Article http://dx.doi.org/10.26855/ea.2024.02.007

Research on Intelligent Perception Architecture of Rail Transit Equipment Based on Modularization


Xiaoyu Shen

CRRC Academy, Beijing, China.

*Corresponding author: Xiaoyu Shen

Published: April 8,2024


This paper focuses on the contradiction between the rapid evolution of intelligent technology and the diverse intelligence requirements of industrial sites. Due to the rapid evolution of intelligent technology, which is challenging to develop, it will take a considerable amount of time to implement in the industrial setting. Meanwhile, there are various types of fault prediction and health management (PHM) systems for rail transit equipment to meet different requirements. These systems have complex interfaces within independent functional systems, which can result in the Islanding phenomenon. The cost of developing the PHM system is high, and it is difficult to modify or reuse it from one scenario to another. In the field of intelligent perception in rail transit, there is an urgent need for a unified architecture of condition monitoring technology. This architecture should be able to create a platform with standardized structure and open interfaces. In order to address these existing issues, an Intelligent Perception Architecture for Rail Transit Equipment based on modularization is proposed. Within this framework, the Device Intelligent Sensing Process Arrangement and Testing System has been implemented. The system can be used for preprocessing in PHM systems to efficiently establish the fault sensing process and conduct online testing. This helps address the challenge of integrating fault diagnosis technology into data processing management and scene-specific root causes.


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How to cite this paper

Research on Intelligent Perception Architecture of Rail Transit Equipment Based on Modularization

How to cite this paper: Xiaoyu Shen. (2024). Research on Intelligent Perception Architecture of Rail Transit Equipment Based on Modularization. Engineering Advances4(1), 38-42.

DOI: http://dx.doi.org/10.26855/ea.2024.02.007