├── Fast_STFT └── STFT.m ├── Fast_Synchrosqueezing_Transform └── Fast_STFT_SST_Matrix_ZoomNoRecon.m ├── LICENSE ├── Pars_Setting.m ├── Polynomial_chriplet_analysis ├── Do_PCT.m ├── Polynomial_chriplet.m └── polylsqr.m ├── README.md ├── Rms_Estimate_single.m ├── STFT_Analysis.m ├── STFT_Analysis_single.m ├── Segfft_single.m ├── Tdomain_Fdomain_single.m ├── Test_Poly_Chrip.m ├── Test_ST.m ├── Test_STFT.m ├── analysis.m ├── readme.txt └── util ├── Cal_Index.m ├── Cal_Plot.m ├── Calculatingbearing.m ├── Data_Convert.m ├── DisplaySTFT.m ├── Dofft.m ├── Hilbert_envelope.m ├── MakeWindows.m ├── MakeWindowsTF.m ├── Rms_Estimate.m └── jet_Linchao.m /Fast_STFT/STFT.m: -------------------------------------------------------------------------------- 1 | function [ X ] = STFT( Sig , Win , Hop_Size , Nfft) 2 | % fast STFT not using any loop 3 | % Input: 4 | % Sig : the inputting signal 5 | % Win : The length of the window 6 | % Hop_Size : the size of the jump <= length(Win) / 2 7 | % Nfft : FFT length >= length(Win) 8 | % Output: 9 | % X : The short time fourier transforming coefficients 10 | % Attention : the length of FFT is equal to the length of the Windows 11 | % Modified by Zhaozhibin from Xi'an Jiaotong University 12 | % Date: 2017.09 13 | % Email:zhaozhibin@stu.xjtu.edu.cn 14 | 15 | if nargin < 3 16 | Hop_Size = 1; 17 | end 18 | if nargin < 4 19 | Nfft = 1024; 20 | end 21 | disp('Calculating the STFT\n.') 22 | Sig = Sig(:); 23 | Sig = hilbert(real(Sig)); 24 | L = length(Win); 25 | Half = floor(L/2); 26 | Sig = [zeros(Half ,1) ; Sig ; zeros(Half-Hop_Size+1 , 1)]; 27 | X = buffer(Sig , L , L-Hop_Size , 'nodelay'); 28 | X = bsxfun(@times, Win(:), X); 29 | X = fft(X,Nfft)/ sqrt(Nfft); 30 | disp('Finishing the STFT\n.') 31 | end 32 | -------------------------------------------------------------------------------- /Fast_Synchrosqueezing_Transform/Fast_STFT_SST_Matrix_ZoomNoRecon.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ZhaoZhibin/Basic-Rotating-Machine-Vibration-Analysis/b71247a4176d0621c5a838a3f542e91810383109/Fast_Synchrosqueezing_Transform/Fast_STFT_SST_Matrix_ZoomNoRecon.m -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /Pars_Setting.m: -------------------------------------------------------------------------------- 1 | function [ Cons ] = Pars_Setting() 2 | % Setting some constant parameters 3 | % Made by Zhibin Zhao, Baoqing Ding, Shuming Wu 4 | % Contact with zhaozhibin@stu.xjtu.edu.cn 5 | % Date: 2017.06.19 6 | Cons.Fs = 10240; % sampling frequency 7 | 8 | %% This is the collection information 9 | Cons.Collect = 1; % 1 : yiheng; 2: yiheng(all-in-one); 3:HBM 10 | Cons.Flag = 0; %0 : you do not want to convert your data(actually, you have save the .mat already; you want to use .mat directly); 1 : you want to save the data as .mat 11 | Cons.type = 1; %1: save as y; 2: save as x-y(determined by your setting in the collector) 12 | 13 | %% This is the channel information 14 | Cons.Channel = 1; % the number of the channels 15 | Cons.ChannelNot = [5,6]; % this is the channel which you do not want to analysis 16 | 17 | %% This is the Speed information 18 | Cons.Speed = []; %This is your speed channel, only calculate the time-frequency figure!!!!! 19 | Cons.Normalized = 6; % This is the Speed Normalized factor, it is depended on the collecting. 20 | 21 | %% This is the calculating information for RMS estimating 22 | Cons.Flag_RMS = 1; % if the value is 0, we do not calculate the RMS, if the value is 1, we calculate the RMS. 23 | Cons.Len = 5120; % Calculating the RMS with Cons.Len points 24 | Cons.Olap = 2560; % Calculating the RMS with Cons.Olap overlapping points 25 | 26 | %% This is the calculating information for STFT estimating 27 | Cons.Win_Len = 20480; % the length of the window used in STFT 28 | Cons.Overlap = 10240; % the oveplap of the window 29 | Cons.Freq = 1000; % This is the max frequency interval which you want to save 30 | Cons.Freq_Res = 1; % the frequency resolution ratio---->1 : 1HZ ; 2 : 2Hz 31 | 32 | end 33 | 34 | -------------------------------------------------------------------------------- /Polynomial_chriplet_analysis/Do_PCT.m: -------------------------------------------------------------------------------- 1 | function [ specgm , fI , p ] = Do_PCT( Iter , t , y , win , Hop_Size , Nfft ,SampFreq , alpha) 2 | % Iteratively using PCT to achieve best solution 3 | 4 | [specgm] = Polynomial_chriplet(y , win , Hop_Size , Nfft ,SampFreq , alpha); 5 | for i = 1 : Iter 6 | nLevel = round(Nfft/2); 7 | specgm_temp = specgm(1:nLevel , :); 8 | f = [0:nLevel-1]/nLevel * SampFreq/2; 9 | [v, I] = max(specgm_temp,[],1); 10 | [p, z] = polylsqr(t,f(I),4); 11 | [specgm] = Polynomial_chriplet(y , win , Hop_Size , Nfft ,SampFreq , z(2:end)); 12 | end 13 | fI = f(I); 14 | end 15 | 16 | -------------------------------------------------------------------------------- /Polynomial_chriplet_analysis/Polynomial_chriplet.m: -------------------------------------------------------------------------------- 1 | function [ X ] = Polynomial_chriplet( Sig , Win , Hop_Size , Nfft , Fs , alpha) 2 | % Polynomial chriplet transform 3 | % Sig : the inputting signal 4 | % Win : The length of the window 5 | % Hop_Size : the size of the jump 6 | % Nfft : FFT length >= length(Win) 7 | % alpha : the parameter of Polynomial chirp transform 8 | % when alpha = [0]---> STFT 9 | % when alpha = [1]---> LCP(Linear Chrip transform) 10 | % Output: 11 | % X : The short time fourier transforming coefficients 12 | % Attention : the length of FFT is equal to the length of the Windows 13 | % Reference: 14 | %) Peng Z.K , Meng G., Lang Z.Q.,Chu F.L, Zhang W.M., Yang Y., Polynomial Chirplet Transform with Application to Instantaneous Frequency Estimation, 15 | % IEEE Transactions on Measurement and Instrumentation 60(2011) 3222-3229 16 | % Modified by Zhaozhibin 17 | % Date: 2017.09 18 | % Email:zhaozhibin@stu.xjtu.edu.cn 19 | Sig = Sig(:); 20 | N = length(Sig); 21 | dt = (0:(N-1))' / Fs; 22 | % Contructing the rotating operator 23 | Rotating = zeros(size(dt)); 24 | for k = 1 : length(alpha) 25 | Rotating = Rotating + alpha(k) / (k+1) * dt .