StatPaDAnSeqMX.rar_building

% Non-Parametric Damping Analysis % Provide an equispaced velocity time series named "input" %sampling rate sampl=20; dt=1/sampl; %data correction detr=input-mean(input); Wn=1.0/(sampl/2) [b,a] = butter(2,Wn,'high'); Hd = dfilt.df2t(b,a); fltrd= filter(b,a,detr); %fltrd=input-mean(input); %data integration to obtain displacements knum=size(fltrd); kum=knum(1); for in=1:knum; ix(in,1)=in*dt; end u=fltrd; nu=length(u); [m,n]=size(u); x=1:nu; if(n==1) x=x'; end dx=x(2:nu)-x(1:nu-1); a=zeros(size(u)); b=u(1:nu-1) + u(2:nu); a(2:nu)=b.*dx/2; corr=cumsum(a); %selection of local maxima nnum=size(corr); num=nnum(1); c=0; for i= 2:num-1; if corr(i,1) >= corr(i-1,1) & corr(i,1) >= corr(i+1,1) & corr(i,1) >0; c=c+1; maxim(c,1)=corr(i,1); maxim(c,2)=(i+2)*dt; end end %estimation of log.decrement and pseudo-frequency cc=0; for j= 1:c-2; if maxim(j,1) > maxim(j+1,1) cc=cc+1; a=maxim(j,1); b=maxim(j+1,1); d=maxim(j+1,2); e=maxim(j,2); declog=log(a/b); psper=(d-e); smorz(cc,1)=1/psper; smorz(cc,2)=100*declog./(2*pi); smorz(cc,3)=a; smorz(cc,4)=d; end end fhist=[0: 0.25: 10]; nh=histc(smorz(:,1),fhist); [maxh, imaxh]=max(nh); fmin=fhist(imaxh)-0.25; fmax=fhist(imaxh)+0.25; idmp=0 for kk= 1:cc if (smorz(kk,1) >= fmin) & (smorz(kk,1) <= fmax) idmp=idmp+1 dmpst= smorz(kk,2) end end dfx=1./diff(smorz(:,4)); isx=0 for ijk=1:cc-1 if (dfx(ijk) >= fmin) & (dfx(ijk) <= fmax) if (smorz(ijk,1) >= fmin) & (smorz(ijk,1) <= fmax) if smorz(ijk+1,3)<smorz(ijk,3) isx=isx+1; dmp2(isx)=(smorz(ijk+1,2)+smorz(ijk,2))/2; end end end end [f,xf] = ecdf(dmp2); mu=mean(log(dmp2)); sigma=std(log(dmp2)); damp25= prctile(dmp2,25) medamp=median(dmp2) damp75= prctile(dmp2,75) yy=logncdf(xf,mu,sigma); ww=lognpdf(xf,mu,sigma); figure plot(xf,f,xf,yy) axis([0 25 0 1]) legend('Empirical cdf','LogNormal cdf') xlabel('Damping') ylabel('%')