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Related Concept Videos

Energy Losses in Transformers01:21

Energy Losses in Transformers

917
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...
917
Reducing Line Loss01:18

Reducing Line Loss

184
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
184
Three-Winding Transformers01:19

Three-Winding Transformers

281
Three identical single-phase transformers can be configured to form a three-phase transformer connection, which involves high-voltage and low-voltage windings. The high-voltage windings are denoted by capital letters A-B-C, while the low-voltage windings are labeled with lowercase letters a-b-c, representing their respective phases. This notation helps distinguish between the high and low voltage sides of the transformer.
In the per-unit equivalent circuit of a grounded Y-Y three-phase...
281
Instrument Transformers01:23

Instrument Transformers

118
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...
118
Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

489
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...
489
The Ideal Transformer01:26

The Ideal Transformer

448
In single-phase two-winding transformers, two windings are coiled around a magnetic core characterized by cross-sectional area A and magnetic permeability μ. A phasor current i1 enters the left winding while i2 exits the right winding, establishing the fundamental working of the transformer through electromagnetic principles.
Ampere's Law forms the basis of understanding the magnetic field within the transformer. It states that the integral of the magnetic field intensity's...
448

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Related Experiment Video

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High-Performance Transformer Tracking.

Xin Chen, Bin Yan, Jiawen Zhu

    IEEE Transactions on Pattern Analysis and Machine Intelligence
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    Summary
    This summary is machine-generated.

    This study introduces TransT, an attention-based network that surpasses traditional correlation methods for object tracking. TransT enhances feature fusion, improving accuracy in visual tracking tasks.

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    Area of Science:

    • Computer Vision
    • Artificial Intelligence

    Background:

    • Correlation operations are crucial in Siamese-based trackers but are limited by local linear matching, losing semantic information and risking local optima.
    • This limitation presents a bottleneck for achieving high-accuracy object tracking algorithms.

    Purpose of the Study:

    • To investigate superior feature fusion methods beyond traditional correlation operations.
    • To introduce a novel attention-based feature fusion network for enhanced visual object tracking.

    Main Methods:

    • A Transformer Tracking (TransT) method is proposed, utilizing a Siamese-like feature extraction backbone and an attention-based fusion mechanism.
    • The network incorporates an ego-context augmentation module (self-attention) and a cross-feature augmentation module (cross-attention).
    • A segmentation branch and a multi-template scheme with an IoU prediction head (TransT-M) were developed for improved performance.

    Main Results:

    • TransT and TransT-M demonstrated promising results across seven popular visual tracking benchmarks.
    • The attention-based fusion effectively combines template and search region features, overcoming limitations of local linear matching.

    Conclusions:

    • The proposed attention-based feature fusion network offers a significant advancement over correlation-based methods in visual tracking.
    • TransT and its enhanced version, TransT-M, establish a new state-of-the-art for accurate and robust object tracking.