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main.py
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#!/usr/bin/python
# -*- coding: utf-8 -*-
"""
Moto: Induction motor parameter estimation tool
Main window
Author: Julius Susanto
Last edited: August 2014
"""
import os, sys
from PyQt4 import QtCore, QtGui
import numpy as np
import dateutil, pyparsing
import matplotlib.pyplot as plt
import globals
import saveload
from common_calcs import get_torque, get_torque_sc
from descent import nr_solver, lm_solver, dnr_solver, nr_solver_sc
from genetic import ga_solver
from hybrid import hy_solver
class Window(QtGui.QMainWindow):
def __init__(self):
super(Window, self).__init__()
globals.init()
self.initUI()
def initUI(self):
self.resize(800, 600)
self.centre()
# Set background colour of main window to white
palette = QtGui.QPalette()
palette.setColor(QtGui.QPalette.Background,QtCore.Qt.white)
self.setPalette(palette)
self.setWindowTitle('SPE Moto | Induction Motor Parameter Estimation Tool')
self.setWindowIcon(QtGui.QIcon('icons\motor.png'))
"""
Actions
"""
exitAction = QtGui.QAction(QtGui.QIcon('icons\exit.png'), '&Exit', self)
exitAction.setShortcut('Ctrl+Q')
exitAction.setStatusTip('Exit application')
exitAction.triggered.connect(QtGui.qApp.quit)
loadAction = QtGui.QAction('&Open File...', self)
loadAction.setStatusTip('Open file and load motor data')
loadAction.triggered.connect(self.load_action)
saveAction = QtGui.QAction('&Save As...', self)
saveAction.setStatusTip('Save motor data')
saveAction.triggered.connect(self.save_action)
aboutAction = QtGui.QAction('&About Moto', self)
aboutAction.setStatusTip('About Moto')
aboutAction.triggered.connect(self.about_dialog)
helpAction = QtGui.QAction('&User Manual', self)
helpAction.setShortcut('F1')
helpAction.setStatusTip('Moto user documentation')
helpAction.triggered.connect(self.user_manual)
"""
Menubar
"""
menu_bar = self.menuBar()
fileMenu = menu_bar.addMenu('&File')
fileMenu.addAction(loadAction)
fileMenu.addAction(saveAction)
fileMenu.addAction(exitAction)
helpMenu = menu_bar.addMenu('&Help')
helpMenu.addAction(helpAction)
helpMenu.addSeparator()
helpMenu.addAction(aboutAction)
"""
Main Screen
"""
heading_font = QtGui.QFont()
heading_font.setPointSize(10)
heading_font.setBold(True)
################
# Motor details
################
header1 = QtGui.QLabel('Motor')
#header1.setMinimumWidth(50)
header1.setMinimumHeight(30)
header1.setFont(heading_font)
label1 = QtGui.QLabel('Description')
#label1.setMinimumWidth(50)
self.le1 = QtGui.QLineEdit()
#self.le1.setMinimumWidth(150)
self.le1.setText(str(globals.motor_data["description"]))
label2 = QtGui.QLabel('Synchronous speed')
#label2.setMinimumWidth(50)
self.le2 = QtGui.QLineEdit()
#self.le2.setMinimumWidth(50)
self.le2.setText(str(globals.motor_data["sync_speed"]))
label2a = QtGui.QLabel('rpm')
#label2a.setMinimumWidth(30)
label3 = QtGui.QLabel('Rated speed')
#label3.setMinimumWidth(50)
self.le3 = QtGui.QLineEdit()
#self.le3.setMinimumWidth(50)
self.le3.setText(str(globals.motor_data["rated_speed"]))
label3a = QtGui.QLabel('rpm')
#label3a.setMinimumWidth(30)
label4 = QtGui.QLabel('Rated power factor')
#label4.setMinimumWidth(50)
self.le4 = QtGui.QLineEdit()
#self.le4.setMinimumWidth(50)
self.le4.setText(str(globals.motor_data["rated_pf"]))
label4a = QtGui.QLabel('pf')
#label4a.setMinimumWidth(20)
