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相关概念视频

Transformers in Distribution System01:27

Transformers in Distribution System

123
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...
123
Energy Losses in Transformers01:21

Energy Losses in Transformers

901
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...
901
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

176
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
176
Transformers01:26

Transformers

1.1K
A device that transforms voltages from one value to another using induction is called a transformer. A transformer consists of two separate coils, or windings, wrapped around the same soft iron core. However, they are electrically insulated from each other.
The iron core has a substantial relative permeability. Therefore, the magnetic field lines generated due to the current in one winding are almost entirely confined within the core, such that the same magnetic flux permeates each turn of both...
1.1K
Types Of Transformers01:16

Types Of Transformers

1.0K
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...
1.0K
The Ideal Transformer01:26

The Ideal Transformer

423
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...
423

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相关实验视频

Updated: Jul 16, 2025

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
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一个转换器优化的深度学习网络用于道路损坏检测和跟踪.

Niannian Wang1, Lihang Shang1, Xiaotian Song2

  • 1School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
概括

本研究介绍了Road-TransTrack,这是一个基于变压器的优化模型,用于准确检测和跟踪道路损坏. 它显著改进了现有的方法,用于识别道路基础设施中的坑洞和裂.

关键词:
对象跟踪是指对象的跟踪.检测道路损坏 检测道路损坏自我注意力机制机制变压器的变压器是一个变压器.

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科学领域:

  • 计算机视觉 计算机视觉
  • 人工智能的人工智能
  • 道路基础设施监测 道路基础设施监测

背景情况:

  • 现有的道路损坏检测和跟踪模型存在低准确性和错误计数问题.
  • 自动监测道路状况对于及时维护和安全至关重要.

研究的目的:

  • 开发一个先进的跟踪模型,Road-TransTrack,用于增强道路损坏对象的检测和跟踪.
  • 提高自动化道路损坏评估的准确性和可靠性.

主要方法:

  • 使用YOLOv5进行图像分类,将道路损坏分类为坑洞和裂.
  • 通过整合变压器优化和自我注意机制,开发了道路-交通轨道.
  • 在定制的道路损坏数据集和真实世界的道路视频上训练并验证了模型.

主要成果:

  • 道路-交通轨道实现了很高的检测准确度:裂为91.60%,坑洞为98.59%.
  • 该模型表现出强的性能,F1分数为裂的0.9417和坑洞的0.9847 .
  • 在检测和计数准确性方面表现优于传统的卷积神经网络.

结论:

  • 道路-TransTrack为道路损坏物体的检测和跟踪提供了卓越的性能.
  • 拟议的基于变压器的方法有效地解决了现有模型的局限性.
  • 这项技术在改善道路维护和安全管理方面具有重大潜力.