Conference proceeding
Minimum Rotation Partitioning for Data Analysis and Its Application to Fault Detection
2010 AMERICAN CONTROL CONFERENCE, pp 5439-5444
01 Jan 2010
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.
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1 citations in Scopus
Details
- Title
- Minimum Rotation Partitioning for Data Analysis and Its Application to Fault Detection
- Creators
- Murat Yasar - Physical SciencesAsok Ray - Pennsylvania State UniversityHarry G. Kwatny - Drexel UniversityIEEE
- Publication Details
- 2010 AMERICAN CONTROL CONFERENCE, pp 5439-5444
- Series
- Proceedings of the American Control Conference
- Publisher
- IEEE
- Number of pages
- 6
- Grant note
- NNC08CA02C / NASA Glen Research Center
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Mechanical Engineering and Mechanics
- Web of Science ID
- WOS:000287187905138
- Scopus ID
- 2-s2.0-77957810648
- Other Identifier
- 991019170136904721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Automation & Control Systems
- Engineering, Electrical & Electronic
- Engineering, Mechanical