Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions

M.W. Hoffmann, S. Wildermuth, R. Gitzel, A. Boyaci, J. Gebhardt, H. Kaul, I. Amihai, B. Forg, M. Suriyah, T. Leibfried, V. Stich, J. Hicking, M. Bremer, L. Kaminski, D. Beverungen, P. zur Heiden, T. Tornede, Sensors (2020).

Journal Article | Published | English
Author
Hoffmann, Martin W.; Wildermuth, Stephan; Gitzel, Ralf; Boyaci, Aydin; Gebhardt, Jörg; Kaul, Holger; Amihai, Ido; Forg, Bodo; Suriyah, Michael; Leibfried, Thomas; Stich, Volker; Hicking, Jan
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Abstract
<jats:p>The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.</jats:p>
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Journal Title
Sensors
Article Number
2099
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Hoffmann MW, Wildermuth S, Gitzel R, et al. Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions. Sensors. 2020. doi:10.3390/s20072099
Hoffmann, M. W., Wildermuth, S., Gitzel, R., Boyaci, A., Gebhardt, J., Kaul, H., … Tornede, T. (2020). Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions. Sensors. https://doi.org/10.3390/s20072099
@article{Hoffmann_Wildermuth_Gitzel_Boyaci_Gebhardt_Kaul_Amihai_Forg_Suriyah_Leibfried_et al._2020, title={Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions}, DOI={10.3390/s20072099}, number={2099}, journal={Sensors}, author={Hoffmann, Martin W. and Wildermuth, Stephan and Gitzel, Ralf and Boyaci, Aydin and Gebhardt, Jörg and Kaul, Holger and Amihai, Ido and Forg, Bodo and Suriyah, Michael and Leibfried, Thomas and et al.}, year={2020} }
Hoffmann, Martin W., Stephan Wildermuth, Ralf Gitzel, Aydin Boyaci, Jörg Gebhardt, Holger Kaul, Ido Amihai, et al. “Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions.” Sensors, 2020. https://doi.org/10.3390/s20072099.
M. W. Hoffmann et al., “Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions,” Sensors, 2020.
Hoffmann, Martin W., et al. “Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions.” Sensors, 2099, 2020, doi:10.3390/s20072099.
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