Anomaly Prediction in Mechanical Systems Using Symbolic Dynamics

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

Anomaly Prediction in Mechanical Systems Using Symbolic Dynamics

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

Research output: Contribution to journal › Conference article › peer-review

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.

Original language	English (US)
Pages (from-to)	4275-4280
Number of pages	6
Journal	Proceedings of the American Control Conference
Volume	5
State	Published - 2003
Event	2003 American Control Conference - Denver, CO, United States Duration: Jun 4 2003 → Jun 6 2003

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Cite this

@article{e4457a0c633e40478ada8edf108b5fd6,

title = "Anomaly Prediction in Mechanical Systems Using Symbolic Dynamics",

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.",

author = "David Friedlander and Ishanu Chattopadhyay and Asok Ray and Shashi Phoha and Noah Jacobson",

year = "2003",

language = "English (US)",

volume = "5",

pages = "4275--4280",

journal = "Proceedings of the American Control Conference",

issn = "0743-1619",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "2003 American Control Conference ; Conference date: 04-06-2003 Through 06-06-2003",

}

TY - JOUR

T1 - Anomaly Prediction in Mechanical Systems Using Symbolic Dynamics

AU - Friedlander, David

AU - Chattopadhyay, Ishanu

AU - Ray, Asok

AU - Phoha, Shashi

AU - Jacobson, Noah

PY - 2003

Y1 - 2003

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0142169046&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0142169046&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0142169046

SN - 0743-1619

VL - 5

SP - 4275

EP - 4280

JO - Proceedings of the American Control Conference

JF - Proceedings of the American Control Conference

T2 - 2003 American Control Conference

Y2 - 4 June 2003 through 6 June 2003

ER -

Anomaly Prediction in Mechanical Systems Using Symbolic Dynamics

Abstract

All Science Journal Classification (ASJC) codes

Other files and links

Fingerprint

Cite this