A Conceptual Model-based Digital Twin Platform for Holistic Large-scale Railway Infrastructure Systems

Zhou, Shiyang; Dumss, Stefan; Nowak, Rebecca; Riegler, Rainer; Kugu, Ozan; Krammer, Martin; Grafinger, Manfred

doi:10.1016/j.procir.2022.05.263

Cited by 11 publications

(10 citation statements)

References 10 publications

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“…(3) Compaction type damage ( z B ∆ ) is caused by insufficient concrete mix proportion, excessive temperature or improper design and construction of the required material quality and material quantity control structure layer during design and construction [14]. Improper design and construction pose a potential danger of sudden failure.…”

Section: Highway Health Trend Modelmentioning

confidence: 99%

Embedded Highway Health Maintenance System Based on Digital Twin Superposition Model

Lei,

Li,

Huang

2024

EAI Endorsed Trans Energy Web

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INTRODUCTION: The highway monitoring data acquisition technology develops quickly. Based on the traditional form of continuous monitoring, intelligent management system focuses on digital and wireless transmission. In the operation of highway maintenance system, each system is independent of each other, lacking of effective connection. Moreover, the level of continuous monitoring is obviously backward, which restricts the development of highway health monitoring. It is necessary to further study the level of integration to achieve the real-time tracking and the monitoring of highway’s healthy development. OBJECTIVES: This paper presents a highway health maintenance system based on digital twin technology, which intends to provide a solution for efficient, stable and automatic data transmission of the highway operation and maintenance management. METHODS: The output of the algorithm after the noise reduction effect is compared with the data containing the generated noise. The average number of nodes is set before running the algorithm to determine the actual length of the vertical position of the embedded sensor (calculating the position of two sensor nodes). The vertical length can be referred to the combined noise level formed and the combined test to determine the position. With the help of the overall data, it can be seen that the Kalman low-pass filtering algorithm can well describe the trend of the received signal and retain the key information in the received signal. RESULTS: It proves that the algorithm in this paper has fast calculation speed and high efficiency, and the basic working principle is simple. Thus, it is a good data denoising solution. CONCLUSION: The output in the paper ensures the data exchange and the update of the whole life cycle of highway, defines the digital twin entity model, and provides a reference for the establishment of information and data network.

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Section: Highway Health Trend Modelmentioning

confidence: 99%

Embedded Highway Health Maintenance System Based on Digital Twin Superposition Model

Lei,

Li,

Huang

2024

EAI Endorsed Trans Energy Web

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“…While their work is performed on a bridge, they are concerned about the flatness of the road on top. subject purpose railway power system [61] decrease failure risk, predict destruction of electric equipment railway tracks [62] determine track load, calculate structural stress high-speed train [99] enable new maintenance paradigms railway wheelset, railway pantograph [22] monitor state of railway infrastructure and vehicle, enable prognostic health management railway turnouts [63] estimate stress change railway [64] predictive maintenance railway point machine [65] enable safe train operations light rail transit [66] forecast remaining useful life, prescribe maintenance plans high-speed railway [67] improve infrastructure management, ensure safety railway infrastructure [68] integrate models into holistic platform…”

Section: Diagnostic Applications Of Digital Twinsmentioning

confidence: 99%

A Systematic Mapping Study of Digital Twins for Diagnosis in Transportation

Prikler,

Wotawa

2023

2023 10th International Conference on Dependable Systems and Their Applications (DSA)

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In recent years, digital twins have been proposed and implemented in various fields with potential applications ranging from prototyping to maintenance. Going forward, they are to enable numerous efficient and sustainable technologies, among them autonomous cars. However, despite a large body of research in many fields, academics have yet to agree on what exactly a digital twin is -and as a result, what its capabilities and limitations might be. To further our understanding, we explore the capabilities of digital twins concerning diagnosis in the field of transportation. We conduct a systematic mapping study including digital twins of vehicles and their components, as well as transportation infrastructure. We discovered that few papers on digital twins describe any diagnostic process. Furthermore, most existing approaches appear limited to system monitoring or fault detection. These findings suggest that we need more research for diagnostic reasoning utilizing digital twins.

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“…However they focus on a single subsystem of the railway infrastructure, from which models and data of different subsystems are to be integrated into the DT appropriately to make the DT system more comprehensive. (Zhou, Dumss, et al 2022) also proposed to continuously integrate the models and data from different railway subsystems into the conceptual model-based R4F Platform, which represents the fully connected and digital version of the holistic railway infrastructure system with a 6-layer system architecture. This work aims to enhance the model integration process occurring in the platform as mentioned before.…”

Section: Digital Twin For Railwaysmentioning

confidence: 99%

“…Finally, we need to ensure user control and visual representation of the railway infrastructure under consideration of user-friendliness and user-interactivity. Therefore we will integrate these models and data into a DT platform, called R4F Platform and proposed by (Zhou, Dumss, et al 2022).…”

Section: Introductionmentioning

confidence: 99%

An FMI- and SSP-based Model Integration Methodology for a Digital Twin Platform of a Holistic Railway Infrastructure System

Kugu,

Zhou,

Nowak

et al. 2023

Linköping Electronic Conference Proceedings

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Nowadays, the digitalization of large-scale railway infrastructure systems is a major trend, which helps to reduce the life-cycle costs of the railway transportation. For this purpose, the Digital Twin (DT) technology can be used to interoperate different digital data and models, belonging to the railway infrastructure system, in a virtual platform for predictive maintenance, diagnostics and condition monitoring in the railway sector. However, the simulation models of the infrastructure system are tool-dependent, lack ease-of-use and platform compatibility. Therefore, we have to customise them in order to make them more representative and then integrate easily and tool-independently into the DT platform. For this purpose, we propose to use the Functional Mock-up Interface (FMI) and System Structure Parameterization (SSP) technologies as open interface standards between the models and software tools. In this work, we demonstrate the application of the FMI and SSP standards separately for two use cases, which include a multibody simulation (MBS) model of a railway vehicle and residual life time (RLT) calculation of a steel bridge.

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A Conceptual Model-based Digital Twin Platform for Holistic Large-scale Railway Infrastructure Systems

Cited by 11 publications

References 10 publications

Embedded Highway Health Maintenance System Based on Digital Twin Superposition Model

Embedded Highway Health Maintenance System Based on Digital Twin Superposition Model

A Systematic Mapping Study of Digital Twins for Diagnosis in Transportation

An FMI- and SSP-based Model Integration Methodology for a Digital Twin Platform of a Holistic Railway Infrastructure System

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