基于规则学习的炼钢-连铸钢包选配方法

针对炼钢-连铸生产钢包选配时，钢包属性众多，且选配目标相互冲突难以同时满足的现状，通过一阶规则学习确定钢包温度最高、钢包使用次数最多、钢包材质等级最低和钢包下水口数量最小为性能指标，以钢包温度、使用次数、钢包材质、钢包水口使用次数、滑板和框架使用次数为约束，为每个炉次决策钢包，建立钢包选配模型.通过最小一般泛化法给出了钢包选配规则，提出了基于规则优先级的启发式钢包选配方法.实际数据仿真与实际应用结果表明，所提方法减少了在线钢包数量和日钢包维护次数，提升了炉次生产效率.

Steelmaking Continuous Casting Ladle Matching Method Based on Rule-Learning

In steelmaking-continuous casting ladle matching， the ladle properties are numerous and the targets are difficult to meet at the same time. The performance indicators are established by first-order rule-learning to maximize the ladle temperature and ladle use times， minimize the ladle material grade and nozzle number. The ladle temperature， life， material， nozzle， skateboard and frame use times are constraints. The selection rules of ladle are given by minimal generalization method. The method of heuristic ladle selection based on rule priority is proposed. The actual data simulation and applying results show that the proposed method can improve the production efficiency and the number of online ladle and ladle maintenance per day can be reduced.