^ (k+1); 26 | end 27 | % Construct the shifting operator 28 | Shift = zeros(size(dt)); 29 | for k = 1 : length(alpha) 30 | Shift = Shift + alpha(k) * dt .^ k; 31 | end 32 | L = length(Win); 33 | Half = floor(L/2); 34 | % padding the components 35 | Rotating = [zeros(Half ,1) ; Rotating ; zeros(Half-Hop_Size+1 , 1)]; 36 | dt = [zeros(Half ,1) ; dt ; zeros(Half-Hop_Size+1 , 1)]; 37 | Sig = [zeros(Half ,1) ; Sig ; zeros(Half-Hop_Size+1 , 1)]; 38 | Sig = hilbert(real(Sig)); 39 | % reshape the vector into matrix 40 | X = buffer(Sig , L , L-Hop_Size , 'nodelay'); 41 | R = buffer(Rotating , L , L-Hop_Size , 'nodelay'); 42 | T = buffer(dt , L , L-Hop_Size , 'nodelay'); 43 | % Construct the chrip kernel 44 | S = Shift(1 : Hop_Size : size(X , 2)*Hop_Size); 45 | C = exp(-1i*2*pi*(R-bsxfun(@times, S' , T))); 46 | % Use the chrip funtion to do STFT 47 | X = X .* C; 48 | X = fft(X,Nfft); 49 | end 50 | -------------------------------------------------------------------------------- /Polynomial_chriplet_analysis/polylsqr.m: -------------------------------------------------------------------------------- 1 | function [p, z] = polylsqr(x,y,m) 2 | % to obtain PCT parameters 3 | % x: time 4 | % y:estimated IF 5 | % m: polynomial order 6 | n=length(x); 7 | n=length(y); 8 | for k=1:2*m+1 9 | c(k)=sum(x.^(k-1)); 10 | end 11 | %Find the coefficient vector b of normal equations 12 | for k=1:m+1 13 | b(k)=sum(y.*x.^(k-1)); 14 | end 15 | % Find the coefficient matrix A of normal equations 16 | for i=1:m+1 17 | for j=1:m+1 18 | A(i,j)=c(j+i-1); 19 | end 20 | end 21 | 22 | z=A\b'; 23 | 24 | p = zeros(size(x)); 25 | 26 | for i=1:n 27 | s=z(1); 28 | for k=2:m+1 29 | s=s+z(k)*x(i)^(k-1); 30 | end 31 | p(i)=s; 32 | end -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Basic-Rotating-Machine-Vibration-Analysis 2 | These codes realize data transformation and simple data processing for fault diagnosis. 3 | 4 | If you want to analysis the data automatically, we need Setting the parameters in Pars_Seeting!!!!!!!! 5 | 6 | If you want to analysis the data one by one, we should use the file with single!!!!!!!! 7 | 8 | % The code will only test on matlab2016b. 9 | 10 | % ---------------------------------------------------------------------- 11 | 12 | % Permission to use, copy, or modify this software and its documentation 13 | 14 | % for educational and research purposes only and without fee is here 15 | 16 | % granted, provided that this copyright notice and the original authors' 17 | 18 | % names appear on all copies and supporting documentation. This program 19 | 20 | % shall not be used, rewritten, or adapted as the basis of a commercial 21 | 22 | % software or hardware product without first obtaining permission of the 23 | 24 | % authors. The authors make no representations about the suitability of 25 | 26 | % this software for any purpose. It is provided "as is" without express 27 | 28 | % or implied warranty. 29 | 30 | %---------------------------------------------------------------------- 31 | 32 | 33 | Attention: 34 | 35 | the analysing folder can not contain any other .txt which is not related to the channels information 36 | 37 | 38 | Additionally!!! 39 | 40 | We will continue to add new algorithms to the this codebook for furthering vibration signal processing. 41 | 42 | Made by Zhibin Zhao, Baoqing Ding, Shuming Wu , Baijie Qiao, Weiluo, Zhixian Shen, Dong He 43 | 44 | State Key Laboratory for Manufacturing Systems Engineer 45 | 46 | Xi'an Jiaotong University 47 | 48 | Date: 2017.06.19 49 | 50 | If you have some new ideas or any confusion, please contact us without hesitation !!! 51 | 52 | Email : zhaozhibin@stu.xjtu.edu.cn 53 | 54 | 55 | 56 | 57 | 58 | Function Details 59 | 60 | STFT : fast STFT not using any loop 61 | 62 | Polynomial_chriplet : Polynomial chriplet transform 63 | 64 | polylsqr : fitting of a polynomial 65 | 66 | Do_PCT : Iteratively using PCT to achieve best solution 67 | 68 | Cal_Index : Calculate the Index of time domain for dimensional and non-dimensional 69 | 70 | Cal_Plot : This function realizes calculating , ploting and save the figure 71 | 72 | Calculatingbearing : calculating the eigenfrequency of bearing 73 | 74 | Data_Convert : This function realizes Converting the data 75 | 76 | DisplaySTFT : Display the spectrogram in the specified range 77 | 78 | Dofft : Calculating the fft of the signal 79 | 80 | Hilbert_envelope : Calculating the Hilbert envelope spectrum of the signal 81 | 82 | jet_Linchao : Variant of HSV 83 | 84 | MakeWindows : Make artificial Window so it will be tight frame 85 | 86 | MakeWindowsTF : Make artificial Window so it will be tight frame 87 | 88 | Rms_Estimate : This function realizes calculating , ploting and save the Rms_Comparison figure 89 | 90 | Pars_Setting : Setting some constant parameters 91 | 92 | Fast_STFT_SST_Matrix_ZoomNoRecon : Fast zoomed Synchrosqueezing Transform 93 | 94 | DisplaySTFT : Display the spectrogram in the specified range 95 | 96 | Dofft : Calculating the fft of the signal 97 | 98 | Hilbert_envelope : Calculating the Hilbert envelope spectrum of the signal 99 | 100 | jet_Linchao : Variant of HSV 101 | 102 | MakeWindows : Make artificial Window so it will be tight frame 103 | 104 | MakeWindowsTF : Make artificial Window so it will be tight frame 105 | 106 | Rms_Estimate : This function realizes calculating , ploting and save the Rms_Comparison figure 107 | 108 | Pars_Setting : Setting some constant parameters 109 | 110 | Fast_STFT_SST_Matrix_ZoomNoRecon : Fast zoomed Synchrosqueezing Transform 111 | 112 | 113 | -------------------------------------------------------------------------------- /Rms_Estimate_single.m: -------------------------------------------------------------------------------- 1 | % This function realizes trend chart plot for all operating conditions 2 | clc; 3 | clear all; 4 | close all; 5 | cl = {'r';'g';'b';'y';'m';'c';'k'}; 6 | Fs = 4000; 7 | for n = 1:2 8 | % if n == 1 || n == 2 || n == 3 || n == 4 9 | % if n == 5 || n == 6 10 | if n == 1 || n == 2 11 | % if n == 2 || n == 6 || n == 7 12 | % if n == 1 || n == 3 || n == 8 13 | % filename = ['HBMchan',num2str(n),'.mat']; 14 | filename = ['Econchan' num2str(n) '.mat']; 15 | load (filename) 16 | Data = Data(:); 17 | Data = Data-mean(Data); 18 | L = length(Data); 19 | 20 | N = 1000*2; 21 | start = 1; 22 | t = (1:L)/Fs; 23 | Timeindex = start:1000:(L-N); 24 | for irow = 1:length(Timeindex) 25 | Vibrationseg = Data(Timeindex(irow):Timeindex(irow)+N-1); 26 | Index= Cal_Index(Vibrationseg); 27 | Rms(irow) = Index; 28 | end 29 | 30 | plot(t(Timeindex + 1000),Rms); 31 | hold all; 32 | axis([-inf,inf,-inf,inf]); 33 | end 34 | end 35 | legend('low pressure','high pressure','Location','NorthEastOutside'); 36 | saveas(gcf, ['J:\XH_test\2017\0610\all_comparison.fig']); 37 | % Made by Zhibin Zhao, Baoqing Ding, Shuming Wu 38 | % Contact with zhaozhibin@stu.xjtu.edu.cn 39 | % Date: 2016.09.13 -------------------------------------------------------------------------------- /STFT_Analysis.m: -------------------------------------------------------------------------------- 1 | % This function realizes the STFT for single channels 2 | 3 | 4 | Fs = 100000; 5 | Data = Data1_AI_A_1(:); 6 | Data = Data-mean(Data); 7 | figure(1) 8 | nLevel = 3000; 9 | win = MakeWindows('Gaussian', 6000 , nLevel); 10 | Nfft = Fs / 1; 11 | [specgmShow] = STFT(Data,win , nLevel , Nfft); 12 | specgmShow = abs(specgmShow(1:size(specgmShow,1)/2,:)); 13 | [ff,tt] = size(specgmShow); 14 | % colormap(jet_Linchao(64)) 15 | imagesc((0:nLevel:(tt-1)*nLevel)/Fs,Fs/2*linspace(0,1,ff),(specgmShow)); %(specgmShow-spmin)/(spmax-spmin) 16 | axis xy; 17 | xlabel('time : s'); 18 | ylabel('frequecy : Hz') 19 | title('ʱƵͼ'); 20 | axis([0 , (((tt-1)*nLevel)/Fs) ,0 , 2000]) 21 | 22 | caxis([0,0.03]) 23 | 24 | 25 | % Made by Zhibin Zhao, Baoqing Ding, Shuming Wu 26 | % Contact with zhaozhibin@stu.xjtu.edu.cn 27 | % Date: 2016.09.13 -------------------------------------------------------------------------------- /STFT_Analysis_single.m: -------------------------------------------------------------------------------- 1 | % This function only realizes STFT without calculating other things 2 | clc 3 | clear all 4 | close all 5 | original_path = fileparts(mfilename('fullpath')); 6 | tools = genpath(original_path); 7 | addpath(tools) 8 | Fs = 6000; 9 | for i = 3:3 10 | if i == 5 11 | continue; 12 | else 13 | % filename = ['HBMchan' num2str(i) '.mat']; 14 | filename = ['Econchan',num2str(i),'.mat']; 15 | load(filename); 16 | Data = Data(:); 17 | % Data = Data(5000*Fs:5100*Fs-1); 18 | Data = Data-mean(Data); 19 | % figure(1) 20 | % plot((1:size(Data,1))/Fs,Data) 21 | figure(i) 22 | nLevel = 3000; 23 | win = MakeWindows('Gaussian', 6000 , nLevel); 24 | Nfft = Fs / 1; 25 | [specgmShow] = STFT(Data,win , nLevel , Nfft); 26 | Step = Fs/1000; 27 | specgmShow = abs(specgmShow(1:floor(size(specgmShow,1)/Step),:)); 28 | [ff,tt] = size(specgmShow); 29 | colormap(jet_Linchao(64)) 30 | imagesc((0:nLevel:(tt-1)*nLevel)/Fs,1000*linspace(0,1,ff),(specgmShow)); %(specgmShow-spmin)/(spmax-spmin) 31 | axis xy; 32 | xlabel('time : s'); 33 | ylabel('frequecy : Hz') 34 | title([num2str(i),'TimeFrequency']); 35 | axis([0 , (((tt-1)*nLevel)/Fs) ,0 , 400]) 36 | 37 | % caxis([0,0.001]) 38 | % saveas(gcf, ['G:\XH_test\2017\0610\' num2str(i) 'TimeFrequency.fig']); 39 | end 40 | end 41 | 42 | % Made by Zhibin Zhao, Baoqing Ding, Shuming Wu 43 | % Contact with zhaozhibin@stu.xjtu.edu.cn 44 | % Date: 2016.09.13 -------------------------------------------------------------------------------- /Segfft_single.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ZhaoZhibin/Basic-Rotating-Machine-Vibration-Analysis/b71247a4176d0621c5a838a3f542e91810383109/Segfft_single.m -------------------------------------------------------------------------------- /Tdomain_Fdomain_single.m: -------------------------------------------------------------------------------- 1 | % This function plots the time domain and frequency domain 2 | clc 3 | clear all 4 | close all 5 | for i = 1:2 6 | if i == 4 7 | continue; 8 | else 9 | % filename = ['HBMchan' num2str(i) '.mat']; 10 | filename = ['Econchan' num2str(i) '.mat']; 11 | load(filename) 12 | % Data = cell2mat(Data); 13 | Data = Data(:)'; 14 | Data = Data-mean(Data); 15 | n = length(Data); 16 | Fs = 4000; 17 | t = 0:1/Fs:(n-1)/Fs; 18 | figure(i) 19 | plot(t,Data); 20 | titlex = ['Channel' num2str(i) 'TimeDomain']; 21 | title(titlex) 22 | xlabel('time /s') 23 | ylabel('amplitude') 24 | saveas(gcf, ['J:\XH_test\2017\0610\Channel' num2str(i) 'TimeDomain.fig']); 25 | close gcf 26 | end 27 | %% 28 | % [Mag,f] = dofft(c,Fs); 29 | % Plot single-sided amplitude spectrum. 