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Cavitation State Recognition Method of Hydraulic Turbine Based on Energy-Entropy Features and Improved Stacked Denoising Auto Encoder
Power Generation Technology   Vol. 47, Issue 1, Pages: 176-184(2026)
Power Generation and Environmental Protection|Updated：2026-05-15
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    • Cavitation State Recognition Method of Hydraulic Turbine Based on Energy-Entropy Features and Improved Stacked Denoising Auto Encoder

    • “2026年5月15日长沙理工大学能源与动力工程学院的刘圳、刘忠团队在《发电技术》发文，介绍了其在水轮机故障诊断领域的研究进展，团队建立了基于能量熵特征和哈里斯鹰优化算法的空化信号识别体系，为解决水轮机空化状态监测难题提供解决方案。”

    • DOI：10.12096/j.2096-4528.pgt.260116    

      CLC：

    • Revised：2025-08-31，

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