联合收获机知识库数据多表联合查询方法研究  

Multi-table Joint Query Method for Combine HarvesterKnowledge Base Data

作　　者：刘宏新[1,2] 张一鸣 解勇涛 赵一健 郭丽峰 LIU Hongxin;ZHANG Yiming;XIE Yongtao;ZHAO Yijian;GUO Lifeng(College of Engineering,Northeast Agricultural University,Harbin 150030,China;School of Mechanical and Electrical Engineering,Suqian College,Suqian 223800,China)

机构地区：[1]东北农业大学工程学院,哈尔滨150030 [2]宿迁学院机电工程学院,宿迁223800

出　　处：《农业机械学报》2023年第5期150-162,共13页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家重点研发计划项目(2017YFD0700100)。

摘　　要：联合收获机知识库系统使用SQL Server数据库,数据库中的众多数据表具有独立性,便于构建和管理。但当知识库数据量达到一定规模后,对数据表逐一查询不具有可操作性,将全部数据表融合又会导致数据结构混乱、内容表述不清、技术无法实现。针对这一问题,提出联合收获机知识库数据多表联合查询方法。从多角度划分数据表类型,分析联合收获机知识库数据存储结构,设置多表联合数据管理范围;应用SQL(Structured query language)语言将多表信息融合为数据集并存入临时表中,实现多表联合运行;利用人机交互界面将用户查询需求转换成多表联合查询语句,生成查询结果,实现多表近似范围查询和多表精确定位查询。多表联合查询与传统单表知识查询之间的测试结果表明,多表近似范围查询比系统原有的单表近似范围查询节约用户操作时间50%及以上,最高达到90.4%;多表精准定位查询比系统原有的单表精准定位查询节约用户操作时间48.1%及以上,最高达到89.6%。多表联合查询的实现使联合收获机知识库系统具有实用性与可行性,可为同类知识库系统数据管理提供可借鉴的思路和方法。The combine harvester knowledge base system uses the SQL server database,numerous data tables in the database are independent and easy to build and manage.But when the amount of knowledge base data reaches a certain size,querying data tables one by one is not actionable and merging all the data tables will lead to confusion in the data structure,unclear content expression,and technical inability to achieve.In response to this problem,a multi-table joint query method of combine harvester knowledge base data was proposed.The data table types was divided from multiple perspectives,the data storage structure of the combine harvester knowledge base was analyzed and the management scope for multi-table joint data was set.The application structured query language(SQL)fused multi-table information into a dataset and stored it into a temporary table to achieve multi-table joint operation.The human-computer interactive interface was used to convert the user query requirements into multi-table joint query statements to generate query results,and multi-table approximate range query and multi-table precise positioning query were realized.The test results between multi-table joint query and traditional singletable knowledge query showed that on the one hand,multi-table approximate range query saved user operation time by 50%or more than the original single-table approximate range query of the system,and the highest reached 90.4%;on the other hand,the multi-table precise positioning query saved 48.1%or more user operation time compared with the original single-table precise positioning query of the system,and the highest reached 89.6%.The implementation of multi-table joint query made the combine harvester knowledge base system practical and feasible and provided a reference idea and method for data management of similar knowledge base system.

关 键 词：联合收获机 知识库系统 多表联合查询 数据表分类 数据同步 人机交互 

分 类 号：S225.3[农业科学—农业机械化工程] TP311.1[农业科学—农业工程]