• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >A Siamese Network-Based Non-Contact Measurement Method for Railway Catenary Uplift Trained in a Free Vibration Test
【2h】

A Siamese Network-Based Non-Contact Measurement Method for Railway Catenary Uplift Trained in a Free Vibration Test

机译：一种基于暹罗的基于网络的无接触式测量方法用于在自由振动试验中训练

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The vibration of the catenary that is initiated by the passing pantograph has a direct influence on the pantograph–catenary contact performance. Monitoring the dynamic uplift of the catenary can help inspectors to evaluate the railway operation conditions and investigate the mechanism of pantograph–catenary interaction further. In this paper, a non-contact measurement method based on the deep leaning method is proposed to monitor the real-time vibration of the catenary. The field test for the catenary free vibration is designed to validate the method’s performance. The measurement method is developed based on the fully convolutional Siamese neural network, and the contact wire is taken as the tracking target. To reduce the recognition errors caused by the changes in the shape and grayscale of the moving contact wire in images, the class-agnostic binary segmentation mask is adopted. A developed down-sampling block is used in the neural network to reduce the image feature loss, which effectively enhances the recognition effect for the catenary vibration under variable lighting conditions. To validate the performance of the proposed measurement method, a series of field tests of catenary free vibration were conducted under various lighting conditions and different excitations, and the recognition results were compared with traditional target tracking methods. The results show that the proposed method performs well for catenary vibration identification in the field test. Additionally, the uplift data extracted from the identified images agree with the numerical results, and also help to further investigate the wave propagation and damping characteristics in the catenary structure.
机译：通过通映引导仪启动的脉络的振动对触摸扰解仪膨胀的接触性能直接影响。监测电网的动态隆起可以帮助检查员评估铁路运行条件并进一步调查受诱变诱导诱导诱变的机制。本文提出了一种基于深层倾斜法的非接触式测量方法来监测衔接性的实时振动。屏蔽自由振动的现场测试旨在验证该方法的性能。基于完全卷积的暹罗神经网络开发了测量方法，并将接触线作为跟踪目标。为了减少由图像中移动接触线的形状和灰度的变化引起的识别误差，采用了类别不可知的二进制分割掩模。在神经网络中使用开发的下采样块以减少图像特征损耗，从而有效地提高了可变照明条件下的凸起振动的识别效果。为了验证所提出的测量方法的性能，在各种照明条件下进行一系列通近自由振动的现场测试，并将识别结果与传统的目标跟踪方法进行比较。结果表明，该方法对现场试验中的脉冲振动识别进行了良好。另外，从所识别的图像中提取的隆起数据与数值结果一致地同意，并且还有助于进一步研究凸起结构中的波传播和阻尼特性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号