Selecting Observation Platforms for Optimized Anomaly Detectability under Unreliable Partial Observations

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Diagnosers for keeping track on the occurrences of special events in the framework of unreliable partially observed discrete-event dynamical systems were developed in previous work. This paper considers observation platforms consisting of sensors that provide partial and unreliable observations and of diagnosers that analyze them. Diagnosers in observation platforms typically perform better as sensors providing the observations become more costly or increase in number. This paper proposes a methodology for finding an observation platform that achieves an optimal balance between cost and performance, while satisfying given observability requirements and constraints. Since this problem is generally computational hard in the framework ... continued below

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Lin, Wen-Chiao; Garcia, Humberto E. & Yoo, Tae-Sic June 1, 2011.

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Diagnosers for keeping track on the occurrences of special events in the framework of unreliable partially observed discrete-event dynamical systems were developed in previous work. This paper considers observation platforms consisting of sensors that provide partial and unreliable observations and of diagnosers that analyze them. Diagnosers in observation platforms typically perform better as sensors providing the observations become more costly or increase in number. This paper proposes a methodology for finding an observation platform that achieves an optimal balance between cost and performance, while satisfying given observability requirements and constraints. Since this problem is generally computational hard in the framework considered, an observation platform optimization algorithm is utilized that uses two greedy heuristics, one myopic and another based on projected performances. These heuristics are sequentially executed in order to find best observation platforms. The developed algorithm is then applied to an observation platform optimization problem for a multi-unit-operation system. Results show that improved observation platforms can be found that may significantly reduce the observation platform cost but still yield acceptable performance for correctly inferring the occurrences of special events.

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  • 2011 American Control Conference -- ACC2011,San Francisco, California, USA,06/29/2011,07/01/2011

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  • Report No.: INL/CON-11-21677
  • Grant Number: DE-AC07-05ID14517
  • Office of Scientific & Technical Information Report Number: 1033879
  • Archival Resource Key: ark:/67531/metadc835521

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  • June 1, 2011

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

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  • June 17, 2016, 10:38 p.m.

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Lin, Wen-Chiao; Garcia, Humberto E. & Yoo, Tae-Sic. Selecting Observation Platforms for Optimized Anomaly Detectability under Unreliable Partial Observations, article, June 1, 2011; Idaho Falls, Idaho. (digital.library.unt.edu/ark:/67531/metadc835521/: accessed October 15, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.