#
# ISC License
#
# Copyright (c) 2023, Autonomous Vehicle Systems Lab, University of Colorado Boulder
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
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# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
#
#
#
# Thermal Sensor Faults Test
#
# Purpose: Test the proper function of the faulty behaviors of the tempMeasurement module.
# Results are compared to simple truth values.
# To test spiking, percent of spike values compared with expected.
# Creation Date: Feb. 9, 2023
#
import os
import numpy as np
import pytest
from Basilisk.architecture import messaging
from Basilisk.architecture import astroConstants
from Basilisk.simulation import sensorThermal, tempMeasurement
from Basilisk.utilities import SimulationBaseClass
from Basilisk.utilities import macros
from Basilisk.utilities import unitTestSupport
path = os.path.dirname(os.path.abspath(__file__))
# The following 'parametrize' function decorator provides the parameters and expected results for each
# of the multiple test runs for this test.
# Need RNGSeed 464374481
[docs]
@pytest.mark.parametrize(
"tempFault",
[
"TEMP_FAULT_NOMINAL",
"TEMP_FAULT_STUCK_CURRENT",
"TEMP_FAULT_STUCK_VALUE",
"TEMP_FAULT_SPIKING",
"BIASED",
"GAUSS_MARKOV"
])
# provide a unique test method name, starting with test_
def test_sensorThermalFault(tempFault):
'''This function is called by the py.test environment.'''
# each test method requires a single assert method to be called
[testResults, testMessage] = run(tempFault)
assert testResults < 1, testMessage
__tracebackhide__ = True
def run(tempFault):
testFailCount = 0 # zero unit test result counter
testMessages = [] # create empty list to store test log messages
# Create simulation variable names
unitTaskName = "unitTask" # arbitrary name (don't change)
unitProcessName = "TestProcess" # arbitrary name (don't change)
# Create a sim module as an empty container
unitTestSim = SimulationBaseClass.SimBaseClass()
# set the simulation time variable used later on
simulationTime = macros.sec2nano(100.)
#
# create the simulation process
#
testProcessRate = macros.sec2nano(1.0) # update process rate update time
testProc = unitTestSim.CreateNewProcess(unitProcessName)
testProc.addTask(unitTestSim.CreateNewTask(unitTaskName, testProcessRate))
#
# set up the simulation tasks/objects
#
# set device status message
sensorStatusMsgPayload = messaging.DeviceStatusMsgPayload()
sensorStatusMsgPayload.deviceStatus = 1
sensorStatusMsg = messaging.DeviceStatusMsg().write(sensorStatusMsgPayload)
# set the spacecraft message
scStateMsgPayload = messaging.SCStatesMsgPayload()
scStateMsgPayload.r_BN_N = [6378*1000., 0., 0.]
scStateMsgPayload.sigma_BN = [0., 0., 0.]
scStateMsg = messaging.SCStatesMsg().write(scStateMsgPayload)
# set the sun message
sunMsgPayload = messaging.SpicePlanetStateMsgPayload()
sunMsgPayload.PositionVector = [astroConstants.AU*1000., 0., 0.]
sunMsg = messaging.SpicePlanetStateMsg().write(sunMsgPayload)
#
# set up the truth value temperature modeling
#
sensorThermalModel = sensorThermal.SensorThermal()
sensorThermalModel.ModelTag = 'sensorThermalModel'
sensorThermalModel.nHat_B = [0, 0, 1]
sensorThermalModel.sensorArea = 1.0 # m^2
sensorThermalModel.sensorAbsorptivity = 0.25
sensorThermalModel.sensorEmissivity = 0.34
sensorThermalModel.sensorMass = 2.0 # kg
sensorThermalModel.sensorSpecificHeat = 890
sensorThermalModel.sensorPowerDraw = 30.0 # W
sensorThermalModel.T_0 = 0 # [ºC]
sensorThermalModel.sunInMsg.subscribeTo(sunMsg)
sensorThermalModel.stateInMsg.subscribeTo(scStateMsg)
sensorThermalModel.sensorStatusInMsg.subscribeTo(sensorStatusMsg)
unitTestSim.AddModelToTask(unitTaskName, sensorThermalModel)
#
# set up the tempMeasurement module
#
tempMeasurementModel = tempMeasurement.TempMeasurement()
tempMeasurementModel.tempInMsg.subscribeTo(sensorThermalModel.temperatureOutMsg)
unitTestSim.AddModelToTask(unitTaskName, tempMeasurementModel)
#
# log data
#
# log the RW temperature
tempLog = tempMeasurementModel.tempOutMsg.recorder()
