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相关概念视频

Unsymmetric Loading of Thin-Walled Members: Problem Solving01:07

Unsymmetric Loading of Thin-Walled Members: Problem Solving

559
The shear center of a channel section with uniform thickness, height, and width, is determined by computing the shear force in the member and calculating the moments of inertia of the sections.
To compute the shear forces, find the shear flow at a specific distance from the endpoint using the vertical shear and the moment of inertia values. The total shear force on the flange is calculated by integrating the shear flow from one end of the flange to the other.
Next, calculate the moments of...
559
Unsymmetric Loading of Thin-Walled Members01:23

Unsymmetric Loading of Thin-Walled Members

462
Thin-walled members with non-symmetrical cross-sections are vital to engineering structures, offering material efficiency and structural integrity. However, unsymmetrical loading on these members leads to complex stress distributions, resulting in simultaneous bending and twisting can cause deformation or structural failure. The interaction between bending and twisting requires detailed analysis to ensure structural resilience.
The concept of the shear center is crucial in countering the...
462
Lumber Defects01:23

Lumber Defects

603
Lumber defects, which can affect both the appearance and structural integrity of wood, include a variety of growth and manufacturing flaws. Growth defects such as knots and knotholes occur where branches were once attached to the tree trunk, with knotholes forming when these knots fall out. Other natural defects include decay and insect damage, which compromise the wood's strength and durability.
Shakes are minor fractures that run along or across the wood's annual rings, while wane is...
603
Reducing Line Loss01:18

Reducing Line Loss

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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.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss in...
408
Deformation of a Beam under Transverse Loading01:15

Deformation of a Beam under Transverse Loading

825
Understanding beam deflection, particularly for indeterminate beams with overhanging segments and multiple concentrated loads, is crucial for ensuring structural integrity and functionality. The process begins with constructing an accurate free-body diagram, which helps identify the forces and moments acting on the beam. This diagram is vital for visualizing how bending moments vary along the beam's length, influencing its curvature.
The insights from the bending moment diagram extend to...
825
Imperfections in Crystal Structure: Point, Line and Plane Defects01:25

Imperfections in Crystal Structure: Point, Line and Plane Defects

14
A perfect crystal, in theory, has a uniform structure with the same unit cell and lattice points throughout. However, any deviation from this periodic arrangement is known as an imperfection or defect. These defects can be categorized into three types: point, line, and plane defects.Point defects occur when there is a deviation from the ideal due to missing atoms, displaced atoms, or additional atoms. These imperfections might occur due to imperfect packing during crystallization or because of...
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相关实验视频

Updated: Mar 2, 2026

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads
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Published on: July 25, 2025

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一个改进的轻量级YOLOv11算法用于接表面缺陷检测.

Runmei Zhang1, Chenfei Pan1, Zihua Chen2

  • 1School of Electronic and Information Engineering, Anhui Jianzhu University, Hefei, Anhui, 230601, China.

Scientific reports
|March 1, 2026
PubMed
概括
此摘要是机器生成的。

本研究介绍了YOLO-Air,这是一个改进的轻量级YOLOv11模型,用于检测接表面缺陷. 该模型提高了准确性,同时显著降低了计算负载和参数,提供了具有成本效益的解决方案.

关键词:
深度学习是一种深度学习.缺陷检测 检测缺陷检测 检测缺陷检测这就是PConvv.这就是YOLOv11的意义.

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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
  • 材料科学 材料科学 材料科学

背景情况:

  • 工业接面临着不清楚缺陷特征和复杂背景的挑战.
  • 现有的缺陷检测模型通常是昂贵的,在接表面缺陷检测方面缺乏效率.

研究的目的:

  • 提出一个改进的,轻量级的YOLOv11模型 (YOLO-Air),用于增强接表面缺陷检测.
  • 解决现有模型在成本,复杂性和检测准确性方面的局限性.

主要方法:

  • 整合特征提取和卷积模块,以提高特征表示和效率.
  • 将GSConv和VOV-GSCSP模块集成到子网络中,以减少功能冗余和计算负载.
  • 轻量级检测头的设计,以进一步降低模型的复杂性.

主要成果:

  • 在接缺陷测试-V2和NEU-DET数据集上,YOLO-Air模型表现出卓越的性能.
  • 在mAP50指标上取得了1.3%的改善.
  • 将参数数量减少了17.3%,计算复杂度减少了31.7%.

结论:

  • 拟议的YOLO-Air模型为接表面缺陷检测提供了有效和高效的解决方案.
  • 该型号的轻量级设计和改进的性能使其成为工业应用的可行选择.
  • 实验数据证实了YOLO-Air模型性能的稳定性.