[moved] Mat-lab GUI code not running

function varargout = fl(varargin)
gui_Singleton = 1;
gui_State = struct('gui_Name'), mfilename,
...
'gui_Singleton',
gui_Singleton, ...
'gui_OpeningFcn',
@fl_OpeningFcn, ...
'gui_OutputFcn',
@fl_OutputFcn, ...
'gui_LayoutFcn', [] , ...
'gui_Callback', []);
if nargin && ischar(varargin{1})
gui_State.gui_Callback =
str2func(varargin{1});
end
if nargout
[varargout{1:nargout}] =
gui_mainfcn(gui_State, varargin{:});
else
gui_mainfcn(gui_State, varargin{:});
end
% --- Executes on button press in delete.
function delete_Callback(hObject, eventdata,
handles)
% hObject handle to delete (see GCBO)
% eventdata reserved - to be defined in a
future version of MATLAB
% handles structure with handles and user
data (see GUIDATA)
axes(handles.axes1); cla reset
axes(handles.axes2); cla reset
axes(handles.axes3); cla reset
set(handles.t1,'String',' ')
axes(handles.axes7); cla reset
axes(handles.axes8); cla reset
axes(handles.axes9); cla reset
set(handles.t2,'String',' ')
set(handles.t4,'String',' ')
set(handles.et1,'String',' ')
set(handles.t_error,'String',' ')
% --- Executes just before fl is made
visible.
function fl_OpeningFcn(hObject, eventdata,
handles, varargin)
handles.output = hObject;
guidata(hObject, handles);
% --- Outputs from this function are returned
to the command line.
function varargout = fl_OutputFcn(hObject,
eventdata, handles)
% varargout cell array for returning output
args (see
% Get default command line output from
handles structure
varargout{1} = handles.output;
% --- Executes on button press in b.
function b_Callback(hObject, eventdata,
handles)
% hObject handle to b (see GCBO)
global th_ph_f;
global dlg_ab;
global l2l_ab;
global slf_A;
global D;
th_ph_f=0; dlg_ab=0; l2l_ab=0; slf_A=0; D=0;
file = uigetfile('*.csv');
newData1 = importdata(file);
% Create new variables in the base workspace
from those fields.
vars = fieldnames(newData1);
for i = 1:length(vars)
assignin('base', vars{i},
newData1.(vars{i}));
end
data = newData1.(vars{1});
t=data(1:20000,1);
A =data(1:20000,2);
B =data(1:20000,3);
C =data(1:20000,4);
I0 = (1/3)* (A+B+C);
I1 = (1/3)*(2*A - B -C);
I2 = (1/3)*(sqrt(3)*B - sqrt(3)*C);
% Perform a multilevel wavelet decomposition
of I0 at level 5
[C0,L0] = wavedec(I0,5,'db4');
[Ea0,Ed0] = wenergy(C0,L0);
% Extract approximation and detail
coefficients.
c0A5 = appcoef(C0,L0,'db4',5);
c0A4 = appcoef(C0,L0,'db4',4);
c0A3 = appcoef(C0,L0,'db4',3);
c0A2 = appcoef(C0,L0,'db4',2);
c0A1 = appcoef(C0,L0,'db4',1);
c0D5 = detcoef(C0,L0,5);
c0D4 = detcoef(C0,L0,4);
c0D3 = detcoef(C0,L0,3);
c0D2 = detcoef(C0,L0,2);
c0D1 = detcoef(C0,L0,1);
%Energy for 1-D wavelet or wavelet packet
decomposition
[Ea0,Ed0] = wenergy(C0,L0);
Ed0_max = max(Ed0);
% Reconstruct the Level 5 approximation and
the Level 1 to 9 details.
A05 = wrcoef('a',C0,L0,'db4',5);
D01 = wrcoef('d',C0,L0,'db4',1);
D02 = wrcoef('d',C0,L0,'db4',2);
D03 = wrcoef('d',C0,L0,'db4',3);
D04 = wrcoef('d',C0,L0,'db4',4);
D05 = wrcoef('d',C0,L0,'db4',5);
% Evaluation of the square of the wavelet
coefficients
s_D01=D01.*D01; sum_s_D01=sum(s_D01);
s_D02=D02.*D02; sum_s_D02=sum(s_D02);
s_D03=D03.*D03; sum_s_D03=sum(s_D03);
s_D04=D04.*D04; sum_s_D04=sum(s_D04);
s_D05=D05.*D05; sum_s_D05=sum(s_D05);
% caculation of the disotrted signal
energy%%%%
d01=sum_s_D01;
d02=d01+sum_s_D02;
d03=d02+sum_s_D03;
d04=d03+sum_s_D04;
d05=d04+sum_s_D05;
% Perform a multilevel wavelet decomposition
of phase A at level 5
[Ca,La] = wavedec(A,5,'db4');
% Extract approximation and detail
coefficients.
caA5 = appcoef(Ca,La,'db4',5);
caA4 = appcoef(Ca,La,'db4',4);
caA3 = appcoef(Ca,La,'db4',3);
caA2 = appcoef(Ca,La,'db4',2);
caA1 = appcoef(Ca,La,'db4',1);
caD5 = detcoef(Ca,La,5);
caD4 = detcoef(Ca,La,4);
caD3 = detcoef(Ca,La,3);
caD2 = detcoef(Ca,La,2);
caD1 = detcoef(Ca,La,1);
% Reconstruct the Level 5 approximation and
the Level 1 to 5 details.
