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相关概念视频

Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

650
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...
650
Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

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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...
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Energy Losses in Transformers01:21

Energy Losses in Transformers

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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...
1.5K
Transformers01:26

Transformers

2.2K
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...
2.2K
Radiation: Applications01:17

Radiation: Applications

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The average temperature of Earth is the subject of much current discussion. Earth is in radiative contact with both the Sun and dark space; it receives almost all its energy from the radiation of the Sun and reflects some of it into outer space. Dark space is very cold, about 3 K, so Earth radiates energy into it. For instance, heat transfer occurs from soil and grasses, the rate of which can be so rapid that frost can occur on clear summer evenings, even in warm latitudes.
The average...
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Three-Winding Transformers01:19

Three-Winding Transformers

865
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...
865

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A Basic Positron Emission Tomography System Constructed to Locate a Radioactive Source in a Bi-dimensional Space
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MTL_TX:一个多任务变压器模型,用于改进辐射时间序列估计.

Hongfang Zhang1, Adam Stavola1,2, Hal Ferguson1

  • 1Department of Electrical & Computer Engineering, Old Dominion University, Norfolk, VA 23529, USA.

Sensors (Basel, Switzerland)
|March 14, 2026
PubMed
概括

一个新的多任务变压器 (MTL_TX) 模型准确地估计了加速器设施的辐射剂量. 这种先进的AI通过使用历史数据预测辐射水平来提高人员和公众的安全性.

关键词:
变压器变压器变压器多任务学习是多任务学习.辐射剂量估计辐射剂量估计

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A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
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A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

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科学领域:

  • 核工程 核工程是指核工程.
  • 人工智能的人工智能
  • 辐射安全 辐射安全

背景情况:

  • 控制辐射剂量对于托马斯·杰斐逊国家加速器设施 (JLab) 等设施的安全至关重要.
  • 在运行过程中,JLab利用多个传感器监测光束电流,能量,泄漏和辐射.

研究的目的:

  • 为加速器设施开发一个准确的辐射剂量估计模型.
  • 通过预测辐射水平来提高人员和公众的安全.

主要方法:

  • 开发了一种多任务变压器 (MTL_TX) 模型,该模型包含分层特征嵌入 (HFE) 和多层分解注意力 (MDA).
  • 利用多任务学习 (MTL) 框架,利用多个传感器之间的相关性进行个人估计.

主要成果:

  • 根据2018年的数据,MTL_TX实现了0.1464的MSE,0.2353的RMSE和0.8584的R2.
  • 在2016-2019年未见的数据上显示出强烈的泛化,MSE为0.1407,RMSE为0.2263和R2为0.8831.

结论:

  • 与最先进的方法相比,MTL_TX模型显著提高了辐射剂量估计的准确性.
  • 开发的模型为加速器设施和周围地区提供了增强的安全解决方案.