基于自适应粒子群算法的玻璃澄清环境评价模型分析

Quantitative Evaluation of Clarification Environment of Glass Melting Process Based on Adaptive Particle Swarm Optimization

玻璃熔制过程是玻璃生产中的高耗能单元,其过程涉及的变量复杂,在实际生产中常因难以合理调节生产参数而造成生产环境不稳定进而导致产品质量缺陷。为了评估澄清环境,基于前人对玻璃液流规律的研究,对气泡逸出难易程度和澄清时间进行定量化分析,建立澄清环境评估模型,并采用自适应变异粒子群算法对模型求解,将优化后的参数应用于实际生产调试,得到非常满意的结果,从而验证模型的正确性。

In the process of glass production, Glass melting is a high energy consumption unit. Because of the many variables involved in the process, it is difficult to adjust the production parameters reasonably in the actual production, which cause the instability of the production environment and lead to the instability of the product quality. In order to evaluate the clarified production environment, the flow rule of glass flow was analyzed. And based on the quantitative calculation of bubble rise time and clarification time, a clarification condition evaluation model was established, and adaptive mutation particle swarm optimization algorithm was applied to solve the model. The optimized parameters were run in the actual production debugging, and a very satisfactory result was obtained, which verified the correctness of the model.