30 | % figure(2) 31 | % plot(f,Mag) 32 | % title('Single-Sided Amplitude Spectrum of y(t)') 33 | % xlabel('Frequency (Hz)') 34 | % ylabel('|Y(f)|') 35 | end 36 | 37 | % Made by Zhibin Zhao, Baoqing Ding, Shuming Wu 38 | % Contact with zhaozhibin@stu.xjtu.edu.cn 39 | % Date: 2016.09.13 40 | -------------------------------------------------------------------------------- /Test_Poly_Chrip.m: -------------------------------------------------------------------------------- 1 | % This function test Fast Polynomial chriplet analysis 2 | clear all 3 | close all 4 | addpath('./util') 5 | addpath('./Polynomial_chriplet_analysis') 6 | Fs = 200; 7 | t = 0 : 1/Fs : 15; 8 | 9 | c1 = 2 * pi * 10; % initial frequency of the chirp excitation 10 | c2 = 2 * pi * 5/2; % set the speed of frequency change be 1 Hz/second 11 | c3 = 2 * pi * 1/3; 12 | c4 = 2 * pi * -1/40; 13 | 14 | Sig = sin(c1 * t + c2 * t.^2 / 2 + c3 * t.^3 /3 + c4 * t.^4 /4); % get the A(t) 15 | n1 = rand(size(Sig)); 16 | n1 = n1 - mean(n1); 17 | n1 = 3*n1 / max(n1) * max(Sig); 18 | std(n1) 19 | Sig = Sig + n1/2; 20 | y = Sig'; 21 | 22 | Hop_Size = 1; 23 | Nfft = 512; 24 | alpha = 0; 25 | Iter = 7; 26 | win = MakeWindows('Gaussian' , 215); 27 | [specgm , f , p] = Do_PCT( Iter , t, y , win , Hop_Size , Nfft , Fs , alpha); 28 | figure 29 | plot(t, f, t, p) 30 | figure 31 | DisplaySTFT(specgm , Fs , Hop_Size , 0,50) 32 | -------------------------------------------------------------------------------- /Test_ST.m: -------------------------------------------------------------------------------- 1 | % This function tests STFT and STFT-based SST 2 | addpath('./util') 3 | addpath('./Fast_Synchrosqueezing_Transform') 4 | close all;clear;clc; 5 | fs=1024; 6 | t=(0:1024-1)/fs; 7 | A1=1;A2=1;A3=1; 8 | fc1=100;fc3=450;Am=20;fm=10;alpha=250;beta=400;gama=-400; 9 | x1=A1*cos(2*pi*fc1*t-Am/fm*cos(2*pi*fm*t)); 10 | x2=A2*cos(2*pi*alpha*t+pi*beta*t.^2+2*pi/3*gama*t.^3); 11 | x3=A3*cos(2*pi*fc1*t-pi/4); 12 | x5=100*(t-0.5); 13 | x4=cos(2*pi*(256*t+0.4*(x5.*log(x5+sqrt(x5.^2+1))-cosh(log(x5+sqrt(x5.^2+1)))))); 14 | x=x2; 15 | % x=awgn(x,5,'measured'); 16 | 17 | figure 18 | plot(t,x) 19 | 20 | sigma=0.01;nfft=length(x); 21 | 22 | %} 23 | tic 24 | [s,Tx,time,freqr,win]=Fast_STFT_SST_Matrix_ZoomNoRecon(x,fs,sigma,5,1,fs/2,4); 25 | toc 26 | figure 27 | imagesc(time,freqr,abs(Tx));axis xy 28 | 29 | %} 30 | -------------------------------------------------------------------------------- /Test_STFT.m: -------------------------------------------------------------------------------- 1 | %% This function tests fast STFT 2 | clear all 3 | addpath('./util') 4 | addpath('./Fast_STFT') 5 | Fs = 2000; 6 | N = 4000; 7 | t = -2:1/Fs:(N-1)*(1/Fs); 8 | y = sin(2*100*pi*t)+sin(2*200*pi*t)+sin(2*400*pi*t); 9 | % y = chirp(t,0,1,150); % Start @ DC, % cross 150Hz at t=1 sec 10 | 11 | Hop_Size = 100; 12 | win = MakeWindowsTF('Gaussian' , 200 , Hop_Size); 13 | 14 | [specgm] = STFT(y , win , Hop_Size ,1000); 15 | DisplaySTFT(specgm , Fs , Hop_Size , 0); 16 | -------------------------------------------------------------------------------- /analysis.m: -------------------------------------------------------------------------------- 1 | clc 2 | clear all 3 | close all 4 | %% setting the path 5 | % get the fundamental file information 6 | original_path = fileparts(mfilename('fullpath')); 7 | tools = genpath(original_path); 8 | FileFolder = uigetdir('C:\'); 9 | cd(FileFolder); 10 | CurrentFolder = pwd; 11 | MyFileInfo = dir; 12 | addpath(tools) 13 | %% setting some fundamental parameters 14 | Cons = Pars_Setting; 15 | 16 | if Cons.Flag % Choose if you have the .mat or not 17 | %% pick up the filename with .txt 18 | k = 1; 19 | for i = 3 : length(MyFileInfo) 20 | [~,~,ext] = fileparts(MyFileInfo(i).name); 21 | if strcmpi(ext , '.txt') 22 | MyFileInfo_Channel1(k).name = MyFileInfo(i).name; 23 | k = k + 1; 24 | end 25 | end 26 | %% load the data and save it 27 | Channel_Number = Data_Convert( CurrentFolder, MyFileInfo_Channel1 , Cons); 28 | else 29 | k = 1 : Cons.Channel; 30 | Channel_Number = setdiff(k , Cons.ChannelNot); 31 | end 32 | 33 | %% Calculate the RMS, STFT, and the time domain 34 | MyFileInfo = dir; 35 | k = 1; 36 | for i = 3 : length(MyFileInfo) 37 | [~,~,ext] = fileparts(MyFileInfo(i).name); 38 | if strcmpi(ext , '.mat') 39 | MyFileInfo_Channel2(k).name = MyFileInfo(i).name; 40 | k = k + 1; 41 | end 42 | end 43 | 44 | Cal_Plot(CurrentFolder, MyFileInfo_Channel2 , Cons , Channel_Number) 45 | 46 | 47 | % Made by Zhibin Zhao, Baoqing Ding, Shuming Wu 48 | % Contact with zhaozhibin@stu.xjtu.edu.cn 49 | % Date: 2017.06.19 50 | -------------------------------------------------------------------------------- /readme.txt: -------------------------------------------------------------------------------- 1 | These codes realize data transformation and simple data processing for fault diagnosis. 2 | 3 | If you want to analysis the data automatically, we need Setting the parameters in Pars_Seeting!!!!!!!! 