SQ1 = 2000; SQ2 = 200 # Sampling quantity
T0 = 25; T1 = 173 # Temperature
T2 = 198; T3 = 230
T4 = 257; T5 = 150
# 距开始处的 Distance
D0 = 0
# 炉前
D1 = 25
# 小温区1~5
D2 = 197.5
# 小温区5与6之间
D3 = 202.5
# 小温区6
D4 = 233
# 小温区6与7之间
D5 = 238
# 小温区7
D6 = 268.5
# 小温区7与8之间
D7 = 273.5
# 小温区8~9
D8 = 339.5
# 小温区9与10之间 & 小温区10
D9 = 375
# 小温区10后
D10 = 800
# 冷却至室温
SD = 78 # Speed (cm/min)
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
from matplotlib import rcParams
import warnings
config = {
"font.family": ["Times New Roman","SimHei"],
"mathtext.fontset": 'stix', # matplotlib渲染数学字体时使用的字体，和Times New Roman差别不大
"font.serif": ['Times New Roman','SimHei'], # 黑体
'axes.unicode_minus': False # 处理负号，即-号
}
rcParams.update(config)
def F1(x,a,b,c):
return a*np.exp(b*x)+c
def L56(x):
return (T2-T1)/(D3-D2)*(x-D2)+T1
def L67(x):
return (T3-T2)/(D5-D4)*(x-D4)+T2
def L78(x):
return (T4-T3)/(D7-D6)*(x-D6)+T3
def L10(x):
return (T5-T4)/(D9-D8)*(x-D8)+T4
def F2(x,a,b,c,x0):
return a*np.exp(-b*(x-x0))+c
x1 = [D0,20,D1]
y1 = [T0,99,T1]
pars1,_= curve_fit(F1,x1,y1,maxfev=10000)
x2 = [D9,425,525,D10]
y2 = [T5,100,50,T0]
guess2 = [1,0.01,25,D9+200]
pars2,_= curve_fit(F2,x2,y2,p0=guess2,maxfev=10000)
X1 = np.linspace(D0,D1,SQ1)
Y1 = F1(X1,*pars1)
X2 = np.linspace(D1,D2,SQ2)
Y2 = [T1]*SQ2
X3 = np.linspace(D2,D3,SQ2)
Y3 = L56(X3)
X4 = np.linspace(D3,D4,SQ2)
Y4 = [T2]*SQ2
X5 = np.linspace(D4,D5,SQ2)
Y5 = L67(X5)
X6 = np.linspace(D5,D6,SQ2)
Y6 = [T3]*SQ2
X7 = np.linspace(D6,D7,SQ2)
Y7 = L78(X7)
X8 = np.linspace(D7,D8,SQ2)
Y8 = [T4]*SQ2
X9 = np.linspace(D8,D9,SQ2)
Y9 = L10(X9)
X10 = np.linspace(D9,D10,SQ1)
Y10 = F2(X10,*pars2)
Xs = [X1,X2,X3,X4,X5,X6,X7,X8,X9,X10]
Ys = [Y1,Y2,Y3,Y4,Y5,Y6,Y7,Y8,Y9,Y10]
# plt.figure(figsize=(4,10))
for i, (X, Y) in enumerate(zip(Xs, Ys)):
if i == 0:
plt.plot(X, Y, color='r', label='环境温度')
else:
plt.plot(X, Y, color='r')
plt.plot([i for i in np.linspace(0,800,200)],[25]*200,color='b',ls='--',label='室温')
plt.legend()
plt.xlabel('距离/cm')
plt.ylabel('温度/℃')
plt.title('环境温度在回焊炉空间上的分布')
plt.axis([0,900,0,300])
plt.show()
