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Hierarchical Fault Diagnosis and Health Monitoring in Satellites Formation Flight

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Hierarchical Fault Diagnosis and Health Monitoring in Satellites Formation Flight

Barua, Amitabh and Khorasani, Khashayar (2011) Hierarchical Fault Diagnosis and Health Monitoring in Satellites Formation Flight. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 41 (2). pp. 223-239. ISSN 1094-6977

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Official URL: http://dx.doi.org/10.1109/TSMCC.2010.2049994

Abstract

Current spacecraft health monitoring and fault-diagnosis practices involve around-the-clock limit-checking and trend analysis on large amount of telemetry data. They do not scale well for future multiplatform space missions due the size of the telemetry data and an increasing need to make the long-duration missions cost-effective by limiting the operations team personnel. The need for efficient utilization of telemetry data achieved by employing machine learning and reasoning algorithms has been pointed out in the literature for enhancing diagnostic performance and assisting the less-experienced personnel in performing monitoring and diagnosis tasks. In this paper, we develop a systematic and transparent fault-diagnosis methodology within a hierarchical fault-diagnosis framework for a satellites formation flight. We present our proposed hierarchical decomposition framework through a novel Bayesian network, whose structure is developed from the knowledge of component health-state dependencies. We have developed a methodology for specifying the network parameters that utilizes both node fault-diagnosis performance data and domain experts' beliefs. Our proposed model development procedure reduces the demand for expert's time in eliciting probabilities significantly. Our proposed approach provides the ground personnel with an ability to perform diagnostic reasoning across a number of subsystems and components coherently. Due to the unavailability of real formation flight data, we demonstrate the effectiveness of our proposed methodology by using synthetic data of a leader-follower formation flight architecture. Although our proposed approach is developed from the satellite fault-diagnosis perspective, it is generic and is targeted toward other types of cooperative fleet vehicle diagnosis problems.

Divisions:Concordia University > Faculty of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Article
Refereed:Yes
Authors:Barua, Amitabh and Khorasani, Khashayar
Journal or Publication:IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
Date:2011
ID Code:974135
Deposited By:ANDREA MURRAY
Deposited On:13 Jun 2012 09:24
Last Modified:13 Jun 2012 09:24
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