Optimal Transport Image Representation and Deep Covariance Alignment (CORAL) for Control Valve Stiction Detection
Control valve stiction is a common cause of unwanted oscillations and poor control-loop performance in industrial processes. Data-driven methods can automatically detect stiction, but models trained purely on simulated data often struggle to generalize to real industrial control loops due to domain shift. To bridge this gap, this work propose a novel stiction detection methodology that combines optimal transport (OT) imaging technique with deep correlation alignment (Deep CORAL) algorithm. Closed loop signals: controller output and process variable are converted into two-dimensional OT images. These images capture the dynamic behaviour of control loops. The proposed methodology includes a...
| Authors | Seshu K. Damarla |
|---|---|
| Primary category | cs.CV |
| Published | 24 July 2026 |
| Last updated at source | 27 July 2026 |
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