PCA and neural networks-based soft sensing strategy with application in sodium aluminate solution

Component concentration of sodium aluminate solution is an important quality index for alumina production. In this article, we propose a new on-line soft sensing strategy for measuring component concentration of sodium aluminate solution. With this method, on-line control can be realised in aluminate production plants. Several advance techniques are used, such as principal component analysis (PCA), neural modelling and the least square algorithm. Industry experiments are conducted in the alumina production process and the results show the effectiveness of this method.