Fault detection and isolation in automated controlled process based on equipment-reliability studies

Vahid Ebrahimipour, Hossam A. Gabbar, Kazuhiko Suzuki

Research output: Contribution to conferencePaperpeer-review


Automated controlled process is vulnerable to faults. Faults can be amplified by the closed loop control systems and they can develop into malfunction of the loop. The closed loop may alternatively hide a fault from being observed until eventually developed to a state where loop failure is inevitable. A control loop failure will easily cause production stop or malfunction at a plant. A way to achieve a stable and effective automated system is to support online fault detection and isolation through equipment- reliability studies. The objective of this paper is to present a framework to support fault diagnosis through reliability-equipment studies. The main idea is to employ Eigen Value Analysis (EVA) and Importance Analysis (IA) to provide insight on equipment performance. The equipment of offshore industries is considered according to OREDA classification. At first EVA is used for analyzing the performance of the equipment and introducing reliability as the most prominent technical performance character. IA is then performed to develop equipment reliability analysis and classify their components based on the Component Criticality Measures (CCM). The analysis of equipment reliability can ferret out the leading causes and common-cause events to pave a way toward knowledge acquisition which enhance online fault diagnosis performance.

Original languageEnglish
Number of pages6
Publication statusPublished - Dec 1 2005
EventSICE Annual Conference 2005 - Okayama, Japan
Duration: Aug 8 2005Aug 10 2005


OtherSICE Annual Conference 2005


  • Dependability analysis
  • Eigen value analysis
  • Equipment-reliability knowledge
  • Fault diagnosis
  • Importance analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


Dive into the research topics of 'Fault detection and isolation in automated controlled process based on equipment-reliability studies'. Together they form a unique fingerprint.

Cite this