一种基于大数据分析和数字孪生的微波炉智能检测方法  

Intelligent detection method for microwave ovens based on big data analysis and digital twin

作　　者：曹磊 刘建圻[1] CAO Lei;LIU Jianqi(Guangdong University of Technology,Guangzhou 510000,China)

机构地区：[1]广东工业大学,广东广州510000

出　　处：《无线互联科技》2025年第3期47-50,共4页Wireless Internet Science and Technology

摘　　要：为了更加智能化地提高微波炉的检测效率,文章提出了基于大数据分析和数字孪生的微波炉智能检测方法,通过将微波炉的历史运行数据传输到大数据分析平台,计算数据的互信息,选择出主要的特征变量,然后计算特征变量的特征权重、耗损阈值和总耗损阈值,完成初步的数据分析;根据微波炉的实时运行数据,构建数字孪生体模型,大数据分析平台筛选出主要的特征变量并计算每个变量的耗损值和总耗损值,通过与指标进行比较,可以判断出微波炉的故障部位和微波炉是否达到寿命期限,以方便人工维修更换。To enhance the detection efficiency of microwave ovens more intelligently,this article presents an intelligent detection method for microwave ovens based on big data analysis and digital twin,By transferring the historical operation data of the microwave oven to the big data analysis platform,the main feature variables are selected by calculating the mutual information of the data,and then the feature weights of the feature variables,the loss threshold and the total loss threshold are calculated to complete the preliminary data analysis;The digital twin model is constructed according to the real-time operation data of the microwave oven,and the main characteristic variables are screened out and the loss value and total loss value of each variable are calculated.By comparing with the indicators,it can be judged whether the malfunctioning part of the microwave oven and whether the microwave oven has reached its lifespan,thereby facilitating manual maintenance and replacement.

关 键 词：大数据分析 数字孪生 微波炉智能检测 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]