WO2022183631A1 - 一种基于数据中间件的高炉专家规则知识库管理系统 - Google Patents

一种基于数据中间件的高炉专家规则知识库管理系统 Download PDF

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WO2022183631A1
WO2022183631A1 PCT/CN2021/101694 CN2021101694W WO2022183631A1 WO 2022183631 A1 WO2022183631 A1 WO 2022183631A1 CN 2021101694 W CN2021101694 W CN 2021101694W WO 2022183631 A1 WO2022183631 A1 WO 2022183631A1
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blast furnace
management system
inference engine
data
expert
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梅超凡
叶理德
欧燕
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中冶南方工程技术有限公司
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    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/02—Knowledge representation; Symbolic representation
    • G06N5/022—Knowledge engineering; Knowledge acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
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    • Y02P90/30—Computing systems specially adapted for manufacturing

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  • the invention relates to a blast furnace expert system, in particular to a blast furnace expert rule knowledge base management system based on data middleware.
  • the purpose of the present invention is to provide a blast furnace expert rule knowledge base management system based on data middleware with high reusability, good adaptability and more flexibility. For this reason, the concrete technical scheme that the present invention adopts is as follows:
  • a blast furnace expert rule knowledge base management system based on data middleware which can include an inference engine management system database, an inference engine management system, a rule base variable configuration module, data middleware and a blast furnace operating state database, wherein the inference engine
  • the management system database is used to store blast furnace expert knowledge rules; the inference engine management system configures and maintains the blast furnace expert knowledge rules through the rule base variable configuration module, and obtains information from the blast furnace operating status through the data middleware.
  • the database reads the blast furnace operation data, performs matching and inference with the inference engine management system database, and then feeds back the furnace type recommendations and furnace condition descriptions matching the rules to the blast furnace operator.
  • the blast furnace expert knowledge rule adopts the form of "condition + adjustment mode & furnace condition description", wherein, the condition includes mode condition and variable condition, and the mode condition includes mode group type, mode group variable and mode group.
  • the adjustment method includes short tuyere, blast furnace temperature, load adjustment, additional coke, alkalinity adjustment, increase of iron times, material line, edge pressure, edge reduction, pressure center, center reduction, adjustment of inlet water temperature and adjustment of inlet water flow .
  • rule base variable configuration module is used to declare the key data in the mode condition and the variable condition, which is the basic part of the knowledge rule of the blast furnace expert.
  • the blast furnace operation data mainly includes: air temperature, air volume, air pressure, carbon consumption reflected by melting loss, heat index, heat load, blanking index and furnace bottom thermocouple temperature.
  • the data middleware includes a configuration file, a configuration file parsing module and a blast furnace operating state database reading module, wherein the configuration file is used to establish a mapping relationship between the variable configuration and the blast furnace operating state database; the configuration The file parsing module is used to read the configuration file into the memory; the blast furnace operation state database reading module is used to read out the corresponding data in the blast furnace operation state database according to the variable configuration information parsed in the memory and return it to the Describe the reasoning engine management system.
  • the present invention adopts the above technical scheme, and has the beneficial effect of decoupling the inference engine and the operation management system related to the blast furnace through the data middleware.
  • a pluggable inference engine management system can be realized by using the blast furnace expert rule knowledge base management system based on the data middleware of the present invention, and it is not necessary to re-develop a whole set of management systems for the blast furnace, and only a small amount of data middleware needs to be developed.
  • the system can be plugged and unplugged, which greatly saves manpower and financial resources; especially for blast furnaces that have been put into production, the invention can be seamlessly applied to the blast furnaces that have been put into production without affecting the operation of the put into production system.
  • FIG. 1 is a schematic structural diagram of a blast furnace expert rule knowledge base management system based on data middleware according to the present invention.
  • FIG. 2 is a functional structure diagram of the inference engine management system in the present invention.
  • FIG. 3 is a functional structure diagram of the data middleware in the present invention.
  • FIG. 1 is a structural diagram of a knowledge base management system for blast furnace expert rules based on data middleware according to an embodiment of the present invention.
  • the blast furnace expert rule knowledge base management system based on data middleware is a key part of the computer network with the blast furnace operating state as the core and other auxiliary systems as the auxiliary. It includes the inference engine management system database, the inference engine management system, and the rule base variable configuration module. , data middleware and blast furnace operation status database.
  • the inference engine management system database stores pattern data, variable data, adjustment mode data and furnace condition description data, which are related to each other using rule numbers to form a series of blast furnace expert knowledge rules. That is, the inference engine management system database is used to store the knowledge rules of blast furnace experts.
  • the blast furnace expert knowledge rule adopts the form of "condition + adjustment method & furnace condition description"; the condition includes mode condition and variable condition; the mode condition includes mode group type, mode group variable and mode group; the adjustment method includes but does not Limited to short tuyere, blast furnace temperature, load adjustment, additional coke, alkalinity adjustment, increase of iron times, material line, edge pressure, edge reduction, center pressure, center reduction, adjustment of inlet water temperature, adjustment of inlet water flow, etc.
  • Figure 2 shows the functional structure diagram of the inference engine management system, which includes condition management and conclusion management.
  • the conditions include mode conditions and variable conditions.
  • the mode conditions can be considered as comprehensive judgments on several specific blast furnace operating parameters. An evaluation of the current operation of the blast furnace is obtained. For example, for the change of the pressure difference in the furnace, the basis for the judgment mainly includes several operating parameters such as air volume, air pressure, and furnace temperature.
  • the machine management system When it is necessary to judge the pressure difference mode in the furnace, reasoning According to the variable configuration of the differential pressure mode, the machine management system reads the corresponding operating data in the blast furnace operating state database for matching, and feeds back the matched expert knowledge conclusions to the blast furnace operation control personnel, so that they can make appropriate adjustments to the operating state of the blast furnace, thereby Improve blast furnace production efficiency and avoid production accidents.
  • the rule base variable configuration module is mainly used to declare the key data in the mode conditions and variable conditions, and is the basic part of the knowledge rules of blast furnace experts.
  • the rule base variable configuration module models some key parameters of blast furnace operation, and stores them in the inference engine management system database to explain the data source for the mode conditions and variable conditions in the blast furnace expert knowledge rule base.
  • Figure 3 is a functional structure diagram of the data middleware, including a variable configuration mapping file, a configuration file parsing module, and a blast furnace operating state database reading module.
  • the variable configuration mapping file is a configuration file that stores the corresponding relationship between the variables in the rule base and the table fields in the blast furnace operating state database in xml file format, and establishes the mapping relationship between the rule variables and the blast furnace operating state database.
  • the configuration file parsing module is used to read the configuration file into the memory, that is, to convert the variable configuration mapping file (xml file) into an executable database query language (SQL statement).
  • the blast furnace operation state database reading module is configured to read out the corresponding data in the blast furnace operation state database according to the variable configuration information parsed in the memory and return it to the inference engine management system. Specifically, the blast furnace operation state database reading module connects to the blast furnace operation state database and executes SQL statements, and encapsulates the execution result as an object and returns it to the inference engine management system as the data basis for inference by the inference engine.
  • the main advantage of the data middleware is that it decouples the inference engine from the operation management system related to the blast furnace.
  • the data-based data-based method of the present invention is used.
  • the knowledge base management system of blast furnace expert rules for middleware can realize a pluggable inference engine management system, without the need to re-develop a whole management system for the blast furnace, and only a small amount of development and configuration of the data middleware can realize the system pluggability The effect, greatly saving manpower and financial resources.
  • the present invention can be seamlessly applied to the blast furnace that has been put into production without affecting the operation of the put into production system.

