Optimization Analysis of Power Coal-Blending Model and Its Control System Based on Intelligent Sensor Network and Genetic Algorithm

Abstract

Research and optimization of the coal-blending system can greatly improve the variety diversity and quality stability of finished coal. However, the existing research on the coal-blending system has some defects, such as fuzzy ash content of coal-blending warehouse products and excessive error of the coal-blending ratio determined by artificial experience, which brings many disadvantages and difficulties to the efficient and stable production of the coal preparation plant. The genetic algorithm and intelligent sensor network are relatively advanced technologies at present. Therefore, the optimization analysis of the coal-blending model and its control system based on the intelligent sensor network and genetic algorithm has become a research hotspot. This paper first introduces the basic theory of the genetic algorithm and intelligent sensor network and their application in coal-blending research, then establishes an optimized dynamic coal-blending model based on the intelligent sensor network and genetic algorithm, and analyzes its application effect. The research results show that the coal quality prediction model can be mined from coal quality data and coal-blending data by using the genetic algorithm and ideas, and the monitoring system based on the intelligent sensor network can monitor the abnormal state anytime and anywhere. Compared with the traditional coal-blending method, the average error is 3.33%, and the accuracy is improved by 4.82%.