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Cavitation State Identification Method of Hydraulic Turbine Based on Knowledge Distillation and Convolutional Neural Network
Power Generation Technology   Vol. 46, Issue 1, Pages: 161-170(2025)
Power Generation and Environmental Protection|Updated:2026-06-29
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    • Cavitation State Identification Method of Hydraulic Turbine Based on Knowledge Distillation and Convolutional Neural Network

    • “Accurately and quickly identifying the cavitation state of water turbines is crucial for the efficient and safe operation of hydropower stations. This article introduces the research progress in the field of fault diagnosis of hydropower equipment. Researchers have established a CNN lightweight identification system based on knowledge distillation, providing a solution to the problems of slow recognition of complex models and low accuracy of simple models.”
    • DOI:10.12096/j.2096-4528.pgt.23114    

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    • Revised:2024-03-02,

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Related Author

WU Qinghua
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TAN Huijuan
ZHAO Ruifeng
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Related Institution

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Power Dispatching Control Center, Guangdong Power Grid Co., Ltd.
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