Estimation of the temperature of stator winding bar



In [1]:

    
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline 

plt.style.use('ggplot')



In [2]:

    
# read in the test data (voltages of thermocouples)
# header u1-u10 thermocouples along the winding bar; 
# u11 - a thermocouple on a bar emersed in water
# u12 - a thermocouple in the water 
header = ['t', 'u1', 'u2', 'u3', 'u4', 'u5', 'u6', 'u7', 'u8', 'u9', 'u10', 'u11', 'u12']
df = pd.read_csv('pomiary.txt', sep='\t', header=None, names=header)
df.head()



In [3]:

    
# definition of thermocouple function
def getTemp(u):
    # coefficient a [degC/mV]
    a = 24
    return a*u + 19



In [4]:

    
t = df['t']
dfT = df.iloc[:,1:13].apply(getTemp)
header = ['T1', 'T2', 'T3', 'T4', 'T5', 'T6', 'T7', 'T8', 'T9', 'T10', 'T11', 'T12']
dfT.columns = header
dfT.head()



In [5]:

    
plt.figure(figsize=(10,5))
for k in dfT.columns:
    plt.plot(t, dfT[k], label=k)
plt.xlabel('Time [min]')
plt.ylabel('Temperature [degC]')
plt.legend();



In [6]:

    
# max temperatures by thermocouples
dfT.max()









    Out[6]:





T1     34.60
T2     52.36
T3     63.16
T4     71.08
T5     73.24
T6     73.24
T7     70.36
T8     60.52
T9     50.20
T10    34.12
T11    24.04
T12    20.92
dtype: float64



In [7]:

    
# max winding temperature
max(dfT.max())









    Out[7]:





73.239999999999995



In [ ]:

	t	u1	u2	u3	u4	u5	u6	u7	u8	u9	u10	u11	u12
0	0	0.09	0.12	0.12	0.13	0.13	0.13	0.15	0.15	0.15	0.13	0.02	0.01
1	2	0.24	0.35	0.37	0.39	0.38	0.39	0.40	0.39	0.36	0.25	0.16	0.01
2	4	0.32	0.50	0.56	0.60	0.60	0.60	0.62	0.57	0.50	0.32	0.18	0.01
3	6	0.38	0.64	0.74	0.80	0.80	0.81	0.81	0.73	0.62	0.37	0.19	0.01
4	8	0.42	0.74	0.88	0.98	0.99	0.99	0.99	0.87	0.72	0.42	0.20	0.01

	T1	T2	T3	T4	T5	T6	T7	T8	T9	T10	T11	T12
0	21.16	21.88	21.88	22.12	22.12	22.12	22.60	22.60	22.60	22.12	19.48	19.24
1	24.76	27.40	27.88	28.36	28.12	28.36	28.60	28.36	27.64	25.00	22.84	19.24
2	26.68	31.00	32.44	33.40	33.40	33.40	33.88	32.68	31.00	26.68	23.32	19.24
3	28.12	34.36	36.76	38.20	38.20	38.44	38.44	36.52	33.88	27.88	23.56	19.24
4	29.08	36.76	40.12	42.52	42.76	42.76	42.76	39.88	36.28	29.08	23.80	19.24