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相关概念视频

Design Example: Strain Gauge Bridge or Wheatstone Bridge01:15

Design Example: Strain Gauge Bridge or Wheatstone Bridge

365
The utilization of strain gauges as transducers for converting mechanical strain into electrical signals is a common practice in various engineering applications. These strain gauges are frequently integrated into Wheatstone bridge circuits to accurately measure parameters such as force or pressure. Within this context, each element within the circuit exhibits a resistance that undergoes subtle variations when subjected to mechanical strain. The primary objective is to convert minuscule...
365
Measurements of Strain01:27

Measurements of Strain

520
Strain quantifies the deformation of a material under force, typically measured as normal strain, which represents the change in length when compared with the original length. Electrical strain gauges are used for enhanced accuracy. These devices consist of a conductive wire mounted on a paper backing that adheres to the material's surface. These gauges operate on the piezoresistive effect, where the wire's electrical resistance changes in response to mechanical deformation. The strain...
520
Stress-Strain Diagram01:10

Stress-Strain Diagram

598
A stress-strain diagram is a crucial tool that graphically displays a material's mechanical characteristics. This diagram is derived from a tensile test performed on a carefully prepared cylindrical specimen. The specimen has two gauge marks inscribed on its central part, and the distance between these marks is known as the gauge length. The cylindrical specimen is placed in a testing machine, which applies an increasing centric load. As this load grows, so does the gauge length. This...
598
Shearing Strain01:20

Shearing Strain

235
The shearing strain represents a cubic element's angular change when subjected to shearing stress. This type of stress can transform a cube into an oblique parallelepiped without influencing normal strains. The cubic element experiences a significant transformation when exposed solely to shearing stress. Its shape alters from a perfect cube into a rhomboid, clearly demonstrating the effect of shearing strain. The degree of this strain is considered positive if it reduces the angle between...
235
True Stress and True Strain01:28

True Stress and True Strain

280
Engineering stress is calculated as the load divided by the original, undeformed cross-sectional area. It approximates a material under load. This approximation is especially relevant post-yield in ductile materials. Though engineering stress-strain diagrams are often used for their convenience and accessibility, they can sometimes fall short in accuracy, particularly when dealing with large strain values.
In contrast, true stress offers a more precise portrayal. It is computed by dividing the...
280
Strain Energy01:13

Strain Energy

393
Strain energy is a fundamental concept in the field of materials science and structural engineering, describing the energy absorbed by a material or structure when it is deformed under load.
Consider a rod that is fixed at one end and subjected to an axial force at the free end. This axial force induces stress within the rod, leading to its elongation. As the axial force increases, so does the elongation of the rod, illustrating a direct relationship between the force applied and the resulting...
393

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相关实验视频

Updated: Jun 13, 2025

Strain Sensing Based on Multiscale Composite Materials Reinforced with Graphene Nanoplatelets
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数据驱动的应变传感器设计基于知识图框架.

Junmin Ke1,2, Furong Liu1,2, Guofeng Xu1,2

  • 1Key Laboratory of Trans-Scale Laser Manufacturing, Beijing University of Technology, Ministry of Education, Beijing 100124, China.

Sensors (Basel, Switzerland)
|September 14, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了知识图和图表表示学习框架,以加快灵活应变传感器的设计. 这种方法提高了预测准确度,并使得能够发现具有卓越性能的新型传感器设计.

关键词:
知识图表知识图表机器学习是机器学习.材料科学 是一种材料科学.应变传感器是一种应变传感器.

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Last Updated: Jun 13, 2025

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科学领域:

  • 材料科学 材料科学 材料科学
  • 传感器技术 传感器技术
  • 人工智能的人工智能

背景情况:

  • 开发可穿戴的灵活应变传感器需要特定应用的性能,但实验方法缓慢且低效.
  • 由于知识冗余和设计空间的有限探索,现有的方法往往导致低于最佳的传感器设计.

研究的目的:

  • 通过整合知识图表和图表表示学习来开发智能传感器设计的新框架.
  • 克服传感器开发中的传统实验方法和基于过程参数的机器学习的局限性.
  • 发现具有目标性能特性的新传感器设计.

主要方法:

  • 为了分析传感器知识,提出了一个结合知识图和图形表示学习的框架.
  • 使用来自知识图中的关系的语义特征,提高了预测精度.
  • 该框架通过设计和测试一种新的灵活应变传感器来验证.

主要成果:

  • 拟议的框架实现了高达0.81的预测精度,超过了传统方法.
  • 一个新设计的应变传感器证明了300%的应变的广泛工作范围.
  • 测试的传感器的性能与预测非常相匹配,并且超过了类似材料的性能.

结论:

  • 开发的框架通过有效地管理和利用传感器知识来促进智能传感器设计.
  • 这种方法减少了知识冗余,并使高性能传感器的发现成为可能.
  • 该研究为传感器系统的基于文本挖掘的知识管理铺平了道路,加速了创新.