A Design and Type Selection Method of Steel Ball Coal Mill Based on Genetic Optimization Algorithm

Abstract

A steel ball coal mill design and type selecting method based on a genetic optimized algorithm comprises the following steps: 1, parameters of a specific steel ball coal mill are designed; 2, an optimal model of steel ball coal mills is selected from the designed model of steel ball coal mills and existing models; 3, optimal operation condition parameters of the steel ball coal mill are determined; and 4, operation of a pulverizing system of the steel ball coal mill is guided. In the invention, according to theoretical foundation, and on the basis of a minimum pulverizing unit consumption principle, parameter automatic optimization searching is carried out through utilization of a genetic algorithm; a optimal economic operation guidance is given; a genetic algorithm control flow is designed; optimal running state parameters beta, gama and tm are calculated; outputting of the pulverizing system is raised; the system safety and economic operation are ensured; the production quality and the production efficiency of the ball mill are raised; energy is saved; and competitiveness of products on the market can be raised, thereby bringing more benefits for enterprises.

Description

technical field [0001] The invention relates to the technical field of system optimization design, in particular to a method for designing and selecting steel ball coal mills based on genetic optimization algorithms. Background technique [0002] As an important auxiliary system in the thermal power generation unit, the pulverization system is a large power consumer of the entire unit. Optimizing the operation of the pulverization system and reducing the plant power consumption of the pulverization system are important means of energy saving for thermal power units. The steel ball coal mill is widely used as an important equipment of the pulverization system, but in the actual operation process, it is difficult to ensure that the coal mill operates at the best economic output point, which will increase the power consumption and waste energy per unit of coal grinding. This is because the coal pulverizer system is a multi-input, multi-output complex system with strong nonlinea...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a method for the design and selection of steel ball coal mills based on genetic optimization algorithms, which is used to solve the problem of excessive selection margin of steel ball coal mills, mismatched parameters, and non-standard size of steel ball coal mills. Designing Questions That Have No Quantitative Basis

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