A comparative study of four nonlinear dynamic methods and their applications in classification of ship-radiated noise

• 作者: Yu-xing Li Shang-bin Jiao Bo Geng Qing Zhang You-min Zhang
• 来源期刊: 防务技术
• 年，卷（期）: 2022,（2）
• 页码范围: 183-193
• 页数: 11页
• 语种: 英文
• DOI: 10.3969/j.issn.2214-9147.2022.02.003

摘要

Refined composite multi-scale dispersion entropy (RCMDE),as a new and effective nonlinear dynamic method,has been applied in the field of medical diagnosis and fault diagnosis.In this paper,we first introduce RCMDE into the field of underwater acoustic signal processing for complexity feature extraction of ship radiated noise,and then propose a novel classification method for ship-radiated noise based on RCMDE and k-nearest neighbor (KNN),termed RCMDE-KNN.The results of a comparative experiment show that the proposed RCMDE-KNN classification method can effectively extract the complexity features of ship-radiated noise,and has better classification performance under one and two scales than the other three classification methods based on multi-scale permutation entropy (MPE) and KNN,multi-scale weighted-permutation entropy (MW-PE) and KNN,and multi-scale dispersion entropy(MDE) and KNN,termed MPE-KNN,MW-PE-KNN,and MDE-KNN.It is proved that the RCMDE-KNN classification method for ship-radiated noise is feasible and effective,and can obtain a very high recognition rate.