•  
  •  
 

Turkish Journal of Electrical Engineering and Computer Sciences

Author ORCID Identifier

ATENA LEMESKI: 0009-0006-7102-911X

DİDEM TEKGÜN: 0000-0003-4143-0720

OZAN KEYSAN: 0000-0002-6311-7906

KEMAL LEBLEBİCİOĞLU: 0000-0002-9735-458X

MURAT GÖL: 0000-0002-2523-1169

Abstract

Eccentricity faults in electric machines remain a critical concern, as they generate uneven magnetic forces that increase vibration and noise, ultimately raising the risk of premature motor failure. This study proposes a method for the early detection of dynamic eccentricity (DE) faults in hydropower plants through an advanced optimization-based parameter identification technique integrated with finite element analysis (FEA). Finite element modeling (FEM) is first used to analyze an existing salient-pole synchronous generator (SPSG) from a hydroelectric power plant in Türkiye. The effects of DE faults on the SPSG’s magnetic equivalent circuit parameters are then examined under various fault severities. A comprehensive hydropower plant model—including the synchronous generator, governor, and excitation system—is developed in MATLAB/Simulink, with all input parameters obtained from real plant data and equivalent circuit variations extracted from FEA. After completing the modeling stage, including fault scenarios, MATLAB and Simulink are employed together to estimate key magnetic equivalent circuit parameters using a modified particle swarm optimization (MPSO) algorithm, achieving highly accurate parameter estimation. Since the hydropower system allows measurement of the three-phase output currents, parameter estimation is performed based on current variations under different fault conditions. The simulation results verify the method’s ability to detect faults with high accuracy; thus, this integrated and noninvasive approach provides a robust framework for ensuring the operational reliability and longevity of large hydro generators.

DOI

10.55730/1300-0632.4163

Keywords

Salient pole synchronous generator (SPSG), parameter identification, condition monitoring, fault detection, finite element modeling (FEM)

First Page

67

Last Page

83

Publisher

The Scientific and Technological Research Council of Türkiye (TÜBİTAK)

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Download

Share

COinS