Assessment of catenary condition monitoring by means of pantograph head acceleration and Artificial Neural Networks-Reference-Cited by-同舟云学术

Assessment of catenary condition monitoring by means of pantograph head acceleration and Artificial Neural Networks

Published:2023-11 Issue: Volume:202 Page:110697
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Gregori S.^ORCID,Tur M.^ORCID,Gil J.^ORCID,Fuenmayor F.J.^ORCID

Funder

Agencia Estatal de Investigación

Gobierno de España Ministerio de Ciencia e Innovación

Generalitat Valenciana

Ministerio de Ciencia e Innovación

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference40 articles.

1. Contact Lines for Electric Railways: Planning, Design, Implementation, Maintenance;Kiessling,2018

2. Eigenfrequency-based Bayesian approach for damage identification in catenary poles;Alkam;Infrastructures,2021

3. Permanent monitoring of railway overhead catenary poles inclination;Efanov,2017

4. Multi-objective performance evaluation of the detection of catenary support components using DCNNs;Liu;IFAC-PapersOnLine,2018

5. Automatic defect detection of fasteners on the catenary support device using deep convolutional neural network;Chen;IEEE Trans. Instrum. Meas.,2017

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