B. Yan, Bin Li, F. Gao, Yunjie Miao, Xi-rong Lin, Da-Hui Hong, Haihong Zhang
{"title":"Research on on-line oil monitoring system for power plant based on condition assessment of oil-using equipment","authors":"B. Yan, Bin Li, F. Gao, Yunjie Miao, Xi-rong Lin, Da-Hui Hong, Haihong Zhang","doi":"10.1117/12.2673556","DOIUrl":null,"url":null,"abstract":"This paper uses the oil monitoring and diagnosis module to conduct diagnosis and early warning based on the change of oil indicators caused by the deterioration products generated after the deterioration of the oil, which can quickly and accurately output the equipment to which the fault belongs and diagnose the link of the problem. Along with the related remote management software for the top computer and the lower oil monitoring equipment, the system also includes the diagnosis technique statistically created by the aforementioned modules. The host computer's software then performs real-time statistical data screening and diagnostics once the monitoring and diagnosis module detects the change in oil quality indicators and transmits the information through the switch.","PeriodicalId":176918,"journal":{"name":"2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2673556","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper uses the oil monitoring and diagnosis module to conduct diagnosis and early warning based on the change of oil indicators caused by the deterioration products generated after the deterioration of the oil, which can quickly and accurately output the equipment to which the fault belongs and diagnose the link of the problem. Along with the related remote management software for the top computer and the lower oil monitoring equipment, the system also includes the diagnosis technique statistically created by the aforementioned modules. The host computer's software then performs real-time statistical data screening and diagnostics once the monitoring and diagnosis module detects the change in oil quality indicators and transmits the information through the switch.