Crack Diagnosis Method of Wind Turbine Blade Based on Convolution Neural Network with 3D Vibration Information Fusion

Yingfu Guo; Weiming Quan; Wenyun Wang; Hao Zhou; Longzhou Zou

doi:10.3788/AOS202040.2212004

Journals >Acta Optica Sinica >Volume 40 >Issue 22 >Page 2212004 > Article

Acta Optica Sinica
Vol. 40, Issue 22, 2212004 (2020)

Crack Diagnosis Method of Wind Turbine Blade Based on Convolution Neural Network with 3D Vibration Information Fusion

Yingfu Guo¹, Weiming Quan¹, Wenyun Wang^2、*, Hao Zhou¹, and Longzhou Zou¹

Author Affiliations

¹Electromechanic Engineering College, Hunan University of Science and Technology, Xiangtan, Hunan 411201, China

²Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Xiangtan, Hunan 411201, China

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DOI: 10.3788/AOS202040.2212004 Cite this Article Set citation alerts

Yingfu Guo, Weiming Quan, Wenyun Wang, Hao Zhou, Longzhou Zou. Crack Diagnosis Method of Wind Turbine Blade Based on Convolution Neural Network with 3D Vibration Information Fusion[J]. Acta Optica Sinica, 2020, 40(22): 2212004 Copy Citation Text

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