تحديد كثافة الغازات من نتائج قياس الضغط والحرارة مع اجهزة استشعار اردوينو

#include <SFE_BMP180.h> SFE_BMP180 pressure; double T,P; void setup() { Serial.begin(9600); pressure.begin(); } void loop() { P = getPressure(); Serial.println(P+0.5, 2); Serial.println(T+0.54, 2); delay(1000); } double getPressure(){ char status; status = pressure.startTemperature(); if (status != 0){ delay(status); //    status = pressure.getTemperature(T); if (status != 0){ status = pressure.startPressure(3); if (status != 0){ delay(status); //    status = pressure.getPressure(P,T); if (status != 0){ return(P); } } } } } 

 import numpy as np import matplotlib.pyplot as plt import serial from drawnow import drawnow import datetime, time from pykalman import KalmanFilter #      transition_matrix = [[1, 1, 0, 0], [0, 1, 0, 0], [0, 0, 1, 1], [0, 0, 0, 1]] observation_matrix = [[1, 0, 0, 0], [0, 0, 1, 0]] #     initial_state_mean = [101000, 0, 28, 0] #    : #   R, [/(*)] R = 8.314459848 #   M, [/] M = 29.04 # k = M/R, [/(*)] k = M / R # , [K] K = 273.16 # () , [] Pn = 101325 #   #    str_m = input("  : ") m = eval(str_m) #    mw = 16 #    ser = serial.Serial() ser.baudrate = 9600 port_num = input("   : ") ser.port = 'COM' + port_num ser #   try: ser.open() ser.is_open print(" : " + ser.portstr) except serial.SerialException: print("   : " + ser.portstr) raise SystemExit(1) #  l1 = [] #   1-  l2 = [] #   2-  t1 = [] #    lw1 = [] #    1-  lw2 = [] #    2-  n = [] #     nw = [] #      l1K = [] #    1-  l2K = [] #    2-  ro = [] #     #      filename = 'count.txt' in_file = open(filename,"r") count = in_file.read() count_v = eval(count) + 1 in_file.close() in_file = open(filename,"w") count = str(count_v) in_file.write(count) in_file.close() filename = count + '_' + filename out_file = open(filename,"w") #      print("\n:\n") print("n -  , ;") print("P - , ;") print("Pf -   P, ;") print("T - , . ;") print("Tf -   T, . ;") print("ro -  , /^3;") print("\n   \n") print('{0}{1}{2}{3}{4}{5}\n'.format('n'.rjust(3),'P'.rjust(10),'Pf'.rjust(10), 'T'.rjust(10),'Tf'.rjust(10),'ro'.rjust(10))) #     #  #   i = 0 while i < m: n.append(i) nw.append(n[i]) if i >= mw: nw.pop(0) ser.flushInput() #flush input buffer, discarding all its contents line1 = ser.readline().decode('utf-8')[:-1] line2 = ser.readline().decode('utf-8')[:-1] t1.append(time.time()) if line1: l = eval(line1) #l = np.random.normal(l,100.0) l1.append(l) lw1.append(l1[i]) if i >= mw: lw1.pop(0) if line2: l = eval(line2) #l = np.random.normal(l,1.5) l2.append(l) lw2.append(l2[i]) if i >= mw: lw2.pop(0) #------------------------- initial_state_mean = [l1[i],0,l2[i],0] kf1 = KalmanFilter(transition_matrices = transition_matrix, observation_matrices = observation_matrix, initial_state_mean = initial_state_mean) if i == 0: measurements = np.array( [ [l1[i], l2[i]], [initial_state_mean[0], initial_state_mean[2]] ] ) measurements = np.array( [ [l1[i], l2[i]], [l1[i-1], l2[i-1]] ] ) kf1 = kf1.em(measurements, n_iter=2) (smoothed_state_means, smoothed_state_covariances) = kf1.smooth(measurements) l1K.append(smoothed_state_means[0, 0]) l2K.append(smoothed_state_means[0, 2]) #     #ro.append( k * l1K[i]/( l2K[i] + K) ) # ,     ro.append( (k * l1K[i]/( l2K[i] + K)) * (Pn*(l2K[i]+K)/K/l1K[i]) ) # ,     #ro.append( (k * l1K[i]/( l2K[i] + K)) * (Pn*(l2K[i]+K)/(K+20)/l1K[i]) ) print('{0:3d} {1:10.3f} {2:10.3f} {3:10.3f} {4:10.3f} {5:10.3f}'. format(n[i],l1[i],l1K[i],l2[i],l2K[i],ro[i])) i += 1 ser.close() time_tm = t1[m - 1] - t1[0] print("\n  : {0:.3f}, c".format(time_tm)) Ts = time_tm / (m - 1) print("\n  : {0:.6f}, c".format(Ts)) #    print("\n    {}\n".format(filename)) for i in np.arange(0,len(n),1): out_file.write('{0:3d} {1:10.3f} {2:10.3f} {3:10.3f} {4:10.3f} {5:10.3f}\n'. format(n[i],l1[i],l1K[i],l2[i],l2K[i],ro[i])) #    out_file.close() now = datetime.datetime.now() #    #  plt.figure('') plt.plot( n, l1, "b-", n, l1K, "r-") plt.ylabel(r'$, $') plt.xlabel(r'$ \ $' + '; (  : {:.6f}, c)'.format(Ts)) plt.title("BMP180\n(" + now.strftime("%d-%m-%Y %H:%M") + ")") plt.grid(True) plt.figure('') plt.plot( n, l2, "b-", n, l2K, "r-") plt.ylabel(r'$, \degree $') plt.xlabel(r'$ \ $' + '; (  : {:.6f}, c)'.format(Ts)) plt.title("BMP180\n(" + now.strftime("%d-%m-%Y %H:%M") + ")") plt.grid(True) plt.figure(' ') plt.plot( n, ro, "r-") plt.ylabel(r'$ , /^3$') plt.xlabel(r'$ \ $' + '; (  : {:.6f}, c)'.format(Ts)) plt.title("BMP180\n(" + now.strftime("%d-%m-%Y %H:%M") + ")") plt.grid(True) plt.show() 

