Junfang Li, Tieqiang Wang, Yang Zhao, Junxiang Yang, Qiang Gao
{"title":"Intelligent analysis platform of industrial circulating water based on VB and Matlab","authors":"Junfang Li, Tieqiang Wang, Yang Zhao, Junxiang Yang, Qiang Gao","doi":"10.1109/ICMA.2015.7237562","DOIUrl":null,"url":null,"abstract":"Circulating cooling water occupies a high proportion in industrial production. The corrosion and scaling are common quality faults in the circulating cooling water system, which affect the operation of industrial equipment seriously. Through the analysis of the high concentrated multiple water quality data, choose the water quality parameters which have a greater impact on the corrosion rate and adhesion rate, then based on NARX neural network, the prediction model of corrosion rate and adhesion rate is established. Finally, using the VB and Matlab, the industrial circulating cooling water intelligent aided analysis platform is founded by combining with the water quality prediction model and embedding the small expert system. The platform realizes the prediction of corrosion rate and adhesion rate of water quality, and can put forward different expert advice for different forecast results. The application shows that the auxiliary analysis platform is feasible and has a good prospect.","PeriodicalId":286366,"journal":{"name":"2015 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Mechatronics and Automation (ICMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2015.7237562","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
Circulating cooling water occupies a high proportion in industrial production. The corrosion and scaling are common quality faults in the circulating cooling water system, which affect the operation of industrial equipment seriously. Through the analysis of the high concentrated multiple water quality data, choose the water quality parameters which have a greater impact on the corrosion rate and adhesion rate, then based on NARX neural network, the prediction model of corrosion rate and adhesion rate is established. Finally, using the VB and Matlab, the industrial circulating cooling water intelligent aided analysis platform is founded by combining with the water quality prediction model and embedding the small expert system. The platform realizes the prediction of corrosion rate and adhesion rate of water quality, and can put forward different expert advice for different forecast results. The application shows that the auxiliary analysis platform is feasible and has a good prospect.