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Time_lapse_code.m
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% Time Lapse code
d_per_pix = 1/12;
%% %experiemnt 1
T_sec = TL1_data(:,1).*(60*60) + TL1_data(:,1).*(60) + TL1_data(:,2) ;
T_hour = T_sec./(60*60);
pix_offset = 3;
pix_disp = TL1_data(:,4) - pix_offset;
d = pix_disp.*d_per_pix;
x_error = 0.5/(60*60);
y_error = 0.5*d_per_pix*1000;
x = T_hour;
y = d.*1000;
% y = y./cos(pi/4);
plot(x,y,'x','color',[0.2 0.2 0.98],'linewidth',1.5);
hold on
% errorbar(y,y_error)
%X = [ones(length(x),1) x]; none zero start
%b = X\y;
%yCalc = X*b;
% red = [0.57 0 0]
% blue = [0.2 0.2 0.98]
% b = x\y;
% yCalc = x*b;
% plot(x,yCalc,'--','color',[0.2 0.2 0.98]);
% https://uk.mathworks.com/matlabcentral/fileexchange/45711-linear-fit-with-both-uncertainties-in-x-and-in-y
% Performs a linear fit with uncertainties in x and y, using a Monte Carlo method
[ p, sp ] = linfitxy( x, y, x_error, y_error); %1 +/- STD lines
% % figure
% % A = p(1);
% % B = p(2);
% % x_lin = x;
% % y_lin = A*x + B;
% % plot(x_lin, y_lin);
xlabel('Time (hours)');
ylabel('Vertical Displacement (micrometers)');
% %
% % % err = ones(size(x));
% % % errorbar(x, y, 0.5, 'LineStyle','none');
% %
% % % Exponential fit
% % figure
% % f = fit(x,y,'exp1'); % 95% confidence bound
% % plot(f,x,y)
% %
% %
% % y1 = 13.11*exp(0.1191*x);
% % hold on
% % plot(x,y1,'k:');
% %
% % y2 = 29.56*exp(0.1692*x);
% % hold on
% % plot(x,y2,'k:');
%% Experiment 2
ex1_u1 = FAT_1(:,1) + (FAT_1(:,2).*FAT_1(:,6)) - 290;
ex2_u1 = FAT_2(:,1) + (FAT_2(:,2).*FAT_2(:,6)) - 290;
ex3_u1 = FAT_3(:,1) + (FAT_3(:,2).*FAT_3(:,6)) - 290;
FL1_u1 = FL_1(:,1) + (FL_1(:,2).*FL_1(:,6)) - 290;
FL2_u1 = FL_2(:,1) + (FL_2(:,2).*FL_2(:,6)) - 290;
FL3_u1 = FL_3(:,1) + (FL_3(:,2).*FL_3(:,6)) - 290;
ex1_un = FAT_1(:,3) + (FAT_1(:,4).*FAT_1(:,6))- 290;
ex2_un = FAT_2(:,3) + (FAT_2(:,4).*FAT_2(:,6))- 290;
ex3_un = FAT_3(:,3) + (FAT_3(:,4).*FAT_3(:,6))- 290;
FL1_un = FL_1(:,3) + (FL_1(:,4).*FL_1(:,6))- 290;
FL2_un = FL_2(:,3) + (FL_2(:,4).*FL_2(:,6))- 290;
FL3_un = FL_3(:,3) + (FL_3(:,4).*FL_3(:,6))- 290;
ex1_dec = log( (ex1_u1)./(ex1_un) ) ./ FAT_1(:,5);
ex2_dec = log( (ex2_u1)./(ex2_un) ) ./ FAT_2(:,5);
ex3_dec = log( (ex3_u1)./(ex3_un) ) ./ FAT_3(:,5);
FL1_dec = log( (FL1_u1)./(FL1_un) ) ./ FL_1(:,5);
FL2_dec = log( (FL2_u1)./(FL2_un) ) ./ FL_2(:,5);
FL3_dec = log( (FL3_u1)./(FL3_un) ) ./ FL_3(:,5);
den = ( (4*pi) + (ex1_dec).^2).^0.5;
ex1_zeta = ex1_dec./(den);
den = ( (4*pi) + (ex2_dec).^2).^0.5;
