Feature extraction method of ship radiated noise based on BOA-VMD and slope entropy
Although the technical requirements for the feature extraction of ship radiated noise (SRN) in the fields of national defense and economy increase with each passing day, the complexity of the marine environment makes the feature extraction of SRN difficult. The traditional feature extraction method...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Physics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2022.1043070/full |
| _version_ | 1811182456540233728 |
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| author | Yingmin Yi Yingmin Yi Ge Tian |
| author_facet | Yingmin Yi Yingmin Yi Ge Tian |
| author_sort | Yingmin Yi |
| collection | DOAJ |
| description | Although the technical requirements for the feature extraction of ship radiated noise (SRN) in the fields of national defense and economy increase with each passing day, the complexity of the marine environment makes the feature extraction of SRN difficult. The traditional feature extraction method based on variational mode decomposition (VMD) is widely used in the feature extraction of SRN. Nevertheless, the use of VMD is greatly affected by parameters. In this paper, the butterfly optimization algorithm (BOA) is introduced to optimize VMD, which is called BOA-VMD algorithm, and realizes the optimal selection of VMD parameters K and α. To further improve the efficiency of feature extraction method, combined with slope entropy (SE), a feature extraction method of SRN based on BOA-VMD and SE is proposed. The experimental results of the simulated signal show that the BOA-VMD algorithm has a smaller envelope entropy value and better decomposition effect than the genetic algorithm (GA) and particle swarm optimization (PSO). The experimental results of feature extraction of SRN show that the highest recognition rate of the four entropy values improve with the increase of the number of extracted features, compared with the three entropy values of dispersion entropy (DE), fluctuation dispersion entropy (FDE) and permutation entropy (PE), the SRN feature extraction method based on BOA-VMD and SE has the highest recognition rate under different quantity features, and the recognition rate has reached 100% under three features. |
| first_indexed | 2024-04-11T09:32:40Z |
| format | Article |
| id | doaj.art-c9111db826844330831f7ff982bbb8de |
| institution | Directory Open Access Journal |
| issn | 2296-424X |
| language | English |
| last_indexed | 2024-04-11T09:32:40Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physics |
| spelling | doaj.art-c9111db826844330831f7ff982bbb8de2022-12-22T04:31:51ZengFrontiers Media S.A.Frontiers in Physics2296-424X2022-10-011010.3389/fphy.2022.10430701043070Feature extraction method of ship radiated noise based on BOA-VMD and slope entropyYingmin Yi0Yingmin Yi1Ge Tian2School of Automation and Information Engineering, Xi’an University of Technology, Xi’an, ChinaShaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an University of Technology, Xi’an, ChinaSchool of Automation and Information Engineering, Xi’an University of Technology, Xi’an, ChinaAlthough the technical requirements for the feature extraction of ship radiated noise (SRN) in the fields of national defense and economy increase with each passing day, the complexity of the marine environment makes the feature extraction of SRN difficult. The traditional feature extraction method based on variational mode decomposition (VMD) is widely used in the feature extraction of SRN. Nevertheless, the use of VMD is greatly affected by parameters. In this paper, the butterfly optimization algorithm (BOA) is introduced to optimize VMD, which is called BOA-VMD algorithm, and realizes the optimal selection of VMD parameters K and α. To further improve the efficiency of feature extraction method, combined with slope entropy (SE), a feature extraction method of SRN based on BOA-VMD and SE is proposed. The experimental results of the simulated signal show that the BOA-VMD algorithm has a smaller envelope entropy value and better decomposition effect than the genetic algorithm (GA) and particle swarm optimization (PSO). The experimental results of feature extraction of SRN show that the highest recognition rate of the four entropy values improve with the increase of the number of extracted features, compared with the three entropy values of dispersion entropy (DE), fluctuation dispersion entropy (FDE) and permutation entropy (PE), the SRN feature extraction method based on BOA-VMD and SE has the highest recognition rate under different quantity features, and the recognition rate has reached 100% under three features.https://www.frontiersin.org/articles/10.3389/fphy.2022.1043070/fullship radiated noiseslope entropyfeature extractionvariational mode decompositionbutterfly optimization algorithm |
| spellingShingle | Yingmin Yi Yingmin Yi Ge Tian Feature extraction method of ship radiated noise based on BOA-VMD and slope entropy Frontiers in Physics ship radiated noise slope entropy feature extraction variational mode decomposition butterfly optimization algorithm |
| title | Feature extraction method of ship radiated noise based on BOA-VMD and slope entropy |
| title_full | Feature extraction method of ship radiated noise based on BOA-VMD and slope entropy |
| title_fullStr | Feature extraction method of ship radiated noise based on BOA-VMD and slope entropy |
| title_full_unstemmed | Feature extraction method of ship radiated noise based on BOA-VMD and slope entropy |
| title_short | Feature extraction method of ship radiated noise based on BOA-VMD and slope entropy |
| title_sort | feature extraction method of ship radiated noise based on boa vmd and slope entropy |
| topic | ship radiated noise slope entropy feature extraction variational mode decomposition butterfly optimization algorithm |
| url | https://www.frontiersin.org/articles/10.3389/fphy.2022.1043070/full |
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