@inproceedings{d8ee4eeee9884f9ea46ab6c1ffce48c4,
title = "Minimum rotation partitioning for data analysis and its application to fault detection",
abstract = "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.",
author = "Murat Yasar and Asok Ray and Kwatny, {Harry G.}",
year = "2010",
doi = "10.1109/acc.2010.5530853",
language = "English (US)",
isbn = "9781424474264",
series = "Proceedings of the 2010 American Control Conference, ACC 2010",
publisher = "IEEE Computer Society",
pages = "5439--5444",
booktitle = "Proceedings of the 2010 American Control Conference, ACC 2010",
address = "United States",
}