烧结过程的运行性能是生产效率和能源利用的综合表现.运行性能评价是保持烧结过程的运行性能处于最优等级的前提.考虑到时间序列数据的冗余,提出一种基于粒度聚类的铁矿石烧结过程运行性能评价方法.首先,利用单因素方差分析方法选取影...烧结过程的运行性能是生产效率和能源利用的综合表现.运行性能评价是保持烧结过程的运行性能处于最优等级的前提.考虑到时间序列数据的冗余,提出一种基于粒度聚类的铁矿石烧结过程运行性能评价方法.首先,利用单因素方差分析方法选取影响运行性能等级的检测参数;然后,采用多粒度区间信息粒化实现检测参数时间序列数据的降维,并进行粒度聚类,得到聚类标签;最后,以聚类得到的聚类标签为输入,利用随机森林算法进行运行性能等级评价.利用实际钢铁企业的运行数据进行实验,构建两个对比实验,分别采用基于时间序列数据聚类(Time series data clustering,TSDC)方法和基于时间序列特征聚类(Time series feature clustering,TSFC)方法.实验结果表明,该方法为有效评价烧结过程的运行性能提供了一套可行方案,为操作人员提升烧结过程运行性能提供了有力的指导.展开更多
In the process of coal mine drilling,controlling the rotary speed is important as it determines the efficiency and safety of drilling.In this paper,a linear extended state observer(LESO)based backstepping controller f...In the process of coal mine drilling,controlling the rotary speed is important as it determines the efficiency and safety of drilling.In this paper,a linear extended state observer(LESO)based backstepping controller for rotary speed is proposed,which can overcome the impact of changes in coal seam hardness on rotary speed.Firstly,the influence of coal seam hardness on the drilling rig’s rotary system is considered for the first time,which is reflected in the numerical variation of load torque,and a dynamic model for the design of rotary speed controller is established.Then an LESO is designed to observe the load torque,and feedforward compensation is carried out to overcome the influence of coal seam hardness.Based on the model of the compensated system,a backstepping method is used to design a controller to achieve tracking control of the rotary speed.Finally,the effectiveness of the controller designed in this paper is demonstrated through simulation and field experiments,the steady-state error of the rotary speed in field is 1 r/min,and the overshoot is reduced to 5.8%.This greatly improves the stability and security,which is exactly what the drilling process requires.展开更多
文摘烧结过程的运行性能是生产效率和能源利用的综合表现.运行性能评价是保持烧结过程的运行性能处于最优等级的前提.考虑到时间序列数据的冗余,提出一种基于粒度聚类的铁矿石烧结过程运行性能评价方法.首先,利用单因素方差分析方法选取影响运行性能等级的检测参数;然后,采用多粒度区间信息粒化实现检测参数时间序列数据的降维,并进行粒度聚类,得到聚类标签;最后,以聚类得到的聚类标签为输入,利用随机森林算法进行运行性能等级评价.利用实际钢铁企业的运行数据进行实验,构建两个对比实验,分别采用基于时间序列数据聚类(Time series data clustering,TSDC)方法和基于时间序列特征聚类(Time series feature clustering,TSFC)方法.实验结果表明,该方法为有效评价烧结过程的运行性能提供了一套可行方案,为操作人员提升烧结过程运行性能提供了有力的指导.
基金supported by the National Natural Science Foundation of China under Grant Nos.62373334,62273317,and 61973286the 111 Project under Grant No.B17040the Fundamental Indoor Funds for the Central Universities,China University of Geosciences under Grant No.2021063.
文摘In the process of coal mine drilling,controlling the rotary speed is important as it determines the efficiency and safety of drilling.In this paper,a linear extended state observer(LESO)based backstepping controller for rotary speed is proposed,which can overcome the impact of changes in coal seam hardness on rotary speed.Firstly,the influence of coal seam hardness on the drilling rig’s rotary system is considered for the first time,which is reflected in the numerical variation of load torque,and a dynamic model for the design of rotary speed controller is established.Then an LESO is designed to observe the load torque,and feedforward compensation is carried out to overcome the influence of coal seam hardness.Based on the model of the compensated system,a backstepping method is used to design a controller to achieve tracking control of the rotary speed.Finally,the effectiveness of the controller designed in this paper is demonstrated through simulation and field experiments,the steady-state error of the rotary speed in field is 1 r/min,and the overshoot is reduced to 5.8%.This greatly improves the stability and security,which is exactly what the drilling process requires.
