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Updated: Jun 3, 2025

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基于数字双胞胎和多任务LSTM-GRU模型预测功率变压器健康指数和预期寿命

Nora El-Rashidy1, Yara A Sultan2, Zainab H Ali3,4

  • 1Department of Machine Learning and Information Retrieval, Faculty of Artificial Intelligence, Kafrelsheikh University, El-Geish St, Kafrelsheikh, 33516, Egypt. Noura.alrashidy@ai.kfs.edu.eg.

Scientific reports
|January 8, 2025
PubMed
概括

本研究介绍了一种使用雾计算和数字双胞胎的智能电力监测系统 (SEMS-FDT),以实时监测变压器的健康状况. 该系统使用先进的机器学习模型预测变压器健康指数 (THI) 和热负荷指数 (LI).

关键词:
数字双胞胎是一个数字双胞胎.在 LSTM_GRU 中使用.机器学习是机器学习.电力变压器的功率变压器变压器健康指数

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