Research On The Method Of Alumina Powder Flow Soft Sensor In The Process Of Alumina Conveyor

Alumina conveying is one of the most important parts in the process of electrolytic aluminum plant for the production of alumina.The transportation technique is straight influence the stabilization of the production of alumina and the consumption per unit of alumina.Along with widely application of hyper dense phase conveying system and the improvement of automatic level day by day,through optimize and control to ensure the quality of product,and then realizing consumption reduction and Enlarging has already become the goal that enterprises have pursued.For the goal more craft parameters and variables are needed to be measured on-line,and alumina powder flow in electrolytic aluminum plant is one of the main parameters.The soft sensor technology have been presented itself as a new technology that settles the main parameter measured on-line, improving the productivity benefit and guarantee the quality of production in recent years.On the background of the aluminium transport course in electrolytic aluminum plant,the soft sensor technology have been presented to measure the flow of alumina powder in electrolytic aluminum plant because of the difficult problem that alumina powder flow can not be precise measured on-line for import instruments cost expensive and the precision of domestic instrument is relatively low.At first on the basis of further investigate the craft of Alumina conveying and the measured information which the automation system can be offered the wind pressure and the wind flux of the centripetal fan are chosen as assistant variable to estimate the flow of alumina powder.Secondly on the basis of the actual industry's on-the-spot data PLS,RBF and LS-SVM simulation research has been carried out with the single model soft sensor of alumina powder flow. And then considering the impact of model parameter chosen on model performance Pso algorithm has been utilized to confirm its parameters and achieved higher precision and better generalization ability forecast model.It is difficult for single model to describe global properties of complex system,and multi-point of complex systems in work is taken into account,so a multi-modeling soft sensor based on double layers intelligent structure is proposed in this paper,in which fuzzy c-means clustering is classification layer,and many PLS,may RBF neural network,many LS-SVM and PLS+RBF+LS-SVM are modeling layers.The degrees of membership are used for combining the output of sub-models to obtain the finial result which is the measured value of estimated parameters,and then the model of alumina powder flow is founded. The result of simulation research proves that the single model and multi-modeling modeling technique all have better generalization ability and higher precision accuracy and different multi-models are superior.The soft sensor technique of LS-SVM is more suitable model that could be revision on-line and proved that this technique is feasible and effective,at the same time the soft sensor technology have offered the basis for the real-time monitoring of alumina powder flow in the field of the industry of aluminium.