{"title":"Advanced turbine generator torsional vibration evaluation method using Kalman filtering","authors":"J. Liška, J. Jakl, S. Kunkel","doi":"10.1784/insi.2022.64.8.437","DOIUrl":null,"url":null,"abstract":"Turbine generator torsional vibration is becoming a major concern in modern power grids with a high level of changeability due to the operation of renewable energy sources. The traditional absence of standard torsional vibration monitoring and a lack of experience with the operation\n of torsional vibration monitoring systems opens up a wide range of opportunities for the design of torsional vibration monitoring systems and the possibility of their installation in power plants. As the measured signals are adversely affected by noise, proper filtering is essential for capturing\n the torsional vibration information. The benefits of the designed Kalman filtering method are the computational efficiency and the possibility of tackling two different types of noise: the state noise and the measurement noise. The feasibility of the proposed method is demonstrated by case\n studies based on practical signals measured on steam turbine generators.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Insight - Non-Destructive Testing and Condition Monitoring","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1784/insi.2022.64.8.437","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
Turbine generator torsional vibration is becoming a major concern in modern power grids with a high level of changeability due to the operation of renewable energy sources. The traditional absence of standard torsional vibration monitoring and a lack of experience with the operation
of torsional vibration monitoring systems opens up a wide range of opportunities for the design of torsional vibration monitoring systems and the possibility of their installation in power plants. As the measured signals are adversely affected by noise, proper filtering is essential for capturing
the torsional vibration information. The benefits of the designed Kalman filtering method are the computational efficiency and the possibility of tackling two different types of noise: the state noise and the measurement noise. The feasibility of the proposed method is demonstrated by case
studies based on practical signals measured on steam turbine generators.