Optimal sensor allocation for system abnormality detection by integrating causal models and set-covering algorithms

Jing Li, Jin Jionghua

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper focuses on optimal sensor allocation in Distributed Sensor Networks (DSN) for complex systems which are represented by Bayesian network (BN) models. The paper presents a new strategy to transfer the optimal sensor allocation problem into a set-covering optimization problem. Furthermore, the efficiency of the search algorithm is improved by integration of BN models and the greedy search algorithm. Case studies on two manufacturing processes are conducted, which demonstrates the effectiveness of the proposed method in abnormality detection.

Original languageEnglish (US)
Title of host publicationIIE Annual Conference and Expo 2008
Number of pages6
StatePublished - 2008
EventIIE Annual Conference and Expo 2008 - Vancouver, BC, Canada
Duration: May 17 2008May 21 2008


OtherIIE Annual Conference and Expo 2008
CityVancouver, BC



  • Bayesian networks
  • Causal models
  • Sensor allocation
  • Set-covering algorithm

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Industrial and Manufacturing Engineering

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