Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Rolling Resistance: Problem Solving01:17

Rolling Resistance: Problem Solving

375
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...
375
Detection of Black Holes01:10

Detection of Black Holes

2.2K
Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
Their closest cousins are neutron stars, which are composed almost entirely of neutrons packed against each other, making them extremely dense. A neutron star has the same mass as the Sun but its diameter is only a few kilometers. Therefore, the escape velocity from their surface is close to the speed of light.
Not until the 1960s, when the first neutron...
2.2K
Force Classification01:22

Force Classification

1.3K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.3K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A Novel Low-Cost Compact High-Performance Flower-Shaped Radiator Design for Modern Smartphone Applications.

Micromachines·2023
Same author

Ethical Dilemmas and Privacy Issues in Emerging Technologies: A Review.

Sensors (Basel, Switzerland)·2023
Same author

Novel Corrugated Long Period Grating Surface Balloon-Shaped Heterocore-Structured Plastic Optical Fibre Sensor for Microalgal Bioethanol Production.

Sensors (Basel, Switzerland)·2023
Same author

Artificial Neural Networks to Solve the Singular Model with Neumann-Robin, Dirichlet and Neumann Boundary Conditions.

Sensors (Basel, Switzerland)·2021

相关实验视频

Updated: Jul 20, 2025

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.5K

使用混合深度学习方法检测车轮缺陷.

Khurram Shaikh1, Imtiaz Hussain2, Bhawani Shankar Chowdhry3

  • 1Department of Electronic Engineering, Mehran University of Engineering and Technology, Jamshoro 76062, Pakistan.

Sensors (Basel, Switzerland)
|July 29, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种混合深度学习方法,用于使用加速度计数据检测铁路车轮缺陷. 该方法实现了高精度,提高了安全性并降低了铁路运营中的维护成本.

关键词:
在MLP中,MLP是MLP.深度学习是一种深度学习.一个虚假的法兰.非线性动力学的非线性动态车轮缺陷 车轮缺陷 车轮缺陷轮子的平面,轮子的平面

更多相关视频

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.7K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

571

相关实验视频

Last Updated: Jul 20, 2025

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.5K
Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.7K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

571

科学领域:

  • 铁路工程 铁路工程是指铁路工程.
  • 机器学习 机器学习
  • 振动分析 振动分析

背景情况:

  • 缺陷的铁路轮损害了运营安全和性能,导致振动,噪音和轨道损坏的增加.
  • 早期检测轮胎缺陷对于安全,舒适和成本有效的维护至关重要.
  • 机载检测受到环境振动的挑战,导致虚假报警和不准确的缺陷识别.

研究的目的:

  • 开发一种混合深度学习方法,用于准确地在车上检测铁路车轮缺陷.
  • 为了提高轮子缺陷检测的准确性,同时保持成本效益和效率.
  • 解决环境振动引起的当前检测方法的局限性.

主要方法:

  • 开发了一种现实的铁路车轮模拟模型,在各种条件下生成振动数据 (无故障和六个故障场景).
  • 在不同的速度和轨道条件下进行模拟,每次代生成20万个数据点.
  • 训练和评估了一种混合深度学习模型,该模型结合了多层感知器 (MLP) 来进行特征提取和几种机器学习模型 (SVM,随机森林,决策树,KNN) 来进行分类.

主要成果:

  • 混合型MLP-RF模型在检测轮子缺陷方面达到99%的准确性,MLP-DT模型在检测轮子缺陷方面达到98%的准确性.
  • 提出的深度学习模型在准确分类和预测轮子缺陷方面表现出高效.
  • 该研究评估了传感器布局的有效性,并应用了深度学习来改进车轮平面检测.

结论:

  • 混合深度学习方法为车载铁路车轮缺陷检测提供了高度准确和有效的解决方案.
  • 开发的模拟模型为生成用于训练和评估检测算法的全面数据集提供了有价值的工具.
  • 这项研究有助于通过先进的缺陷检测技术提高铁路安全和运营效率.