ex2_zeta = ex2_dec./(den);
den = ( (4*pi) + (ex3_dec).^2).^0.5;
ex3_zeta = ex3_dec./(den);
den = ( (4*pi) + (FL1_dec).^2).^0.5;
FL1_zeta = FL1_dec./(den);
den = ( (4*pi) + (FL2_dec).^2).^0.5;
FL2_zeta = FL2_dec./(den);
den = ( (4*pi) + (FL3_dec).^2).^0.5;
FL3_zeta = FL3_dec./(den);
M = 155.99/1000;
k = 4*54.04;
Wn = (k/M)^0.5;
const = 2*(M*Wn)^0.5;
ex1_c = ex1_zeta.*const;
ex2_c = ex2_zeta.*const;
ex3_c = ex3_zeta.*const;
FL1_c = FL1_zeta.*const;
FL2_c = FL2_zeta.*const;
FL3_c = FL3_zeta.*const;
%% errors
ex1_zeta_Aerror = (4.*(FAT_1(:,6)./2).*ex1_un)./(FAT_1(:,5).*ex1_u1);
ex2_zeta_Aerror = (4.*(FAT_2(:,6)./2).*ex2_un)./(FAT_2(:,5).*ex2_u1);
ex3_zeta_Aerror = (4.*(FAT_3(:,6)./2).*ex3_un)./(FAT_3(:,5).*ex3_u1);
FL1_zeta_Aerror = (4.*(FL_1(:,6)./2).*FL1_un)./(FL_1(:,5).*FL1_u1);
FL2_zeta_Aerror = (4.*(FL_2(:,6)./2).*FL2_un)./(FL_2(:,5).*FL2_u1);
FL3_zeta_Aerror = (4.*(FL_3(:,6)./2).*FL3_un)./(FL_3(:,5).*FL3_u1);
k_Aerror = 2.05;
k_Perror = 3.80;
const_Perror = k_Perror/4;
ex1_zeta_Perror = (ex1_zeta_Aerror./ex1_zeta).*100;
ex2_zeta_Perror = (ex2_zeta_Aerror./ex2_zeta).*100;
ex3_zeta_Perror = (ex3_zeta_Aerror./ex3_zeta).*100;
FL1_zeta_Perror = (FL1_zeta_Aerror./FL1_zeta).*100;
FL2_zeta_Perror = (FL2_zeta_Aerror./FL2_zeta).*100;
FL3_zeta_Perror = (FL3_zeta_Aerror./FL3_zeta).*100;
ex1_c_Perror = ex1_zeta_Perror + const_Perror;
ex2_c_Perror = ex2_zeta_Perror + const_Perror;
ex3_c_Perror = ex3_zeta_Perror + const_Perror;
FL1_c_Perror = FL1_zeta_Perror + const_Perror;
FL2_c_Perror = FL2_zeta_Perror + const_Perror;
FL3_c_Perror = FL3_zeta_Perror + const_Perror;
ex1_c_Aerror = (ex1_c_Perror.*ex1_c)./100;
ex2_c_Aerror = (ex2_c_Perror.*ex2_c)./100;
ex3_c_Aerror = (ex3_c_Perror.*ex3_c)./100;
FL1_c_Aerror = (FL1_c_Perror.*FL1_c)./100;
FL2_c_Aerror = (FL2_c_Perror.*FL2_c)./100;
FL3_c_Aerror = (FL3_c_Perror.*FL3_c)./100;
ex1_c_mean = mean(ex1_c);
ex2_c_mean = mean(ex2_c);
ex3_c_mean = mean(ex3_c);
FL1_c_mean = mean(FL1_c);
FL2_c_mean = mean(FL2_c);
FL3_c_mean = mean(FL3_c);
% ex1_c_error_mean = mean(ex1_c_Aerror)/sqrt(length(ex1_c_Aerror));
% ex2_c_error_mean = mean(ex2_c_Aerror)/sqrt(length(ex2_c_Aerror));
% ex3_c_error_mean = mean(ex3_c_Aerror)/sqrt(length(ex3_c_Aerror));
% FL1_c_error_mean = mean(FL1_c_Aerror)/sqrt(length(FL1_c_Aerror));
ex1_c_Aerror_mean = mean(ex1_c_Aerror)/sqrt(length(ex1_c_Aerror));
ex2_c_Aerror_mean = mean(ex2_c_Aerror)/sqrt(length(ex2_c_Aerror));
ex3_c_Aerror_mean = mean(ex3_c_Aerror)/sqrt(length(ex3_c_Aerror));
