PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
August 16, 2024Measurement Science and Technology0 citations

Ship Radiated Noise Signal Denoising Method With SVMD-AAPE-RPE-CC-AWTD

View Full Paper
BLBinjie LuXZXiaobing ZhangZDZhonghua DAI

Key Points

Key points are not available for this paper at this time.

Abstract

Abstract To solve the denoising problem of ship radiated noise signal (SRNSs), a method based on successive variational mode decomposition (SVMD), amplitude-aware permutation entropy (AAPE), reverse permutation entropy (RPE), correlation coefficient (CC) and adaptive wavelet thresholding denoising (AWTD) algorithm, named SVMD-AAPE-RPE-CC-AWTD, is proposed. The algorithm integrates intrinsic mode functions (IMFs) decomposition, IMFs classification, IMFs denoising and reconstruction, and is designed in an integrated manner. In IMFs decomposition, SVMD is introduced to decompose the signal into several IMFs, which select the number of adaptive decomposition levels without the need for manual parameter presetting. In IMFs classification, AAPE and RPE are introduced to adaptively adjust the entropy threshold to discriminate between signal IMFs and non-signal IMFs. By calculating the CC between the non-signal IMFs and the original signal, the noisy IMFs and noise IMFs are further distinguished. In terms of IMFs denoising and reconstruction, an ATWD algorithm is designed based on the optimal wavelet selection method to adaptively select appropriate wavelet basis and decomposition levels, and the improved threshold selection and threshold function are introduced. Finally, comparison tests of denoising simulated signals and the measured SRNS are designed to verify the effectiveness and superiority of the proposed method.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Lu et al. (2024) studied this question.

synapsesocial.com/papers/68e5bfacb6db6435875578d4https://doi.org/10.1088/1361-6501/ad704e
Ask AI
Helpful
Bookmark
Share
View Full Paper