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相关概念视频

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

590
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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Transformers in Distribution System01:27

Transformers in Distribution System

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

Transformers with Off-Nominal Turns Ratios

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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...
122
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

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The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
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Rolling Resistance: Problem Solving01:17

Rolling Resistance: Problem Solving

267
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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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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基于双合组合聚合和变压器优化的自主机器人适应式避障模型.

Yuhu Tang1, Ying Bai1, Qiang Chen2

  • 1School of Artificial Intelligence and Big Data, Hefei University, Hefei 230601, China.

Sensors (Basel, Switzerland)
|April 28, 2025
PubMed
概括

本研究介绍了GAS-H-Trans,这是自动驾驶机器人的增强型变压器模型,可以在复杂的环境中更好地识别和避免障碍物. 该模型在图像细分和成功避开障碍方面实现了高精度,提高了机器人的安全性和效率.

关键词:
哈里斯·霍克优化的优化自主机器人 自主机器人动态环境的认可 动态环境的认可分组聚合策略 聚合策略变压器架构的架构

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 人工智能的人工智能
  • 计算机视觉 计算机视觉

背景情况:

  • 自主机器人需要强大的障碍物识别和避免,以便在动态环境中安全操作.
  • 当前的深度学习方法在适应复杂,现实世界的场景方面面临挑战.

研究的目的:

  • 提出一个改进的基于变压器的架构,GAS-H-Trans,以提高自主机器人的语义理解和避开障碍.
  • 在动态环境中提高避障策略的准确性和适应性.

主要方法:

  • 采用基于变压器的双合组合聚合策略,以优化特征提取和全球表示.
  • 集成的哈里斯霍克优化 (HHO) 用于超参数调整和粒子群优化 (PSO) 用于人工潜力场 (APF) 系数优化.
  • 实施了二次精确图像细分策略,在关键障碍物附近设置了观察点.

主要成果:

  • 在图像细分任务中,GAS-H-Trans实现了85.2%的欧盟平均交叉点 (mIoU),表现优于基线模型.
  • 在GAS-H-Trans + PSO优化的APF框架中,在虚拟环境中,避免障碍的成功率为93.6%.
  • 提出的方法显著提高了动态运动规划和细分精度的性能.

结论:

  • GAS-H-Trans模型为自动驾驶机器人提供了在障碍物识别和避免方面取得的重大进步.
  • 综合优化技术提高了模型的适应性和复杂的导航任务的成功率.
  • 这种方法为现实世界的自主导航应用提供了一个有希望的解决方案.