label5 = QtGui.QLabel('Rated efficiency')
#label5.setMinimumWidth(50)
self.le5 = QtGui.QLineEdit()
#self.le5.setMinimumWidth(50)
self.le5.setText(str(globals.motor_data["rated_eff"]))
label5a = QtGui.QLabel('pu')
#label5a.setMinimumWidth(20)
label6 = QtGui.QLabel('Breakdown torque')
#label6.setMinimumWidth(50)
self.le6 = QtGui.QLineEdit()
#self.le6.setMinimumWidth(50)
self.le6.setText(str(globals.motor_data["T_b"]))
label6a = QtGui.QLabel('T/Tn')
#label6a.setMinimumWidth(40)
label7 = QtGui.QLabel('Locked rotor torque')
#label7.setMinimumWidth(50)
self.le7 = QtGui.QLineEdit()
#self.le7.setMinimumWidth(50)
self.le7.setText(str(globals.motor_data["T_lr"]))
label7a = QtGui.QLabel('T/Tn')
#label7a.setMinimumWidth(40)
label8 = QtGui.QLabel('Locked rotor current')
#label8.setMinimumWidth(50)
self.le8 = QtGui.QLineEdit()
#self.le8.setMinimumWidth(50)
self.le8.setText(str(globals.motor_data["I_lr"]))
label8a = QtGui.QLabel('pu')
#label8a.setMinimumWidth(40)
########
# Model
########
header2 = QtGui.QLabel('Model')
header2.setMinimumHeight(40)
header2.setFont(heading_font)
label_model = QtGui.QLabel('Model')
#label_model.setMinimumWidth(150)
self.combo_model = QtGui.QComboBox()
self.combo_model.addItem("Single cage")
# self.combo_model.addItem("Single cage w/o core losses")
self.combo_model.addItem("Double cage")
self.combo_model.setCurrentIndex(1)
self.img1 = QtGui.QLabel()
self.img1.setPixmap(QtGui.QPixmap('images\dbl_cage.png'))
#####################
# Algorithm settings
#####################
header3 = QtGui.QLabel('Settings')
header3.setMinimumHeight(40)
header3.setFont(heading_font)
label9 = QtGui.QLabel('Maximum # iterations')
self.le9 = QtGui.QLineEdit()
self.le9.setText(str(globals.algo_data["max_iter"]))
self.le9.setStatusTip('Maximum number of iterations allowed')
label10 = QtGui.QLabel('Convergence criterion')
self.le10 = QtGui.QLineEdit()
self.le10.setText(str(globals.algo_data["conv_err"]))
self.le10.setStatusTip('Squared error required to qualify for convergence')
self.label11 = QtGui.QLabel('Linear constraint k_r')
self.le11 = QtGui.QLineEdit()
self.le11.setText(str(globals.algo_data["k_r"]))
self.le11.setStatusTip('Linear constraint for Rs')
self.label12 = QtGui.QLabel('Linear constraint k_x')
self.le12 = QtGui.QLineEdit()
self.le12.setText(str(globals.algo_data["k_x"]))
self.le12.setStatusTip('Linear constraint for Xr2')
# Genetic Algorithm Widgets
############################
self.labeln_gen = QtGui.QLabel('Maximum # generations')
self.labeln_gen.setVisible(0)
self.labelpop = QtGui.QLabel('Members in population')
self.labelpop.setVisible(0)
self.labeln_r = QtGui.QLabel('Members in mating pool')
self.labeln_r.setVisible(0)
self.labeln_e = QtGui.QLabel('Elite children')
self.labeln_e.setVisible(0)
self.labelc_f = QtGui.QLabel('Crossover fraction')
self.labelc_f.setVisible(0)
self.len_gen = QtGui.QLineEdit()
self.len_gen.setText(str(globals.algo_data["n_gen"]))
self.len_gen.setStatusTip('Maximum number of generations allowed')
self.len_gen.hide()
self.lepop = QtGui.QLineEdit()
self.lepop.setText(str(globals.algo_data["pop"]))
self.lepop.setStatusTip('Number of members in each generation')
self.lepop.hide()
self.len_r = QtGui.QLineEdit()
self.len_r.setText(str(globals.algo_data["n_r"]))
self.len_r.setStatusTip('Number of members in a mating pool')
self.len_r.hide()
self.len_e = QtGui.QLineEdit()
self.len_e.setText(str(globals.algo_data["n_e"]))
