Novel identification technique of moving loads using the random response power spectral density and deep transfer learning-Reference-Cited by-同舟云学术

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Novel identification technique of moving loads using the random response power spectral density and deep transfer learning

Published:2022-05 Issue: Volume:195 Page:111120
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Tang Qizhi,Xin Jingzhou,Jiang Yan,Zhou Jianting,Li Shuangjiang,Chen Zhiyong

Funder

Natural Science Foundation of Chongqing

Chongqing Jiaotong University

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference42 articles.

1. Vehicle weight identification system for spatiotemporal load distribution on bridges based on non-contact machine vision technology and deep learning algorithms;Zhou;Measurement,2020

2. Sparse regularization for traffic load monitoring using bridge response measurements;Zhong;Measurement.,2019

3. An accurate and robust monitoring method of full-bridge traffic load distribution based on YOLO-v3 machine vision;Ge;Struct. Control Hlth.,2020

4. Identification of dynamic vehicular axle loads: theory and simulations;Deng;J. Sound Vib.,2010

5. A novel preconditioned range restricted GMRES algorithm for moving force identification and its experimental validation;Chen;Mech. Syst. Signal Pr.,2021

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1. An online reconstruction method of dynamic loading based on adaptive tracking dual nested Kalman filter;Measurement;2025-02

2. A Generative adversarial network model for estimating temporal frequency variation of vehicle-bridge interaction using modified Stockwell transform;Journal of Sound and Vibration;2025-01

3. Research status of monitoring, detection, and intelligent identification of weathering steel bridges;Journal of Constructional Steel Research;2024-09

4. Low frequency load identification under high noise level using weighted total least squares;Measurement;2024-08

5. A deep learning method for heavy vehicle load identification using structural dynamic response;Computers & Structures;2024-07

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