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Journal Article

Citation

Cai S, Wan A, Xu Q. China Saf. Sci. J. 2022; 32(11): 126-133.

Copyright

(Copyright © 2022, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2022.11.2321

PMID

unavailable

Abstract

In order to avoid the problem of associated alarm flooding due to the large number of process equipment and the increase of process alarm configuration in complex large-scale systems, a process alarm propagation path analysis method based on time-delay analysis was proposed for the existing causal analysis methods with strong subjectivity and uncertainty factors and lack of validity test of time-delay relationship between variables. Based on K nearest neighbor impuation (KNNI) method, the time delay between variables was estimated to determine the direction of process risk propagation. By calculating the Sorgenfrei similarity coefficient, the alarm correlation degree between the two variables was determined, and the process alarm propagation path diagram was established. This method was applied to a central heating system in a school. The results show that the proposed method can accurately identify two associated alarm propagation paths in the process, namely X1(outlet temperature of No.102 heat exchanger) → X2(hot water supply temperature in school) → X3(hot water supply temperature of No.3 building in Tercero area) and X1→ X2→ X4(hot water supply temperature of canteen in Tercero area). The obtained time-delay estimation result are in line with the actual situation of the process. According to the model, the time delay of X2→X3(5 min) is much smaller than the time delay of X2→X4(24 min), but the degree of alarm correlation is similar. Based on the difference of the time delay between the two paths, if X1 has a high alarm, it can prompt the operator to take prior measures (such as reducing hot water flow) to prevent X3 from having high alarm in a short time, so as to prevent alarm and and ensure the process safety. © 2022 China Safety Science Journal. All rights reserved.


Language: zh

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