Research On Modeling Of Temperature Rise Of Main Motor Of Hot Rolling Mill And Optimization Of Cooling System

Along with the ongoing process of the adjustment of industrial structure,overcapacity of the traditional heavy industry has become an issue of deep concern,the direct consequence of which is energy waste.Taking hot tandem rolling mill of a steelmaking company as case study,the practical work load of it is far below the rated power,while its forced-air cooling motor still runs at full capacity regardless of any change of heat load or season.In terms of energy saving policies advocated by the State or the company's own interests,the research on energy-saving on existing cooling fan and motor has important significance.This paper focused on the establishment of temperature rise model of main motor and optimization of cooling system.This research proposed a modeling approach for temperature rise of main motor of hot rolling mill based on mechanism analysis and statistical analysis of field data.Least squares regression algorithm and support vector machine regression algorithm are used for parameter identification.Comparison results indicate that support vector machine regression algorithm is more flexible and can be for outlier detection.An equivalent current model is established and used to calculate the frequency according to the temperature rise model.Estimation error was analyzed and improved with dependent variable substitutions.Numerical methods were used to solve implicit function of frequency.The results showed that the predicted temperature rise and frequency agree well with the reference data.The hardware and software implementation of the algorithm and safe strategy are also included.