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Related Concept Videos

Transformers in Distribution System01:27

Transformers in Distribution System

98
Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
98
Instrument Transformers01:23

Instrument Transformers

64
Instrument transformers, comprising voltage transformers (VTs) and current transformers (CTs), play crucial roles in power substations by providing isolated replicas of current or voltage for measurement and protection purposes. Voltage transformers reduce the primary voltage to levels suitable for relay operation and measurement, while current transformers scale down the primary current. The primary winding of a current transformer often consists of a single turn, achieved by threading the...
64
Types Of Transformers01:16

Types Of Transformers

943
Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
943
Fault Types01:18

Fault Types

63
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...
63
Energy Losses in Transformers01:21

Energy Losses in Transformers

818
In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
818
Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

376
The practical equivalent circuits of single-phase two-winding transformers exhibit significant deviations from their idealized versions due to the inherent properties of winding resistance and finite core permeability. These properties result in real and reactive power losses, affecting the transformer's performance. Understanding these deviations is crucial for designing more efficient transformers.
In a practical transformer, each winding exhibits resistance and leakage reactance. The...
376

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Related Experiment Video

Updated: May 23, 2025

Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt
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A transformer-based real-time earthquake detection framework in heterogeneous environments.

Aming Wu1, Irshad Khan1, Young-Woo Kwon2

  • 1School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea.

Scientific Reports
|March 12, 2025
PubMed
Summary

This study introduces TFEQ, a transformer-based model for real-time earthquake detection. TFEQ analyzes both P and S waves, improving detection in diverse IoT environments.

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Area of Science:

  • Seismology
  • Artificial Intelligence
  • Internet of Things

Background:

  • Deep learning methods show superior efficacy in earthquake detection compared to conventional approaches.
  • Deploying deep learning in heterogeneous environments presents challenges due to data variations and diverse evaluation metrics.
  • Current models often prioritize S-wave detection, overlooking the critical early identification of P-waves.

Purpose of the Study:

  • To introduce TFEQ, a novel transformer-based model for real-time earthquake detection.
  • To enable concurrent analysis of both P and S waves for improved seismic event identification.
  • To validate the model's effectiveness and applicability in diverse Internet of Things (IoT) environments.

Main Methods:

  • Development of TFEQ, a transformer-based deep learning architecture.
  • Concurrent analysis of P-wave and S-wave seismic data.
  • Case studies utilizing MEMS sensor data from the CrowdQuake initiative.

Main Results:

  • TFEQ demonstrates effective real-time earthquake detection capabilities.
  • The model concurrently analyzes P and S waves across different data domains.
  • Case studies confirm TFEQ's reliability and generalization across diverse datasets.

Conclusions:

  • TFEQ offers a robust solution for real-time earthquake detection in heterogeneous IoT settings.
  • Concurrent P and S wave analysis enhances seismic event identification accuracy.
  • The model shows significant potential for improving seismological research and disaster preparedness.