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Abstract

一种基于数据中间件的高炉专家规则知识库管理系统，其包括推理机管理系统数据库、推理机管理系统、规则库变量配置模块、数据中间件和高炉运行状态数据库，其中，所述推理机管理系统数据库用于存储高炉专家知识规则；所述推理机管理系统通过所述规则库变量配置模块对所述高炉专家知识规则进行配置和维护，以及通过所述数据中间件从所述高炉运行状态数据库读取高炉运行数据，并与所述推理机管理系统数据库进行匹配和推理，进而将与规则匹配的操作炉型建议以及炉况说明反馈给高炉操作人员。该数据中间件使推理机从专家系统中独立出来，形成一个平台化产品，可将其复用于不同高炉，从而节省高炉信息化软件的开发成本。

Description

一种基于数据中间件的高炉专家规则知识库管理系统 技术领域
本发明涉及高炉专家系统，具体地涉及一种基于数据中间件的高炉专家规则知识库管理系统。
背景技术
自20世纪70年代以来高炉炼铁的自动化控制，已经成为冶金行业技术人员重点研究的对象，高炉被公认为是最复杂的冶金反应器之一。为了更好地理解、优化和智能控制高炉炼铁过程，许多从业人员已经对其进行了大量的研究。例如1995年1月25日中国专利局公布的首钢总公司申请专利《人工智能高炉冶炼专家系统方法》(专利号为1097804A)，介绍了一种高炉冶炼专家系统方法，其特点就是将专家知识库、推理机集成进高炉冶炼专家系统。这也是传统的高炉冶炼专家系统的实施方案，也被广泛应用于国内的钢铁厂。而随着时间的推移，传统的高炉冶炼专家系统的弊端开始显现，其主要体现在高炉操作专家系统规则库在经过长时间运行后，不能适应工艺要求的变化，造成传统高炉操作专家系统中的推理机功能模块不能适应需求的变化而逐步被弃用。对于广大钢铁企业来讲重新开发和部署一套全新的高炉操作专家系统代价太大，而独立开发一套推理机管理系统使之应用于已投产的高炉是广钢铁企业的一个更为经济可行的方案。
发明内容
本发明的目的是提供一种复用性高、适配性好、更灵活的基于数据中间件的高炉专家规则知识库管理系统。为此，本发明采用的具体技术方案如下：
一种基于数据中间件的高炉专家规则知识库管理系统，其可包括推理机管理系统数据库、推理机管理系统、规则库变量配置模块、数据中间件和高炉运行状态数据库，其中，所述推理机管理系统数据库用于存储高炉专家知识规则；所述推理机管理系统通过所述规则库变量配置模块对所述高炉专家知识规则进行配置和维护，以及通过所述数据中间件从所述高炉运行状态数据库读取高炉运行数据，并与所述推理机管理系统数据库进行匹配和推理，进而将与规则匹配的操作炉型建议以及炉况说明反馈给高炉操作人员。
进一步地，所述高炉专家知识规则采用“条件+调剂方式&炉况说明”的形式，其中，所述条件包括模式条件和变量条件，所述模式条件包括模式组类型、模式组变量和模式组；所述调剂方式包括短风口、高炉温、调负荷、附加焦、调碱度、增加铁次、料线、压边缘、减边缘、压中心、减中心、调进水温度和调进水流量。
进一步地，其特征在于，所述规则库变量配置模块用于对模式条件和变量条件中的关键数据进行声明，是所述高炉专家知识规则的基础部分。
进一步地，所述高炉运行数据主要包括：风温、风量、风压、熔损反映消耗的炭量、热指数、热负荷、下料指数和炉底热电偶温度。
进一步地，所述数据中间件包括配置文件、配置文件解析模块以及高炉运行状态数据库读取模块，其中，所述配置文件用于建立所述变量配置与高炉运行状态数据库的映射关系；所述配置文件解析模块用于将配置文件读入内存之中；所述高炉运行状态数据库读取模块用于根据内存中解析的变量配置信息将高炉运行状态数据库中相对应的数据读取出来并返回给所述推理机管理系统。
本发明采用上述技术方案，具有的有益效果是：通过数据中间件将推理机与高炉相关的运行管理系统进行了解耦，当高炉的一些工艺参数发生变化，或 厂家希望将推理机应用于不同高炉时，利用本发明的基于数据中间件的高炉专家规则知识库管理系统可实现可插拔的推理机管理系统，而无需为高炉重新开发一整套管理系统，仅需对数据中间件进行少量开发与配置即可实现系统可插拔的效果，大大节省了人力和财力；尤其对于已投产高炉，本发明可无缝应用于已投产高炉而不影响已投产系统的运行。
