Fault Injection

This module Fault Injection is created to insert random faults(errors to be selected from a continuous distribution type) into the telemetries aka sensors like – Arm Joint angle, Arm acceleration etc. of Europa Mission Lander so that we can train our underlying causal models against the abrupt environmental changes on the surface.

Import Libraries

Import necessary libraries

Selecting Parameters of a Distribution**

The parameters of a distribution are variables included in the density function so that the distribution can be adapted to a variety of situations. Of greatest importance is the number of parameters as shown below:

2 Parameters: The two parameters determine the average and standard deviation of the distribution. Such distributions are represented as a point on a skewness-kurtosis plot as they have fixed values of the skewness and kurtosis. Examples are the exponential, normal and uniform distributions.

3 Parameters: The three parameters determine the average, standard deviation and skewness of the distribution. Such distributions are represented as a curve on a skewness-kurtosis plot as the kurtosis depends of the skewness. Examples are the gamma and lognormal distributions.

4 Parameters: The four parameters determine the average, standard deviation, skewness and kurtosis of the distribution. Such distributions are represented as a region on a skewness-kurtosis plot as they can take on a variety of skewness and kurtosis values. Examples are the beta, Johnson and Pearson distributions.

Selecting Telemetries

Selecting telemetries in which we want to introduce the errors. For now we have 7 telemetries, namely,
ARM_FT_FORCE
ARM_FT_FORCE_2
ARM_FT_FORCE_3
ARM_FT_TORQUE
ARM_JOINT_ACCELERATIONS
ARM_JOINT_ANGLES
ARM_JOINT_VELOCITIES
PT_POS
Tilt_POS

Number of Faulty Environment

Choose how many faulty environments need to be created

Inject fault

Inject faults into the selected telemetries and generate environment

Export the faulty environment

Export the faulty environment to the desired location, use the faulty environment to enhace the robustness of the models.

UML diagrams

Flow chart:

Random Error
Fault Injection
Telemetries
Robust Causal Model Training

Module