4 | 5 | If you want to analysis the data one by one, we should use the file with single!!!!!!!! 6 | 7 | % The code will only test on matlab2016b. 8 | 9 | % ---------------------------------------------------------------------- 10 | % Permission to use, copy, or modify this software and its documentation 11 | % for educational and research purposes only and without fee is here 12 | % granted, provided that this copyright notice and the original authors' 13 | % names appear on all copies and supporting documentation. This program 14 | % shall not be used, rewritten, or adapted as the basis of a commercial 15 | % software or hardware product without first obtaining permission of the 16 | % authors. The authors make no representations about the suitability of 17 | % this software for any purpose. It is provided "as is" without express 18 | % or implied warranty. 19 | %---------------------------------------------------------------------- 20 | 21 | 22 | Attention: 23 | the analysing folder can not contain any other .txt which is not related to the channels information 24 | 25 | 26 | Additionally!!! 27 | We will continue to add new algorithms to the this codebook for furthering vibration signal processing. 28 | 29 | Made by Zhibin Zhao, Baoqing Ding, Shuming Wu , Baijie Qiao, Weiluo, Zhixian Shen, Dong He 30 | State Key Laboratory for Manufacturing Systems Engineer 31 | Xi'an Jiaotong University 32 | Date: 2017.06.19 33 | 34 | If you have some new ideas or any confusion, please contact us without hesitation !!! 35 | Email : zhaozhibin@stu.xjtu.edu.cn 36 | 37 | 38 | 39 | 40 | 41 | Function Details 42 | STFT : fast STFT not using any loop 43 | Polynomial_chriplet : Polynomial chriplet transform 44 | polylsqr : fitting of a polynomial 45 | Do_PCT : Iteratively using PCT to achieve best solution 46 | Cal_Index : Calculate the Index of time domain for dimensional and non-dimensional 47 | Cal_Plot : This function realizes calculating , ploting and save the figure 48 | Calculatingbearing : calculating the eigenfrequency of bearing 49 | Data_Convert : This function realizes Converting the data 50 | DisplaySTFT : Display the spectrogram in the specified range 51 | Dofft : Calculating the fft of the signal 52 | Hilbert_envelope : Calculating the Hilbert envelope spectrum of the signal 53 | jet_Linchao : Variant of HSV 54 | MakeWindows : Make artificial Window so it will be tight frame 55 | MakeWindowsTF : Make artificial Window so it will be tight frame 56 | Rms_Estimate : This function realizes calculating , ploting and save the Rms_Comparison figure 57 | Pars_Setting : Setting some constant parameters 58 | Fast_STFT_SST_Matrix_ZoomNoRecon : Fast zoomed Synchrosqueezing Transform 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | -------------------------------------------------------------------------------- /util/Cal_Index.m: -------------------------------------------------------------------------------- 1 | function [ Index ] = Cal_Index( x ) 2 | % Calculate the Index of time domain for dimensional and non-dimensional 3 | % Made by Zhibin Zhao, Baoqing Ding, Shuming Wu 4 | % Contact with zhaozhibin@stu.xjtu.edu.cn 5 | % Date: 2016.09.13 6 | % x:the original signal 7 | 8 | [a,b] = size(x); 9 | y = mean(x); 10 | x = x-y; 11 | if a == 1 12 | x = x'; 13 | end 14 | % disp('Result of parameters'); 15 | % disp('Mean Value=');% the average 16 | % disp(y) 17 | % disp('Standard Deviation Value='); 18 | % Sta=std(x); 19 | % disp(Sta) 20 | % disp('Variance Value='); 21 | % Var=var(x); 22 | % disp(Var) 23 | % disp('Skewness Value='); 24 | % Ske=skewness(x); 25 | % disp(Ske) 26 | % disp('kurtosis Value='); 27 | % Kur=kurtosis(x); 28 | % disp(Kur) 29 | % disp('P_P Value='); 30 | % Ppv=max(x)-min(x); 31 | % disp(Ppv) 32 | % disp('Xr Value='); 33 | % Xr=(mean(sqrt(abs(x))))^2; 34 | % disp(Xr); 35 | % disp('Xmean Value='); 36 | % Xmean=mean(abs(x)); 37 | % disp(Xmean); 38 | % disp('Xrms Value='); 39 | % Xrms=sqrt(mean(x.*x)); 40 | % disp(Xrms); 41 | % disp('Xp Value='); 42 | % Xp=max(max(x), -min(x)); 43 | % disp(Xp); 44 | % disp('W Value='); 45 | % W=Xrms/Xmean; 46 | % disp(W) 47 | % disp('C Value='); 48 | % C=Xp/Xrms; 49 | % disp(C) 50 | % disp('I Value='); 51 | % I=Xp/Xmean; 52 | % disp(I) 53 | % disp('L Value='); 54 | % L=Xrms/Xr; 55 | % disp(L) 56 | % 57 | % disp('S Value='); 58 | % S=Ske/(mean(sum(x.^3)) ); 59 | % disp(S) 60 | % 61 | % disp('K Value='); 62 | % K=Kur/(mean(sum(x.^4)) ); 63 | % disp(K) 64 | % Index=[y,Sta,Var,Ske,Kur,Ppv,Xr,Xmean,Xrms,Xp,W,C,I,L,S,K]; 65 | Xrms = sqrt(mean(x.*x)); 66 | Index = Xrms; 67 | end 68 | 69 | -------------------------------------------------------------------------------- /util/Cal_Plot.m: -------------------------------------------------------------------------------- 1 | function Cal_Plot(CurrentFolder, MyFileInfo_Channel , Cons , Channel_Number) 2 | % This function realizes calculating , ploting and save the figure 3 | % Input: 4 | % CurrentFolder : the folder where you save the data 5 | % MyFileInfo_Channel : the channels' name 6 | % Cons : some constant parameters 7 | % Channel_Number : the channels' sequences without the channels which 8 | % you do not want to analysis 9 | % Made by Zhibin Zhao, Baoqing Ding, Shuming Wu 10 | % Contact with zhaozhibin@stu.xjtu.edu.cn 11 | % Date: 2017.06.19 12 | 13 | Fs = Cons.Fs; % Setting the sampling frequency 14 | 15 | 16 | 