电工电子实验室智能辅助管理系统设计与研究  

Design and research of intelligent auxiliary management system for electrical and electronic laboratory

作　　者：隋首钢[1] 乔镔 SUI Shougang;QIAO Bin(School of Information and Electrical Engineering,Shandong Jianzhu University,Jinan 250101,China)

机构地区：[1]山东建筑大学信息与电气工程学院,山东济南250101

出　　处：《实验室科学》2023年第4期48-52,57,共6页Laboratory Science

摘　　要：人工智能技术的发展以及电工电子教育的普及为电工电子实验室的教学和管理环境提出了更高的要求。实验室管理系统提出了将智能化与人工管理相结合的管理模式,利用python-web开发技术实现系统软件平台设计,具有学生选课、退课、上传实验数据,教师排课、发布实验课程等功能。利用机器学习算法技术实现了对学生上传实验数据的聚类分析,将实验数据分为正确、操作错误以及机器故障三类数据,从而实现了学生成绩的自动评判以及设备故障辨识。另外,空调设备模块也基于机器学习算法技术,通过自动采集周围环境温度和湿度数据,实现了空调的自动控制,在综合考虑舒适度与节能的基础上,达到自主调节室温的实验室环境控制智能化。The development of artificial intelligence technology and popularization of electrical and electronic education have put forward higher requirements for the teaching and management environment of electrical and electronic laboratory.A management mode combining intelligence and manual management is proposed for the laboratory management system.Using Python-Web development technology to realize the design of the system software platform,with the functions of students selecting courses,quitting courses,uploading experimental data,teachers arranging courses,releasing experimental courses and so on.At the same time,the machine learning algorithm technology is used to realize the clustering analysis of the experimental data uploaded by students,and the experimental data is divided into three types:correct data,operation error data and machine fault data,so as to realize the automatic evaluation of students’performance and equipment fault identification.In addition,the air conditioning equipment module is also based on machine learning algorithm technology,through the automatic collection of ambient temperature and humidity data,the automatic control of the air conditioning,on the basis of comprehensive consideration of comfort and energy saving,to achieve the independent regulation of room temperature laboratory environment control intelligence.

关 键 词：电工电子实验室 机器学习 Python-Web开发 自动控制 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]