Location

https://www.kennesaw.edu/ccse/events/computing-showcase/sp26-cday-program.php

Document Type

Event

Start Date

22-4-2026 4:00 PM

Description

Satellite systems cost hundreds of millions of dollars or more to launch. To be resistant to catastrophic failures (and total loss of investment), satellite systems are designed with redundant sub-systems and are further equipped with numerous sensors and other health-monitoring sub-systems. In this poster, we consider an approach to fault diagnosis based on probabilistic logic programming. In particular, we propose to use ProbLog to model and reason with the electrical power system (EPS) of a satellite. Once we model a system using (probabilistic) first-order logic, we can take the system state and any (unexpected) sensor readings, and through automated reasoning, we can provide ranked predictions about the most likely faults in the system. We present our approach to fault diagnosis using ProbLog, and present a case study in a simplified EPS, highlighting our ability to isolate and diagnose different categories of faults.

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Apr 22nd, 4:00 PM

GRP-08-168 Diagnosing Faults in Electrical Power Systems of Satellites

https://www.kennesaw.edu/ccse/events/computing-showcase/sp26-cday-program.php

Satellite systems cost hundreds of millions of dollars or more to launch. To be resistant to catastrophic failures (and total loss of investment), satellite systems are designed with redundant sub-systems and are further equipped with numerous sensors and other health-monitoring sub-systems. In this poster, we consider an approach to fault diagnosis based on probabilistic logic programming. In particular, we propose to use ProbLog to model and reason with the electrical power system (EPS) of a satellite. Once we model a system using (probabilistic) first-order logic, we can take the system state and any (unexpected) sensor readings, and through automated reasoning, we can provide ranked predictions about the most likely faults in the system. We present our approach to fault diagnosis using ProbLog, and present a case study in a simplified EPS, highlighting our ability to isolate and diagnose different categories of faults.