Study On Energy Measurement Of Iron And Steel Industry Based On Kalman Filter

Nowadays, the supply of energy resources has become increasingly tense, and as an energy intensive industry, the iron and steel industry will face a severe energy situation. Most of the Chinese iron and steel enterprises have a big gap in energy consumption level with the international advanced enterprises, therefore, reducing energy consumption has great potential. Based on the iron and steel production, this thesis puts forward the energy media measurement problem and designs the solving method for this problem based on the Kalman Filter Principle to realize accurate and elaborate measurement of energy data, so as to improve energy efficiency, reduce production costs, guide enterprise production and improve enterprise revenue. The main contents of this thesis are as follows:(1) Taking the production process in iron and steel enterprises as the research background, this thesis puts forward the problem of energy media measurement. After comparisons of existing energy measurement evaluation indicators, this thesis chooses the most significant energy media consumption as the research object of energy measurement problem, and discusses the method in the dimension of process, production lines and products to measure energy media consumption data. Considering to the characteristics of the energy data collection devices, for the energy media measurement problems in the dimensions of process and production lines, this thesis designs allocation method; for the energy media measurement problems in the product dimension, this thesis makes use of single consumption relations between products and production lines, and then designs multiple linear regression method.(2) Because of the error existing in the original energy measurement data and the insufficient of the multiple linear regression method, energy media consumption data is lack of accuracy, therefore, this thesis proposes to use the Kalman Filter to estimate energy media consumption data, so as to achieve more precise energy media consumption data.(3) In order to solve the problems existed in practical application of Kalman Filter, this thesis proposes two adaptive strategies, that is, generalized least square method to modify state transition matrix and the principle of variance compensation to modify state disturbance noise, to realize the improvement of Adaptive Kalman Filter. These improvements can deal with model parameters and noise design efficiently, with which the filter distortion, even the divergence can be avoided, and improve filtering accuracy is improved.(4) Based on the practical demand of the iron and steel enterprises, the iron and steel enterprise energy measurement system is designed. The relational database of the energy measurement system is designed, the function module designs of energy allocation, consumption metering, consumption query are achieved, and the development of human-computer interface is completed.