Regular Papers

International Journal of Control, Automation, and Systems 2024; 22(2): 360-372

https://doi.org/10.1007/s12555-023-0080-9

© The International Journal of Control, Automation, and Systems

Mathematical Modeling and Analysis of a Piston Air Compressor of a Railway Vehicle for Abnormal Data Generation

Myeong-Joon Kim, Hyun-Jik Cho, and Chul-Goo Kang*

Konkuk University

Abstract

To effectively implement condition-based maintenance for the air compressor in a railway vehicle, a thorough understanding of its fault characteristics and the collection of abnormal data is crucial. However, obtaining sufficient abnormal data from actual railway vehicles is challenging due to the rarity of air compressor failures in commercial railway services. This paper presents a detailed mathematical model of a two-stage piston air compressor that takes into account heat transfer effects. The mathematical model and the fault characteristics of the air compressor are analyzed through MATLAB simulation studies. The accuracy of the proposed model and analysis is verified by comparing it to real pressure data collected from a commercial Seoul subway train. The paper also generates abnormal data through simulations for specific fault conditions, including discharge valve leakages, air cooler malfunctions and pressure switch malfunctions.

Keywords Abnormal data, condition monitoring, mathematical modeling, piston air compressor, railway vehicle.

Article

Regular Papers

International Journal of Control, Automation, and Systems 2024; 22(2): 360-372

Published online February 1, 2024 https://doi.org/10.1007/s12555-023-0080-9

Copyright © The International Journal of Control, Automation, and Systems.

Mathematical Modeling and Analysis of a Piston Air Compressor of a Railway Vehicle for Abnormal Data Generation

Myeong-Joon Kim, Hyun-Jik Cho, and Chul-Goo Kang*

Konkuk University

Abstract

To effectively implement condition-based maintenance for the air compressor in a railway vehicle, a thorough understanding of its fault characteristics and the collection of abnormal data is crucial. However, obtaining sufficient abnormal data from actual railway vehicles is challenging due to the rarity of air compressor failures in commercial railway services. This paper presents a detailed mathematical model of a two-stage piston air compressor that takes into account heat transfer effects. The mathematical model and the fault characteristics of the air compressor are analyzed through MATLAB simulation studies. The accuracy of the proposed model and analysis is verified by comparing it to real pressure data collected from a commercial Seoul subway train. The paper also generates abnormal data through simulations for specific fault conditions, including discharge valve leakages, air cooler malfunctions and pressure switch malfunctions.

Keywords: Abnormal data, condition monitoring, mathematical modeling, piston air compressor, railway vehicle.

IJCAS
April 2024

Vol. 22, No. 4, pp. 1105~1460

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