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Optimal Heating in Heat-Treatment Process Based on Grey Asynchronous Particle Swarm Optimization

机译:基于灰色异步粒子群算法的热处理过程最佳加热

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摘要

To ensure plate heating quality and reduce energy consumption in heat-treatment process, optimal heating for plates in a roller hearth furnace was investigated and a new strategy for heating procedure optimization was developed. During solving process, plate temperature forecast model based on heat transfer mechanics was established to calculate plate temperature with the assumed heating procedure. In addition, multi-objective feature of optimal heating was analyzed. And the method, which is composed of asynchronous particle swarm optimization and grey relational analysis, was adopted for solving the multi-objective problem. The developed strategy for optimizing heating has been applied to the mass production. The result indicates that the absolute plate discharging temperature deviation between measured value and target value does not exceed ± 8 ℃, and the relative deviation is less than ± 0.77%.
机译:为了确保板的加热质量并减少热处理过程中的能源消耗,研究了辊底式炉中板的最佳加热方式,并开发了优化加热程序的新策略。在求解过程中,建立了基于传热力学的板温预测模型,以假定的加热程序计算板温。此外,分析了最佳加热的多目标特征。并采用异步粒子群优化和灰色关联分析相结合的方法解决了多目标问题。优化加热的已开发策略已应用于批量生产。结果表明,测量值与目标值之间的绝对印版排出温度偏差不超过±8℃,相对偏差小于±0.77%。

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