17 | 18 | 19 | % plot the Rms comparison figure 20 | if Cons.Flag_RMS 21 | Rms_Estimate(CurrentFolder, MyFileInfo_Channel , Fs , Cons , Channel_Number) 22 | end 23 | 24 | for i = 1 : length(MyFileInfo_Channel) 25 | 26 | filename = MyFileInfo_Channel(i).name; 27 | [~,name,~] = fileparts(filename); 28 | load(filename); 29 | Data = Data(:); 30 | Data = Data-mean(Data); 31 | if isempty(find(Cons.Speed == Channel_Number(i))) 32 | % plot the time domain 33 | n = length(Data); 34 | t = 0:1/Fs:(n-1)/Fs; 35 | plot(t,Data); 36 | title([name '-Time-Domain']); 37 | xlabel('Time /s') 38 | ylabel('Amplitude') 39 | filename_save = [CurrentFolder '\' name '_Time.fig']; 40 | saveas(gcf, filename_save); 41 | close gcf 42 | end 43 | 44 | 45 | % plot the time-frequency figure 46 | nLevel = Cons.Win_Len-Cons.Overlap; 47 | win = MakeWindows('Gaussian', Cons.Win_Len , nLevel); 48 | Nfft = Fs / Cons.Freq_Res; 49 | [specgmShow] = STFT(Data , win , nLevel); 50 | Step = Fs/Cons.Freq; 51 | specgmShow = abs(specgmShow(1:floor(size(specgmShow,1)/Step),:)); 52 | [ff,tt] = size(specgmShow); 53 | colormap(jet_Linchao(64)) 54 | if isempty(find(Cons.Speed == Channel_Number(i))) 55 | imagesc((0:nLevel:(tt-1)*nLevel)/Fs , Cons.Freq*linspace(0,1,ff) , (specgmShow)); %(specgmShow-spmin)/(spmax-spmin) 56 | axis xy; 57 | xlabel('Time : s'); 58 | ylabel('Frequecy : Hz') 59 | title([name '-Time-Frequency']); 60 | axis([0 , (((tt-1)*nLevel)/Fs) ,0 , Cons.Freq]) 61 | % caxis([0,0.001]) 62 | filename_save = [CurrentFolder '\' name '_TF.fig']; 63 | saveas(gcf, filename_save); 64 | close gcf 65 | else 66 | imagesc((0:nLevel:(tt-1)*nLevel)/Fs ,Cons.Freq*linspace(0,1,ff)/Cons.Normalized , (specgmShow)); %(specgmShow-spmin)/(spmax-spmin) 67 | axis xy; 68 | xlabel('Time : s'); 69 | ylabel('Frequecy : Hz') 70 | title([name '-Speed-Time-Frequency']); 71 | axis([0 , (((tt-1)*nLevel)/Fs) ,0 , 500]) 72 | % caxis([0,0.001]) 73 | filename_save = [CurrentFolder '\' name '_Speed_TF.fig']; 74 | saveas(gcf, filename_save); 75 | close gcf 76 | end 77 | 78 | end 79 | 80 | -------------------------------------------------------------------------------- /util/Calculatingbearing.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ZhaoZhibin/Basic-Rotating-Machine-Vibration-Analysis/b71247a4176d0621c5a838a3f542e91810383109/util/Calculatingbearing.m -------------------------------------------------------------------------------- /util/Data_Convert.m: -------------------------------------------------------------------------------- 1 | function [Channel_Number] = Data_Convert( CurrentFolder, MyFileInfo_Channel , Cons) 2 | % This function realizes Converting the data 3 | % Input: 4 | % CurrentFolder : the folder where you save the data 5 | % MyFileInfo_Channel : the channels' name 6 | % Cons : some constant parameters 7 | % Made by Zhibin Zhao, Baoqing Ding, Shuming Wu 8 | % Contact with zhaozhibin@stu.xjtu.edu.cn 9 | % Date: 2017.06.19 10 | k = 1 : Cons.Channel; 11 | Channel_Number = setdiff(k , Cons.ChannelNot); 12 | switch Cons.Collect 13 | case 1 14 | % Realize the data transformation from Econ all-in-one machine 15 | % Channel is the speed channel 16 | for i = 1 : length(Channel_Number) 17 | filename = [CurrentFolder '\' MyFileInfo_Channel(Channel_Number(i)).name]; 18 | fileID = fopen(filename); 19 | if Cons.type == 1 20 | % only save amplitude 21 | x = textscan(fileID,'%f','HeaderLines',21); 22 | fclose(fileID); 23 | Data = cell2mat(x); 24 | else 25 | % save amplitude and time simultaneously 26 | x = textscan(fileID,'%f %f','HeaderLines',21); 27 | fclose(fileID); 28 | Data = cell2mat(x(1,2)); 29 | end 30 | %% If your sampling frequency is too high, you need down sampling 31 | % Data = decimate(Data,4); 32 | 33 | filename = ['Econchan' num2str(Channel_Number(i)) '.mat']; 34 | save(filename,'Data','-v7.3'); 35 | end 36 | 37 | case 2 38 | % Realize the data transformation from Econ (not all-in-one 39 | % machine) 40 | for i = 1 : length(Channel_Number) 41 | filename = [CurrentFolder '\' MyFileInfo_Channel(Channel_Number(i)).name]; 42 | fileID = fopen(filename); 43 | if Cons.type == 1 44 | % only save amplitude 45 | x = textscan(fileID,'%f','HeaderLines',18); 46 | fclose(fileID); 47 | Data = cell2mat(x); 48 | else 49 | % save amplitude and time simultaneously 50 | x = textscan(fileID,'%f %f','HeaderLines',18); 51 | fclose(fileID); 52 | Data = cell2mat(x(1,2)); 53 | end 54 | %% If your sampling frequency is too high, you need down sampling 55 | % Data = decimate(Data,4); 56 | filename = ['Econchan' num2str(Channel_Number(i)) '.mat']; 57 | save(filename,'Data','-v7.3'); 58 | end 59 | 60 | 61 | case 3 62 | % Realize the data transformation from HBN 63 | for i = 1 : length(MyFileInfo_Channel) 64 | filename = [CurrentFolder '\' MyFileInfo_Channel(i).name]; % this is the name of the file 65 | fileID = fopen(filename); 66 | % textscan(fileID,'%s') 67 | x = textscan(fileID,'%f %f %f %f %f %f %f %f %f %f %f %f %f %f %f %f'); 68 | fclose(fileID); 69 | for j = Channel_Number %According to the number of channels 70 | Data = cell2mat(x(j)); 71 | filename = ['HBMchan' num2str(j) '.mat']; 72 | save(filename,'Data'); 73 | end 74 | end 75 | 76 | 77 | 78 | end 79 | 80 | -------------------------------------------------------------------------------- /util/DisplaySTFT.m: -------------------------------------------------------------------------------- 1 | function DisplaySTFT( X , Fs , Hop_Size , mode , Fr) 2 | % Display the