Fault Diagnosis of Squirrel Cage Induction Generator for Wind Turbine Applications Using a Hybrid Deep Neural Network and Decision Tree Approach

Toshani, Hamid; Abdi, Salman; Hosseini, Narges Khadem; Abdi, Ehsan

doi:10.1109/icecet52533.2021.9698556

Cited by 3 publications

(2 citation statements)

References 24 publications

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“…The authors in [15] proposed a residual generator based on Kalman filter (KF) to detect the faults in a linear drive system affected by system noise. In [16], a decision tree and deep neural network combined method is proposed to detect and classify the faults in wind turbine generators through the analysis of features in the stator current signals. Literature by Li et al [17] uses the back propagation neural network and improved genetic algorithm to diagnose the complex fault of marine generators.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Frequency-Tracking Method Based on Interpolated Kalman Filter Using Vibration and Surface Noise

Li,

Wan,

Pan

et al. 2024

Mathematical Problems in Engineering

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The variation of frequency is a significant indicator of the operation status of rotating machinery. Generally, the frequency is extracted and tracked in real-time based on the vibration signal produced by the rotating machinery. However, various interferences generated from contact sampling and transmitting result in difficulty in obtaining the frequency correctly in real-time from the vibration. To solve this problem, this paper presents an interpolated Kalman filter (IKF) based on the vibration and surface noise signals for real-time frequency tracking. First, the cross-correlation operation is performed on the vibration and surface noise signals sampled synchronously to enhance the energy concentration. After that, a frequency search procedure is carried out to calculate the input of the tracking task. Finally, an IKF-based frequency lock procedure is applied to eliminate the interferences and track the frequency in real time. Besides, a correction procedure is added to prevent the measurement process from tracking the frequency incorrectly. The performance of the proposed method is verified by the experiments based on an ARM-based test bench using standard signals and actual test signals.

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Section: Introductionmentioning

confidence: 99%

Real-Time Frequency-Tracking Method Based on Interpolated Kalman Filter Using Vibration and Surface Noise

Li,

Wan,

Pan

et al. 2024

Mathematical Problems in Engineering

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“…They are often used as generators in wind energy conversion systems of low power [1][2][3][4]. Several studies have revealed that induction machines are subject to different stresses applying on stator windings and causing different faults [5][6][7][8][9][10][11][12][13][14][15][16]. It has been illustrated that the stator asymmetries are considered as the most severe disturbances which cause severe effects such as increase losses, temperature rise, torque pulsation, vibration and noise [17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Theoretical and Experimental Analysis of the Squirrel Cage Induction Generators Operating under Unbalanced Conditions

Kouchih¹,

Hachelaf

2022

Preprint

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This work involves a new approach for the analysis of the squirrel cage induction generators operation operating under unbalanced load conditions. For this purpose, a state model is synthetized considering the change of the stator common point voltage during unbalanced conditions. Theoretical and experimental studies have been investigated to extract some important electromagnetic signatures such as common point voltage, stator voltages and currents. This approach offers a good compromise between modeling precision and simulation time. Simulation and experimental results show good coherence with previous results which have been obtained using symmetrical components and finite elements methods.

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A Fault Diagnosis Model for Wind Turbine Blade Using a Deep Learning Method

Li,

Xiao,

Zhang

et al. 2023

2023 8th International Conference on Power and Renewable Energy (ICPRE)

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Fault Diagnosis of Squirrel Cage Induction Generator for Wind Turbine Applications Using a Hybrid Deep Neural Network and Decision Tree Approach

Cited by 3 publications

References 24 publications

Real-Time Frequency-Tracking Method Based on Interpolated Kalman Filter Using Vibration and Surface Noise

Real-Time Frequency-Tracking Method Based on Interpolated Kalman Filter Using Vibration and Surface Noise

Theoretical and Experimental Analysis of the Squirrel Cage Induction Generators Operating under Unbalanced Conditions

A Fault Diagnosis Model for Wind Turbine Blade Using a Deep Learning Method

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