Application of Least Square Support Vector Machine with Adaptive Particle Swarm Parameter Optimization in Grate Pressure Optimization Setting of Grate Cooler

Grate cooler is an important equipment in the process of new dry process cement production, The grate down pressure of the grate cooler is an important indicator reflecting the clinker cooling effect of the grate cooler. When the pressure under the grate of the grate cooler is stable within a reasonable range, on the one hand, the grate cooler can maintain the highest cooling effect, and on the other hand, the maximum waste heat can be recovered to ensure the normal operation of the kiln system. Therefore, a method of optimizing the set value of the grate cooler pressure based on the least squares support vector machine algorithm based on adaptive particle swarm parameter optimization is proposed, through the adaptive particle swarm optimization algorithm to achieve the least squares support vector machine model parameters and optimization calculation, Solve the limitation of the prediction accuracy of the least squares support vector machine by the value of the model parameters, furthermore, the optimal setting value of the grate down pressure of the grate cooler is reasonably given to ensure the cooling effect and clinker quality of the grate cooler.