Alarm Prediction with Variational Output Dimension for Alarm Floods Using Transformer

Industrial alarm systems play crucial roles in assessing the production status and ensuring process safety. However, the presence of alarm floods can make alarm systems partially or fully fail, and thus would cause serious consequences. Alarm prediction, as an advanced approach to address alarm floo...

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Bibliographic Details
Main Authors: Pang, Long, Jiang, Wenbin, Hu, Wenkai, Wang, Zhuang, Cao, Weihua
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Adaptation models
Alarm Floods
Alarm Prediction
Alarm System
Alarm systems
Feature extraction
Predictive models
Production
Transformer
Transformers
Online Access:Request full text
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Summary:Industrial alarm systems play crucial roles in assessing the production status and ensuring process safety. However, the presence of alarm floods can make alarm systems partially or fully fail, and thus would cause serious consequences. Alarm prediction, as an advanced approach to address alarm floods, offers operators decision supports when an alarm flood occurs. Existing alarm prediction methods requires that the output alarm sequences are of a fixed dimension, making such methods unable to adapt to the changing alarm rate. Accordingly, this paper proposes an alarm prediction model based on Transformer. The proposed model can predict alarm sequences with variational dimensions and can also achieve remarkable accuracy. The effectiveness of the proposed method is demonstrated by a case study with data from the Vinyl Acetate Monomer (VAM) simulation model.
ISSN:1934-1768
DOI:10.23919/CCC63176.2024.10662574