Stationarity fusion with SVM: A stationary combined features support vector machine approach for blast furnace iron-making process fault diagnosis

Yang Cao

doi:10.1016/j.compchemeng.2025.109543

Stationarity fusion with SVM: A stationary combined features support vector machine approach for blast furnace iron-making process fault diagnosis

2025-12-24

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PRE

AI

Y

Yang Cao

C

Chunjie Yang *

S

Siwei Lou

Y

Yuelin Yang

DOI：10.1016/j.compchemeng.2025.109543

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• We develop a novel method to diagnose faults in blast furnace iron-making processes. • The model extracts differential dynamic features to capture transitional states. • A stationary classifier handles unstable operating conditions robustly. • It reduces false alarms by 3.0% and improves detection accuracy by 9.5%. • The system supports both offline training and online industrial deployment.

Stationarity fusion with SVM: A stationary combined features support vector machine approach for blast furnace iron-making process fault diagnosis

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