self.len_e.setStatusTip('Number of elite children')
self.len_e.hide()
self.lec_f = QtGui.QLineEdit()
self.lec_f.setText(str(globals.algo_data["c_f"]))
self.lec_f.setStatusTip('Proportion of children spawned through crossover')
self.lec_f.hide()
label_algo = QtGui.QLabel('Algorithm')
#label_algo.setMinimumWidth(150)
self.combo_algo = QtGui.QComboBox()
self.combo_algo.addItem("Newton-Raphson")
self.combo_algo.addItem("Levenberg-Marquardt")
self.combo_algo.addItem("Damped Newton-Raphson")
self.combo_algo.addItem("Genetic Algorithm")
self.combo_algo.addItem("Hybrid GA-NR")
self.combo_algo.addItem("Hybrid GA-LM")
self.combo_algo.addItem("Hybrid GA-DNR")
calc_button = QtGui.QPushButton("Calculate")
calc_button.setStatusTip('Estimate equivalent circuit parameters')
self.plot_button = QtGui.QPushButton("Plot")
self.plot_button.setDisabled(1)
self.plot_button.setStatusTip('Plot torque-speed and current-speed curves')
####################
# Algorithm results
####################
header4 = QtGui.QLabel('Results')
#header4.setMinimumWidth(150)
header4.setMinimumHeight(40)
header4.setFont(heading_font)
label13 = QtGui.QLabel('R_s')
#label13.setFixedWidth(50)
self.leRs = QtGui.QLineEdit()
self.leRs.setStatusTip('Stator resistance (pu)')
label14 = QtGui.QLabel('X_s')
#label14.setMinimumWidth(150)
self.leXs = QtGui.QLineEdit()
self.leXs.setStatusTip('Stator reactance (pu)')
label15 = QtGui.QLabel('X_m')
#label15.setMinimumWidth(150)
self.leXm = QtGui.QLineEdit()
self.leXm.setStatusTip('Magnetising resistance (pu)')
label16 = QtGui.QLabel('X_r1')
#label16.setMinimumWidth(150)
self.leXr1 = QtGui.QLineEdit()
self.leXr1.setStatusTip('Inner cage rotor reactance (pu)')
label17 = QtGui.QLabel('R_r1')
#label17.setMinimumWidth(150)
self.leRr1 = QtGui.QLineEdit()
self.leRr1.setStatusTip('Inner cage rotor resistance (pu)')
self.label18 = QtGui.QLabel('X_r2')
#label18.setMinimumWidth(150)
self.leXr2 = QtGui.QLineEdit()
self.leXr2.setStatusTip('Outer cage rotor reactance (pu)')
self.label19 = QtGui.QLabel('R_r2')
#label19.setMinimumWidth(150)
self.leRr2 = QtGui.QLineEdit()
self.leRr2.setStatusTip('Outer cage rotor resistance (pu)')
label20 = QtGui.QLabel('R_c')
#label20.setMinimumWidth(150)
self.leRc = QtGui.QLineEdit()
self.leRc.setStatusTip('Core loss resistance (pu)')
label21 = QtGui.QLabel('Converged?')
#label21.setMinimumWidth(150)
self.leConv = QtGui.QLineEdit()
self.leConv.setStatusTip('Did algorithm converge?')
label22 = QtGui.QLabel('Squared Error')
#label22.setMinimumWidth(150)
self.leErr = QtGui.QLineEdit()
self.leErr.setStatusTip('Squared error of estimate')
label23 = QtGui.QLabel('Iterations')
#label23.setMinimumWidth(150)
self.leIter = QtGui.QLineEdit()
self.leIter.setStatusTip('Number of iterations / generations')
##############
# Grid layout
##############
grid = QtGui.QGridLayout()
# Motor details
i = 0
grid.addWidget(header1, i, 0)
grid.addWidget(label1, i+1, 0)
grid.addWidget(self.le1, i+1, 1, 1, 5)
grid.addWidget(label2, i+2, 0)
grid.addWidget(self.le2, i+2, 1)
grid.addWidget(label2a, i+2, 2)
grid.addWidget(label3, i+3, 0)
grid.addWidget(self.le3, i+3, 1)
grid.addWidget(label3a, i+3, 2)
grid.addWidget(label4, i+4, 0)
grid.addWidget(self.le4, i+4, 1)
grid.addWidget(label4a, i+4, 2)
grid.addWidget(label5, i+5, 0)
grid.addWidget(self.le5, i+5, 1)
grid.addWidget(label5a, i+5, 2)
grid.addWidget(label6, i+3, 4)
