Rule and Data Driven Strip Coiling Temperature Model in Laminar Cooling Process

The existing cooling process models lack the methods to compute the heat transfer parameter and the position that strip reaches and cannot be used to compute the strip coiling temperature directly. So a strip coiling temperature model is proposed, which consists of the status of cooling unit valves calculating model, the strip segment tracking model, and the top surface temperature model under different heat transfer conditions. What is more, a rule and data driven hybrid intelligent identification algorithm is developed combining the case-based reasoning, rule-reasoning with the neural network. The tests using real industrial data of a steel plant have been conducted and indicated that the proposed strip coiling temperature model has made a great contribution to the prediction precision of the strip coiling temperature during the laminar cooling process.