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Updated: May 1, 2026

Data Acquisition Protocol for Determining Embedded Sensitivity Functions
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Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

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在浮动风力轮机中使用振动信号进行基于机器学习的损害诊断:在不同风速和方向下进行实验室规模的研究

John S Korolis1, Dimitrios M Bourdalos1, John S Sakellariou1

  • 1Stochastic Mechanical Systems & Automation (SMSA) Laboratory, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, Greece.

Sensors (Basel, Switzerland)
|February 26, 2025
PubMed
概括

远程诊断使用机器学习 (ML) 结构健康监测 (SHM) 准确检测,识别和评估漂浮风力轮机 (FWT) 的损坏. 这种先进的方法可以确保及时修复,提高安全性,并降低离岸运营的成本.

关键词:
损害诊断 损害诊断 损害诊断 损害诊断 损害诊断漂浮式风力轮机是什么意思机器学习方法 机器学习方法不同的风力条件.振动信号表示振动信号.

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