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Research paper | Open Access

Research and design of an expert diagnosis system for rail vehicle driven by data mechanism models

Lin Li1, Jiushan Wang2( ), Shilu Xiao2
Zhuzhou Guochuang Rail Technology Company Limited, Zhuzhou, China
Zhuzhou Guochuang Rail Technology Company Limited, Industrial Intelligence Research Institute, Zhuzhou, China
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Abstract

Purpose

The aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.

Design/methodology/approach

The expert diagnosis system utilizes statistical and deep learning methods to model the real-time status and historical data features of rail vehicle. Based on data mechanism models, it predicts the lifespan of key components, evaluates the health status of the vehicle and achieves intelligent monitoring and diagnosis of rail vehicle.

Findings

The actual operation effect of this system shows that it has improved the intelligent level of the rail vehicle monitoring system, which helps operators to monitor the operation of vehicle online, predict potential risks and faults of vehicle and ensure the smooth and safe operation of vehicle.

Originality/value

This system improves the efficiency of rail vehicle operation, scheduling and maintenance through intelligent monitoring and diagnosis of rail vehicle.

Keywords

Deep learningReliability analysisIntelligent operation and maintenanceRail transitRail vehicleExpert diagnosisLifespan prediction

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Railway Sciences
Volume 3 Issue 4,
August 2024
Pages 480-502
DOI: 10.1108/RS-05-2024-0016
Cite this article:
Li L, Wang J, Xiao S. Research and design of an expert diagnosis system for rail vehicle driven by data mechanism models. Railway Sciences, 2024, 3(4): 480-502. https://doi.org/10.1108/RS-05-2024-0016

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Received: 28 May 2024
Revised: 03 July 2024
Accepted: 05 July 2024
Published: 30 July 2024
© Lin Li, Jiushan Wang and Shilu Xiao. Published in Railway Sciences.

This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
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