Fault Diagnosis of Hot Rolling Equipment Under Uncertain Conditions Based on Cloud Rough Model, Game Theory, and Improved GRA-TOPSIS

Fault Diagnosis of Hot Rolling Equipment Under Uncertain Conditions Based on Cloud Rough Model, Game Theory, and Improved GRA-TOPSIS

Abstract The hot-rolled strip steel is a critical process in steel production, where equipment stability directly impacts product quality. Traditional evaluation methods struggle to balance uncertainties between influencing factors and expert judgments. This study proposes a novel fault evaluation f...

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Bibliographic Details
Main Authors: Bo Hu, Yongjun Zhang, Fengwei Jing
Format: Article
Language:English
Published: Springer 2025-08-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Fault assessment
Cloud rough theory
Uncertainty
GRA-TOPSIS
MCDM
Online Access:https://doi.org/10.1007/s44196-025-00945-x
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Summary:Abstract The hot-rolled strip steel is a critical process in steel production, where equipment stability directly impacts product quality. Traditional evaluation methods struggle to balance uncertainties between influencing factors and expert judgments. This study proposes a novel fault evaluation framework: first, a cloud rough model is adopted to handle multi-source uncertainties in expert evaluations; second, game theory is used to optimize the combined weights of subjective and objective criteria; finally, an improved Grey Relational Analysis-Technique for Order Preference by Similarity to Ideal Solution (GRA-TOPSIS) method constructs a dual-scale measurement model by fusing grey relational degree and Euclidean distance, effectively reducing the influence of geometric sequence similarity and distance on fault prioritization and enhancing the robustness of ranking results under complex working conditions. A case study on hot rolling loopers demonstrates a diagnostic accuracy of 90%. Comparative analyses with seven typical multicriteria decision-making methods indicate the proposed method's feasibility and effectiveness in practical applications, offering a novel reference for equipment status evaluation.
ISSN:1875-6883

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