基于遗传算法的温度传感器布置优化

doi:10.16180/j.cnki.issn1007-7820.2021.09.004

摘要/Abstract

摘要：

温度场分布信息在工业应用中反映了工业设备的内部运行状态,有助于制定控制策略并确保工业设备运行的安全性。针对钢铁冶炼设备中的链篦机鼓风干燥段温度场检测的局限性,文中提出了一种解决温度传感器布置的最佳位置和数量的方法。采用传热学理论建立了鼓风干燥段数学模型,通过计算流体动力学获得鼓风干燥段理论温度场。设计评价传感器布点位置优劣的目标函数,采用遗传算法进行求解,得到温度传感器布点数量和位置的最优解。采用数值模拟的方式验证该方案的效果,结果显示采用径向基函数重构温度场时,优化后的温度场较优化前平均绝对误差提高了30.90%,模型命中率从99.88%提升到了99.99%。

关键词: 球团链篦机, 鼓风干燥段, 传感器布置优化, 温度场重构, 遗传算法, 径向基函数

Abstract:

The temperature field distribution information reflects the internal operating state of industrial equipment in industrial applications, which helps to formulate control strategies and ensure the safety of industrial equipment operation. In view of the limitation of UDD section temperature field detection of chain grate in the iron and steel smelting equipment, a method is proposed to solve the problem of the optimal position and number of temperature sensor layout. A mathematical model of the UDD section is established using heat transfer theory, and the theoretical temperature field of the UDD section is obtained through computational fluid dynamics. An objective function for evaluating the location of sensor placement is designed and calculated using genetic algorithm to obtain the optimal solution for the number and location of temperature sensors. The effect of the scheme is verified by numerical simulation. The results show that when the radial basis function is used to convert the temperature field, the temperature field after optimization is increased by 30.90% when compared with the average before optimization, and the model hit rate is increased from 99.88% to 99.99 %.

Key words: pellet chain grate, updraft drying section, sensor location optimization, temperature field reconstruction, genetic algorithm, radial basis function

中图分类号:

TP301.6

修晓波,李伯全,周峰. 基于遗传算法的温度传感器布置优化[J]. 电子科技, 2021, 34(9): 17-23.

XIU Xiaobo,LI Boquan,ZHOU Feng. Optimization of Temperature Sensor Location Based on Genetic Algorithm[J]. Electronic Science and Technology, 2021, 34(9): 17-23.

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参数	数值
染色体代表	传感器坐标组合
最大代数	1 000
变异概率	0.05
种群大小	100