欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
为了有效地解决当前加热炉能源消耗高、控制精度差、控制滞后等问题,针对步进式加热炉的工艺特点,提出了加热炉燃烧过程的智能控制策略,即模糊RBF网络自学习和自寻优功能,并结合动态PID反馈补偿策略。经试验表明,该系统不仅保证了在工况波动下的炉温控制精度,提高升降温速度,减少吨钢燃耗、电耗和钢坯烧损,而且提高了加热炉的生产能力。
英文摘要：
In order to efficiently solve such the problems in the combustion process of reheating furnace as the high consumption of energy,the poor precision and time-delay of the temperature control.etc.,an intelligent control strategy of the combustion process of reheating furnace was proposed,according to the technical characteristics of walking beam reheating furnace,namely Fuzzy-RBF networks self-learning and the optimization function,and the dynamic PID feedback compensation strategy of reheating furnace.The results show,the system not only can ensure the accuracy of the furnace temperature controlled,increases the speed of temperature adjustment and reduces the energy consumption,electricity consumption and the billet combustion loss,but also can effectively improve production capacity.
同期刊论文项目
同项目期刊论文
Effect of Extrusion Ratio on Microstructure and Mechanical Properties of As-cast AZ91D Magnesium All
Effects of Multiple Plastic Deformations on Microstructure and Mechanical Properties of 7A04 Ultra-h
Influence of Plastic Deformation on Mechanical Properties and Microstructure of Annealed ZL102 Alloy
Modelling of Microstructure Evolution In AISI 5140 Steel Triple Valve Forming Under Multi-Way Loadin
Influence of Solution Treatment on Impact Toughness and Microstructure of Cobalt-free Maraging Steel
Microstructure evolution of different loading zones during TA15 alloy multi-cycle isothermal local f
Mechanism of unequal deformation during large-scale complex integral component isothermal local load
期刊信息
位置：