Anomaly prediction in mechanical systems using symbolic dynamics

Author

Friedlander, David ; Chattopadhyay, Ishanu ; Ray, Asok ; Phoha, Shashi ; Jacobson, Noah

Author_Institution

Pennsylvania State Univ., University Park, PA, USA

Volume

5

fYear

2003

fDate

4-6 June 2003

Firstpage

4275

Abstract

This paper presents anomaly prediction in complex mechanical systems at an early stage where anomaly is defined as an observable deviation from the nominal dynamical response. The anomaly prediction algorithm is built upon two-time-scale analysis of time series data and relies on a combination of nonlinear systems theory and language theory. The algorithm has been validated for anomaly prediction on a rotorcraft gearbox testbed for two different types of anomalies.

Keywords

data analysis; dynamics; fault diagnosis; formal languages; helicopters; information theory; nonlinear control systems; nonlinear dynamical systems; time series; anomaly prediction; complexity measure; formal language; language theory; mechanical system; nominal dynamical response; nonlinear systems theory; rotorcraft gearbox testbed; symbolic dynamics; time series data; two-time-scale analysis; Algorithm design and analysis; Delay effects; Mechanical systems; Nonlinear dynamical systems; Nonlinear systems; Pollution measurement; Prediction algorithms; Sensor systems; Testing; Time series analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2003. Proceedings of the 2003

ISSN

0743-1619

Print_ISBN

0-7803-7896-2

Type

conf

DOI

10.1109/ACC.2003.1240508

Filename

1240508