【作者】 金迪；

【导师】 邵诚；

【作者基本信息】 大连理工大学 ， 控制理论与控制工程， 2005， 硕士

【摘要】 钢坯的加热过程和轧制过程是热轧生产线上非常重要的两个生产环节,加热炉需要将钢坯加热到满足粗轧机轧制工艺要求的温度分布,粗轧机则需要根据生产要求将加热好的钢坯轧制成指定规格的产品,这两者是热轧生产线上的主要耗能设备。 由于以往实际生产和理论研究均把加热炉和粗轧机作为两个独立的生产设备进行控制,割裂了两者在生产过程上的前后连续性和在生产能耗上的相互影响性,针对每一个设备的控制即使保证了其自身能耗的最小化,也不能实现将这两者作为一个整体来看待的整个热轧生产线的能耗最小化。在当前世界能源日益匮乏的情况下,结合当前热轧过程中存在的能耗浪费过大、钢坯加热质量不好、轧制安全难以保证的实际问题,本文从以下几个方面着手,试图解决上述问题。 首先,本文从加热炉和钢坯之间的热交换机理入手,以加热炉能耗最小、钢坯损耗最小、钢坯出炉温度与期望温度之差最小为目标函数,利用基于专家经验的炉温优化调整策略寻求钢坯在加热炉内的最佳温升曲线以及与此相对应的最佳炉温分布曲线,从而得到了最优的炉温预设定曲线,实现了炉温的优化设定,减少了加热能耗的浪费。 其次,针对目前加热炉和粗轧机的分离控制带来的生产信息难以共享、钢坯的加热过程难以动态调整而造成的能耗浪费过大、粗轧机轧制安全难以保障等问题,提出了基于轧制信息反馈的加热炉综合优化控制策略,利用模糊控制和神经网络的方法,将粗轧机一侧的能够反映钢坯加热质量好坏的生产信息,如粗轧机的轧制力、钢坯的温度等,反馈到加热炉一侧并计算出炉温设定值的补偿量,从而能够根据钢坯的加热状况动态地调整后续钢坯的加热过程,减少了能耗浪费,保障了轧制安全。 另外,在文中提出了将热轧过程中的质量指标与经济指标相结合的综合优化指标,阐述了基于生产目标的热轧过程综合优化控制策略的基本思想,并通过仿真实验验证了控制策略的有效性。更多还原

【Abstract】 The heating process and rolling process of slab are very important procedures in hot rolling production line. Reheating furnace should heat the slab to the temperature distribution that is needed by the rolling technology of roughing mill, and roughing mill should roll the slab into the product with the desired dimension. Reheating furnace and roughing mill are two main energy-consuming facilities in hot rolling production line.Because the practical production and theoretical research in the past treat reheating furnace and roughing mill as two separate facilities, which dissevers the continuity of production process and the interaction on energy consumption of the two facilities, even though the minimal energy consumption may be achieved in a single facility, there is no way to guarantee the total energy consumption minimization of the two facilities as a whole. Now in the condition of world energy resource deficiency, there are still some problems to be solved, such as exceeding energy consumption, low heating quality of slab, the difficulty of guaranteeing rolling security, so this paper tries to give solutions to the mentioned problems from the following several aspects.First of all, start with the heat exchange mechanism, form an objective function whose objective is to make the energy consumption of the reheating furnace, the burning loss of the slab and the slab temperature difference between the expectation value and actual value at the exit of the furnace minimized. A furnace temperature optimizing adjustment strategy based on the expertise of skilled workers is used to hunt the optimal temperature rise curve of the slab and the corresponding optimal furnace temperature distribution curve, and then the optimizing setting of furnace temperature is realized, the energy consumption of heating process is reduced.Secondly, aiming at the difficulty of information sharing between reheating furnace and roughing mill which is brought by the separate control of the two facilities, and the problems of exceeding energy consumption and low security of rolling process given by the difficulty to adjust the heating process of slab dynamically, this paper presents a comprehensive optimizing control strategy of reheating furnace based on the rolling information feedback. In the presented strategy, fuzzy control and neural network are used to feed roll force and slab temperature of therolling process back to reheating furnace and the concrete furnace temperature setting compensation value can be worked out. So that the heating process of slab can be adjusted dynamically according to the heating quality of the slab, and energy consumption can be reduced, the rolling security can be ensured as well.In addition, this paper puts forward a comprehensive optimizing index which combines the quality index with the economy index in hot rolling process, and expounds the fundamental idea of production-oriented comprehensive optimizing control strategy of hot rolling process. Simulation results are provided to prove the effectiveness of the comprehensive optimizing control strategy.更多还原