Tiina M. Komulainen, A. M. Baqeri, Katrine Marsteng Jansen, T. Saltnes, Axel Tveiten Bech, Olga Korostynska
{"title":"希阿斯工艺的虚拟传感器","authors":"Tiina M. Komulainen, A. M. Baqeri, Katrine Marsteng Jansen, T. Saltnes, Axel Tveiten Bech, Olga Korostynska","doi":"10.2166/wpt.2024.176","DOIUrl":null,"url":null,"abstract":"\n \n This article presents the development of virtual sensors for estimation of phosphates (PO4) and soluble COD profiles in a novel, continuous flow, moving bed bioreactor with enhanced biological phosphorus removal and simultaneous nitrification and denitrification, the Hias process. The virtual sensors combine online measurements with additional electrical conductivity (EC), oxidation–reduction potential (ORP) measurements, and state-space models at inlet, zone 3 and zone 7. The data were collected from Hias municipal WRRF, Norway from March to July 2023, and include both online data and laboratory data. Input variables were selected using correlation plots. Linear measurement equations were fitted to relate PO4 and COD concentrations in the laboratory data set with the online measurements including EC/ORP measurements. The state-space models were identified from the online data with model accuracy from moderate to strong. The estimated PO4 and COD concentrations correspond to most of the scarce laboratory data points at inlet and zone 3, whereas the model in zone 7 requires more work. A Kalman filter was developed for zone 3 and implemented in KYB industrial internet of things (IIoT) platform. Future work is suggested on improvement of the model accuracy in zone 7, and development of energy-efficient control strategies using the virtual sensors.","PeriodicalId":104096,"journal":{"name":"Water Practice & Technology","volume":"71 15","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Virtual sensors for the Hias process\",\"authors\":\"Tiina M. Komulainen, A. M. Baqeri, Katrine Marsteng Jansen, T. Saltnes, Axel Tveiten Bech, Olga Korostynska\",\"doi\":\"10.2166/wpt.2024.176\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n This article presents the development of virtual sensors for estimation of phosphates (PO4) and soluble COD profiles in a novel, continuous flow, moving bed bioreactor with enhanced biological phosphorus removal and simultaneous nitrification and denitrification, the Hias process. The virtual sensors combine online measurements with additional electrical conductivity (EC), oxidation–reduction potential (ORP) measurements, and state-space models at inlet, zone 3 and zone 7. The data were collected from Hias municipal WRRF, Norway from March to July 2023, and include both online data and laboratory data. Input variables were selected using correlation plots. Linear measurement equations were fitted to relate PO4 and COD concentrations in the laboratory data set with the online measurements including EC/ORP measurements. The state-space models were identified from the online data with model accuracy from moderate to strong. The estimated PO4 and COD concentrations correspond to most of the scarce laboratory data points at inlet and zone 3, whereas the model in zone 7 requires more work. A Kalman filter was developed for zone 3 and implemented in KYB industrial internet of things (IIoT) platform. Future work is suggested on improvement of the model accuracy in zone 7, and development of energy-efficient control strategies using the virtual sensors.\",\"PeriodicalId\":104096,\"journal\":{\"name\":\"Water Practice & Technology\",\"volume\":\"71 15\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Water Practice & Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2166/wpt.2024.176\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Practice & Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/wpt.2024.176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This article presents the development of virtual sensors for estimation of phosphates (PO4) and soluble COD profiles in a novel, continuous flow, moving bed bioreactor with enhanced biological phosphorus removal and simultaneous nitrification and denitrification, the Hias process. The virtual sensors combine online measurements with additional electrical conductivity (EC), oxidation–reduction potential (ORP) measurements, and state-space models at inlet, zone 3 and zone 7. The data were collected from Hias municipal WRRF, Norway from March to July 2023, and include both online data and laboratory data. Input variables were selected using correlation plots. Linear measurement equations were fitted to relate PO4 and COD concentrations in the laboratory data set with the online measurements including EC/ORP measurements. The state-space models were identified from the online data with model accuracy from moderate to strong. The estimated PO4 and COD concentrations correspond to most of the scarce laboratory data points at inlet and zone 3, whereas the model in zone 7 requires more work. A Kalman filter was developed for zone 3 and implemented in KYB industrial internet of things (IIoT) platform. Future work is suggested on improvement of the model accuracy in zone 7, and development of energy-efficient control strategies using the virtual sensors.