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A real-time fault detection and isolation strategy for gas sensor arrays

  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A real-time fault detection and isolation strategy for gas sensor arrays is presented in this paper. To improve the efficiency of the basic kernel principal component analysis (KPCA) algorithm, a sample selection method is utilized to extract the approximate basis of the entire training sample set, and reduce the time consumption on the calculation of the kernel matrix. Further, a novel algorithm for reducing the number of fault direction set candidates is also developed to improve the efficiency of the basic reconstruction-based contribution (RBC) method in fault isolation. The proposed strategy is fully verified in a real experimental system for gas sensor arrays under multiple-fault situations. The results of the experiments illustrate that the proposed strategy provides an efficient scheme for the real-time process monitoring of gas sensor arrays.

Original languageEnglish
Title of host publicationI2MTC 2017 - 2017 IEEE International Instrumentation and Measurement Technology Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509035960
DOIs
StatePublished - 5 Jul 2017
Event2017 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2017 - Torino, Italy
Duration: 22 May 201725 May 2017

Publication series

NameI2MTC 2017 - 2017 IEEE International Instrumentation and Measurement Technology Conference, Proceedings

Conference

Conference2017 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2017
Country/TerritoryItaly
CityTorino
Period22/05/1725/05/17

Keywords

  • Fault detection and isolation
  • Gas sensor arrays
  • Kernel principal component analysis
  • Real-time
  • Reconstruction-based contribution

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