附图说明
为进一步说明各实施例，本发明提供有附图。这些附图为本发明揭露内容的一部分，其主要用以说明实施例，并可配合说明书的相关描述来解释实施例的运作原理。配合参考这些内容，本领域普通技术人员应能理解其他可能的实施方式以及本发明的优点。图中的组件并未按比例绘制，而类似的组件符号通常用来表示类似的组件。
图1为本发明的一种基于数据中间件的高炉专家规则知识库管理系统的结构示意图。
图2为本发明中的推理机管理系统的功能结构图。
图3为本发明中的数据中间件的功能结构图。
具体实施方式
现结合附图和具体实施方式对本发明进一步说明。
图1为本发明实施例提供的一种基于数据中间件的高炉专家规则知识库管理系统的结构图。基于数据中间件的高炉专家规则知识库管理系统是以高炉运行状态为核心其他附属系统为辅助的计算机网络中的关键部分，它包括推理机管理系统数据库、推理机管理系统、规则库变量配置模块、数据中间件和高炉运行状态数据库。
推理机管理系统数据库存储有模式数据、变量数据、调剂方式数据和炉况说明数据，它们之间使用规则号相互关联组成了一条条高炉专家知识规则。即，推理机管理系统数据库用于存储高炉专家知识规则。高炉专家知识规则采用“条件+调剂方式&炉况说明”的形式；条件包括模式条件和变量条件；其所述模式条件包括模式组类型、模式组变量和模式组；所述调剂方式包括但不限于短风口、高炉温、调负荷、附加焦、调碱度、增加铁次、料线、压边缘、减边缘、压中心、减中心、调进水温度、调进水流量等。
如图2所示为推理机管理系统的功能结构图，包含了条件管理和结论管理，其所述条件包括模式条件和变量条件，模式条件可认为是对特定的几个高炉运行参数进行综合判断得出当前高炉的一种运行的评估，例如针对炉内压差变化，其所判断的依据主要包含风量、风压、炉温等几个运行参数，当需要判断炉内压差模式时，推理机管理系统根据压差模式的变量配置读取高炉运行状态数据库中相应的运行数据进行匹配，将匹配到的专家知识结论反馈给高炉运行控制人员，令其对高炉的运行状态进行适当调整，从而提高高炉生产效率，避免发生生产事故。
规则库变量配置模块主要用于对模式条件和变量条件中关键数据声明，是高炉专家知识规则的基础部分。规则库变量配置模块将高炉运行的一些关键参数进行模型化，并将其存入推理机管理系统数据库，为高炉专家知识规则库中的模式条件与变量条件说明数据来源。
图3为数据中间件的功能结构图，包括变量配置映射文件、配置文件解析模块、高炉运行状态数据库读取模块。其中，变量配置映射文件是以xml文件格式存储规则库中的变量与高炉运行状态数据库中的表字段对应关系的配置文件，建立了规则变量与高炉运行状态数据库的映射关系。配置文件解析模块用 于将配置文件读入内存之中，即，将变量配置映射文件(xml文件)转化为可执行的数据库查询语言(SQL语句)。高炉运行状态数据库读取模块用于根据内存中解析的变量配置信息将高炉运行状态数据库中相对应的数据读取出来并返回给所述推理机管理系统。具体地说，高炉运行状态数据库读取模块连接高炉运行状态数据库并执行SQL语句，将执行结果封装称对象返回给推理机管理系统，作为推理机推理的数据依据。
数据中间件的主要优点在于其将推理机与高炉相关的运行管理系统进行了解耦，当高炉的一些工艺参数发生变化，或厂家希望将推理机应用于不同高炉时，利用本发明的基于数据中间件的高炉专家规则知识库管理系统可实现可插拔的推理机管理系统，而无需为高炉重新开发一整套管理系统，仅需对数据中间件进行少量开发与配置即可实现系统可插拔的效果，大大节省了人力和财力。尤其对于已投产高炉，本发明可无缝应用于已投产高炉而不影响已投产系统的运行。
尽管结合优选实施方案具体展示和介绍了本发明，但所属领域的技术人员应该明白，在不脱离所附权利要求书所限定的本发明的精神和范围内，在形式上和细节上可以对本发明做出各种变化，均为本发明的保护范围。

