为了提高抛丸设备的自动化控制与数据管理水平,本文基于数据采集与监视控制系统(Supervisory Control and Data Acquisition,SCADA)、数据库技术、网络与信息技术对抛丸设备进行智能化自动控制与数据监测。首先,合理的机械结构设计与电...为了提高抛丸设备的自动化控制与数据管理水平,本文基于数据采集与监视控制系统(Supervisory Control and Data Acquisition,SCADA)、数据库技术、网络与信息技术对抛丸设备进行智能化自动控制与数据监测。首先,合理的机械结构设计与电气控制设计是重要的前提。其次,基于SCADA对抛丸设备进行人机交互控制、实时数据监控、历史数据采集与存储、数据分析与可视化为系统主要功能。最后,系统平台可以利用服务器进行本地化部署与网络化访问。本文详细介绍了系统平台的架构、功能、实施过程与相关技术,来实现对抛丸设备的控制与管理。展开更多
The permeability index is one of the important production indicators to monitor the operation of blast furnace.It is crucial to grasp the trends of changes in the new permeability index in time.For the complex vibrati...The permeability index is one of the important production indicators to monitor the operation of blast furnace.It is crucial to grasp the trends of changes in the new permeability index in time.For the complex vibration spectrum of the permeability index,a prediction model of the permeability index based on the VMD-PSO-BP(variational mode decomposition-particle swarm optimization-back propagation)method was proposed.Firstly,the key factors that affect the permeability index of blast furnace were studied from multiple perspectives.Then,the permeability index was divided into multiple sub-modes based on the difference of frequency bands by the VMD algorithm,and a PSO-BP prediction model was established for each sub-mode.Finally,the prediction results of each sub-mode were summed to obtain the final one.The results show that the composite prediction accuracy by using the VMD algorithm is 3%higher than that of the traditional prediction method,which has better applicability.展开更多
文摘为了提高抛丸设备的自动化控制与数据管理水平,本文基于数据采集与监视控制系统(Supervisory Control and Data Acquisition,SCADA)、数据库技术、网络与信息技术对抛丸设备进行智能化自动控制与数据监测。首先,合理的机械结构设计与电气控制设计是重要的前提。其次,基于SCADA对抛丸设备进行人机交互控制、实时数据监控、历史数据采集与存储、数据分析与可视化为系统主要功能。最后,系统平台可以利用服务器进行本地化部署与网络化访问。本文详细介绍了系统平台的架构、功能、实施过程与相关技术,来实现对抛丸设备的控制与管理。
基金supports from the National Natural Science Foundation of China Youth Fund Project(52004096).
文摘The permeability index is one of the important production indicators to monitor the operation of blast furnace.It is crucial to grasp the trends of changes in the new permeability index in time.For the complex vibration spectrum of the permeability index,a prediction model of the permeability index based on the VMD-PSO-BP(variational mode decomposition-particle swarm optimization-back propagation)method was proposed.Firstly,the key factors that affect the permeability index of blast furnace were studied from multiple perspectives.Then,the permeability index was divided into multiple sub-modes based on the difference of frequency bands by the VMD algorithm,and a PSO-BP prediction model was established for each sub-mode.Finally,the prediction results of each sub-mode were summed to obtain the final one.The results show that the composite prediction accuracy by using the VMD algorithm is 3%higher than that of the traditional prediction method,which has better applicability.
