Methods for improved forewarning of critical events across multiple data channels

Hively, Lee M

Title: Methods for improved forewarning of critical events across multiple data channels

Abstract

This disclosed invention concerns improvements in forewarning of critical events via phase-space dissimilarity analysis of data from mechanical devices, electrical devices, biomedical data, and other physical processes. First, a single channel of process-indicative data is selected that can be used in place of multiple data channels without sacrificing consistent forewarning of critical events. Second, the method discards data of inadequate quality via statistical analysis of the raw data, because the analysis of poor quality data always yields inferior results. Third, two separate filtering operations are used in sequence to remove both high-frequency and low-frequency artifacts using a zero-phase quadratic filter. Fourth, the method constructs phase-space dissimilarity measures (PSDM) by combining of multi-channel time-serial data into a multi-channel time-delay phase-space reconstruction. Fifth, the method uses a composite measure of dissimilarity (C.sub.i) to provide a forewarning of failure and an indicator of failure onset.

Inventors:

Hively, Lee M ^[1]

Philadelphia, TN

Publication Date:: 2007-04-24

Research Org.:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 908987

Patent Number(s):: 7,209,861

Application Number:: 10/667,045

Assignee:: UT-Battelle LLC (Oak Ridge, TN)

DOE Contract Number:: AC05-00OR22725

Resource Type:: Patent

Country of Publication:: United States

Language:: English

Subject:: 47 OTHER INSTRUMENTATION

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                    Hively, Lee M. Methods for improved forewarning of critical events across multiple data channels.  United States: N. p., 2007. 
        Web.

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                    Hively, Lee M. Methods for improved forewarning of critical events across multiple data channels.  United States.

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                    Hively, Lee M. 2007.  
        "Methods for improved forewarning of critical events across multiple data channels".  United States.  https://www.osti.gov/servlets/purl/908987.

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@article{osti_908987,

  title        = {Methods for improved forewarning of critical events across multiple data channels},

  author       = {Hively, Lee M},

  abstractNote = {This disclosed invention concerns improvements in forewarning of critical events via phase-space dissimilarity analysis of data from mechanical devices, electrical devices, biomedical data, and other physical processes. First, a single channel of process-indicative data is selected that can be used in place of multiple data channels without sacrificing consistent forewarning of critical events. Second, the method discards data of inadequate quality via statistical analysis of the raw data, because the analysis of poor quality data always yields inferior results. Third, two separate filtering operations are used in sequence to remove both high-frequency and low-frequency artifacts using a zero-phase quadratic filter. Fourth, the method constructs phase-space dissimilarity measures (PSDM) by combining of multi-channel time-serial data into a multi-channel time-delay phase-space reconstruction. Fifth, the method uses a composite measure of dissimilarity (C.sub.i) to provide a forewarning of failure and an indicator of failure onset.},

  doi          = {},

  url          = {https://www.osti.gov/biblio/908987},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {2007},

  month        = {4}

}

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Works referenced in this record:

Reconstructing embedding spaces of coupled dynamical systems from multivariate data
journal, February 2002

Boccaletti, S.; Valladares, D. L.; M. Pecora, Louis
Physical Review E, Vol. 65, Issue 3
https://doi.org/10.1103/PhysRevE.65.035204

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Title: Methods for improved forewarning of critical events across multiple data channels

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Citation Formats

Reconstructing embedding spaces of coupled dynamical systems from multivariate data journal, February 2002

Reconstructing embedding spaces of coupled dynamical systems from multivariate data
journal, February 2002