grid.addWidget(self.le6, i+3, 5)
grid.addWidget(label6a, i+3, 6)
grid.addWidget(label7, i+4, 4)
grid.addWidget(self.le7, i+4, 5)
grid.addWidget(label7a, i+4, 6)
grid.addWidget(label8, i+5, 4)
grid.addWidget(self.le8, i+5, 5)
grid.addWidget(label8a, i+5, 6)
# Model
i = 9
#grid.addWidget(header2, i, 0)
grid.addWidget(label_model, i+1, 0)
grid.addWidget(self.combo_model, i+1, 1)
grid.addWidget(self.img1, i+1, 3, i-7, 6)
# Algorithm settings
i = 12
grid.addWidget(header3, i, 0)
grid.addWidget(label_algo, i+1, 0)
grid.addWidget(self.combo_algo, i+1, 1)
grid.addWidget(label9, i+2, 0)
grid.addWidget(self.le9, i+2, 1)
grid.addWidget(label10, i+3, 0)
grid.addWidget(self.le10, i+3, 1)
grid.addWidget(self.label11, i+2, 3)
grid.addWidget(self.le11, i+2, 4)
grid.addWidget(self.label12, i+3, 3)
grid.addWidget(self.le12, i+3, 4)
# Genetic algorithm parameters
grid.addWidget(self.labeln_gen, i+2, 3)
grid.addWidget(self.len_gen, i+2, 4)
grid.addWidget(self.labelpop, i+3, 3)
grid.addWidget(self.lepop, i+3, 4)
grid.addWidget(self.labeln_r, i+4, 3)
grid.addWidget(self.len_r, i+4, 4)
grid.addWidget(self.labeln_e, i+2, 5)
grid.addWidget(self.len_e, i+2, 6)
grid.addWidget(self.labelc_f, i+3, 5)
grid.addWidget(self.lec_f, i+3, 6)
grid.addWidget(calc_button, i+4, 5)
grid.addWidget(self.plot_button, i+4, 6)
# Algorithm results
i = 17
grid.addWidget(header4, i, 0)
grid.addWidget(label13, i+1, 0)
grid.addWidget(self.leRs, i+1, 1)
grid.addWidget(label14, i+2, 0)
grid.addWidget(self.leXs, i+2, 1)
grid.addWidget(label15, i+3, 0)
grid.addWidget(self.leXm, i+3, 1)
grid.addWidget(label20, i+4, 0)
grid.addWidget(self.leRc, i+4, 1)
grid.addWidget(label16, i+1, 3)
grid.addWidget(self.leXr1, i+1, 4)
grid.addWidget(label17, i+2, 3)
grid.addWidget(self.leRr1, i+2, 4)
grid.addWidget(self.label18, i+3, 3)
grid.addWidget(self.leXr2, i+3, 4)
grid.addWidget(self.label19, i+4, 3)
grid.addWidget(self.leRr2, i+4, 4)
grid.addWidget(label21, i+1, 5)
grid.addWidget(self.leConv, i+1, 6)
grid.addWidget(label22, i+2, 5)
grid.addWidget(self.leErr, i+2, 6)
grid.addWidget(label23, i+3, 5)
grid.addWidget(self.leIter, i+3, 6)
grid.setAlignment(QtCore.Qt.AlignTop)
main_screen = QtGui.QWidget()
main_screen.setLayout(grid)
main_screen.setStatusTip('Ready')
self.setCentralWidget(main_screen)
# Event handlers
calc_button.clicked.connect(self.calculate)
self.plot_button.clicked.connect(self.plot_curves)
self.le1.editingFinished.connect(self.update_data)
self.le2.editingFinished.connect(self.update_data)
self.le3.editingFinished.connect(self.update_data)
self.le4.editingFinished.connect(self.update_data)
self.le5.editingFinished.connect(self.update_data)
self.le6.editingFinished.connect(self.update_data)
self.le7.editingFinished.connect(self.update_data)
self.le8.editingFinished.connect(self.update_data)
self.le9.editingFinished.connect(self.update_data)
self.le10.editingFinished.connect(self.update_data)
self.le11.editingFinished.connect(self.update_data)
self.le12.editingFinished.connect(self.update_data)
self.len_gen.editingFinished.connect(self.update_data)
self.lepop.editingFinished.connect(self.update_data)
self.len_r.editingFinished.connect(self.update_data)
self.len_e.editingFinished.connect(self.update_data)
self.lec_f.editingFinished.connect(self.update_data)
##########################
#TO DO - connects for combo boxes - combo_model and combo_algo (what signal to use?)
