129 lines
5.3 KiB
Python
129 lines
5.3 KiB
Python
import matplotlib.pyplot as plt
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import math
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from inputs.Inputs import AveragingInput, PhysicalInput
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from inputs.Pressure_Sensors import PressureTransmitter
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from inputs.Temperature_Sensors import RTD, Thermocouple
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from inputs.Force_Sensors import LoadCell
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from inputs.Flow_Speed_Sensors import TurbineFlowMeter
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from inputs.Fluid_Lookup import DensityLookup
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from inputs.Math_Functions import Integration
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from System_Uncertainty_Monte_Carlo import SystemUncertaintyMonteCarlo
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from typing import List, Tuple
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from typing import TYPE_CHECKING
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if TYPE_CHECKING:
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from inputs.Inputs import Input, CombinedInput
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def plot_sensitivity_analysis(gain_values: list, stdev_values: list, normal_stdev: float, sensor_name: str):
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# Plotting the standard deviation values against the gain settings
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plt.figure(figsize=(10, 6))
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plt.plot(gain_values, stdev_values, marker='o', linestyle='-', color='b')
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plt.axhline(y=normal_stdev, color='r', linestyle='--', label='Normal System STD Dev')
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plt.title(f'Sensitivity Analysis for Error Gain on {sensor_name}')
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plt.xlabel('Error Gain')
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plt.ylabel('Standard Deviation of Output')
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plt.grid(True)
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plt.show()
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def main(num_of_tests: int = 1000, num_of_processes: int = 1):
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# Define true values and sensor error ranges
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pt_1_errors = {
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"k": 2, # How many standard deviations each of these errors represents (if applicable)
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"fso": 100, # full scale output so that stdev can be calculated for errors based on FSO
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"static_error_band": 0.15, # +-% of FSO
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"repeatability": 0.02, # +-% of FSO
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"hysteresis": 0.07, # +-% of FSO
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"non-linearity": 0.15, # +-% of FSO
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"temperature_zero_error": 0.005, # +% of FSO per degree F off from calibration temp
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"temperature_offset": 30, # Degrees F off from calibration temp
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}
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RTD_1_errors = {
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"k": 3, # How many standard deviations each of these errors represents (if applicable)
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"class": "A", # class AA, A, B, C
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}
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flow_1_errors = {
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"k": 2, # How many standard deviations each of these errors represents (if applicable)
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"fso": 20, # full scale output so that stdev can be calculated for errors based on FSO
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"static_error_band": 0.25, # +-% of FSO
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}
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pipe_diameter_error = {
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"tolerance": 0.05,
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"cte": 8.8E-6, # degrees F^-1
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"temperature_offset": -100 # Degrees off from when the measurement was taken
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}
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# Create sensor instances
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pressure_transmitter_1 = PressureTransmitter(25, pt_1_errors, name="PT 1")
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pressure_transmitter_2 = PressureTransmitter(20, pt_1_errors, name="PT 2")
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temperature_sensor_1 = RTD(250, RTD_1_errors, name="RTD 1")
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average_pressure = AveragingInput([pressure_transmitter_1, pressure_transmitter_2])
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# Create DensityLookup instance
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density_lookup = DensityLookup(pressure_sensor=average_pressure, temperature_sensor=temperature_sensor_1)
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flow_speed = TurbineFlowMeter(10, flow_1_errors, "Flow Sensor 1")
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pipe_diameter = PhysicalInput(1, pipe_diameter_error, name="Pipe Diameter")
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# Define the combined sensor
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combined_input: CombinedInput = math.pi * density_lookup * flow_speed * (pipe_diameter / 12 / 2)**2
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monte_carlo = SystemUncertaintyMonteCarlo(combined_input)
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monte_carlo.perform_system_analysis(monte_carlo_settings={
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"num_runs": num_of_tests,
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"num_processes": num_of_processes
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})
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sensitivity_analysis_num_runs = num_of_tests // 100
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monte_carlo.perform_sensitivity_analysis(input_to_analyze=flow_speed,
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gain_settings=[1, 10, 10],
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monte_carlo_settings={
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"num_runs": sensitivity_analysis_num_runs,
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"num_processes": num_of_processes
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})
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monte_carlo.perform_sensitivity_analysis(input_to_analyze=pressure_transmitter_1,
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gain_settings=[0.1, 10, 10],
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monte_carlo_settings={
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"num_runs": sensitivity_analysis_num_runs,
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"num_processes": num_of_processes
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})
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monte_carlo.perform_sensitivity_analysis(input_to_analyze=temperature_sensor_1,
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gain_settings=[0.01, 1, 10],
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monte_carlo_settings={
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"num_runs": sensitivity_analysis_num_runs,
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"num_processes": num_of_processes
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})
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monte_carlo.perform_range_analysis(input_to_analyze=pressure_transmitter_1,
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range_settings=[28, 31, 20],
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monte_carlo_settings={
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"num_runs": sensitivity_analysis_num_runs,
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"num_processes": num_of_processes
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}
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)
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monte_carlo.perform_range_analysis(input_to_analyze=temperature_sensor_1,
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range_settings=[237, 244, 20],
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monte_carlo_settings={
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"num_runs": sensitivity_analysis_num_runs,
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"num_processes": num_of_processes
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}
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)
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monte_carlo.save_report()
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if __name__ == "__main__":
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num_of_tests = 1_000_000
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num_of_processes = 10
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main(num_of_tests, num_of_processes) |