Analyze first measurements

This commit is contained in:
2021-06-01 23:16:49 +02:00
parent 4f7f9c4721
commit 9961970547
7 changed files with 614 additions and 59 deletions

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@@ -1,52 +1,36 @@
% Analysis
% :PROPERTIES:
% :header-args: :tangle matlab/frf_analyze.m
% :END:
%% Clear Workspace and Close figures
clear; close all; clc;
%% Intialize Laplace variable
s = zpk('s');
addpath('./src/');
% Test with one APA
%% Load measurement data for APA number 1
load(sprintf('mat/frf_data_%i.mat', 1), 't', 'Va', 'Vs', 'de', 'da');
%% Load all the measurements
% meas_data = {};
% for i = 1:7
% meas_data(i) = {load(sprintf('mat/frf_data_%i.mat', i), 't', 'Va', 'Vs', 'da', 'de')};
% end
%%
load(sprintf('mat/frf_data_%i_sweep.mat', 1), 't', 'Va', 'Vs', 'da', 'de')
% Time domain data:
%%
figure;
plot(t, de);
%%
figure;
plot(t, Va);
%%
% Compute transfer functions:
Ts = (t(end) - t(1))/(length(t)-1);
Fs = 1/Ts;
win = hanning(ceil(5*Fs)); % Hannning Windows
win = hanning(ceil(0.5*Fs)); % Hannning Windows
%%
[G_dvf, f] = tfestimate(Va, de, win, [], [], 1/Ts);
[G_d, ~] = tfestimate(Va, da, win, [], [], 1/Ts);
[G_iff, ~] = tfestimate(Va, Vs, win, [], [], 1/Ts);
[coh_dvf, ~] = mscohere(Va, de, win, [], [], 1/Ts);
[coh_d, ~] = mscohere(Va, da, win, [], [], 1/Ts);
[coh_iff, ~] = mscohere(Va, Vs, win, [], [], 1/Ts);
%%
figure;
hold on;
plot(f, coh_dvf);
plot(f, coh_d);
plot(f, coh_iff);
hold off;
set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin');
xlim([1, 5e3]); ylim([0, 1]);
%%
figure;
tiledlayout(2, 1, 'TileSpacing', 'None', 'Padding', 'None');
@@ -58,6 +42,7 @@ hold off;
set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log');
ylabel('Amplitude $V_{out}/V_{in}$ [V/V]'); set(gca, 'XTickLabel',[]);
hold off;
ylim([10, 30]);
ax2 = nexttile;
hold on;
@@ -72,7 +57,6 @@ yticks(-360:90:360);
linkaxes([ax1,ax2],'x');
xlim([5, 5e3]);
%%
figure;
tiledlayout(2, 1, 'TileSpacing', 'None', 'Padding', 'None');
@@ -81,6 +65,7 @@ plot(f, abs(G_iff));
set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log');
ylabel('Amplitude $V_{out}/V_{in}$ [V/V]'); set(gca, 'XTickLabel',[]);
hold off;
ylim([10, 30]);
ax2 = nexttile;
plot(f, 180/pi*angle(G_iff));
@@ -90,4 +75,12 @@ hold off;
yticks(-360:90:360);
linkaxes([ax1,ax2],'x');
xlim([5, 5e3]);
xlim([5, 5e3]);
% Comparison of all APA
%% Load all the measurements
meas_data = {};
for i = 1:7
meas_data(i) = {load(sprintf('mat/frf_data_%i.mat', i), 't', 'Va', 'Vs', 'de', 'da')};
end

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@@ -1,4 +1,4 @@
% Save Data
% =frf_save.m= - Save Data
% :PROPERTIES:
% :header-args: :tangle matlab/frf_save.m
% :END:

