** Some plots
2019-05-02 08:45:08 +02:00
#+begin_src matlab :results none
figure;
hold on;
plot(f, sqrt(pxx1m));
plot(f, sqrt(pxx2m));
hold off;
set(gca, 'xscale', 'log');
set(gca, 'yscale', 'log');
xlabel('Frequency [Hz]'); ylabel('PSD [m/s/sqrt(Hz)]')
#+end_src
#+begin_src matlab :results none
figure;
hold on;
plot(f, sqrt(pxx1h));
plot(f, sqrt(pxx2h));
hold off;
set(gca, 'xscale', 'log');
set(gca, 'yscale', 'log');
xlabel('Frequency [Hz]'); ylabel('PSD [m/s/sqrt(Hz)]')
#+end_src
#+begin_src matlab :results none
figure;
hold on;
plot(f, sqrt(pxx2m));
plot(f, sqrt(pxx2h));
hold off;
set(gca, 'xscale', 'log');
set(gca, 'yscale', 'log');
xlabel('Frequency [Hz]'); ylabel('PSD [m/s/sqrt(Hz)]')
#+end_src
#+begin_src matlab :results none
figure;
hold on;
plot(f, cumtrapz(f, pxx1m))
plot(f, cumtrapz(f, pxx2m))
set(gca, 'XScale', 'log');
xlabel('Frequency [Hz]'); ylabel('CAS [m]')
#+end_src
2019-05-03 17:33:15 +02:00
** Scaling to take into account the sensibility of the geophone and the voltage amplifier
The Geophone used are L22. Their sensibility is shown on figure [[fig:geophone_sensibility]].
#+begin_src matlab :results none
S0 = 88; % Sensitivity [V/(m/s)]
f0 = 2; % Cut-off frequnecy [Hz]
S = S0*(s/2/pi/f0)/(1+s/2/pi/f0);
#+end_src
We also take into account the gain of the electronics which is here set to be $60dB$.
#+begin_src matlab :results none
G0_db = 60; % [dB]
G0 = 10^(60/G0_db); % [abs]
#+end_src
We divide the ASD measured (in $\text{V}/\sqrt{\text{Hz}}$) by the gain of the voltage amplifier to obtain the ASD of the voltage across the geophone.
We further divide the result by the sensibility of the Geophone to obtain the ASD of the velocity in $m/s/\sqrt{Hz}$.
#+begin_src matlab :results none
scaling = 1./squeeze(abs(freqresp(G0*S, f, 'Hz'))); scaling(1) = 0;
#+end_src
** Computation of the ASD of the velocity
#+begin_src matlab :results none
figure;
hold on;
plot(f, sqrt(pxx1h).*scaling);
plot(f, sqrt(pxx2h).*scaling);
hold off;
set(gca, 'xscale', 'log');
set(gca, 'yscale', 'log');
xlabel('Frequency [Hz]'); ylabel('ASD of the measured Velocity $\left[\frac{m/s}{\sqrt{Hz}}\right]$')
xlim([0.1, 500]);
#+end_src
#+begin_src matlab :results none
figure;
hold on;
plot(f, (sqrt(pxx1).*scaling)./(2*pi*f));
plot(f, (sqrt(pxx2).*scaling)./(2*pi*f));
hold off;
set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log');
xlabel('Frequency [Hz]'); ylabel('ASD of the displacement $\left[\frac{m}{\sqrt{Hz}}\right]$')
xlim([0.1, 500]);
#+end_src
** RMS value of the difference between the two geophones
We also compute the Power Spectral Density of the difference between the two geophones. This is done in order to estimate the relative displacement of the sample with respect to the granite.
#+begin_src matlab :results none
[pxxd1, ~] = pwelch(data1.x2-data1.x1, windows_psd, [], [], Fs); pxxd1(1) = [];
[pxxd2, ~] = pwelch(data2.x2-data2.x1, windows_psd, [], [], Fs); pxxd2(1) = [];
#+end_src
#+begin_src matlab :results none
figure;
hold on;
plot(f, (sqrt(pxxd1).*scaling)./(2*pi*f));
plot(f, (sqrt(pxxd2).*scaling)./(2*pi*f));
hold off;
set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log');
xlabel('Frequency [Hz]'); ylabel('ASD of the displacement $\left[\frac{m}{\sqrt{Hz}}\right]$')
xlim([0.1, 500]);
#+end_src
#+begin_src matlab :results none
psd_d1 = ((sqrt(pxxd1).*scaling)./(2*pi*f)).^2;
psd_d2 = ((sqrt(pxxd2).*scaling)./(2*pi*f)).^2;
df = f(2) - f(1);
figure;
hold on;
plot(f, sqrt(cumsum(df.*psd_d1, 'reverse')));
plot(f, sqrt(cumsum(df.*psd_d2, 'reverse')));
hold off;
set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log');
xlabel('Frequency [Hz]'); ylabel('CAS $\left[m\right]$')
xlim([0.1, 500]);
#+end_src