unitTestSim.AddModelToTask(unitTaskName, tempLog)
#
# initialize Simulation
#
# Truth Values
if tempFault == "TEMP_FAULT_NOMINAL":
truthValue = -4.251289338192501
unitTestSim.InitializeSimulation()
unitTestSim.ConfigureStopTime(simulationTime)
unitTestSim.ExecuteSimulation()
elif tempFault == "TEMP_FAULT_STUCK_CURRENT":
truthValue = -2.1722164230619447
unitTestSim.InitializeSimulation()
unitTestSim.ConfigureStopTime(round(simulationTime/2.0))
unitTestSim.ExecuteSimulation()
tempMeasurementModel.faultState = tempMeasurement.TEMP_FAULT_STUCK_CURRENT
unitTestSim.ConfigureStopTime(simulationTime)
unitTestSim.ExecuteSimulation()
elif tempFault == "TEMP_FAULT_STUCK_VALUE":
truthValue = 10.0
tempMeasurementModel.stuckValue = 10.0
unitTestSim.InitializeSimulation()
unitTestSim.ConfigureStopTime(round(simulationTime/2.0))
unitTestSim.ExecuteSimulation()
tempMeasurementModel.faultState = tempMeasurement.TEMP_FAULT_STUCK_VALUE
unitTestSim.ConfigureStopTime(simulationTime)
unitTestSim.ExecuteSimulation()
elif tempFault == "TEMP_FAULT_SPIKING":
tempMeasurementModel.faultState = tempMeasurement.TEMP_FAULT_SPIKING
truthValue = 0.1
unitTestSim.InitializeSimulation()
unitTestSim.ConfigureStopTime(simulationTime)
unitTestSim.ExecuteSimulation()
nominals = np.array([ 0., -0.04439869, -0.08875756, -0.13307667,
-0.17735608, -0.22159584, -0.265796, -0.30995662, -0.35407775,
-0.39815946, -0.44220178, -0.48620479, -0.53016852, -0.57409304,
-0.6179784, -0.66182465, -0.70563184, -0.74940004, -0.79312929,
-0.83681965, -0.88047117, -0.9240839, -0.9676579, -1.01119321,
-1.0546899, -1.09814802, -1.14156761, -1.18494873, -1.22829144,
-1.27159578, -1.31486181, -1.35808958, -1.40127914, -1.44443055,
-1.48754385, -1.5306191, -1.57365634, -1.61665564, -1.65961704,
-1.7025406, -1.74542636, -1.78827437, -1.83108469, -1.87385737,
-1.91659246, -1.95929001, -2.00195007, -2.04457269, -2.08715792,
-2.12970582, -2.17221642, -2.21468979, -2.25712597, -2.29952502,
-2.34188697, -2.38421189, -2.42649982, -2.46875082, -2.51096492,
-2.55314219, -2.59528266, -2.6373864, -2.67945344, -2.72148384,
-2.76347765, -2.80543491, -2.84735568, -2.88924, -2.93108792,
-2.9728995 , -3.01467477, -3.05641378, -3.0981166, -3.13978325,
-3.1814138, -3.22300829, -3.26456677, -3.30608928, -3.34757587,
-3.38902659, -3.43044149, -3.47182062, -3.51316402, -3.55447174,
-3.59574383, -3.63698033, -3.67818129, -3.71934677, -3.76047679,
-3.80157142, -3.8426307, -3.88365467, -3.92464338, -3.96559689,
-4.00651522, -4.04739844, -4.08824658, -4.1290597, -4.16983783,
-4.21058103, -4.25128934])
testValue = 0
sensorTemp = np.array(tempLog.temperature)
for ii in range(len(nominals)):
if abs(nominals[ii]) > 0.0001:
if abs(nominals[ii] - sensorTemp[ii]) > 1e-6:
testValue = testValue + 1
else:
if abs(sensorTemp[ii]) > 1e-6:
testValue = testValue + 1
testValue = testValue/len(nominals)
elif tempFault == "BIASED":
biasVal = 1.0
tempMeasurementModel.senBias = biasVal
truthValue = -3.251289338192501
unitTestSim.InitializeSimulation()
unitTestSim.ConfigureStopTime(simulationTime)
unitTestSim.ExecuteSimulation()
elif tempFault == "GAUSS_MARKOV":
[testResults, testMessage] = gauss_markov_test()
return [testResults, testMessage]
else:
NotImplementedError("Fault type specified does not exist.")
sensorTemp = np.array(tempLog.temperature)
print(sensorTemp)
#
# compare the module results to the true values
#
if tempFault == "TEMP_FAULT_SPIKING":
if not unitTestSupport.isDoubleEqualRelative(testValue, truthValue, 5E-1): # only 101 values so need this to be relatively relaxed (within 50%)
testFailCount+= 1
elif not unitTestSupport.isDoubleEqualRelative(sensorTemp[-1], truthValue, 1E-12):
testFailCount += 1
return [testFailCount, ''.join(testMessages)]
# each test method requires a single assert method to be called
# this check below just makes sure no sub-test failures were found
[docs]
def test_gauss_markov_properties():
"""
Test the statistical properties of the Gauss-Markov noise model in tempMeasurement.