spectrogram in the specified range 3 | % Input : 4 | % X : STFT coefficients 5 | % Fs : the sampling frequency 6 | % Hop_Size : the length of the jumpping 7 | % mode : 1 ----> dB 0----> normal 8 | % Fr : the maximal frequency you want to display 9 | % Modified by Zhaozhibin from Xi'an Jiaotong University 10 | % Date: 2017.09 11 | % Email:zhaozhibin@stu.xjtu.edu.cn 12 | if nargin < 4 13 | mode = 0; 14 | end 15 | if nargin < 5 16 | Fr = Fs/2; 17 | end 18 | [Nf , Nt] = size(X); 19 | if mode 20 | Spec = 20*log10(abs(X(1:round(Nf/2),:))); 21 | else 22 | Spec = abs(X(1:round(Nf/2),:)); 23 | end 24 | tt = (0:Hop_Size:(Nt-1)* Hop_Size) / Fs; 25 | ff = (0 : Nf-1) / Nf *( Fs / 2); 26 | % colormap(jet_Linchao(64)) % the white background 27 | colormap jet % the blue background 28 | clf 29 | set(gcf,'Position',[20 100 350 300]); 30 | set(gcf,'Color','w'); 31 | imagesc(tt , ff , Spec) 32 | axis xy; 33 | xlabel('Time (seconds)') 34 | ylabel('Frequency (Hz)') 35 | ylim([0 Fr]); 36 | 37 | end 38 | 39 | -------------------------------------------------------------------------------- /util/Dofft.m: -------------------------------------------------------------------------------- 1 | function [yf , f] = Dofft( Sig , Fs ,Flag) 2 | % Calculating the fft of the signal 3 | % Input: 4 | % Sig : the input signal 5 | % Fs : the sampling frequency 6 | % Flag : if Flag = 0 or not exist, then not plot the frequency 7 | % spectrum if Flag = 1, then plot the frequency spectrum 8 | % Output: 9 | % yf : the FFT of the signal's envelope 10 | % f : the frequency index 11 | if ~exist('Flag','var') || isempty(Flag) 12 | Flag = 0; 13 | end 14 | xlen = length(Sig); 15 | Sig = Sig - mean(Sig); 16 | NFFT = 2 ^ nextpow2(xlen); 17 | yf = fft(Sig,NFFT) / xlen * 2; 18 | yf = abs(yf(1 : NFFT/2+1)); 19 | f = Fs / 2 * linspace(0,1,NFFT/2+1); 20 | f = f(:); 21 | % Plot the frequency spectrum 22 | if Flag 23 | plot(f,yf); 24 | title('single side amplitude spectrum of x(t)') 25 | xlabel('frequency (Hz)') 26 | ylabel('|y(f)|') 27 | end 28 | 29 | end 30 | 31 | % Made by Zhibin Zhao 32 | % Contact with zhaozhibin@stu.xjtu.edu.cn 33 | % Date: 2016.09.13 34 | 35 | -------------------------------------------------------------------------------- /util/Hilbert_envelope.m: -------------------------------------------------------------------------------- 1 | function [ yf, f ] = Hilbert_envelope( Sig , Fs , Flag) 2 | % Calculating the Hilbert envelope spectrum of the signal 3 | % Input: 4 | % Sig : the input signal 5 | % Fs : the sampling frequency 6 | % Flag : if Flag = 1 or not exist, then perform square 7 | % HilbertEnvelope; if Flag = 0, then perform HilbertEnvelope 8 | % Output: 9 | % yf : the FFT of the signal's envelope 10 | % f : the frequency index 11 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 12 | 13 | if ~exist('Flag','var') || isempty(Flag) 14 | Flag = 1; 15 | end 16 | Sig = Sig(:); % build the column vector 17 | 18 | HSig = abs(hilbert(Sig)); 19 | if Flag 20 | [yf , f] = Dofft(HSig.^2 , Fs); % square HilbertEnvelope 21 | else 22 | [yf , f] = Dofft(HSig , Fs); % HilbertEnvelope 23 | end 24 | 25 | end 26 | 27 | %% Do fast fourier transform 28 | function [yf , f] = Dofft(Sig , Fs) 29 | % Calculating the fft of the signal 30 | % Input: 31 | % Sig : the input signal 32 | % Fs : the sampling frequency 33 | % Output: 34 | % yf : the FFT of the signal's envelope 35 | % f : the frequency index 36 | xlen = length(Sig); 37 | Sig = Sig - mean(Sig); 38 | NFFT = 2 ^ nextpow2(xlen); 39 | yf = fft(Sig,NFFT) / xlen * 2; 40 | yf = abs(yf(1 : NFFT/2+1)); 41 | f = Fs / 2 * linspace(0,1,NFFT/2+1); 42 | f = f(:); 43 | end 44 | 45 | % Made by Zhibin Zhao 46 | % Contact with zhaozhibin@stu.xjtu.edu.cn 47 | % Date: 2016.09.13 -------------------------------------------------------------------------------- /util/MakeWindows.m: -------------------------------------------------------------------------------- 1 | function win2 = MakeWindows(Name , n) 2 | % MakeWindow -- Make artificial Window so it will be tight frame 3 | % this file is modified from 'STFT.m' originally by 4 | % Ilker Bayram, Istanbul Technical University, 5 | % Usage 6 | % wig = MakeWindow(Name,n) 7 | % Inputs 8 | % Name string: 'Rectangle', 'Hanning', 'Hamming', 9 | % 'Gaussian', 'Blackman'; 10 | % n Window length 11 | % Hop_Size: the steps 12 | % Outputs 13 | % win 1-d Window, with length 2n+1; 14 | % Description 15 | % Rectangle 1 16 | % Hanning cos(pi*t)^2 17 | % Hamming .54 + .46cos(2pi*t) 18 | % Gaussian exp(-18 * t^2/2) 19 | % Blackman .42 + .50*cos(2pi*t) + .08cos(4.*pi.*t) 20 | % Examples 21 | % win = MakeWindow('Rectangle',17); plot(win); 22 | % win = MakeWindow('Hanning', 17); plot(win); 23 | % win = MakeWindow('Hamming', 17); plot(win); 24 | % win = MakeWindow('Gaussian', 17); plot(win); 25 | % win = MakeWindow('Blackman', 17); plot(win); 26 | % 27 | 28 | % Modified by Zhaozhibin 29 | % Date: 2017.09 30 | % Email:zhaozhibin@stu.xjtu.edu.cn 31 | n = n+1-rem(n,2); 32 | n = floor(n / 2); 33 | t = ((1:(2*n+1))-(n+1))./n./2; 34 | if strcmp(Name,'Rectangle') 35 | win = ones(size(t)); 36 | elseif strcmp(Name,'Hanning') 37 | win = realpow(cos(pi.*t),2); 38 | elseif strcmp(Name,'Hamming') 39 | win = .54 + .46*cos(2.*pi.*t); 40 | elseif strcmp(Name,'Gaussian') 41 | win = exp(-realpow(t,2)*18); 42 | elseif strcmp(Name,'Blackman') 43 | win = .42 + .50*cos(2.*pi.*t) + .08*cos(4.*pi.