A method of convolutional neural network based on frequency segmentation for monitoring the state of wind turbine blades

Zhu, Weijun; Wu, Yunan; Sun, Zhenye; Shen, Wenzhong; Guo, Guangxing; Lin, Jianwei

doi:10.1016/j.taml.2023.100479

Theoretical and Applied Mechanics Letters

2023

DOI: 10.1016/j.taml.2023.100479

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A method of convolutional neural network based on frequency segmentation for monitoring the state of wind turbine blades

Weijun Zhu,

Yunan Wu,

Zhenye Sun

et al.

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A method of convolutional neural network based on frequency segmentation for monitoring the state of wind turbine blades

Cited by 3 publications

References 22 publications

Failure analysis in predictive maintenance: Belt drive diagnostics with expert systems and Taguchi method for unconventional vibration features

Failure analysis in predictive maintenance: Belt drive diagnostics with expert systems and Taguchi method for unconventional vibration features

Accelerable adaptive cepstrum and L2-Dual Net for acoustic emission-based quality monitoring in laser shock peening

Anomaly identification of wind turbine blades based on Mel-Spectrogram Difference feature of aerodynamic noise

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