Remote Health Monitoring of Wind Turbines Employing Vibroacoustic Transducers and Autoencoders

被引：0
|
作者：
Czyzewski, Andrzej [1 ]
机构：
[1] Gdansk Univ Technol, Fac Elect Telecommun & Informat, Multimedia Syst Dept, Gdansk, Poland
来源：
FRONTIERS IN ENERGY RESEARCH | 2022年 / 10卷
关键词：
wind turbines; remote monitoring; acoustic intensity; accelerometers; machine learning; neural networks; autoencoders; NOISE;
D O I：
10.3389/fenrg.2022.858958
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Implementation of remote monitoring technology for real wind turbine structures designed to detect potential sources of failure is described. An innovative multi-axis contactless acoustic sensor measuring acoustic intensity as well as previously known accelerometers were used for this purpose. Signal processing methods were proposed, including feature extraction and data analysis. Two strategies were examined: Mel Frequency Cepstral Coefficients pruned with principal component analysis and autoencoder-based feature extraction. The scientific experiment resulted in data gathering and analysis to predict potential wind turbine mechanism failures.
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收藏
页数：20
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