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Related Concept Videos

Generator Voltage Control01:21

Generator Voltage Control

181
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,...
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Turbine-Governor Control01:17

Turbine-Governor Control

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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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Load-frequency control01:28

Load-frequency control

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Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
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Control of Power Flow01:30

Control of Power Flow

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There are several methods to control power flow in power systems:
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Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

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Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...
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Distribution Reliability and Automation01:25

Distribution Reliability and Automation

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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Related Experiment Video

Updated: Jul 16, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Application of condition-based maintenance for electrical generators based on statistical control charts.

Mohammad A Shbool1, Badi Alanazi2

  • 1Industrial Engineering Department, School of Engineering, The University of Jordan, Amman 11942, Jordan.

Methodsx
|September 11, 2023
PubMed
Summary

Statistical control charts enhance condition-based maintenance for electrical generators by monitoring performance parameters. Temperature monitoring proved most effective in detecting failures, improving equipment reliability.

Keywords:
Condition-based maintenanceLSTMStatistical control chartsStatistical control charts for condition-based maintenance of electrical generatorsURL

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Area of Science:

  • Engineering
  • Data Science

Background:

  • Condition-based maintenance (CBM) optimizes equipment upkeep by aligning activities with performance status.
  • Continuous monitoring is crucial for effective CBM strategies.

Purpose of the Study:

  • To propose a framework for applying statistical control charts in CBM for electrical generators.
  • To evaluate the effectiveness of different monitoring parameters and control charts in failure detection.

Main Methods:

  • Developed a four-component framework to establish performance thresholds for electrical equipment.
  • Utilized Long Short-term Memory (LSTM) and Useful Remaining Life (URL) models for maintenance decision-making.
  • Analyzed process parameters (vibration, noise, temperature) using statistical control charts and experimental data.

Main Results:

  • X-bar control charts demonstrated consistent failure detection capabilities.
  • R charts showed limitations when data deviated from normality.
  • Temperature monitoring was superior to vibration and noise in detecting failures, with temperature control charts successfully identifying issues.

Conclusions:

  • Statistical control charts play a vital role in CBM decision-making for electrical generators.
  • The proposed framework and analysis support the integration of advanced models and statistical tools for predictive maintenance.