Preprocessing of operation data in heating furnace
Chai Tian-you · Control theory & applications · 2012
Because of the complex environmental interferences,the operation data of a heating furnace is disturbed or even lost in measuring;this deteriorates the accuracy and stability of the control system,or even causes potential security risks in production.To deal with this problem,we propose a preprocessing system for the operation data of a heating furnace.It employs the self-adaptive fuzzy neural network(FNN) method to predict the immeasurable data,provides the data-filtering,and rejects abnormal data by case-based reasoning.It uses the case-based reasoning(CBR) method to build a new mechanism for data replacement and modification.This intelligent preprocessing system has been successfully applied to a heating furnace in an iron-and-steel company,achieving desirable production results.