Rotor Electrical Fault Detection of Wind Turbine Induction Generators Using an Unscented Kalman Filter

Hashemi, Zhale; Rahideh, Akbar

doi:10.1007/s40998-019-00282-8

Cited by 6 publications

(2 citation statements)

References 33 publications

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“…On the other hand, model-based approaches are widely used to detect rotor faults in squirrel cage induction motors (SCIMs). Rotor asymmetry faults were detected in a wind turbine by [16], where there is more scope for detecting rotor asymmetry faults (RAFs) in WRIMs using the model-based approach.…”

Section: Introductionmentioning

confidence: 99%

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Rotor Asymmetry Detection in Wound Rotor Induction Motor Using Kalman Filter Variants and Investigations on Their Robustness: An Experimental Implementation

John Basha,

Somasundaram

2023

Machines

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This paper analyzes the performance of Kalman filter-based estimators for robust filtering and rotor asymmetry detection in wound rotor induction machines (WRIMs) using real-time data. Filter models were designed based on an extended model of WRIMs. The detection of rotor asymmetry was achieved by estimating the states of rotor resistance and speed using four filters. The sensitivity of the parameters under healthy and asymmetry conditions was thoroughly analyzed and categorized as low, medium, and high sensitivity parameters. Robust model-based estimators were designed to minimize the probability of false alarms. The performance analysis demonstrated that the dual unscented Kalman filter (DUKF) outperformed other Kalman filters such as the extended Kalman filter (EKF), dual extended Kalman filter (DEKF), and unscented Kalman filter (UKF) for state estimation of WRIM.

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Section: Introductionmentioning

confidence: 99%

“…Based on the literature, the detection of rotor electrical asymmetry using model-based approaches is described by [16]. The author chose the unscented Kalman filter (UKF) to detect the fault.…”

Section: Introductionmentioning

confidence: 99%