A methodology for integrated study and optimization of the heating systems in conveyer roasting machines

Abstract

In pellet production, it is possible to significantly improve the performance of the equipment and to eliminate ineffective approaches by means of a new methodology for the integrated investigation and optimization of the heating parameters in the conveyer roasting of iron-ore pellets. This methodology includes analysis of the heating equipment and an optimization criterion based on a systems approach; integrated methods of investigating individual system components and the technology as a whole; improved mathematical models; the formulation and solution of optimization problems; and engineering principles for an automatic control system based on up-to-date information technology. The performance of roasting machines is improved by modifying the heating systems, which make the main contribution to the economics of production. In particular, the productivity is improved, and the fuel and power consumption is reduced, with specified pellet quality. The overall (global) optimization criterion is maximization of the economic benefit E = E pr + E fu + E po max, where E pr , E fu , and E po are the economic effects of increasing the productivity, reducing fuel consumption, and reducing power consumption, respectively. Calculation of the economic effect by the standard method, using the actual initial data, shows that, if all the characteristics are improved by the same proportion, the greatest contribution to the optimization criterion in financial terms (up to 70%) is due to increase in roasting-machine productivity. If we resolve the optimization criterion into its components (Fig. 1), technological analysis indicates that the economic benefit is determined by the following factors: 1) the basic design components; 2) the heating parameters of the pellet bed; 3) the structure of the heating-system components. The structure and performance of the roasting machines are also determined by the initial characteristics of the ore, the requirements on product quality, and the efficiency of the automatic control system. In view of the complexity of the system, stage-bystage optimization is employed. In the first stage, the basic design components of the system (the design choices determining the structure of the system) are investigated and optimized, including the organization