Research Of Process Monitoring Method For The Operation Evaluation Of Reheating Furnace

The production process of modern industry tends to be large-scaled and complicated constantly. Once the control system or equipment breaks down, it will cause huge losses. Therefore, research of the real-time monitoring and diagnosis for production process is particularly important. Process monitoring and diagnosis method based on multivariate statistical method have made great progress in theory and practical application nowadays. The content of this paper is derived from the multivariate statistical method.In this paper, it is not used for fault diagnosis but it is applied to the on-line monitoring of operation parameters for reheating furnace process as a basis of improving the online mathematical model of equipment.In a word, it is process monitoring method for the operation evaluation.Accurate mathematical models play an important role in the process of reheating furnace. Total heat exchange factor method has been widely used in online control mathematical models in reheating furnace for its simple algorithm and small computational cost. However, total heat exchange factor which is the key parameter in this method is related to the production process of operation (heat transfer and operating parameter). In this paper, the process monitoring methods based on the evaluation of multivariate statistics provide a basis for the on-line calibration of total heat exchange factor. The main research is as follows:(1) The mathematical model of the reheating furnace based on total heat exchange factor and the influence of the mathematical model parameters are analyzed. And then the relationship between operation and total heat exchange factor is determined.(2) Process monitoring methods based on principal component analysis (PCA) and independent component analysis (ICA) are introduced.The two methods regard the reheating furnace process as the Gauss distribution and non Gauss distribution and then make experiment research and comparative analysis for the operating parameter of the heating zone. Two classes of slabs results prove the effectiveness of the methods.(3) Process monitoring methods based on canonical variate-independent component analysis (CV-ICA) is introduced. Reheating furnace process is considered as a dynamical process here. Therefore, we apply CVA to solution the canonical variate space and do ICA on the space. The experimental results show that the method is superior to PCA and ICA methods.(4) According to the operation monitoring results, we make online calibration for the continuous production process of abnormal slabs.As a result, the mathematical models which have been calibrated have more accurate results compared to the original mathematical models. Therefore, the monitoring methods of this paper have a certain practical significance in practical production.