Wind Turbine Blades Fault Diagnosis Based on Vibration Signals Utilizing Convolutional Neural Network

Mouaad Bougoffa; Samir Benmoussa; Mohand Djeziri; T. Contaret

doi:10.1109/dasa63652.2024.10836616

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Wind Turbine Blades Fault Diagnosis Based on Vibration Signals Utilizing Convolutional Neural Network

Mouaad Bougoffa Samir Benmoussa Mohand Djeziri T. Contaret

Year: 2024 Pages: 1-5

DOI: 10.1109/dasa63652.2024.10836616

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Abstract

International audience

Keywords:

Convolutional neural network Fault (geology) Vibration Computer science Turbine Artificial neural network Wind power Condition monitoring Turbine blade Artificial intelligence Acoustics Engineering Geology Mechanical engineering Electrical engineering Seismology Physics

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0.64

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0.67

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Citation History

Topics

Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Engineering Diagnostics and Reliability

Physical Sciences → Engineering → Mechanics of Materials

Advanced Measurement and Detection Methods

Physical Sciences → Engineering → Electrical and Electronic Engineering

Wind Turbine Blades Fault Diagnosis Based on Vibration Signals Utilizing Convolutional Neural Network

Abstract

Metrics

Citation History

Topics

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