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Advanced turbine generator torsional vibration evaluation method using Kalman filtering

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43966029" target="_blank" >RIV/49777513:23520/22:43966029 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.ingentaconnect.com/content/bindt/insight/2022/00000064/00000008/art00004;jsessionid=1k6zup5sgd3ry.x-ic-live-01" target="_blank" >https://www.ingentaconnect.com/content/bindt/insight/2022/00000064/00000008/art00004;jsessionid=1k6zup5sgd3ry.x-ic-live-01</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1784/INSI.2022.64.8.437" target="_blank" >10.1784/INSI.2022.64.8.437</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Advanced turbine generator torsional vibration evaluation method using Kalman filtering

  • Original language description

    Turbine-generator torsional vibration is getting a major concern in modern power grids with high level of changeability due to the operation of renewable sources of energy. The traditional absence of standard torsional vibration monitoring and the lack of experience with the operation of torsional vibration monitoring systems open 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 proves to be essential to capture the torsional vibration information. The benefits of the designed Kalman filtering method are the computational efficiency and the possibility to tackle with two different kinds 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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

    <a href="/en/project/EF16_026%2F0008389" target="_blank" >EF16_026/0008389: Research Cooperation for Higher Efficiency and Reliability of Blade Machines</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    INSIGHT

  • ISSN

    1354-2575

  • e-ISSN

    1754-4904

  • Volume of the periodical

    64

  • Issue of the periodical within the volume

    8

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    5

  • Pages from-to

    437-441

  • UT code for WoS article

    000860987900004

  • EID of the result in the Scopus database

    2-s2.0-85137272461