   : 33    : 6  : COM6 : n -  , ; P - , ; Pf -   P, ; T - , . ; Tf -   T, . ; ro -  , /^3;     n P Pf T Tf ro 0 101141.000 101141.000 28.120 28.120 1295.574 1 101140.000 101140.099 28.190 28.183 1295.574 2 101140.000 101140.000 28.130 28.136 1295.574 3 101141.000 101140.901 28.100 28.103 1295.574 4 101140.000 101140.099 28.100 28.100 1295.574 5 101141.000 101140.901 28.110 28.109 1295.574 6 101141.000 101141.000 28.100 28.101 1295.574 7 101139.000 101139.217 28.100 28.100 1295.574 8 101138.000 101138.099 28.090 28.091 1295.574 9 101137.000 101137.099 28.100 28.099 1295.574 10 101151.000 101149.028 28.100 28.100 1295.574 11 101136.000 101138.117 28.110 28.109 1295.574 12 101143.000 101142.052 28.110 28.110 1295.574 13 101139.000 101139.500 28.100 28.101 1295.574 14 101150.000 101148.463 28.110 28.109 1295.574 15 101154.000 101153.500 28.120 28.119 1295.574 16 101151.000 101151.354 28.110 28.111 1295.574 17 101141.000 101142.391 28.130 28.127 1295.574 18 101141.000 101141.000 28.120 28.121 1295.574 19 101142.000 101141.901 28.110 28.111 1295.574 20 101141.000 101141.099 28.120 28.119 1295.574 21 101142.000 101141.901 28.110 28.111 1295.574 22 101146.000 101145.500 28.120 28.119 1295.574 23 101144.000 101144.217 28.130 28.129 1295.574 24 101142.000 101142.217 28.130 28.130 1295.574 25 101142.000 101142.000 28.140 28.139 1295.574 26 101142.000 101142.000 28.130 28.131 1295.574 27 101146.000 101145.500 28.150 28.147 1295.574 28 101142.000 101142.500 28.190 28.185 1295.574 29 101146.000 101145.500 28.230 28.225 1295.574 30 101146.000 101146.000 28.230 28.230 1295.574 31 101146.000 101146.000 28.220 28.221 1295.574 32 101150.000 101149.500 28.210 28.211 1295.574   : 6.464, c   : 0.201998, c     68_count.txt