Algorithm of acid temperature setup model based on the CBR

In the continuous pickling line, the acid temperature setup accuracy was low, which not only caused excessive pickling defects, but also caused excessive consumption of hydrochloric acid and a decrease in pickling efficiency. In order to solve this problem, the acid temperature setup model based on case-based reasoning (CBR) technology was established by using a large amount of production data with good temperature setting precision. After the model was put into operation on a 1450mm pickling and rolling line, the average pickling defect ratio decreased from 14.99904% to 11.7332% and the fluctuation range of the pickling defect ratio was effectively controlled. Practical application showed that the setup accuracy of the acid temperature model was effectively improved. As the number of strip steel production increases, the model has the adaptive ability to change with the working conditions, which is suitable for industrial promotion.