Ying Shen, C. Tan, F. Dong, Keith M. Smith, J. Escudero
{"title":"Gas-water two-phase flow pattern recognition based on ERT and ultrasound Doppler","authors":"Ying Shen, C. Tan, F. Dong, Keith M. Smith, J. Escudero","doi":"10.1109/I2MTC.2018.8409540","DOIUrl":null,"url":null,"abstract":"Two phase flow is widely encountered and of high importance in the manufacturing process and related scientific research. The two-phase flow process is complex, and the flow patterns are jointly determined by the phase fraction and the flow rate. The traditional way of studying the flow patterns uses a single sensor, generally sensing one point, to discover and identify the flow patterns. However, these methods lack a comprehensive description from both the phase distribution and flow velocity. Therefore, it is essential to fuse different detection mechanism sensors to investigate the flow patterns in a more comprehensive way. In this work, an electrical resistance tomography (ERT) sensor measures phase fraction and a continuous wave ultrasound Doppler (CWUD) sensor measures velocity of two-phase flow. For the measurement, data of ERT is treated as a multivariate time-series and a method of graph signal processing named Modular Dirichlet Energy (MDE) is adopted to extract features. The results show that the combination of these two sensors can distinguish horizontal gas-water flow well and lays the foundation for the identification of oil-gas-water three-phase flow.","PeriodicalId":393766,"journal":{"name":"2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2MTC.2018.8409540","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Two phase flow is widely encountered and of high importance in the manufacturing process and related scientific research. The two-phase flow process is complex, and the flow patterns are jointly determined by the phase fraction and the flow rate. The traditional way of studying the flow patterns uses a single sensor, generally sensing one point, to discover and identify the flow patterns. However, these methods lack a comprehensive description from both the phase distribution and flow velocity. Therefore, it is essential to fuse different detection mechanism sensors to investigate the flow patterns in a more comprehensive way. In this work, an electrical resistance tomography (ERT) sensor measures phase fraction and a continuous wave ultrasound Doppler (CWUD) sensor measures velocity of two-phase flow. For the measurement, data of ERT is treated as a multivariate time-series and a method of graph signal processing named Modular Dirichlet Energy (MDE) is adopted to extract features. The results show that the combination of these two sensors can distinguish horizontal gas-water flow well and lays the foundation for the identification of oil-gas-water three-phase flow.