Eliminate Outliers and filtering signal

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I am using this code to apply different filters to my data from strain gages. How can I remove the outliers first, appy the filters and plot both signals? Do I need to use FFT ?
Thank you.
load('RRData.mat');
R=RRData.Strain_C_Fz;
L=RRData.Strain_HB_Fy;
t=RRData.Time;
samples = length(t);
Fs = (samples-1)/(t(samples)-t(1));
[R_max,idx]= max(R);
[L_max,idx]= max(L);
t_m = t(idx);
figure(1)
%subplot(3,2,1) ;
plot(t,R);hold on;plot(t,L);legend('Right','Left');
plot(t_m, R_max,'^r');hold on; plot (t_m, L_max,'ro')
text(t_m,R(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', R_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')
text(t_m,L(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', L_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')
title(['Data samples at Fs = ' num2str(round(Fs)) 'Hz' ]);
grid
% NB : decim = 1 will do nothing (output = input)
decim = 50;
if decim > 1
R = decimate (R,decim);
L = decimate (L,decim);
Fs = Fs/decim;
end
samples = length(R);
t = (0:samples - 1)*1/Fs;
[R_max,idx]= max(R);
[L_max,idx]= max(L);
t_m = t(idx);
figure(2)
%subplot(3,2,2) ;
plot(t,R); hold on; plot (t,L); legend('Right','Left');
plot(t_m, R_max,'^r');hold on; plot (t_m, L_max,'ro')
text(t_m,R(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', R_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')
text(t_m,L(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', L_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')
title(['Data samples at Fs = ' num2str(round(Fs)) 'Hz']);
grid on
figure(3)
N = 25;
Rs = slidingavg(R,N);
Ls = slidingavg(L,N);
[R_max,idx]= max(Rs);
[L_max,idx]= max(Ls);
t_m = t(idx);
%subplot(3,2,3) ;
plot(t,Rs); hold on; plot (t,Ls); legend('Right','Left');
plot(t_m, R_max,'^r');hold on; plot (t_m, L_max,'ro')
text(t_m,R(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', R_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')
text(t_m,L(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', L_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')
title(['Data samples at Fs = ' num2str(round(Fs)) 'Hz / Smoothed with slidingavg' ]);
grid on
figure(4)
N = 50;
Rs = medfilt1(R, N, 'truncate');
Ls = medfilt1(L, N, 'truncate');
[R_max,idx]= max(Rs);
[L_max,idx]= max(Ls);
t_m = t(idx);
%subplot(3,2,4) ;
plot(t,Rs); hold on; plot (t,Ls); legend('Right','Left');
plot(t_m, R_max,'^r');hold on; plot (t_m, L_max,'ro')
text(t_m,R(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', R_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')
text(t_m,L(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', L_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')
title(['Data samples at Fs = ' num2str(round(Fs)) 'Hz / Smoothed with medfilt1' ]);
grid on
figure(5)
N = 50;
Rs = sgolayfilt(R,3,51);
Ls = sgolayfilt(L,3,51);
[Rs_max,index]= max(Rs);
[Ls_max,index]= max(Ls);
t_max = t(index);
%subplot(3,2,5) ;
plot(t,Rs); hold on; plot (t,Ls); legend('Right','Left');
plot(t_max, Rs_max,'^r');hold on; plot (t_max, Ls_max,'ro')
text(t_max,Rs(index),sprintf('\\leftarrow Max = %.6f\n t = %.2f ', Rs_max, t_max), 'HorizontalAlignment','left', 'VerticalAlignment','top')
text(t_max,Ls(index),sprintf('\\leftarrow Max = %.6f\n t = %.2f ', Ls_max, t_max), 'HorizontalAlignment','left', 'VerticalAlignment','top')
title(['Data samples at Fs = ' num2str(round(Fs)) 'Hz / Smoothed with sgolayfilt' ]);
grid on

回答(1 个)

Chunru
Chunru 2021-8-13
load RRData
% median filter to remove outliers (for 1 channel)
y1 = medfilt1(RRData.Strain_C_Fz, 7);
plot(RRData.Time, RRData.Strain_C_Fz, RRData.Time, y1)

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