相关实验视频

Updated: Jun 23, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.7K

通过时间自回归建模来识别铁路桥梁的损坏.

Stefano Anastasia1, Enrique García-Macías2, Filippo Ubertini3

  • 1Department of Civil Engineering, University of Alicante, Carr. de San Vicente del Raspeig sn, 03690 Alicante, Spain.

Sensors (Basel, Switzerland)
|November 14, 2023
PubMed
概括

本研究引入了一种新的铁路桥梁损坏识别方法,使用应变数据和自回归系数. 它有效地检测,量化和定位损坏,优于加速测量.

关键词:
这就是SHM SHM.自动回归建模自动回归建模损害的识别损害的识别移动负载的移动负载铁路桥梁铁路桥梁统计模式识别 统计模式识别

更多相关视频

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior10:52

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

8.8K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K

相关概念视频

Maximum Deflection01:13

Maximum Deflection

When analyzing beams under unsymmetrical loads, such as a train moving on a bridge, it is crucial to accurately determine the points of maximum stress and deflection. The process involves identifying the maximum deflection of the beam, which may not always occur at its midpoint due to the uneven distribution of the load.
The maximum deflection occurs at a specific point, known as point O, where the tangent to the deflection curve is horizontal. To find point O, the slope of the tangent at any...