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@@ -1,25 +1,32 @@
s = tf('s');
addpath('src')
%% Clear Workspace and Close figures
clear; close all; clc;
%%
Fs = 10e3; % Sampling Frequency [Hz]
Ts = 1/Fs; % Sampling Time [s]
%% Intialize Laplace variable
s = zpk('s');
addpath('./src/');
%% Simulation configuration
Fs = 10e3; % Sampling Frequency [Hz]
Ts = 1/Fs; % Sampling Time [s]
%% Data record configuration
Trec_start = 5; % Start time for Recording [s]
Trec_dur = 100; % Recording Duration [s]
Tsim = 2*Trec_start + Trec_dur; % Simulation Time [s]
Tsim = 2*Trec_start + Trec_dur; % Simulation Time [s]
%% Sweep Sine
gc = 0.1;
xi = 0.5;
wn = 2*pi*94.3;
% Notch filter at the resonance of the APA
G_sweep = 0.2*(s^2 + 2*gc*xi*wn*s + wn^2)/(s^2 + 2*xi*wn*s + wn^2);
V_sweep = generateSweepExc('Ts', Ts, ...
'f_start', 10, ...
'f_end', 2e3, ...
'f_end', 1e3, ...
'V_mean', 3.25, ...
't_start', Trec_start, ...
'exc_duration', Trec_dur, ...
@@ -32,7 +39,16 @@ V_noise = generateShapedNoise('Ts', 1/Fs, ...
't_start', Trec_start, ...
'exc_duration', Trec_dur, ...
'smooth_ends', true, ...
'V_exc', 0.00/(1 + s/2/pi/50));
'V_exc', 0.05/(1 + s/2/pi/10));
%% Sinus excitation with increasing amplitude
V_sin = generateSinIncreasingAmpl('Ts', 1/Fs, ...
'V_mean', 3.25, ...
'sin_ampls', [0.1, 0.2, 0.4, 1, 2, 4], ...
'sin_period', 1, ...
'sin_num', 5, ...
't_start', 10, ...
'smooth_ends', true);
%% Select the excitation signal
V_exc = timeseries(V_noise(2,:), V_noise(1,:));
@@ -41,16 +57,16 @@ figure;
tiledlayout(1, 2, 'TileSpacing', 'Normal', 'Padding', 'None');
ax1 = nexttile;
plot(V_exc.Time, squeeze(V_exc.Data));
plot(V_exc(1,:), V_exc(2,:));
xlabel('Time [s]'); ylabel('Amplitude [V]');
ax2 = nexttile;
win = hanning(floor(length(V_exc.Data)/8));
[pxx, f] = pwelch(squeeze(V_exc.Data), win, 0, [], Fs);
win = hanning(floor(length(V_exc)/8));
[pxx, f] = pwelch(V_exc(2,:), win, 0, [], Fs);
plot(f, pxx)
xlabel('Frequency [Hz]'); ylabel('Power Spectral Density [$V^2/Hz$]');
set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log');
xlim([1, Fs/2]); ylim([1e-10, 1e0]);
%% Save
%% Save data that will be loaded in the Simulink file
save('./frf_data.mat', 'Fs', 'Ts', 'Tsim', 'Trec_start', 'Trec_dur', 'V_exc');

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@@ -0,0 +1,54 @@
function [U_exc] = generateSinIncreasingAmpl(args)
% generateSinIncreasingAmpl - Generate Sinus with increasing amplitude
%
% Syntax: [U_exc] = generateSinIncreasingAmpl(args)
%
% Inputs:
% - args - Optinal arguments:
% - Ts - Sampling Time - [s]
% - V_mean - Mean value of the excitation voltage - [V]
% - sin_ampls - Excitation Amplitudes - [V]
% - sin_freq - Excitation Frequency - [Hz]
% - sin_num - Number of period for each amplitude - [-]
% - t_start - Time at which the excitation begins - [s]
% - smooth_ends - 'true' or 'false': smooth transition between 0 and V_mean - [-]
arguments
args.Ts (1,1) double {mustBeNumeric, mustBePositive} = 1e-4
args.V_mean (1,1) double {mustBeNumeric} = 0
args.sin_ampls double {mustBeNumeric, mustBePositive} = [0.1, 0.2, 0.3]
args.sin_period (1,1) double {mustBeNumeric, mustBePositive} = 1
args.sin_num (1,1) double {mustBeNumeric, mustBePositive, mustBeInteger} = 3
args.t_start (1,1) double {mustBeNumeric, mustBePositive} = 5
args.smooth_ends logical {mustBeNumericOrLogical} = true
end
t_noise = 0:args.Ts:args.sin_period*args.sin_num;
sin_exc = [];
for sin_ampl = args.sin_ampls
sin_exc = [sin_exc, args.V_mean + sin_ampl*sin(2*pi/args.sin_period*t_noise)];
end
t_smooth_start = args.Ts:args.Ts:args.t_start;
V_smooth_start = zeros(size(t_smooth_start));
V_smooth_end = zeros(size(t_smooth_start));
if args.smooth_ends
Vd_max = args.V_mean/(0.7*args.t_start);
V_d = zeros(size(t_smooth_start));
V_d(t_smooth_start < 0.2*args.t_start) = t_smooth_start(t_smooth_start < 0.2*args.t_start)*Vd_max/(0.2*args.t_start);
V_d(t_smooth_start > 0.2*args.t_start & t_smooth_start < 0.7*args.t_start) = Vd_max;
V_d(t_smooth_start > 0.7*args.t_start & t_smooth_start < 0.9*args.t_start) = Vd_max - (t_smooth_start(t_smooth_start > 0.7*args.t_start & t_smooth_start < 0.9*args.t_start) - 0.7*args.t_start)*Vd_max/(0.2*args.t_start);
V_smooth_start = cumtrapz(V_d)*args.Ts;
V_smooth_end = args.V_mean - V_smooth_start;
end
V_exc = [V_smooth_start, sin_exc, V_smooth_end];
t_exc = args.Ts*[0:1:length(V_exc)-1];
U_exc = [t_exc; V_exc];