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相关概念视频

Instrument Transformers01:23

Instrument Transformers

84
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...
84
Types Of Transformers01:16

Types Of Transformers

975
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...
975
Energy Losses in Transformers01:21

Energy Losses in Transformers

872
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...
872
The Ideal Transformer01:26

The Ideal Transformer

391
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...
391
Three-Winding Transformers01:19

Three-Winding Transformers

224
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...
224
Power Factor Correction01:20

Power Factor Correction

176
The power transmission to a factory involves the transfer of apparent power, a combination of active and reactive power. The power factor measures how effectively electrical power is converted into useful work output. The ratio of the real power (KW) that does the work to the apparent power (KVA) supplied to the circuit.
176

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相关实验视频

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Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers
06:50

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VRT:一个视频修复变压器.

Jingyun Liang, Jiezhang Cao, Yuchen Fan

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |March 7, 2024
    PubMed
    概括

    视频恢复转换器 (VRT) 通过使用多个的时间信息来提高视频质量. 这种新的方法在各种视频恢复任务中取得了最先进的结果.

    科学领域:

    • 计算机视觉 计算机视觉
    • 人工智能的人工智能
    • 信号处理 信号处理

    背景情况:

    • 视频恢复需要从相邻的,往往不对齐的中利用时间信息.
    • 现有的深度学习方法通常受限于使用滑动窗口或循环架构的对处理.

    研究的目的:

    • 引入一种新的视频恢复变压器 (VRT) 架构,能够进行并行预测.
    • 提高视频恢复技术的效率和有效性.

    主要方法:

    • 拟议的VRT采用了一个多尺度的架构,具有时间交互自我注意 (TRSA) 和并行曲模块.
    • 在视频片段中,TRSA可实现关节运动估计,特征对齐和融合,而自我注意力则可以提取特征.
    • 通过转移视频序列来促进交叉剪辑交互,并行曲将来自邻近的信息融合在一起.

    主要成果:

    • 在五个视频修复任务中,VRT表现出了卓越的性能:超分辨率,消除模糊,无色化,插入和时空超分辨率.
    • 该方法取得了显著的改进,在14个基准数据集上,高达2.16dB的性能超过了最先进的方法.

    结论:

    • VRT架构为各种视频恢复挑战提供了强大而高效的解决方案.

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  • 它的并行预测能力和先进的注意力机制代表了该领域的重大进步.