{"title":"Application of Internet of Things Technology in Mechanical Automation Control","authors":"Yonghui Xie, Haiqing Li, Q. Jia, Xiumin Nie","doi":"10.1155/2022/9388942","DOIUrl":null,"url":null,"abstract":"In order to solve the problem of low production efficiency of the mechanical electromechanical automatic control system, this paper proposes a manufacturing mechanical automatic detection system based on Internet of things technology. Automatic detection of manufacturing machinery is realized by setting data module monitoring, which includes the data monitoring module and signal detection module. The experimental results show that compared with the traditional computer vision system, the detection system designed in this paper has a higher level of basic data and better detection accuracy. The detection accuracy can be improved by about 10% in different detection times. Conclusion. The mechanical and electrical automation control system based on the Internet of things can effectively improve the production efficiency and control accuracy of the mechanical and electrical automation control system.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"14 1","pages":"1-7"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Sensors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2022/9388942","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In order to solve the problem of low production efficiency of the mechanical electromechanical automatic control system, this paper proposes a manufacturing mechanical automatic detection system based on Internet of things technology. Automatic detection of manufacturing machinery is realized by setting data module monitoring, which includes the data monitoring module and signal detection module. The experimental results show that compared with the traditional computer vision system, the detection system designed in this paper has a higher level of basic data and better detection accuracy. The detection accuracy can be improved by about 10% in different detection times. Conclusion. The mechanical and electrical automation control system based on the Internet of things can effectively improve the production efficiency and control accuracy of the mechanical and electrical automation control system.