Fault Prediction of Hydropower Station Based on CNN-LSTM-GAN with Biased Data

Fault Prediction of Hydropower Station Based on CNN-LSTM-GAN with Biased Data

Fault prediction of hydropower station is crucial for the stable operation of generator set equipment, but the traditional method struggles to deal with data with an imbalanced distribution and untrustworthiness. This paper proposes a fault detection method based on a convolutional neural network (C...

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Bibliographic Details
Main Authors: Bei Liu, Xiao Wang, Zhaoxin Zhang, Zhenjie Zhao, Xiaoming Wang, Ting Liu
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Energies
Subjects:
failure prediction
hydropower station
biased data
CNN-LSTM
multi-scale feature extraction
Online Access:https://www.mdpi.com/1996-1073/18/14/3772
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