Towards AI-assisted Long-term Maintenance in Power Electronics
| Autor: | Shuai Zhao, Saeed Peyghami, Daniel Gebbran, Tomislav Dragicevic, Huai Wang, Frede Blaabjerg |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Zdroj: | Zhao, S, Peyghami, S, Gebbran, D, Dragicevic, T, Wang, H & Blaabjerg, F 2022, ' Towards AI-assisted Long-term Maintenance in Power Electronics ', ETG Journal, no. 2, pp. 6-11 . < https://vde.1kcloud.com/ep1627a22222d248/#6 > Aalborg University |
| Popis: | This paper presents the applications of artificial intelligence (AI) in the long-term maintenance of power electronics. Longterm system performance depends on two major factors including intrinsic material strength and extrinsic stressors. To fulfill the reliability and safety requirements, various life-cycle maintenance approaches can be employed to either reinforce the strength of components or control the stressors. This paper presents the AI-assisted methods for these purposes, including the basics of AI tools, maintenance applications, and implementation hardware of AI for maintenance in power converters. Finally, a perspective on challenges and outlooks in the synergy of AI in power electronics is provided. |
| Databáze: | OpenAIRE |
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