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1、吴国曾：石油钻井事故预报中数据的滤波方法研究A2.1卡尔曼滤波程序：loadxinshuju.mat%调入数据h=xinshuju;t1=14000;t2=15000;t=t1:t2;n=t2-t1+1;s=h(t);fori=1:n-1;b(i)=s(i+1)/s(i);end%a=mean(b);a=1;w(1)=0;w=randn(1,n);x(1)=s(1);fork=2:nx(k)=b(i)*x(k-1)+w(k-1);endv=randn(1,n);q1=std(v);rvv=q1.^2;q2=std(w);rww=q2.^2;c=1;z=c*s'+
2、v;p(1)=5;m(1)=0;fort=2:n%卡尔曼滤波过程p1(t)=a.^2*p(t-1)+rww;g(t)=c*p1(t)/(p1(t)+rvv);m(t)=a*m(t-1)+g(t)*(z(t)-a*c*m(t-1));p(t)=p1(t)-c*g(t)*p1(t);endt=1:n;figure-5-吴国曾：石油钻井事故预报中数据的滤波方法研究subplot(211);plot(s);title('theorignaldata');subplot(212);plot(m,'g');title('thede-noisingdata')figurepl
3、ot(s);holdonplot(m,'r');A2.2小波滤波：loadxinshuju.mat%调入数据h=xinshuju;t1=1;t2=15000;t=t1:t2;n=t2-t1+1;s=h(t);l_s=length(s);[cA1,cD1]=dwt(s,'db8');%用db8小波对信号s进行单层分解a1=upcoef('a',cA1,'db8',1,l_s);%重建小波系数至上一层a代表低通，d表高通，1表a作用在d1=upcoef('d',cD1,'db8',1,l_s);%ca1上的次数subplot(311);plot(a1);title(
4、'ApproximationA1')subplot(312);plot(d1);title('DetailD1')subplot(313);plot(s,'g');A0=idwt(cA1,cD1,'db8',l_s);%用于单层小波重建err=max(abs(s-A0))figureplot(A0,'r');title('therecontrustsignal');%%%%%%%%%%%%%%%%%%[C,L]=wavedec(s,3,'db8')%三次小波分解cA3=appcoef(C,L,'db8',3);%求得第三层的近似系数，长度60[cD1,cD2,c
5、D3]=detcoef(C,L,[1,2,3]);%求得1到3层的细节系数，长度依次减小A3=wrcoef('a',C,L,'db8',3);%重建小波系数，长度和源信号一样D1=wrcoef('d',C,L,'db8',1);D2=wrcoef('d',C,L,'db8',2);D3=wrcoef('d',C,L,'db8',3);figuresubplot(411);plot(A3);-5-吴国曾：石油钻井事故预报中数据的滤波方法研究title('ApproximationA3')subplot(412);plot(D1);title('DetailD1')
6、subplot(413);plot(D2);title('DetailD2')subplot(414);plot(D3);title('DetailD3')%%%%%%%%%%%%%%%%%A0=waverec(C,L,'db8');%多层小波重建原始信号err1=max(abs(s-A0))figureplot(A0,'g');title('fromthe3-dem-recontrustsignal');%Removenoisebythresholding.[thr,sorh,keepapp]=ddencmp('den','wv',s);%den用于降噪，cm
7、p用于压缩，wv使用小波变换，%wp使用小波包变换，thr求得的阈值，sorh，s%表软阈值，h表硬阈值，keepapp表保留的近似系数的层数。clean=wdencmp('gbl',s,'db1',3,thr,sorh,keepapp);figuresubplot(211);plot(s);title('theorignalsignal');subplot(212);plot(clean,'g');title('Removenoisebythresholding');;A2.3MA滤波：Max_m=59;Min_m=19;%给定启动新滤波段的阈值loadEB_
8、Da24.mat%调入数