FL1_c_Aerror_mean = mean(FL1_c_Aerror)/sqrt(length(FL1_c_Aerror));
FL2_c_Aerror_mean = mean(FL2_c_Aerror)/sqrt(length(FL2_c_Aerror));
FL3_c_Aerror_mean = mean(FL3_c_Aerror)/sqrt(length(FL3_c_Aerror));
% printf('experiment 1 mean = %f +- %f ', ex1_c_mean, ex1_c_error_mean);
% printf('experiment 2 mean = %f +- %f ', ex2_c_mean, ex2_c_error_mean);
% printf('experiment 3 mean = %f +- %f ', ex3_c_mean, ex3_c_error_mean);
% printf('experiment FL1 mean = %f +- %f ', FL1_c_mean, FL1_c_error_mean);
exp_all = [ex1_c_mean;ex2_c_mean;ex3_c_mean];
exp_mean = mean(exp_all)
exp_all_error = [ex1_c_Aerror_mean;ex2_c_Aerror_mean;ex3_c_Aerror_mean];
exp_mean_error = mean(exp_all_error)/sqrt(length(exp_all_error))
FL_all = [FL1_c_mean;FL2_c_mean;FL3_c_mean];
FL_mean = mean(FL_all)
FL_all_error = [FL1_c_Aerror_mean;FL2_c_Aerror_mean;FL3_c_Aerror_mean];
FL_mean_error = mean(FL_all_error)/sqrt(length(FL_all_error))
%%
x = [1:10];
x_all = [1:10,1:10,1:10];
y_all_exp = [ex1_c;ex2_c;ex3_c];
error_all = [ex1_c_Aerror;ex2_c_Aerror;ex3_c_Aerror];
% figure
% % scatter(x_all, y_all);
% plot(x_all,y_all_exp,'x','color',[0.2 0.2 0.98],'linewidth',1.5);
% % hold on
% % [ p, sp ] = linfitxy( x_all, y_all, 0, error_all); %1 +/- STD lines
% % % A = p(1);
% % % B = p(2);
% % % x_lin = x;
% % % y_lin = A*x + B;
% % % plot(x_lin, y_lin);
%
% % figure
hold on
y_all_FL = [FL1_c;FL2_c;FL3_c];
% % scatter(x_all, y_all);
% plot(x_all,y_all_FL,'^','color',[0.57 0 0],'linewidth',1.5);
% % hold on
% % [ p, sp ] = linfitxy( x, y_all, 0, FL1_c_Aerror); %1 +/- STD lines
% % % A = p(1);
% % % B = p(2);
% % % x_lin = x;
% % % y_lin = A*x + B;
% % % plot(x_lin, y_lin);
figure
% Just Scatter
plot(x_all,y_all_exp,'x','color',[0.2 0.2 0.98],'linewidth',1.5);
hold on
plot(x_all,y_all_FL,'^','color',[0.57 0 0],'linewidth',1.5);
xlabel('Iteration');
ylabel('Damping Coeficient (Ns/m)');
legend('Air Pocket Bearing','Flooded Bearing');
% figure
% f = fit(x', FL1_c,'exp1'); % 95% confidence bound
% plot(f,x', FL1_c)
% figure
% scatter(x, ex1_c);
% hold on
% f = fit(x', ex1_c,'exp1'); % 95% confidence bound
% plot(f,x', ex1_c)
% [ p, sp ] = linfitxy( [1:10], ex1_c, 0, 0.1); %1 +/- STD lines
% A = p(1);
% B = p(2);
% x_lin = x;
% y_lin = A*x + B;
% plot(x_lin, y_lin);
% polyfit(x,y,1)
% % plot([1:10], ex1_c);
% % hold on
% scatter([1:10], ex2_c);
% hold on
% % plot([1:10], ex2_c);
% % hold on
% scatter([1:10], ex3_c);
% hold on
% % plot([1:10], ex3_c);
% % hold on
% scatter([1:10], FL1_c);
% % hold on
% % plot([1:10], FL1_c);
% legend