Aa5 = wrcoef('a',Ca,La,'db4',11);
Da1 = wrcoef('d',Ca,La,'db4',1);
Da2 = wrcoef('d',Ca,La,'db4',2);
Da3 = wrcoef('d',Ca,La,'db4',3);
Da4 = wrcoef('d',Ca,La,'db4',4);
Da5 = wrcoef('d',Ca,La,'db4',5);
%Energy for 1-D wavelet or wavelet packet
decomposition
[Eaa,Eda] = wenergy(Ca,La);
Eda_max = max(Eda);
% Evaluation of the square of the wavelet
coefficients
s_Da1=Da1.*Da1; sum_s_Da1=sum(s_Da1);
s_Da2=Da2.*Da2; sum_s_Da2=sum(s_Da2);
s_Da3=Da3.*Da3; sum_s_Da3=sum(s_Da3);
s_Da4=Da4.*Da4; sum_s_Da4=sum(s_Da4);
s_Da5=Da5.*Da5; sum_s_Da5=sum(s_Da5);
% caculation of the disotrted signal
energy%%%%
da1=sum_s_Da1;
da2=da1+sum_s_Da2;
da3=da2+sum_s_Da3;
da4=da3+sum_s_Da4;
da5=da4+sum_s_Da5;
% Perform a multilevel wavelet decomposition
of phase B at level 5
[Cb,Lb] = wavedec(B,5,'db4');
% Extract approximation and detail
coefficients.
cbA5 = appcoef(Cb,Lb,'db4',5);
cbA4 = appcoef(Cb,Lb,'db4',4);
cbA3 = appcoef(Cb,Lb,'db4',3);
cbA2 = appcoef(Cb,Lb,'db4',2);
cbA1 = appcoef(Cb,Lb,'db4',1);
cbD5 = detcoef(Cb,Lb,5);
cbD4 = detcoef(Cb,Lb,4);
cbD3 = detcoef(Cb,Lb,3);
cbD2 = detcoef(Cb,Lb,2);
cbD1 = detcoef(Cb,Lb,1);
% Reconstruct the Level 5 approximation and
the Level 1 to 5 details.
Ab5 = wrcoef('a',Cb,Lb,'db4',1);
Db1 = wrcoef('d',Cb,Lb,'db4',1);
Db2 = wrcoef('d',Cb,Lb,'db4',2);
Db3 = wrcoef('d',Cb,Lb,'db4',3);
Db4 = wrcoef('d',Cb,Lb,'db4',4);
Db5 = wrcoef('d',Cb,Lb,'db4',5);
%Energy for 1-D wavelet or wavelet packet
decomposition
[Eab,Edb] = wenergy(Cb,Lb);
Edb_max = max(Edb);
% Evaluation of the square of the wavelet
coefficients
s_Db1=Db1.*Db1; sum_s_Db1=sum(s_Db1);
s_Db2=Db2.*Db2; sum_s_Db2=sum(s_Db2);
s_Db3=Db3.*Db3; sum_s_Db3=sum(s_Db3);
s_Db4=Db4.*Db4; sum_s_Db4=sum(s_Db4);
s_Db5=Db5.*Db5; sum_s_Db5=sum(s_Db5);
% caculation of the disotrted signal
energy%%%%
db1=sum_s_Db1;
db2=db1+sum_s_Db2;
db3=db2+sum_s_Db3;
db4=db3+sum_s_Db4;
db5=db4+sum_s_Db5;
% Perform a multilevel wavelet decomposition
of phase C at level 5
[Cc,Lc] = wavedec(C,5,'db4');
% Extract approximation and detail
coefficients.
ccA5 = appcoef(Cc,Lc,'db4',5);
ccA4 = appcoef(Cc,Lc,'db4',4);
ccA3 = appcoef(Cc,Lc,'db4',3);
ccA2 = appcoef(Cc,Lc,'db4',2);
ccA1 = appcoef(Cc,Lc,'db4',1);
ccD5 = detcoef(Cc,Lc,5);
ccD4 = detcoef(Cc,Lc,4);
ccD3 = detcoef(Cc,Lc,3);
ccD2 = detcoef(Cc,Lc,2);
ccD1 = detcoef(Cc,Lc,1);
% Reconstruct the Level 5 approximation and
the Level 1 to 5 details.
