Integrated spatio‐temporal process monitoring and fault spatial location for the laminar cooling of hot‐rolled strip steel

Abstract

Laminar cooling process is crucial for the production and the quality of the strip steel in the hot‐rolled strip steel. Abnormalities or faults influence the temperature distributions in the direction of the length and the thickness, which determine the mechanical and physical performance of the strip steel. Considering that the spatial distribution of the strip temperature is hardly measured, the distributed parameter model can be constructed to deal with the problem of the abnormality detection and location. In this paper, a process monitoring and fault spatial location method with spatio‐temporal integration is proposed for the laminar cooling. First, a spatio‐temporal model is constructed by multi‐modelling method to monitor the spatial distribution of the strip temperature, and the dimension of the local thermodynamic model is reduced by time‐space separation. Then, a residual generator is provided for fault detection in the data‐driven realization, and the statistic and the threshold are formed to evaluate it. Next, the spatial location of the fault can be identified by reconstruction based contribution method. Finally, an experiment is conducted to demonstrate the practical application effects by a real laminar cooling process data.