DocumentCode :
1792798
Title :
Fault propagation analysis by combining data-driven causal analysis and plant connectivity
Author :
Landman, Rinat ; Kortela, Jukka ; Jamsa-Jounela, Sirkka-Liisa
Author_Institution :
Process Control & Autom. Res. Group, Aalto Univ., Espoo, Finland
fYear :
2014
fDate :
16-19 Sept. 2014
Firstpage :
1
Lastpage :
4
Abstract :
This paper presents a novel technique for integrating process causality and topology which ultimately enables to determine the propagation path of oscillations in control loops. The integration is performed using a dedicated search algorithm which validates the quantitative results of the data-driven causality using the qualitative information on plant connectivity extracted from a piping and instrumentation diagram. The outcome is an enhanced causal model which reveals the propagation path. The analysis is demonstrated on a case study of an industrial paperboard machine with multiple oscillations in its drying section due to valve stiction.
Keywords :
industrial control; instrumentation; pipelines; search problems; valves; control loops; data-driven causal analysis; dedicated search algorithm; fault propagation analysis; industrial paperboard machine; instrumentation diagram; multiple oscillations; piping; plant connectivity; propagation path; valve stiction; Algorithm design and analysis; Mathematical model; Oscillators; Process control; Time series analysis; Topology; Valves; Plant topology; causal analysis; control loops;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Technology and Factory Automation (ETFA), 2014 IEEE
Conference_Location :
Barcelona
Type :
conf
DOI :
10.1109/ETFA.2014.7005337
Filename :
7005337
Link To Document :
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