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Minimum rotation partitioning for data analysis and its application to fault detection

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3 Author(s)
Yasar, M. ; Techno-Sci., Inc., Beltsville, MD, USA ; Ray, A. ; Kwatny, H.G.

Symbolic dynamics provide a new set of tools for data analysis, fault detection and investigation of the dynamical systems. The main concept is partitioning the phase space into a finite number of non-overlapping segments that provide a low-dimensional representation of time series. By simplifying the dynamics this way, a novel method for nonlinear analysis of systems, including fault progression, can be constructed from observed data. This paper presents a novel space partitioning technique, referred as minimum rotation partitioning for the purpose of fault detection and quantification. The results obtained from a permanent magnet synchronous machine is presented as an example of fault detection and quantification.

Published in:

American Control Conference (ACC), 2010

Date of Conference:

June 30 2010-July 2 2010

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