Machine and Process System Diagnostics Using One-Step Prediction Maps

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This paper describes a method for machine or process system diagnostics that uses one-step prediction maps. The method uses nonlinear time series analysis techniques to form a one-step prediction map that estimates the next time series data point when given a sequence of previously measured time series data point. The difference between the predicted and measured time series values is a measure of the map error. The average value of this error should remain within some bound as long as both the dynamic system and its operating condition remain unchanged. However, changes in the dynamic system or operating condition will ... continued below

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14 pages

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Breeding, J. E.; Damiano, B. & Tucker, R. W., Jr. May 10, 1999.

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Description

This paper describes a method for machine or process system diagnostics that uses one-step prediction maps. The method uses nonlinear time series analysis techniques to form a one-step prediction map that estimates the next time series data point when given a sequence of previously measured time series data point. The difference between the predicted and measured time series values is a measure of the map error. The average value of this error should remain within some bound as long as both the dynamic system and its operating condition remain unchanged. However, changes in the dynamic system or operating condition will cause an increase in average map error. Thus, for a constant operating condition, monitoring the average map error over time should indicate when a change has occurred in the dynamic system. Furthermore, the map error itself forms a time series that can be analyzed to detect changes in system dynamics. The paper provides technical background in the nonlinear analysis techniques used in the diagnostic method, describes the creation of one-step prediction maps and their application to machine or process system diagnostics, and then presents results obtained from applying the diagnostic method to simulated and measured data.

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14 pages

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  • Maintenance and Reliability Conference, MARCON99, Gatlinburg, TN, May 10-12, 1999

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  • Other: DE00006932
  • Report No.: ORNL/CP-103164
  • Grant Number: AC05-96OR22464
  • Office of Scientific & Technical Information Report Number: 6932
  • Archival Resource Key: ark:/67531/metadc708918

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • May 10, 1999

Added to The UNT Digital Library

  • Sept. 12, 2015, 6:31 a.m.

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  • Nov. 12, 2015, 1:11 p.m.

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Breeding, J. E.; Damiano, B. & Tucker, R. W., Jr. Machine and Process System Diagnostics Using One-Step Prediction Maps, article, May 10, 1999; Oak Ridge, Tennessee. (digital.library.unt.edu/ark:/67531/metadc708918/: accessed October 20, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.