Tests:
1. Error bounds are not violated too often (<0.3% of samples)
2. Error bounds are actually being used (at least one >80% excursion)
"""
[testResults, testMessage] = gauss_markov_test()
assert testResults < 1, testMessage
def gauss_markov_test():
testFailCount = 0
testMessages = []
# Create simulation variable names
unitTaskName = "unitTask"
unitProcessName = "TestProcess"
# Create a sim module as an empty container
unitTestSim = SimulationBaseClass.SimBaseClass()
testProcessRate = macros.sec2nano(1.0)
testProc = unitTestSim.CreateNewProcess(unitProcessName)
testProc.addTask(unitTestSim.CreateNewTask(unitTaskName, testProcessRate))
# Set up the thermal sensor model
sensorThermalModel = sensorThermal.SensorThermal()
sensorThermalModel.ModelTag = 'sensorThermalModel'
sensorThermalModel.nHat_B = [0, 0, 1]
sensorThermalModel.sensorArea = 1.0
sensorThermalModel.sensorAbsorptivity = 0.25
sensorThermalModel.sensorEmissivity = 0.34
sensorThermalModel.sensorMass = 2.0
sensorThermalModel.sensorSpecificHeat = 890
sensorThermalModel.sensorPowerDraw = 30.0
sensorThermalModel.T_0 = 0
# Set up required messages
scStateMsg = messaging.SCStatesMsg().write(messaging.SCStatesMsgPayload())
sunMsg = messaging.SpicePlanetStateMsg().write(messaging.SpicePlanetStateMsgPayload())
deviceStatusMsg = messaging.DeviceStatusMsg().write(messaging.DeviceStatusMsgPayload())
sensorThermalModel.stateInMsg.subscribeTo(scStateMsg)
sensorThermalModel.sunInMsg.subscribeTo(sunMsg)
sensorThermalModel.sensorStatusInMsg.subscribeTo(deviceStatusMsg)
unitTestSim.AddModelToTask(unitTaskName, sensorThermalModel)
# Set up tempMeasurement module
tempMeasurementModel = tempMeasurement.TempMeasurement()
tempMeasurementModel.tempInMsg.subscribeTo(sensorThermalModel.temperatureOutMsg)
# Configure noise parameters
tempSigma = 1.0 # Start with larger sigma
# Set up Gauss-Markov noise with more conservative bounds
tempMeasurementModel.faultState = tempMeasurement.TEMP_FAULT_GAUSS_MARKOV
tempMeasurementModel.senNoiseStd = tempSigma
tempMeasurementModel.walkBounds = 20.0
# Set RNG seed for repeatability
tempMeasurementModel.RNGSeed = 464374481
unitTestSim.AddModelToTask(unitTaskName, tempMeasurementModel)
# Setup message logging
tempLog = tempMeasurementModel.tempOutMsg.recorder()
unitTestSim.AddModelToTask(unitTaskName, tempLog)
# Run simulation with more samples
unitTestSim.InitializeSimulation()
simulationTime = macros.sec2nano(100.0)
unitTestSim.ConfigureStopTime(simulationTime)
unitTestSim.ExecuteSimulation()
# Extract temperature data for analysis
tempData = np.array(tempLog.temperature)
# Print debug info
print(f"Number of samples: {len(tempData)}")
print(f"Mean error: {np.mean(np.abs(tempData - sensorThermalModel.T_0))}")
print(f"Max error: {np.max(np.abs(tempData - sensorThermalModel.T_0))}")
print(f"Bound: {tempMeasurementModel.walkBounds}")
# Test 1: Statistical Checks
countAllow = len(tempData) * 0.3/100. # Allow 0.3% violations
tempDiffCount = 0
for temp in tempData:
if abs(temp - sensorThermalModel.T_0) > tempMeasurementModel.walkBounds:
tempDiffCount += 1
if tempDiffCount > countAllow:
testFailCount += 1
testMessages.append(f"FAILED: Too many temperature errors ({tempDiffCount} > {countAllow})")
# Test 2: Error Bound Usage Check - similar to simpleNav approach
sigmaThreshold = 0.8
hasLargeError = False
for temp in tempData:
if abs(temp - sensorThermalModel.T_0) > tempMeasurementModel.walkBounds * sigmaThreshold:
hasLargeError = True
break
if not hasLargeError:
testFailCount += 1
testMessages.append("FAILED: Temperature errors too small")
if testFailCount == 0:
print("PASSED: Gauss-Markov noise tests successful")
return [testFailCount, ''.join(testMessages)]
if __name__ == "__main__":
run("TEMP_FAULT_NOMINAL")