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相关概念视频

Reducing Line Loss01:18

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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.
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The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
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Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
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相关实验视频

Updated: Sep 12, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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道路损坏检测基于改进的YOLO算法.

Luyao Ma1,2, Ming Chen3,4

  • 1Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle, Hubei University of Arts and Science, Xiangyang, China.

Scientific reports
|August 5, 2025
PubMed
概括
此摘要是机器生成的。

这项研究通过深度学习增强了道路损坏检测,提高了小缺陷和路面状况评估的准确性. 带有注意力机制的新YOLOv5模型为基础设施监控提供了更有效的解决方案.

关键词:
注意力机制注意力机制深度学习是一种深度学习.道路断路造成的破坏这是YOLOv5的.

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科学领域:

  • 计算机科学 计算机科学
  • 土木工程 土木工程是指土木工程.
  • 人工智能的人工智能

背景情况:

  • 城市化和交通需求的增加加剧了道路损坏问题.
  • 传统的手动道路检查方法效率低下,成本高昂,无法满足当前的需求.
  • 基于深度学习的道路损坏检测提供了一种尖端,高效的解决方案.

研究的目的:

  • 为道路损坏检测提供一个增强的物体检测算法.
  • 为了提高检测准确度和定位能力,特别是对于小物体.
  • 整合注意力机制和先进的损失功能,以提高性能.

主要方法:

  • 一个基于YOLOv5.5的增强物体检测算法.
  • 道注意力 (CA) 和空间注意力 (SA) 双分支注意力机制的整合.
  • 在边界框回归中使用通用交叉与联盟 (GIoU) 损失.

主要成果:

  • 改进的算法显示了改进的特征表示和界限框本地化.
  • 在小物体检测和定位准确度方面观察到显著的改进.
  • 实验结果表明,与现有方法相比,检索率增加了2.3%,平均值增加了0.3%,F1得分改善了0.7%.
  • 计算了路面状况指数 (PCI) 值,提供了预期的路面评估结果.

结论:

  • 提出的基于YOLOv5的算法,具有双分支注意力和GIoU损失,显著提高了道路损坏的检测.
  • 该方法提供了卓越的准确性和定位,特别是在诸如小道路缺陷等具有挑战性的情况下.
  • 这种先进的方法为道路基础设施的监测和评估提供了更高效和有效的解决方案.