Improving expressional power and validation for multilevel flow models

Research output: Contribution to journalArticle

Abstract

Multilevel flow modeling (MFM) is a modeling method for complex technical systems in which the goals and functions of the system are explicitly described. MFM can be used as a basis for root cause analysis, where primary root causes are separated from consequential faults, in complex fault situations. Model representations for use in diagnostic reasoning usually describe causality, between parameters, faults, of, process states. However, the causality of a system may vary depending on details in the construction, as well as over time with the process state. One contribution of this paper is a general method of describing varying causality in a simple and efficient way. The method has been tested using multilevel flow models. Causality is visible in measurements and can be used to increase process understanding. The standard cross-correlation technique is insufficient for causality detection in industrial processes. Another contribution of this paper is a new method that can detect causality in industrial signals, and thus be used to validate the design of multilevel flow models.

Details

Authors
  • Jan Eric Larsson
  • Jonas Ahnlund
  • Tord Bergquist
  • F Dahlstrand
  • B Ohman
  • Lambert Spaanenburg
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Electrical Engineering, Electronic Engineering, Information Engineering

Keywords

  • alarm analysis, complex technical systems, correlation, fault detection, causality, multilevel flow models, root cause analysis
Original languageEnglish
Pages (from-to)61-73
JournalJournal of Intelligent & Fuzzy Systems
Volume15
Issue number1
Publication statusPublished - 2004
Publication categoryResearch
Peer-reviewedYes