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A Ship Noise Recognition Method Based on Holographic Spectrum and Deep Learning

A deep learning and holographic spectrum technology, applied in the field of signal processing, can solve the problems that affect the recognition effect, it is difficult to completely match the frequency band of cavitation noise, etc., and achieve accurate and stable recognition results

Active Publication Date: 2022-03-01
THE FIRST INST OF OCEANOGRAPHY SOA
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, in the modulation spectrum method, the modulated noise may appear in different frequency bands, which makes it difficult for the modulation spectrum method to completely match the real cavitation noise frequency band, which affects the identification effect

Method used

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  • A Ship Noise Recognition Method Based on Holographic Spectrum and Deep Learning
  • A Ship Noise Recognition Method Based on Holographic Spectrum and Deep Learning
  • A Ship Noise Recognition Method Based on Holographic Spectrum and Deep Learning

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Embodiment 1

[0031] Hydrophones used to collect ship noise are generally deployed in seawater in the form of submersible buoys, some work in a self-contained manner, and some transmit the collected data back to the shore-based computing center through cables, underwater acoustics or radio. There is a processing platform in the shore-based computing center to realize the analysis and processing of ship noise signals. The impact of platform vibration and noise on hydrophones should be considered during deployment. Under normal circumstances, the platform should carry out vibration and noise reduction work, including the streamlined design of the main floating body, and the use of rubber vibration isolation at the connection between the swivel and the shackle. In addition, the hydrophone and the platform are generally connected by springs or elastic lines to isolate the vibration of the platform. Another deployment method is a surface ship or a submarine. At this time, the ship noise heard b...

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Abstract

The invention relates to a ship noise identification method based on holographic spectrum and deep learning, which belongs to the field of signal processing. The method firstly standardizes the extracted signal, and then uses the empirical mode decomposition method to calculate the amplitude modulation hologram of the standardized signal. Spectrum. The amplitude-modulated hologram is used as the feature input of the convolutional neural network classification model to train the classification model. Use the trained classification model to classify and identify ship noise. The method of the invention uses the amplitude modulation hologram as the characteristic of the ship noise, and the amplitude modulation hologram obtains the amplitude modulation information in the ship noise, and is more stable in the complex and changeable ocean environment.

Description

technical field [0001] The invention belongs to the field of signal processing, and relates to a ship noise recognition method based on holographic spectrum and deep learning. Background technique [0002] Accurate identification of ship targets at sea has important practical significance for maritime search and rescue, sea area and port monitoring, ship collision avoidance, military reconnaissance and marine resource development. At present, optical, electromagnetic and radiation noise are commonly used features in ship identification. [0003] The radiated noise generated during the ship's navigation is transmitted to the surroundings in the form of sound waves. The propagation of sound waves is affected by sea water, sea surface and seabed, and is a complex physical process. Its complexity is manifested in two aspects: one is the dispersion characteristics of the ocean acoustic channel, which will modulate the acoustic signal; the other is the uncertainty of acoustic pr...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G10L25/51G10L25/30G10L25/18
CPCG10L25/51G10L25/30G10L25/18
Inventor 刘宗伟段德鑫吕连港姜莹杨春梅
Owner THE FIRST INST OF OCEANOGRAPHY SOA
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