Diagnosis of nonlinear systems using time series analysis

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Diagnosis and analysis techniques for linear systems have been developed and refined to a high degree of precision. In contrast, techniques for the analysis of data from nonlinear systems are in the early stages of development. This paper describes a time series technique for the analysis of data from nonlinear systems. The input and response time series resulting from excitation of the nonlinear system are embedded in a state space. The form of the embedding is optimized using local canonical variate analysis and singular value decomposition techniques. From the state space model, future system responses are estimated. The expected degree ... continued below

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Pages: (23 p)

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Hunter, N.F. Jr. January 1, 1991.

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Description

Diagnosis and analysis techniques for linear systems have been developed and refined to a high degree of precision. In contrast, techniques for the analysis of data from nonlinear systems are in the early stages of development. This paper describes a time series technique for the analysis of data from nonlinear systems. The input and response time series resulting from excitation of the nonlinear system are embedded in a state space. The form of the embedding is optimized using local canonical variate analysis and singular value decomposition techniques. From the state space model, future system responses are estimated. The expected degree of predictability of the system is investigated using the state transition matrix. The degree of nonlinearity present is quantified using the geometry of the transfer function poles in the z plane. Examples of application to a linear single-degree-of-freedom system, a single-degree-of-freedom Duffing Oscillator, and linear and nonlinear three degree of freedom oscillators are presented. 11 refs., 9 figs.

Physical Description

Pages: (23 p)

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OSTI; NTIS; GPO Dep.

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  • 3. international machinery monitoring and diagnostic conference, Las Vegas, NV (United States), 9-12 Dec 1991

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  • Other: DE91016041
  • Report No.: LA-UR-91-2283
  • Report No.: CONF-911241--2
  • Grant Number: W-7405-ENG-36
  • Office of Scientific & Technical Information Report Number: 5242934
  • Archival Resource Key: ark:/67531/metadc1067958

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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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  • January 1, 1991

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  • Feb. 4, 2018, 10:51 a.m.

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  • March 2, 2018, 5:20 p.m.

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Hunter, N.F. Jr. Diagnosis of nonlinear systems using time series analysis, article, January 1, 1991; United States. (digital.library.unt.edu/ark:/67531/metadc1067958/: accessed April 23, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.