THE MODEL OF REMOTE MONITORING SYSTEM FOR ELECTRIC ROLLING STOCK CONDITION USING ARTIFICIAL NEURAL NETWORKS The Model of Remote Monitoring System for Electric Rolling Stock Condition Using Artificial Neural Networks

Published in Intellectual Technologies on Transport · Pages 27–37 · Rubric: Articles
DOI: https://doi.org/10.24412/2413-2527-2023-133-27-37
Received: 11.01.2025 Accepted: 11.01.2025 Published: 11.01.2025 Language of publication: RUS
The paper analyzes tools for automated monitoring of rolling stock, establishes requirements, and develops a model of information system to monitor the characteristics of the rolling stock. A number of artificial neural network architectures have been analyzed, and a convolutional neural network algorithm for determining the percentage of the rolling stock current collector wear on the basis of pictures has been proposed. The algorithm includes image preprocessing, creation of convolutional neural network model, its training and use for classification of new images.
artificial neural networks, neural network technologies, information technologies, railway transport, remote monitoring