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相关概念视频

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...
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Relative Motion Analysis using Rotating Axes01:25

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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
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Derivatives of Inverse Trigonometric Functions01:30

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A ship tracking an approaching aircraft relies on geometric measurements to find out the aircraft’s position relative to the observer. By measuring the slant distance to the aircraft and the angle of elevation, the horizontal and vertical components of the distance can be obtained using trigonometric relationships. This geometric approach provides a basis for analyzing how the observed angle changes as the aircraft moves closer to the ship.To examine the mathematical behavior of the angle...
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使用低计算成本的基于变压器的跟踪方法进行地震强度预测.

Honglei Wang1, Zhixuan Bai2, Ruxue Bai2

  • 1Hebei Earthquake Agency, Shijiazhuang 050021, China.

Sensors (Basel, Switzerland)
|October 29, 2025
PubMed
概括

一种新的低计算成本的基于变压器的视觉跟踪 (LCCTV) 方法使用监控视频准确预测地震强度. 这种具有成本效益的方法为实时地震强度分析和灾难救援指导提供了可扩展的解决方案.

关键词:
低成本的低成本的成本.地震强度的地震强度模拟地震站的模拟基于变压器的视觉跟踪.

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科学领域:

  • 地质物理学 地质物理学
  • 计算机视觉 计算机视觉
  • 人工智能的人工智能

背景情况:

  • 准确的地震强度预测对于救灾至关重要.
  • 传统的地震仪方法在响应时间和成本方面存在局限性.
  • 需要新的方法来有效地进行地震监测.

研究的目的:

  • 为地震强度预测引入低计算成本的基于变压器的视觉跟踪 (LCCTV) 方法.
  • 开发一套新的地震视频数据集,用于培训和评估LCCTV方法.
  • 为地震强度分析提供具有成本效益和可扩展的解决方案.

主要方法:

  • 开发了一种低计算成本的基于变压器的视觉跟踪 (LCCTV) 方法,用于在视频中跟踪校准板的运动.
  • 使用巴特沃斯波器来平滑运动轨迹并消除低频干扰.
  • 预测地震强度是使用从光滑轨迹中得出的速度和加速来预测的.

主要成果:

  • 与最先进的方法相比,拟议的LCCTV方法显示出更高的性能.
  • 实验结果验证了LCCTV对实时地震强度估计的有效性.
  • 该方法成功地根据视觉跟踪数据预测了地震强度.

结论:

  • 低成本CCTV方法为地震强度分析提供了一个低成本,可扩展的替代方案.
  • 这种视觉跟踪方法可以提高灾难准备和应对能力.
  • 开发的地震视频数据集有助于进一步研究地震监测.