节能2025，Vol.44Issue(9)：147-150,4.DOI:10.3969/j.issn.1004-7948.2025.09.033
基于深度学习的海上风电导管架基础振动异常模式识别与预警技术
Recognition and early warning technology for abnormal vibration patterns of offshore wind power jacket foundations based on deep learning
金波1
作者信息
- 1. 浙江华东测绘与工程安全技术有限公司,浙江 杭州 310014
- 折叠
摘要
Abstract
Aiming at the problem of abnormal vibration identification of offshore wind power jacket foundations,a recognition and early warning system based on deep learning is established.By combining wavelet packet transform and convolutional neural networks,multi-scale vibration features are extracted;By fusing multi-source sensor data through the attention mechanism,an end-to-end anomaly recognition model is constructed,and an energy-saving technical solution for vibration control and energy recovery is designed.The results show that through scale-down tests and engineering verification,the structural optimization reduces weight by 25%,and the vibration control reduces the peak response by 35%to 42%,effectively lowering operation and maintenance costs and shortening the payback period of investment.关键词
海上风电/导管架基础/振动异常识别/深度学习/预警技术Key words
offshore wind power/jacket foundation/identification of abnormal vibration/deep learning/early warning technology分类
能源科技引用本文复制引用
金波..基于深度学习的海上风电导管架基础振动异常模式识别与预警技术[J].节能,2025,44(9):147-150,4.
