xiaobosuanfa
采样频率
fs=10000
轴承外环故障信号
fid=fopen( bearingout.dat , r ) 故障
N=1024
xdata=fread(fid,N, int16 )
fclose(fid)
xdata=(xdata-mean(xdata))/std(xdata,1)
时域波形
figure(1)
plot(1:N,xdata)
xlabel( 时间 t/n )
ylabel( 电压 V/v )
db10小波进行4层分解
一维小波分解
[c,l] = wavedec(xdata,4, db10 )
重构第1～4层细节信号
d4 = wrcoef( d ,c,l, db10 ,4)
d3 = wrcoef( d ,c,l, db10 ,3)
d2 = wrcoef( d ,c,l, db10 ,2)
d1 = wrcoef( d ,c,l, db10 ,1)
( Sampling frequency fs = 10000 bearing outer ring fault signal fid = fopen (' bearingout.dat' , ' r' ) failure N = 1024 xdata = fread (fid, N, ' int16' ) fclose (fid ) xdata = (xdata-mean (xdata))/std (xdata, 1) time-domain waveform figure (1) plot (1: N, xdata) xlabel (' Time t/n' ) ylabel ( ' voltage V/v' ) db10 wavelet decomposition 4 layer one-dimensional wavelet decomposition [c, l] = wavedec (xdata, 4, ' db10' ) 1 ~ 4 reconstructed detail signal d4 = wrcoef (' d' , c, l, ' db10' , 4) d3 = wrcoef (' d' , c, l, ' db10' , 3) d2 = wrcoef (' d' , c, l, ' db10' , 2) d1 = wrcoef (' d' , c, l, ' db10' , 1) )
- 2011-05-21 16:48:36下载
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