Procedure for tracking damage evolution and predicting remaining useful life with application to an electromechanical experimental system

David Chelidze, Joseph Paul Cusumano, Anindya Chatterjee

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

A general method for tracking the evolution of hidden damage processes and predicting remaining useful life is presented and applied experimentally to an electromechanical system with a failing supply battery. The fundamental theory for the method is presented. In this theory, damage processes are viewed as occurring in a hierarchical dynamical system consisting of ”fast”, directly observable subsystem coupled with a ”slow”, hidden subsystem describing damage evolution. In the algorithm, damage tracking is achieved using a two-time-scale modeling strategy based on phase space reconstruction. Using the reconstructed phase space of the reference (undamaged) system, short-time predictive models are constructed. Fast-time data from later stages of damage evolution of a given system are collected and used to estimate the short time reference model prediction error or a tracking metric. The tracking metric is used as an input to a nonlinear recursive filter, the output of which provides an estimate of the current damage (or, equivalently, health) state. Estimates of remaining useful life (or, equivalently, time to failure) are obtained recursively using the current damage state estimates under the assumption of a particular battery voltage evolution model. In the experimental application, the method is shown to accurately estimate both the battery state and the time to failure throughout the whole experiment.

Original languageEnglish (US)
Pages (from-to)12-22
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4389
Issue number1
DOIs
StatePublished - Jul 20 2001

Fingerprint

Damage
damage
Battery
electric batteries
estimates
Estimate
Dynamical systems
Health
Subsystem
Phase Space Reconstruction
IIR filters
Metric
Electric potential
Model Error
reference systems
Predictive Model
Reference Model
Prediction Error
Life
dynamical systems

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

@article{8cdcbb9895aa4307bd53c5f09064ee5e,
title = "Procedure for tracking damage evolution and predicting remaining useful life with application to an electromechanical experimental system",
abstract = "A general method for tracking the evolution of hidden damage processes and predicting remaining useful life is presented and applied experimentally to an electromechanical system with a failing supply battery. The fundamental theory for the method is presented. In this theory, damage processes are viewed as occurring in a hierarchical dynamical system consisting of ”fast”, directly observable subsystem coupled with a ”slow”, hidden subsystem describing damage evolution. In the algorithm, damage tracking is achieved using a two-time-scale modeling strategy based on phase space reconstruction. Using the reconstructed phase space of the reference (undamaged) system, short-time predictive models are constructed. Fast-time data from later stages of damage evolution of a given system are collected and used to estimate the short time reference model prediction error or a tracking metric. The tracking metric is used as an input to a nonlinear recursive filter, the output of which provides an estimate of the current damage (or, equivalently, health) state. Estimates of remaining useful life (or, equivalently, time to failure) are obtained recursively using the current damage state estimates under the assumption of a particular battery voltage evolution model. In the experimental application, the method is shown to accurately estimate both the battery state and the time to failure throughout the whole experiment.",
author = "David Chelidze and Cusumano, {Joseph Paul} and Anindya Chatterjee",
year = "2001",
month = "7",
day = "20",
doi = "10.1117/12.434238",
language = "English (US)",
volume = "4389",
pages = "12--22",
journal = "Proceedings of SPIE - The International Society for Optical Engineering",
issn = "0277-786X",
publisher = "SPIE",
number = "1",

}

TY - JOUR

T1 - Procedure for tracking damage evolution and predicting remaining useful life with application to an electromechanical experimental system

AU - Chelidze, David

AU - Cusumano, Joseph Paul

AU - Chatterjee, Anindya

PY - 2001/7/20

Y1 - 2001/7/20

N2 - A general method for tracking the evolution of hidden damage processes and predicting remaining useful life is presented and applied experimentally to an electromechanical system with a failing supply battery. The fundamental theory for the method is presented. In this theory, damage processes are viewed as occurring in a hierarchical dynamical system consisting of ”fast”, directly observable subsystem coupled with a ”slow”, hidden subsystem describing damage evolution. In the algorithm, damage tracking is achieved using a two-time-scale modeling strategy based on phase space reconstruction. Using the reconstructed phase space of the reference (undamaged) system, short-time predictive models are constructed. Fast-time data from later stages of damage evolution of a given system are collected and used to estimate the short time reference model prediction error or a tracking metric. The tracking metric is used as an input to a nonlinear recursive filter, the output of which provides an estimate of the current damage (or, equivalently, health) state. Estimates of remaining useful life (or, equivalently, time to failure) are obtained recursively using the current damage state estimates under the assumption of a particular battery voltage evolution model. In the experimental application, the method is shown to accurately estimate both the battery state and the time to failure throughout the whole experiment.

AB - A general method for tracking the evolution of hidden damage processes and predicting remaining useful life is presented and applied experimentally to an electromechanical system with a failing supply battery. The fundamental theory for the method is presented. In this theory, damage processes are viewed as occurring in a hierarchical dynamical system consisting of ”fast”, directly observable subsystem coupled with a ”slow”, hidden subsystem describing damage evolution. In the algorithm, damage tracking is achieved using a two-time-scale modeling strategy based on phase space reconstruction. Using the reconstructed phase space of the reference (undamaged) system, short-time predictive models are constructed. Fast-time data from later stages of damage evolution of a given system are collected and used to estimate the short time reference model prediction error or a tracking metric. The tracking metric is used as an input to a nonlinear recursive filter, the output of which provides an estimate of the current damage (or, equivalently, health) state. Estimates of remaining useful life (or, equivalently, time to failure) are obtained recursively using the current damage state estimates under the assumption of a particular battery voltage evolution model. In the experimental application, the method is shown to accurately estimate both the battery state and the time to failure throughout the whole experiment.

UR - http://www.scopus.com/inward/record.url?scp=0034773473&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0034773473&partnerID=8YFLogxK

U2 - 10.1117/12.434238

DO - 10.1117/12.434238

M3 - Article

AN - SCOPUS:0034773473

VL - 4389

SP - 12

EP - 22

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

SN - 0277-786X

IS - 1

ER -