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Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine

Abstract

Article presents a comparison of process anomaly detection in nuclear power plant steam turbine using combination of data driven methods. Three types of faults are considered: water hammering, fouling and thermocouple fault. As a virtual plant a nonlinear, dynamic, mathe- matical steam turbine model is used. Two approaches for fault detection using one class and two class classiers are tested and compared.

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Details

Category:
Conference activity
Type:
materiały konferencyjne indeksowane w Web of Science
Title of issue:
Trends in Advanced Intelligent Control, Optimization and Automation strony 631 - 640
ISSN:
2194-5357
Language:
English
Publication year:
2017
Bibliographic description:
Kulkowski K., Grochowski M., Kobylarz A..: Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine, W: Trends in Advanced Intelligent Control, Optimization and Automation, 2017, ,.
DOI:
Digital Object Identifier (open in new tab) 10.1007/978-3-319-60699-6_61
Verified by:
Gdańsk University of Technology

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