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Ship noise identification 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 problem of difficult to completely match the frequency band of cavitation noise, affecting the recognition effect, etc.

Active Publication Date: 2021-07-06
THE FIRST INST OF OCEANOGRAPHY SOA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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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  • Ship noise identification method based on holographic spectrum and deep learning
  • Ship noise identification method based on holographic spectrum and deep learning
  • Ship noise identification method based on holographic spectrum and deep learning

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Experimental program
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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, and belongs to the field of signal processing. The method comprises the steps of firstly, carrying out standardization on an extracted signal, and then carrying out calculation through employing an empirical mode decomposition method to obtain an amplitude modulation holographic spectrum of the standardized signal; taking the amplitude modulation holographic spectrogram as feature input of a convolutional neural network classification model, and training the classification model; and using the trained classification model to classify and identify the ship noise. According to the method, the amplitude modulation holographic spectrogram is used as the feature of the ship noise, and the amplitude modulation information in the ship noise is obtained through the amplitude modulation holographic spectrum. The method is more stable in the complex and changeable marine 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 Applications(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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