##########################
self.combo_algo.currentIndexChanged.connect(self.update_algo)
self.combo_model.currentIndexChanged.connect(self.update_model)
self.statusBar().showMessage('Ready')
# Calculate parameter estimates
def calculate(self):
self.statusBar().showMessage('Calculating...')
sf = (globals.motor_data["sync_speed"] - globals.motor_data["rated_speed"]) / globals.motor_data["sync_speed"]
if self.combo_model.currentIndex() == 0:
# Single cage
p = [sf, globals.motor_data["rated_eff"], globals.motor_data["rated_pf"], globals.motor_data["T_b"]]
[z, iter, err, conv] = nr_solver_sc(p, 0, globals.algo_data["k_x"], globals.algo_data["k_r"], globals.algo_data["max_iter"], globals.algo_data["conv_err"])
else:
# Double cage
p = [sf, globals.motor_data["rated_eff"], globals.motor_data["rated_pf"], globals.motor_data["T_b"], globals.motor_data["T_lr"], globals.motor_data["I_lr"] ]
if self.combo_algo.currentText() == "Newton-Raphson":
[z, iter, err, conv] = nr_solver(p, 0, globals.algo_data["k_x"], globals.algo_data["k_r"], globals.algo_data["max_iter"], globals.algo_data["conv_err"])
if self.combo_algo.currentText() == "Levenberg-Marquardt":
[z, iter, err, conv] = lm_solver(p, 0, globals.algo_data["k_x"], globals.algo_data["k_r"], 1e-7, 5.0, globals.algo_data["max_iter"], globals.algo_data["conv_err"])
if self.combo_algo.currentText() == "Damped Newton-Raphson":
[z, iter, err, conv] = dnr_solver(p, 0, globals.algo_data["k_x"], globals.algo_data["k_r"], 1e-7, globals.algo_data["max_iter"], globals.algo_data["conv_err"])
if self.combo_algo.currentText() == "Genetic Algorithm":
[z, iter, err, conv] = ga_solver(self, p, globals.algo_data["pop"], globals.algo_data["n_r"], globals.algo_data["n_e"], globals.algo_data["c_f"], globals.algo_data["n_gen"], globals.algo_data["conv_err"])
if self.combo_algo.currentText() == "Hybrid GA-NR":
[z, iter, err, conv] = hy_solver(self, "NR", p, globals.algo_data["pop"], globals.algo_data["n_r"], globals.algo_data["n_e"], globals.algo_data["c_f"], globals.algo_data["n_gen"], globals.algo_data["conv_err"])
if self.combo_algo.currentText() == "Hybrid GA-LM":
[z, iter, err, conv] = hy_solver(self, "LM", p, globals.algo_data["pop"], globals.algo_data["n_r"], globals.algo_data["n_e"], globals.algo_data["c_f"], globals.algo_data["n_gen"], globals.algo_data["conv_err"])
if self.combo_algo.currentText() == "Hybrid GA-DNR":
[z, iter, err, conv] = hy_solver(self, "DNR", p, globals.algo_data["pop"], globals.algo_data["n_r"], globals.algo_data["n_e"], globals.algo_data["c_f"], globals.algo_data["n_gen"], globals.algo_data["conv_err"])
self.leRs.setText(str(np.round(z[0],5)))
self.leXs.setText(str(np.round(z[1],5)))
self.leXm.setText(str(np.round(z[2],5)))
self.leRr1.setText(str(np.round(z[3],5)))
if self.combo_model.currentIndex() == 1:
self.leXr1.setText(str(np.round(z[4],5)))
self.leRr2.setText(str(np.round(z[5],5)))
self.leXr2.setText(str(np.round(z[6],5)))
self.leRc.setText(str(np.round(z[7],5)))
else:
self.leRc.setText(str(np.round(z[4],5)))
self.leXr1.setText(str(np.round(z[5],5)))
if conv == 1:
self.leConv.setText("Yes")
else:
QtGui.QMessageBox.warning(self, 'Warning', "Algorithm did not converge.", QtGui.QMessageBox.Ok)
self.leConv.setText("No")
self.leErr.setText(str(np.round(err,9)))
self.leIter.setText(str(iter))
# Only enable the plot button if the squared error is within the bounds of reason
if err < 1:
self.plot_button.setEnabled(1)
else:
self.plot_button.setDisabled(1)
