A Network-Based Method to Analyze EMI Events of On-Board Signaling System in Railway
The On-board Train Control System (OTCS) plays an important role in the real-time operation of the electric multiple units (EMU) in high-speed railway. The EMU is a complex system made up of various electrical and electronic equipment, so the interactions of the electromagnetic (EM) environment and...
Gespeichert in:
Veröffentlicht in: | Applied sciences 2020-12, Vol.10 (24), p.9059 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The On-board Train Control System (OTCS) plays an important role in the real-time operation of the electric multiple units (EMU) in high-speed railway. The EMU is a complex system made up of various electrical and electronic equipment, so the interactions of the electromagnetic (EM) environment and OTCS are difficult to study, which leads to more challenges to analyze EM interference (EMI) events at the system level. To overcome this difficulty, this paper proposes the thought of a graph model to solve the problem. First, a framework is proposed to more clearly reflect the relationship between the EMC (Electromagnetic Compatibility) problem and network through a comparison with them. Second, a network theory-based model is presented to express the EMC elements for the OTCS in EMU. It decomposes the OTCS and EMU with EMC elements into edges and nodes of the network, which parameters are defined corresponding to EM sources, sensitive equipment, and coupling paths. Thus, each part could be modeled separately or together by calculation, simulation, or measurement, respectively, and the EMC problem could be represented by the paths from origin to destination in the network. Moreover, the modeling process was elucidated by the specific cases in OTCS and the validity of the proposed approach was verified by calculation and measurement results in the case study. |
---|---|
ISSN: | 2076-3417 2076-3417 |
DOI: | 10.3390/app10249059 |