【故障诊断】基于FCM模糊聚类算法实现轴承故障诊断附Matlab代码

clear allclcball=load ('ball.mat');              inner=load ('inner.mat');outer=load ('outer.mat') ;  outer1=load ('outer1.mat') ;normal=load('normal.mat');inner1=load('inner1.mat');ball1=load ('ball1.mat');ball_names = fieldnames(ball);       inner_names = fieldnames(inner);outer_names = fieldnames(outer);outer_names1 = fieldnames(outer1);normal_names = fieldnames(normal);inner_names1 = fieldnames(inner1);ball_names1 = fieldnames(ball1);ball_data=ball.(ball_names{1});      inner_data=inner.(inner_names{1});outer_data=outer.(outer_names{1});outer_data1=outer1.(outer_names1{1});normal_data=normal.(normal_names{1});inner_data1=inner1.(inner_names1{1});ball_data1=ball1.(ball_names1{1}); numPoint=4096;numExample=100;n=6;BearingFeature1=ExteactFeature(normal_data,numPoint,numExample,n);BearingFeature4=ExteactFeature(ball_data,numPoint,numExample,n);BearingFeature2=ExteactFeature(inner_data,numPoint,numExample,n);BearingFeature6=ExteactFeature(outer_data,numPoint,numExample,n);BearingFeature3=ExteactFeature(inner_data1,numPoint,numExample,n);BearingFeature5=ExteactFeature(ball_data1,numPoint,numExample,n);BearingFeature7=ExteactFeature(outer_data1,numPoint,numExample,n);K=[1,4,21,6,12,9,7,15,18,3,14,17,10,11,8,20,5,13,16,19,2];K_J=[1,4,21,6,12,3,9,15,18,7,14,17,10,11,8,5,20,2,13,16,19];fg=K(1:7);SelectFeature1=BearingFeature1(fg,:);SelectFeature2=BearingFeature2(fg,:);SelectFeature3=BearingFeature3(fg,:);SelectFeature4=BearingFeature4(fg,:);SelectFeature5=BearingFeature5(fg,:);SelectFeature6=BearingFeature6(fg,:);SelectFeature7=BearingFeature7(fg,:);input=[SelectFeature1,SelectFeature2,SelectFeature3,SelectFeature4,SelectFeature5,SelectFeature6,SelectFeature7]'; for i=1:700     input(i,:)=input(i,:)/max(input(i,:)); end[ iter,Obj_Fcn,CAT]=fuzzycm(input,14,2,1.0e-6)YLSF_ART_CAT=CAT;Sample1=1:100;YLSF_ART_CAT1=YLSF_ART_CAT(1:100);plot(Sample1,YLSF_ART_CAT1,'xy','markersize',10)hold onSample2=101:200;YLSF_ART_CAT2=YLSF_ART_CAT(101:200);plot(Sample2,YLSF_ART_CAT2,'pg','markersize',10)hold onSample3=201:300;YLSF_ART_CAT3=YLSF_ART_CAT(201:300);plot(Sample3,YLSF_ART_CAT3,'ob','markersize',14)Sample4=301:400;YLSF_ART_CAT4=YLSF_ART_CAT(301:400);plot(Sample4,YLSF_ART_CAT4,'vc','markersize',14)Sample5=401:500;YLSF_ART_CAT5=YLSF_ART_CAT(401:500);plot(Sample5,YLSF_ART_CAT5,'Dm','markersize',14)Sample6=501:600;YLSF_ART_CAT6=YLSF_ART_CAT(501:600);plot(Sample6,YLSF_ART_CAT6,'*r','markersize',14)Sample7=601:700;YLSF_ART_CAT7=YLSF_ART_CAT(601:700);plot(Sample7,YLSF_ART_CAT7,'hk','markersize',14)hold ond=15;k=d;for i=1:dplot([0,730],[i,i],':K')hold onendfor j=1:7    h=100*j;    plot([h,h],[0,k],':K')    hold onendaxis([0 700 0 k]);set(gca,'fontsize',20);set(gca,'xtick',0:100:700);set(gca,'ytick',0:1:k);title('FCM诊断结果','FontName','宋体','FontSize',18)xlabel('样本','FontName','宋体','FontSize',18)ylabel('种类','FontName','宋体','FontSize',18)% gtext('a','FontName','Times New Roman','FontSize',24)