Recognition method of ship radiated noise based on VMD and improved CNN
NI Junshuai1,2, HU Changqing1, ZHAO Mei1
Author information+
1.Donghai Research Station, Institute of Acoustics, Chinese Academy of Sciences, Shanghai 201815, China;
2.University of Chinese Academy of Sciences, Beijing 100049, China
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.
NI Junshuai1,2, HU Changqing1, ZHAO Mei1.
Recognition method of ship radiated noise based on VMD and improved CNN[J]. Journal of Vibration and Shock, 2023, 42(5): 74-82
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