Using Event-Intervals to Analyze Alarm Sequences in a Chemical Plant
Document Type
Journal Article
Publisher
Science Press
Faculty
Faculty of Computing, Health and Science
School
School of Computer and Security Science
RAS ID
8502
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.
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.