*t); 44 | end 45 | win2 = win / norm(win); 46 | 47 | 48 | end 49 | 50 | -------------------------------------------------------------------------------- /util/MakeWindowsTF.m: -------------------------------------------------------------------------------- 1 | function win2 = MakeWindowsTF(Name,n , Hop_Size) 2 | % MakeWindow -- Make artificial Window so it will be tight frame 3 | % this file is modified from 'STFT.m' originally by 4 | % Ilker Bayram, Istanbul Technical University, 5 | % Usage 6 | % wig = MakeWindow(Name,n) 7 | % Inputs 8 | % Name string: 'Rectangle', 'Hanning', 'Hamming', 9 | % 'Gaussian', 'Blackman'; 10 | % n Window length 11 | % Hop_Size: the steps 12 | % Outputs 13 | % win 1-d Window, with length 2n+1; 14 | % Description 15 | % Rectangle 1 16 | % Hanning cos(pi*t)^2 17 | % Hamming .54 + .46cos(2pi*t) 18 | % Gaussian exp(-18 * t^2/2) 19 | % Blackman .42 + .50*cos(2pi*t) + .08cos(4.*pi.*t) 20 | % Examples 21 | % win = MakeWindow('Rectangle',17); plot(win); 22 | % win = MakeWindow('Hanning', 17); plot(win); 23 | % win = MakeWindow('Hamming', 17); plot(win); 24 | % win = MakeWindow('Gaussian', 17); plot(win); 25 | % win = MakeWindow('Blackman', 17); plot(win); 26 | % 27 | 28 | % Modified by Zhaozhibin from Xi'an Jiaotong University 29 | % Date: 2017.09 30 | % Email:zhaozhibin@stu.xjtu.edu.cn 31 | if mod(n , 2) 32 | n = floor(n / 2); 33 | t = ((1:(2*n+1))-(n+1))./n./2; 34 | else 35 | n = n / 2; 36 | t = linspace(-n , n , n*2)./n./2; 37 | end 38 | if strcmp(Name,'Rectangle') 39 | win = ones(size(t)); 40 | elseif strcmp(Name,'Hanning') 41 | win = realpow(cos(pi.*t),2); 42 | elseif strcmp(Name,'Hamming') 43 | win = .54 + .46*cos(2.*pi.*t); 44 | elseif strcmp(Name,'Gaussian') 45 | win = exp(-realpow(t,2)*18); 46 | elseif strcmp(Name,'Blackman') 47 | win = .42 + .50*cos(2.*pi.*t) + .08*cos(4.*pi.*t); 48 | end 49 | 50 | % normalize the window according to the Hop_Size so that the STFT is a 51 | % tight frame 52 | K = floor(n / Hop_Size); 53 | win2 = win .^ 2; 54 | Temp = win2; 55 | for k = 1 : K 56 | Temp(1:end-k*Hop_Size) = Temp(1:end-k*Hop_Size) + win2(k*Hop_Size+1:end); 57 | end 58 | for k = 1 : K 59 | Temp(k*Hop_Size+1:end) = Temp(k*Hop_Size+1:end) + win2(1:end-k*Hop_Size); 60 | end 61 | win2 = win ./ sqrt(Temp); 62 | end 63 | 64 | -------------------------------------------------------------------------------- /util/Rms_Estimate.m: -------------------------------------------------------------------------------- 1 | function Rms_Estimate(CurrentFolder, MyFileInfo_Channel , Fs , Cons , Channel_Number) 2 | % This function realizes calculating , ploting and save the 3 | % Rms_Comparison figure 4 | % Input: 5 | % CurrentFolder : the folder where you save the data 6 | % MyFileInfo_Channel : the channels' name 7 | % Fs : the sampling frequency 8 | % Cons : some constant parameters 9 | % Channel_Number : the channels' sequences without the channels which 10 | % you do not want to analysis 11 | % Made by Zhibin Zhao, Baoqing Ding, Shuming Wu 12 | % Contact with zhaozhibin@stu.xjtu.edu.cn 13 | % Date: 2017.06.19 14 | 15 | 16 | cl = {'r';'g';'b';'y';'m';'c';'k'}; %Refer to the number of channels 17 | for i = 1 : length(MyFileInfo_Channel) 18 | if ~isempty(find(Cons.Speed == Channel_Number(i))) 19 | continue; 20 | end 21 | filename = MyFileInfo_Channel(i).name; 22 | load(filename) 23 | Data = Data(:); % transfer to column vector 24 | Data = Data-mean(Data); 25 | L = length(Data); 26 | % Calculate RMS 27 | N = Cons.Len; 28 | start = 1; 29 | t = (1:L)/Fs; 30 | Timeindex = start : Cons.Olap : (L-N); 31 | for irow = 1:length(Timeindex) 32 | Vibrationseg = Data(Timeindex(irow):Timeindex(irow)+N-1); 33 | Index= Cal_Index(Vibrationseg); 34 | Rms(irow) = Index; 35 | end 36 | plot(t(Timeindex + Cons.Olap),Rms); 37 | hold all; 38 | axis([-inf,inf,-inf,inf]); 39 | end 40 | % legend('low pressure','high pressure','Location','NorthEastOutside'); 41 | legend('low pressure','high pressure','Location','NorthEastOutside'); 42 | filename_save = [CurrentFolder '\Total_Comparison.fig']; 43 | saveas(gcf, filename_save); 44 | close gcf 45 | end 46 | 47 | -------------------------------------------------------------------------------- /util/jet_Linchao.m: -------------------------------------------------------------------------------- 1 | function J = jet_Linchao(m) 2 | %JET Variant of HSV 3 | % JET(M), a variant of HSV(M), is an M-by-3 matrix containing 4 | % the default colormap used by CONTOUR, SURF and PCOLOR. 5 | % The colors begin with dark blue, range through shades of 6 | % blue, cyan, green, yellow and red, and end with dark red. 7 | % JET, by itself, is the same length as the current figure's 8 | % colormap. If no figure exists, MATLAB creates one. 9 | % 10 | % See also HSV, HOT, PINK, FLAG, COLORMAP, RGBPLOT. 11 | 12 | % Copyright 1984-2004 The MathWorks, Inc. 13 | % $Revision: 5.7.4.2 $ $Date: 2005/06/21 19:31:40 $ 14 | 15 | if nargin < 1 16 | m = size(get(gcf,'colormap'),1); 17 | end 18 | n = ceil(m/4); 19 | u = [(1:1:n)/n ones(1,n-1) (n:-1:1)/n]'; 20 | g = ceil(n/2) - (mod(m,4)==1) + (1:length(u))'; 21 | r = g + n; 22 | b = g - n; 23 | g(g>m) = []; 24 | r(r>m) = []; 25 | b(b<1) = []; 26 | J = zeros(m,3); 27 | J(r,1) = u(1:length(r)); 28 | J(g,2) = u(1:length(g)); 29 | J(b,3) = u(end-length(b)+1:end); 30 | 31 | p = ceil(n/2) - (mod(m,4)==1); 32 | rg =(p:-1:1)/p; 33 | J(1:p,1) = rg; 34 | J(1:p,2) = rg; 35 | J(1:p,3) = ones(1,p); 36 | --------------------------------------------------------------------------------