The Data-Driven Optimization Method and Its Application in Feature Extraction of Ship-Radiated Noise with Sample Entropy

Yuxing Li, Xiao Chen, Jing Yu, Xiaohui Yang and Huijun Yang
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Yuxing Li: Faculty of Information Technology and Equipment Engineering, Xi’an University of Technology, Xi’an 710048, Shaanxi, China
Xiao Chen: College of Electrical & Information Engineering, ShaanXi University of Science & Technology, Xi’an 710021, Shaanxi, China
Jing Yu: School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, China
Xiaohui Yang: School of Art and Design, Inner Mongolia University of Science & Technology, Baotou 014010, Inner Mongolia, China
Huijun Yang: College of Information Engineering, Northwest A&F University, Yang’ling 712100, Shaanxi, China

Energies, 2019, vol. 12, issue 3, 1-18

Abstract: The data-driven method is an important tool in the field of underwater acoustic signal processing. In order to realize the feature extraction of ship-radiated noise (S-RN), we proposed a data-driven optimization method called improved variational mode decomposition (IVMD). IVMD, as an improved method of variational mode decomposition (VMD), solved the problem of choosing decomposition layers for VMD by using a frequency-aided method. Furthermore, a novel method of feature extraction for S-RN, which combines IVMD and sample entropy (SE), is put forward in this paper. In this study, four types of S-RN signals are decomposed into a group of intrinsic mode functions (IMFs) by IVMD. Then, SEs of all IMFs are calculated. SEs are different in the maximum energy IMFs (EIMFs), thus, SE of the EIMF is seen as a novel feature for S-RN. To verify the effectiveness of the proposed method, a comparison has been conducted by comparing features of center frequency and SE of the EIMF by IVMD, empirical mode decomposition (EMD) and ensemble EMD (EEMD). The analysis results show that the feature of S-RN can be obtain efficiently and accurately by using the proposed method.

Keywords: data-driven; variational mode decomposition (VMD); improved variational mode decomposition (IVMD); empirical mode decomposition (EMD); feature extraction; sample entropy (SE); ship-radiated noise (S-RN) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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