def plot_healthy_and_damaged_at_operating_condition():
fig,axs = plt.subplots(2,2)
response_list = []
for oc in enumerate([5,10]):
for health in enumerate([0, 0.5
]):
# oc = (oc[0],10)
# health = (health[0],0)
stiffness_reduction = np.array([health[1]])
obj = g_maps.Chen2011(theta, stiffness_reduction)
t = obj.constants["t_range"][obj.samples_before_fault:]
#axs[oc[0],health[0]].text(0,0,str(stiffness_reduction[0])
y = obj.get_y(np.array([oc[1]]))
response_list.append(y)
max_oc_0 = np.max([np.max(response_list[0]), np.max(response_list[1])])
min_oc_0 = np.min([np.min(response_list[0]), np.min(response_list[1])])
max_oc_1 = np.max([np.max(response_list[2]), np.max(response_list[3])])
min_oc_1 = np.min([np.min(response_list[2]), np.min(response_list[3])])
count = 0
for oc in enumerate(["5 Nm","10 Nm"]):
for health in enumerate(["Healthy","Damaged"]):
axs[oc[0], health[0]].plot(t,response_list[count],"k")
axs[oc[0], health[0]].set_xlabel("time [s]")
axs[oc[0], health[0]].set_ylabel(r"ring acceleration [m/$s^2$]")
axs[oc[0], health[0]].set_title(health[1] + " " + oc[1])
if oc[0]>0:
axs[oc[0], health[0]].set_ylim(min_oc_1,max_oc_1)
axs[oc[0], health[0]].set_ylabel(r"acceleration [m/$s^2$]")
else:
axs[oc[0], health[0]].set_ylim(min_oc_0,max_oc_0)
axs[oc[0], health[0]].set_ylabel(r"acceleration [m/$s^2$]")
count+=1
# Plot the time varying stiffness
# tvms = np.array([obj.tvms(ti, stiffness_reduction) for ti in t])
#
# plt.plot(t,tvms, label = str(stiff_red) + " N/m reduction")
# plt.legend(loc= "lower right")
#plt.subplot_tool()
plt.subplots_adjust(wspace=0.4, hspace=0.53)
save_plot_to_directory("chen_2011_response")
return
def plot_healthy_and_damged_TVMS():
plt.figure()
plt.xlabel("Time [s]")
plt.ylabel("Meshing stiffness [N/m]")
for stiff_red in np.linspace(0,1,4):
stiffness_reduction = np.array([stiff_red])*0.5
obj = g_maps.Chen2011(theta, stiffness_reduction,cycles_before_fault=2)
t = np.linspace(0,obj.constants["t_range"][-1]*2,1000)
# Plot the time varying stiffness
k_at_first_transition_end = obj.smooth_square(obj.first_transition_end_time) - obj.x*1e8
k_at_second_transition_start = obj.smooth_square(obj.second_transition_start_time) - obj.x*1e8
first_transition_gradient = (obj.k_at_first_transition_start - k_at_first_transition_end) /obj.transition_time
second_transition_gradient = (k_at_second_transition_start - obj.k_at_second_transition_end) / obj.transition_time
tvms = np.array([obj.tvms(ti, first_transition_gradient,second_transition_gradient,k_at_second_transition_start) for ti in t])
plt.plot(t,tvms, label = str(np.round(stiffness_reduction[0],3)) + "e8 N/m reduction")
plt.legend(loc= "lower right")
save_plot_to_directory("TVMS_20201119")
return
import numpy as np
t_start = time.time()
# Define the true model parameters
theta_real = np.array([1.116, 6.405]) # theta = [m_ring, I_ring, k1 ,k2] # I is adjusted for 1e-3
phi_real = np.array([np.sin(np.deg2rad(20))]) # Measurement model transfer function is multiplication by constant.
# Fraction of pressure angle
# Define healthy state of health
x_real_d0 = np.array([0]) # 0 N/m mean stiffness reduction (healthy)
# Define the real measurement model (Independent of health state)
h_real = h_maps.Constant(phi_real)
# Define the real physics based model g for healthy and damaged states
g_real_d0 = g_maps.Chen2011(theta_real, x_real_d0)
# Define the system
sys_real_d0 = sys_model.System(g_real_d0, h_real)
# Define the operating conditions where measurements were made
c = [np.array([i]) for i in np.linspace(10, 1, 4) * 1] # c is applied moment 10Nm-100Nm
#c = [np.array([i]) for i in [5]] # c is applied moment 10Nm-100Nm
# Get the Measured data under healthy conditions
noise = {"sd": 0.1} # Small noise
z_real_d0 = sys_real_d0.simulate(c, noise=noise, plot=True) # INFO: Toggle if plot
#plt.title("Measured data at healthy condition")
#plt.ylabel("Acceleration of ring gear")
#plt.show()
import matplotlib.pyplot as plt
import src.models.h_mappings as h_maps
import src.models.g_mappings as g_maps
import src.models.system_modeller as sys_model
import numpy as np
#1 get tvms with a fault
# if t_fault_start<t<t_fault_end
# use a completely different profile
# Just make sure your synchronize the periods
obj = g_maps.Chen2011(np.array([22]), np.array([33]))
opperating_condition = 12
t = obj.constants["t_range"]
frequency = 10 #Hz
k = np.array([obj.tvms(t_inc, 500) for t_inc in t])
plt.figure()
plt.plot(t, k)
# y = obj.get_y(opperating_condition)
# Plot the time varying stiffness
# Plot the lumped mass response. First transients and then the steady state response
# t = obj.constants["t_range"]
#
# plt.figure()
# plt.plot(t, y)
# plt.xlabel("time [s]")
# plt.ylabel(r"Measured ring gear acceleration [$m/s^2$]")