Claims (5)

  1. 一种基于数据中间件的高炉专家规则知识库管理系统，其特征在于，包括推理机管理系统数据库、推理机管理系统、规则库变量配置模块、数据中间件和高炉运行状态数据库，其中，所述推理机管理系统数据库用于存储高炉专家知识规则；所述推理机管理系统通过所述规则库变量配置模块对所述高炉专家知识规则进行配置和维护，以及通过所述数据中间件从所述高炉运行状态数据库读取高炉运行数据，并与所述推理机管理系统数据库进行匹配和推理，进而将与规则匹配的操作炉型建议以及炉况说明反馈给高炉操作人员。
  2. 如权利要求1所述的基于数据中间件的高炉专家规则知识库管理系统，其特征在于，所述高炉专家知识规则采用“条件+调剂方式&炉况说明”的形式，其中，所述条件包括模式条件和变量条件，所述模式条件包括模式组类型、模式组变量和模式组；所述调剂方式包括短风口、高炉温、调负荷、附加焦、调碱度、增加铁次、料线、压边缘、减边缘、压中心、减中心、调进水温度和调进水流量。
  3. 如权利要求2所述的基于数据中间件的高炉专家规则知识库管理系统，其特征在于，所述规则库变量配置模块用于对模式条件和变量条件中的关键数据进行声明，是所述高炉专家知识规则的基础部分。
  4. 如权利要求1所述的基于数据中间件的高炉专家规则知识库管理系统，其特征在于，所述高炉运行数据主要包括：风温、风量、风压、熔损反映消耗的炭量、热指数、热负荷、下料指数和炉底热电偶温度。
  5. 如权利要求1所述的基于数据中间件的高炉专家规则知识库管理系统，其特征在于，所述数据中间件包括配置文件、配置文件解析模块以及高炉运行状态数据库读取模块，其中，所述配置文件用于建立所述变量配置与高炉运行状态数据库的映射关系；所述配置文件解析模块用于将配置文件读入内存之中；所 述高炉运行状态数据库读取模块用于根据内存中解析的变量配置信息将高炉运行状态数据库中相对应的数据读取出来并返回给所述推理机管理系统。
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