Recognition method of ship radiated noise based on VMD and improved CNN
NI Junshuai1,2, HU Changqing1, ZHAO Mei1
1.Donghai Research Station, Institute of Acoustics, Chinese Academy of Sciences, Shanghai 201815, China;
2.University of Chinese Academy of Sciences, Beijing 100049, China
Abstract：Aiming at the problem of ship target recognition at sea with low signal-to-noise ratio, the traditional convolutional neural network is improved and combined with variational modal decomposition, a ship radiated noise recognition method based on Variational Modal Decomposition(VMD) and improved Convolutional Neural Network(CNN) is proposed. The proposed method is applied to identify 12 ship targets with radiated noise signal-to-noise ratio lower than 5dB in the East China Sea experiment, and the average accuracy is 98.6%; Compared with the other 7 recognition methods, it increased by 24.8%, 17.0%, 15.1%, 8.0%, 13.1%, 16.8% and 5.2% respectively; Compared with the traditional convolution network, the improved convolution network has obvious advantages in computation and recognition rate.
收稿日期: 2022-01-19
出版日期: 2023-03-15
引用本文:
倪俊帅1,2，胡长青1，赵梅1. 基于VMD和改进CNN的舰船辐射噪声识别方法[J]. 振动与冲击, 2023, 42(5): 74-82.
NI Junshuai1,2, HU Changqing1, ZHAO Mei1. Recognition method of ship radiated noise based on VMD and improved CNN. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(5): 74-82.
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