Using Event-Intervals to Analyze Alarm Sequences in a Chemical Plant

Document Type

Journal Article

Keywords

Data mining, alarm sequences, correlated alarms, chemical processes

Publisher

Science Press

Faculty

Faculty of Computing, Health and Science

School

School of Computer and Security Science

RAS ID

8502

Comments

Kordic, S., Lam, C. P., Xiao, J., & Li, H. (2009). Using event-intervals to analyze alarm sequences in a chemical plant. Journal of Frontiers of Computer Science and Technology, 3(3), 267-281.

Abstract

A data mining approach is designed to support alarm rationalization by discovering correlated sets of alarm tags. The proposed approach is evaluated using simulation data from a model of the Vinyl Acetate chemical process as well as real plant alarm data. Results show that the propsed approach, using an event segmentation and data filtering strategy based on a cross-effect test, is significant.

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