Architecting a Digital Twin-Based Predictive Maintenance System for Modelling Cable Joint Degradation

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Sep 4, 2023
Raymon van Dinter Görkem Ekmekci Sander Rieken Bedir Tekinerdogan Cagatay Catal

Abstract

The large scale adoption of wind turbines and solar panels in the Netherlands places new demands on the medium voltage power grid. For example, highly varying loads can cause failures in certain cables. Cable joints are natural weak spots prone to faults due to varying currents, creating downtime challenges for public utility companies. Predictive maintenance (PdM) practices are necessary to minimize downtime for users. We present a Model-Based System Engineering approach using formal models and UML views to provide a scalable PdM design ontology for modeling cable joint degradation. We aim to monitor cable joint degradation from different manufacturers under varying conditions throughout the Netherlands in real-time using a Digital Twin (DT) approach. Our design provides high-resolution, real-time synchronization between the DT-based PdM system and the cable joints. The proposed architecture is scalable, robust, and flexible, and the software implementation is publicly available in an open-source repository.  

Abstract 179 | PDF Downloads 199

##plugins.themes.bootstrap3.article.details##

Keywords

predictive maintenance, digital twin, system architecture, electricity grid, partial discharge

References
Aizpurua, J. I., & Catterson, V. M. (2015). Towards a methodology for design of prognostic systems [Conference Proceedings]. In Annual conference of the phm society (Vol. 7).

Aizpurua, J. I., & Catterson, V. M. (2016). Adeps: a methodology for designing prognostic applications [Conference Proceedings]. In Phm society european conference (Vol. 3).

Alliander. (n.d.). Weather api (Vol. 2023) (Web Page No. 7 March). Retrieved from https://weather.appx .cloud/api/v2/docs#

Cocheteux, P., Voisin, A., Levrat, E., & Iung, B. (2009). Prognostic design: requirements and tools. In 11th international conference on the modern information technology in the innovation processes of the industrial enterprises,, mitip 2009 (p. CDROM).

Kruchten, P. B. (1995). The 4+ 1 view model of architecture. IEEE software, 12(6), 42–50.

Lee, J., Bagheri, B., & Kao, H.-A. (2015). A cyber-physical systems architecture for industry 4.0-based manufacturing systems [Journal Article]. Manufacturing letters, 3, 18-23.

Li, R., Verhagen, W. J., & Curran, R. (2018). A functional architecture of prognostics and health management using a systems engineering approach [Conference Proceedings]. In Proc. eur. conf. phm soc (p. 1-10).

Mall, R. (2018). Fundamentals of software engineering [Book]. PHI Learning Pvt. Ltd.

Tiddens, W. W. (2018). Setting sail towards predictive maintenance: developing tools to conquer difficulties in the implementation of maintenance analytics [Journal Article].

van Dinter, R., Ekmekci, G., Netten, G., Rieken, S., Tekinderdogan, B., & Catal, C. (2023, April). A code repository for predictive maintenance on cable joints. doi: 10.5281/zenodo.7863853

van Dinter, R., Tekinerdogan, B., & Catal, C. (2022). Predictive maintenance using digital twins: A systematic literature review. Information and Software Technology, 107008.

van Dinter, R., Tekinerdogan, B., & Catal, C. (2023). Reference architecture for digital twin-based predictive maintenance systems [Journal Article]. Computers Industrial Engineering, 177, 109099.

van Osch, M. (2021). Analyzing data of the medium voltage grid and the weather to predict power outages (Thesis, Radboud University). Retrieved from https://www.math.ru.nl/ ̃bosma/ Students/MeesvanOschMSc.pdf

Vogl, G. W., Weiss, B. A., & Donmez, M. A. (2014). Standards for prognostics and health management (phm) techniques within manufacturing operations (Report). National Institute of Standards and Technology Gaithersburg United States.

Wagenaars, P. (2010). Integration of online partial discharge monitoring and defect location in medium-voltage cable networks (Doctoral dissertation, Technische Universiteit Eindhoven). doi: 10.6100/IR656994
Section
Regular Session Papers