Application of SN-EMD in Mode Feature Extraction of Ship Radiated Noise

Fang Niu, Juan Hui, Anbang Zhao, Yue Cheng and Yang Chen

Mathematical Problems in Engineering, 2018, vol. 2018, 1-16

Abstract:

Due to the randomness of added noise, noise-assisted versions based on EMD (empirical mode decomposition) usually cause new “mode mixing” problem. In addition, these algorithms also have problems such as high time-consuming and large recovering error. For the reasons, a new method SN-EMD (Selective Noise-assisted EMD) is put forward in this paper. It determines whether to add noise as assistance by judging whether there is high frequency intermittent component contained in the signal or not. The new method was proved to have the optimal performance by comparing the performance parameters for evaluating the decomposition. In this paper, SN-EMD was used to decompose ship radiated noise. On account of the differences in the original information contained in each mode of radiated noise signals from different ship, we selected the first three modes for processing. Average instantaneous frequency, center frequency, energy density, and energy distribution ratio were extracted as mode feature of ship targets for classification and recognition. Spatial distribution of the feature quantities in three-dimensional space verified similarity of the same target and separability of different targets.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:2184612

DOI: 10.1155/2018/2184612

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