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Monitoring Equipment Operation Through Model and Event Discovery

  • Sławomir NowaczykEmail author
  • Anita Sant’Anna
  • Ece Calikus
  • Yuantao Fan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11315)

Abstract

Monitoring the operation of complex systems in real-time is becoming both required and enabled by current IoT solutions. Predicting faults and optimising productivity requires autonomous methods that work without extensive human supervision. One way to automatically detect deviating operation is to identify groups of peers, or similar systems, and evaluate how well each individual conforms with the group.

We propose a monitoring approach that can construct knowledge more autonomously and relies on human experts to a lesser degree: without requiring the designer to think of all possible faults beforehand; able to do the best possible with signals that are already available, without the need for dedicated new sensors; scaling up to “one more system and component” and multiple variants; and finally, one that will adapt to changes over time and remain relevant throughout the lifetime of the system.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Sławomir Nowaczyk
    • 1
    Email author
  • Anita Sant’Anna
    • 1
  • Ece Calikus
    • 1
  • Yuantao Fan
    • 1
  1. 1.CAISR, Halmstad UniversityHalmstadSweden

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