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Related Concept Videos

Wind Turbine Machine Models01:24

Wind Turbine Machine Models

In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
Power System Three-Phase Short Circuits01:21

Power System Three-Phase Short Circuits

Determining the subtransient fault current in a power system involves representing transformers by their leakage reactances, transmission lines by their equivalent series reactances, and synchronous machines as constant voltage sources behind their subtransient reactances. In this analysis, certain elements are excluded, such as winding resistances, series resistances, shunt admittances, delta-Y phase shifts, armature resistance, saturation, saliency, non-rotating impedance loads, and small...
Three-Phase Short Circuit—Unloaded Synchronous Machine01:21

Three-Phase Short Circuit—Unloaded Synchronous Machine

Conducting a three-phase short circuit test on an unloaded synchronous machine helps understand its impact on the system. The AC fault current's oscillogram, with the DC offset removed, reveals that the waveform amplitude decreases from an initially high value to a steady-state level for one phase of the machine.
This behavior occurs due to the magnetic flux produced by the short-circuit armature currents. Initially, these currents follow high-reluctance paths but eventually shift to...
Fault Types01:18

Fault Types

When analyzing a single line-to-ground fault from phase A to ground at a three-phase bus, it is important to consider the fault impedance. This impedance is zero for a bolted fault, equal to the arc impedance for an arcing fault, and represents the total fault impedance for a transmission-line insulator flashover. To derive sequence and phase currents, fault conditions are translated from the phase domain to the sequence domain.
For line-to-line faults occurring between phases B and C, the...
Generator Voltage Control01:21

Generator Voltage Control

Generator voltage control is crucial for maintaining the stable operation of synchronous generators and wind turbines. In older models, a DC generator driven by the rotor delivers DC power to the rotor's field winding, and the power is transferred through slip rings and brushes. In the latest models, static or brushless exciters are used. Static exciters rectify AC power from the generator terminals and then transfer the DC power directly to the rotor. Brushless exciters, on the other hand, use...
Turbine-Governor Control01:17

Turbine-Governor Control

Turbine-governor control is crucial for maintaining power system stability by balancing turbine mechanical power output with electrical load demand. This mechanism ensures that generator frequency and rotor speed are within acceptable limits during load variations. Turbine-generator units store kinetic energy due to their rotating masses; this energy is released to meet the load requirement when the load increases. The electrical torque of turbines rises to meet the demand, whereas the...

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Related Experiment Video

Updated: Jun 27, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

A Two-Stage Classification Method for Improved Fault Detection in Wind Turbines Based on SCADA Data.

Jiazhi Dai1,2, Mario Rotea2,3, Nasser Kehtarnavaz1,2

  • 1Department of Electrical and Computer Engineering, University of Texas at Dallas, Richardson, TX 75080, USA.

Sensors (Basel, Switzerland)
|June 26, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a two-stage fault detection method for wind turbines, combining unsupervised and supervised learning. This approach significantly improves accuracy and reduces missed faults in SCADA data analysis.

Keywords:
fault detection based on SCADA datatwo-stage unsupervised and supervised fault detectionwind turbine fault detection

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Data Acquisition Protocol for Determining Embedded Sensitivity Functions
07:46

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

Related Experiment Videos

Last Updated: Jun 27, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

Data Acquisition Protocol for Determining Embedded Sensitivity Functions
07:46

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

Area of Science:

  • Engineering
  • Computer Science
  • Data Science

Background:

  • Wind turbine operation relies on effective fault detection.
  • Supervised methods struggle with imbalanced SCADA data (normal vs. fault samples).

Purpose of the Study:

  • To develop an improved fault detection method for wind turbines using SCADA data.
  • To overcome limitations of traditional supervised methods in handling imbalanced datasets.

Main Methods:

  • A two-stage approach integrating unsupervised and supervised learning.
  • Stage 1: Unsupervised One-Class Support Vector Machine (OCSVM) with anomaly scores to identify deviations.
  • Stage 2: Supervised Convolutional Neural Network (CNN) applied to flagged abnormal data for fault identification.

Main Results:

  • The two-stage method significantly enhances fault detection performance.
  • Demonstrated improvements in accuracy and reduction in missed fault rates compared to purely supervised methods.
  • Effective in discriminating between normal and abnormal operational conditions.

Conclusions:

  • The proposed two-stage fault detection strategy is highly effective for wind turbine SCADA data.
  • This hybrid approach offers a robust solution for reliable wind turbine operation.
  • Addresses the challenge of imbalanced datasets in wind turbine fault diagnostics.