self.statusBar().showMessage('Ready')
# Plot torque-speed and current-speed curves
def plot_curves(self):
sf = (globals.motor_data["sync_speed"] - globals.motor_data["rated_speed"]) / globals.motor_data["sync_speed"]
if self.combo_model.currentIndex() == 0:
# Single cage
x = [float(self.leRs.text()), float(self.leXs.text()) , float(self.leXm.text()), float(self.leRr1.text()), float(self.leRc.text()), float(self.leXr1.text())]
else:
# Double cage
x = [float(self.leRs.text()), float(self.leXs.text()) , float(self.leXm.text()), float(self.leRr1.text()), float(self.leXr1.text()), float(self.leRr2.text()), float(self.leXr2.text()), float(self.leRc.text())]
# Rated per-unit torque
T_rtd = globals.motor_data["rated_eff"] * globals.motor_data["rated_pf"] / (1 - sf)
Tm = np.zeros(1001)
Im = np.zeros(1001)
speed = np.zeros(1001)
speed[1000] = globals.motor_data["sync_speed"]
for n in range(0,1000):
speed[n] = float(n) / 1000 * globals.motor_data["sync_speed"]
i = 1 - float(n) / 1000
if self.combo_model.currentIndex() == 0:
# Single cage
[Ti, Ii] = get_torque_sc(i,x)
else:
# Double cage
[Ti, Ii] = get_torque(i,x)
Tm[n] = Ti / T_rtd # Convert torque to T/Tn value
Im[n] = np.abs(Ii)
# Plot torque-speed and current-speed curves
if plt.fignum_exists(1):
# Do nothing
QtGui.QMessageBox.warning(self, 'Warning', "A plot is already open. Please close to create a new plot.", QtGui.QMessageBox.Ok)
else:
plt.figure(1, facecolor='white')
plt.subplot(211)
plt.plot(speed, Tm)
plt.xlim([0, globals.motor_data["sync_speed"]])
plt.xlabel("Speed (rpm)")
plt.ylabel("Torque (T/Tn)")
plt.grid(color = '0.75', linestyle='--', linewidth=1)
plt.subplot(212)
plt.plot(speed, Im, 'r')
plt.xlim([0, globals.motor_data["sync_speed"]])
plt.xlabel("Speed (rpm)")
plt.ylabel("Current (pu)")
plt.grid(color = '0.75', linestyle='--', linewidth=1)
plt.show()
# Update global variables on change in data fields
def update_data(self):
globals.motor_data["description"] = str(self.le1.text())
globals.motor_data["sync_speed"] = float(self.le2.text())
globals.motor_data["rated_speed"] = float(self.le3.text())
globals.motor_data["rated_pf"] = float(self.le4.text())
globals.motor_data["rated_eff"] = float(self.le5.text())
globals.motor_data["T_b"] = float(self.le6.text())
globals.motor_data["T_lr" ] = float(self.le7.text())
globals.motor_data["I_lr"] = float(self.le8.text())
globals.algo_data["max_iter"] = int(self.le9.text())
globals.algo_data["conv_err"] = float(self.le10.text())
globals.algo_data["k_r"] = float(self.le11.text())
globals.algo_data["k_x"] = float(self.le12.text())
globals.algo_data["n_gen"] = int(self.len_gen.text())
globals.algo_data["pop"] = int(self.lepop.text())
globals.algo_data["n_r"] = int(self.len_r.text())
globals.algo_data["n_e"] = int(self.len_e.text())
globals.algo_data["c_f"] = float(self.lec_f.text())
# Update data in the main window
def update_window(self):
self.le1.setText(str(globals.motor_data["description"]))
self.le2.setText(str(globals.motor_data["sync_speed"]))
self.le3.setText(str(globals.motor_data["rated_speed"]))
self.le4.setText(str(globals.motor_data["rated_pf"]))
self.le5.setText(str(globals.motor_data["rated_eff"]))
self.le6.setText(str(globals.motor_data["T_b"]))
self.le7.setText(str(globals.motor_data["T_lr"]))
self.le8.setText(str(globals.motor_data["I_lr"]))
self.le9.setText(str(globals.algo_data["max_iter"]))
self.le10.setText(str(globals.algo_data["conv_err"]))
self.le11.setText(str(globals.algo_data["k_r"]))