Ac5 = wrcoef('a',Cc,Lc,'db4',11);
Dc1 = wrcoef('d',Cc,Lc,'db4',1);
Dc2 = wrcoef('d',Cc,Lc,'db4',2);
Dc3 = wrcoef('d',Cc,Lc,'db4',3);
Dc4 = wrcoef('d',Cc,Lc,'db4',4);
Dc5 = wrcoef('d',Cc,Lc,'db4',5);
%Energy for 1-D wavelet or wavelet packet
decomposition
[Eac,Edc] = wenergy(Cc,Lc);
Edc_max = max(Edc);
% Evaluation of the square of the wavelet
coefficients
s_Dc1=Dc1.*Dc1; sum_s_Dc1=sum(s_Dc1);
s_Dc2=Dc2.*Dc2; sum_s_Dc2=sum(s_Dc2);
s_Dc3=Dc3.*Dc3; sum_s_Dc3=sum(s_Dc3);
s_Dc4=Dc4.*Dc4; sum_s_Dc4=sum(s_Dc4);
s_Dc5=Dc5.*Dc5; sum_s_Dc5=sum(s_Dc5);
% caculation of the disotrted signal
energy%%%%
dc1=sum_s_Dc1;
dc2=dc1+sum_s_Dc2;
dc3=dc2+sum_s_Dc3;
dc4=dc3+sum_s_Dc4;
dc5=dc4+sum_s_Dc5;
axes(handles.axes1);
plot(t,A );hold on; plot(t, Aa5,'r');
axes(handles.axes2);
plot(t,B,'.' );hold on; plot(t, Ab5,'r')
axes(handles.axes3);
plot(t,C );hold on; plot(t, Ac5,'r')
axes(handles.axes4);
imshow('panel.png')
axes(handles.axes5);
imshow('panel_b.png')
axes(handles.axes6);
imshow('panel_c.png')
set(handles.t1,'String',file)
axes(handles.axes7); plot(t,Da5);
axes(handles.axes8); plot(t,Db5);
axes(handles.axes9); plot(t,Db5);
% no fault
if (da5<15) && (db5<15) && (dc5<15)
set(handles.t2,'String','No Fault')
Fault=0;
else
Fault=1;
end
%%%%%% Fault Classification
%%%%%
if Fault==1
FUZ = readfis('class');
clas = evalfis([Ed0_max Eda_max Edb_max
Edc_max ], FUZ)
if (clas>0.5)&& (clas<1.5)
set(handles.t2,'String','Three Phase
Fault')
th_ph_f= 1;
elseif (clas>1.5)&& (clas<2.5)
set(handles.t2,'String','Double line to
ground Fault between phase A and B')
dlg_ab=1;
elseif (clas>2.5)&& (clas<3.5)
set(handles.t2,'String','line to line
Fault between phase A and B')
l2l_ab=1;
elseif (clas>3.5)&& (clas<4.5)
set(handles.t2,'String','Single line to
ground Fault at phase A')
slf_A=1;
else
set(handles.t2,'String','Wrong')
end
%%%%%%%% Fault location
%%%%%%%%%%%%%%%
if th_ph_f==1
FUZ = readfis('anfis_3ph');
D = evalfis([Ed0_max Eda_max Edb_max Edc_max
], FUZ)
set(handles.t4,'String',D);
end
if slf_A == 1
FUZ = readfis('anfis_slg');
D = evalfis([Ed0_max Eda_max Edb_max Edc_max
], FUZ)
set(handles.t4,'String',D);
end
if l2l_ab == 1
FUZ = readfis('anfis_l2l');
D = evalfis([Ed0_max Eda_max Edb_max Edc_max
], FUZ)
set(handles.t4,'String',D);
end
if dlg_ab ==1
FUZ = readfis('anfis_dlg');
D = evalfis([Ed0_max Eda_max Edb_max Edc_max
], FUZ)
set(handles.t4,'String',D);
end
end
function et1_Callback(hObject, eventdata,
handles)
function et1_CreateFcn(hObject, eventdata,
handles)
if ispc &&
isequal(get(hObject,'BackgroundColor'),
get(0,'defaultUicontrolBackgroundColor'))
set(hObject,'BackgroundColor','white');
end
% --- Executes on button press in calc_error.
function calc_error_Callback(hObject,
eventdata, handles)
d = get(handles.t4,'String');
d_val = str2double(d);
AFL = get(handles.et1,'String');
AFL_val = str2double(AFL);
error = 100 * abs(AFL_val-d_val)/6 ;
set(handles.t_error,'String',error);
A.2 Creating and Training the ANFIS MODEL
files_names = dir(fullfile(matlabroot,
'anfis'));
no_files = length (files_names);
for nf=3:no_files
fp = files_names(nf).name;
savefile = 'trnError_3ph.csv';
file_Path = ['C:\Program
Files\MATLAB2\R2011a\anfis\' , fp];
importfile_anfis(file_Path)
trnData = train_3ph;
numMFs = 5;
mfType = 'gbellmf';
in_fis = genfis1(trnData,numMFs,mfType);
[out_fis,trnError_class] = anfis(trnData,
in_fis,300);
plot(trnError_class , '*');grid;
xlabel('Epochs');
ylabel('RMSE (Root Mean Squared Error)');
title('Error Curves');
figure(2)
out_fis_o = evalfis(trnData(:,1:4),out_fis);
plot([out_fis_o ,trnData(:,5)], 'x');
end