TROA-SVM

Zhuo Lei1, Haijun Lin1, Xudong Tang1

  • 1College of Engineering and Design, Hunan Normal University, Changsha 410081, China.

PubMed
概括

这项研究引入了一种使用Tyrannosaurus优化算法 (TROA) 和支持矢量机器 (SVM) 的新方法,用于从噪音信号中检测风力轮机叶片故障. TROA-SVM模型实现了98.7%的准确性,超过了传统方法.

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Turbine-Governor Control01:17

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Fault Types01:18

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