Abstract
In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship-radiated noise is presented based on empirical mode decomposition theory and permutation entropy. It analyzes the separability for permutation entropies of the intrinsic mode functions of three types of ship-radiated noise signals, and discusses the permutation entropy of the intrinsic mode function with the highest energy. In this study, ship-radiated noise signals measured from three types of ships are decomposed into a set of intrinsic mode functions with empirical mode decomposition method. Then, the permutation entropies of all intrinsic mode functions are calculated with appropriate parameters. The permutation entropies are obviously different in the intrinsic mode functions with the highest energy, thus, the permutation entropy of the intrinsic mode function with the highest energy is regarded as a new characteristic parameter to extract the feature of ship-radiated noise. After that, the characteristic parameters—namely, the energy difference between high and low frequency, permutation entropy, and multi-scale permutation entropy—are compared with the permutation entropy of the intrinsic mode function with the highest energy. It is discovered that the four characteristic parameters are at the same level for similar ships, however, there are differences in the parameters for different types of ships. The results demonstrate that the permutation entropy of the intrinsic mode function with the highest energy is better in separability as the characteristic parameter than the other three parameters by comparing their fluctuation ranges and the average values of the four characteristic parameters. Hence, the feature of ship-radiated noise can be extracted efficiently with the method.
Highlights
The complex ocean environment has made it difficult to extract the ship feature that can reflect the ship property from the ship-radiated noise (SRN) [1,2]
The first step is to choose the appropriate parameters of permutation entropy (PE) based on PE theory, the Empirical mode decomposition (EMD) is used as the pretreatment to decompose SRN signals into a set of intrinsic mode function (IMF), and the PEs of the IMFs at all levels are calculated
In order to distinguish the three types of SRN signals, the IMFs are rearranged according to energy descending order, and simulation results show the first PEs of the IMFs with greater energy are significant different from that of the other IMFs
Summary
The complex ocean environment has made it difficult to extract the ship feature that can reflect the ship property from the ship-radiated noise (SRN) [1,2]. Yang Hong et al have studied the feature extraction of SRN signals with the EMD and its extended methods in the field of underwater acoustic signal processing, an energy or frequency parameter without combining the complexity analysis is adopted, such as in the research [14,15]. In the fields of fault diagnosis and medicine, the combination of EMD or its extended methods and sample entropy or other entropies have been proven effective and feasible, such as in the research [9,22] In these studies, more characteristic parameters or vectors are selected, which have a high computational cost, and sample entropy or other entropies are more complex than the PE in calculation.
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