self.le12.setText(str(globals.algo_data["k_x"]))
self.len_gen.setText(str(globals.algo_data["n_gen"]))
self.lepop.setText(str(globals.algo_data["pop"]))
self.len_r.setText(str(globals.algo_data["n_r"]))
self.len_e.setText(str(globals.algo_data["n_e"]))
self.lec_f.setText(str(globals.algo_data["c_f"]))
# Update the screen if the algorithm changes
def update_algo(self):
if (self.combo_algo.currentText() == "Genetic Algorithm") or (self.combo_algo.currentText() == "Hybrid GA-LM") or (self.combo_algo.currentText() == "Hybrid GA-NR") or (self.combo_algo.currentText() == "Hybrid GA-DNR"):
self.label11.setVisible(0)
self.le11.hide()
self.label12.setVisible(0)
self.le12.hide()
self.labeln_gen.setVisible(1)
self.labelpop.setVisible(1)
self.labeln_r.setVisible(1)
self.labeln_e.setVisible(1)
self.labelc_f.setVisible(1)
self.len_gen.show()
self.lepop.show()
self.len_r.show()
self.len_e.show()
self.lec_f.show()
else:
self.label11.setVisible(1)
self.le11.show()
self.label12.setVisible(1)
self.le12.show()
self.labeln_gen.setVisible(0)
self.labelpop.setVisible(0)
self.labeln_r.setVisible(0)
self.labeln_e.setVisible(0)
self.labelc_f.setVisible(0)
self.len_gen.hide()
self.lepop.hide()
self.len_r.hide()
self.len_e.hide()
self.lec_f.hide()
# Update if model combo box changed
def update_model(self):
if self.combo_model.currentIndex() == 0:
# Single cage
self.img1.setPixmap(QtGui.QPixmap('images\single_cage.png'))
self.combo_algo.setCurrentIndex(0)
self.combo_algo.clear()
self.combo_algo.addItem("Newton-Raphson")
self.label18.setVisible(0)
self.label19.setVisible(0)
self.leXr2.hide()
self.leRr2.hide()
else:
# Double cage
self.img1.setPixmap(QtGui.QPixmap('images\dbl_cage.png'))
self.combo_algo.addItem("Levenberg-Marquardt")
self.combo_algo.addItem("Damped Newton-Raphson")
self.combo_algo.addItem("Genetic Algorithm")
self.combo_algo.addItem("Hybrid GA-NR")
self.combo_algo.addItem("Hybrid GA-LM")
self.combo_algo.addItem("Hybrid GA-DNR")
self.label18.setVisible(1)
self.label19.setVisible(1)
self.leXr2.show()
self.leRr2.show()
# Open file and load motor data
def load_action(self):
# Open file dialog box
filename = QtGui.QFileDialog.getOpenFileName(self, "Open Moto File", "library/", "Moto files (*.mto)")
if filename:
saveload.load_file(filename)
self.update_window()
# Save motor data to file
def save_action(self):
# Open save file dialog box
filename = QtGui.QFileDialog.getSaveFileName(self, "Save Moto File", "library/", "Moto files (*.mto)")
if filename:
saveload.save_file(filename)
# Launch user manual
def user_manual(self):
os.system("start docs/moto_user_manual.pdf")
# About dialog box
def about_dialog(self):
QtGui.QMessageBox.about(self, "About Moto",
"""<b>Moto</b> is a parameter estimation tool that can be used to determine the equivalent circuit parameters of induction machines. The tool is intended for use in dynamic time-domain simulations such as stability and motor starting studies.
<p>
Version: <b>v0.2<b><P>
<p>
Website: <a href="http://www.sigmapower.com.au/moto.html">www.sigmapower.com.au/moto.html</a>
<p> </p>
<p><img src="images/Sigma_Power.png"></p>
<p>© 2014 Sigma Power Engineering Pty Ltd</p>
<p>All rights reserved.</p>
""")
# Centre application window on screen
def centre(self):
qr = self.frameGeometry()
cp = QtGui.QDesktopWidget().availableGeometry().center()
qr.moveCenter(cp)
self.move(qr.topLeft())
def main():
app = QtGui.QApplication(sys.argv)
w = Window()
w.show()
sys.exit(app.exec_())
if __name__ == '__main__':
main()