Fault Detection and Diagnosis in Spacecraft Electrical Power Systems

Author:

Carbone Marc A.1ORCID,Loparo Kenneth A.2

Affiliation:

1. NASA Glenn Research Center, Cleveland, Ohio 44135

2. Case Western Reserve University, Cleveland, Ohio 44106

Abstract

The ability to accurately identify and isolate failures in the electrical power system (EPS) is critical to ensure the reliability of spacecraft. This paper proposes a novel solution to the problem of fault detection and diagnosis in direct current (DC) electric power systems for spacecraft. Autonomous operation becomes essential during deep space missions that lack the ability to monitor and control the spacecraft from ground locations. The current state of EPS fault supervision is insufficient to guarantee highly reliable operation. To solve this issue, a combination of model-based and knowledge-based techniques are used in a hierarchical framework to improve the diagnostic performance of the system. Noise, disturbances, and modeling errors are considered in the design of the fault detection system. Practical considerations related to spacecraft flight hardware and software are accounted for in the system design for flight applications. To assess the functionality of the design, a wide array of failures are simulated in a series of experiments. The experiments showed that the technique improved the capability of the autonomous system by increasing the number of fault types diagnosed. The significance of this study is to provide a framework capable of advanced diagnostics of an EPS with little to no interaction from human operators.

Funder

NASA’s Exploration Systems Development Mission Directorate/Exploration Capabilities

Publisher

American Institute of Aeronautics and Astronautics (AIAA)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Aerospace Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Discrete Features Enhancement Based Online Anomaly Detection for Satellite Telemetry Series;IEEE Transactions on Instrumentation and Measurement;2023

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