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相关概念视频

Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

433
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...
433
Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

309
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. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...
309
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

369
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.
Here, in order to determine the magnitude of velocity and acceleration for point...
369
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

312
A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
312
Kinematic Equations for Rotation01:30

Kinematic Equations for Rotation

292
In mechanics, when one observes a rigid body in rotational motion with constant angular acceleration, it is possible to establish equations for its rotational kinematics. This process resembles how linear kinematics are dealt with in simpler motion studies.
For instance, imagine a point A on a rigid body engaged in circular motion. The translational velocity of this particular point can be calculated by taking the time derivatives of the displacement equation, which essentially measures the...
292
Kinematic Equations: Problem Solving01:15

Kinematic Equations: Problem Solving

11.7K
When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
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相关实验视频

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Corticospinal Excitability Modulation During Action Observation
12:33

Corticospinal Excitability Modulation During Action Observation

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基于视频的起重动作识别使用排列改变的动力学特征对.

SeHee Jung1, Bingyi Su1, Lu Lu1

  • 1North Carolina State University, USA.

Human factors
|December 26, 2024
PubMed
概括

本研究介绍了一种计算机视觉方法,用于实时识别和计数提升动作. 有效的方法使用动力学特征进行可靠的监控,有助于预防与工作有关的伤害.

科学领域:

  • 生物力学 生物力学
  • 计算机视觉 计算机视觉
  • 人体工程学就是人体工程学.

背景情况:

  • 传统的提升动作识别依赖于可穿戴传感器和深度学习,这可能是资源密集的.
  • 在有限的硬件上实施这些方法对实时监控提出了重大挑战.

研究的目的:

  • 开发一种简化,基于计算机视觉的方法,用于识别和计算视频中的举重动作.
  • 为了防止伤害,使提升任务的可靠实时监控成为可能.

主要方法:

  • 利用BlazePose进行实时的人类关键点检测.
  • 从检测到的关键点中提取和预处理动力学特征.
  • 员工级别改变的动力学特征对用于起重/非起重分类.
  • 开发了一个基于分类预测的升降计数算法.

主要成果:

  • 一个使用九个关键级别改变动态特征对的整体分类器在准确度,精度,回忆和F1分数方面取得了超过0.89的成绩.
  • 升降计数精度达到0.90,最小延迟为0.06毫秒.
  • 与基线分类器相比,拟议的方法显示的性能至少是基线分类器的12.5倍.

结论:

关键词:
计算机视觉 计算机视觉举起 计数 举起 计数肌肉骨疾病 肌肉骨疾病排名第一的得分对.工作场所安全工作场所安全

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  • 基于计算机视觉的动态特征为识别起重动作提供了有效和高效的解决方案.
  • 开发的方法适合在资源有限的平台上部署,如移动和嵌入式系统.
  • 提升任务的实时监控可以主动预防与工作相关的腰部伤害.