Research on Soft Sensor Model for Slab Temperature in Reheating Furnace
加热炉钢坯温度软测量模型研究

A slab temperature neural network soft sensor model based on fuzzy clusteringis studied.The approach consists of two components:an FCM(Fuzzy C-Means)clustering,which classifies training objects into a couple of clusters,and a distributed RBF(RadialBasis Unction)network,which is used to train each cluster.In the online stage,the valuesof membership are computed using an adaptive fuzzy clustering algorithm for the new object.The proposed approach has been applied to the slab temperature estimation in an actualreheating furnace.Simulations show that the approach is effective.