Intelligent Framework and System for Remote Monitoring and Prediction of Power Transformer Conditions
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-96196-1_29
Reference12 articles.
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2. Rokani, V., Kaminaris, S.D.: Power transformers fault diagnosis using AI techniques. Presented at the Technologies and Materials for Renewable Energy, Environment and Sustainability: TMREES20, Athens, Greece (2020). https://doi.org/10.1063/5.0032820
3. Memala, W.A., Bhuvaneswari, C., Mana, S.C., Selvan, M.P., Maniraj, M., Kishore, S.: An approach to remote condition monitoring of electrical machines based on IOT. J. Phys. Conf. Ser. 1770, 012023 (2021). https://doi.org/10.1088/1742-6596/1770/1/012023
4. Bustamante, S., Manana, M., Arroyo, A., Castro, P., Laso, A., Martinez, R.: Dissolved gas analysis equipment for online monitoring of transformer oil: a review. Sensors 19, 4057 (2019). https://doi.org/10.3390/s19194057
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