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A method for false alarm recognition considering threshold

  • Fei Guan*
  • , Junyou Shi
  • , Weiwei Cui
  • , Dongpao Hong
  • , Jie Wu
  • *Corresponding author for this work
  • National University of Defense Technology

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

Abstract

A new approach to false alarm recognition is proposed. The described method divides the state of a system into three types: normal, false-alarm, and faulty, and analyzes the overlapping relations of the distribution functions of different states to determine the optimal thresholds. After a brief introduction to support vector machine (SVM), the proposed strategy based on the results using thresholds is explained. The presented evolutionary approach is illustrated by a fault injection system. The accuracy of the technique is compared with the conventional and other intelligent methods, and the obtained results are discussed.

Original languageEnglish
Title of host publicationProceedings - 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019
EditorsChuan Li, Shaohui Zhang, Jianyu Long, Diego Cabrera, Ping Ding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1043-1049
Number of pages7
ISBN (Electronic)9781728101996
DOIs
StatePublished - Aug 2019
Event2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019 - Beijing, China
Duration: 15 Aug 201917 Aug 2019

Publication series

NameProceedings - 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019

Conference

Conference2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019
Country/TerritoryChina
CityBeijing
Period15/08/1917/08/19

Keywords

  • Built-in test
  • False alarm
  • PDF
  • SVM
  • Threshold

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