Electric Field Detection System Based on Denoising Algorithm and High-Speed Motion Platform.

ICEEMDAN denoising high-speed boat low frequency electric field noise

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
07 Jul 2022
Historique:
received: 13 05 2022
revised: 27 06 2022
accepted: 28 06 2022
entrez: 27 7 2022
pubmed: 28 7 2022
medline: 29 7 2022
Statut: epublish

Résumé

Effective denoising can ensure fast and accurate target detection. This paper presents an electric field measurement system based on a high-speed motion platform, which was built to analyze the characteristics of low frequency electric field noise. An offshore test has shown that it is possible to detect a low-frequency electric field using a high-speed motion platform. Low frequency electric field noise was then collected to analyze its characteristics in terms of time and frequency domains. Based on the noise characteristics, complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) was improved and combined with an adaptive threshold algorithm for denoising and reconstructing target containing noise signals. As revealed in the results, the proposed algorithm achieved highly effective denoising to overcome the line spectrum detection failure resulting from a high-speed motion platform. The detection range had also been improved from the original 853 m to 1306 m, a 53.1% increase.

Identifiants

pubmed: 35890798
pii: s22145118
doi: 10.3390/s22145118
pmc: PMC9318447
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Science Foundation for Outstanding Young Scholars
ID : 42122025
Organisme : Natural Science Foundation for Distinguished Young Scholars of Hubei Province of China
ID : 2019CFA086

Références

Sensors (Basel). 2017 Feb 24;17(3):
pubmed: 28245587
Sensors (Basel). 2017 Jul 28;17(8):
pubmed: 28788097
Sensors (Basel). 2018 Jan 02;18(1):
pubmed: 29301318
Entropy (Basel). 2020 Nov 28;22(12):
pubmed: 33266531

Auteurs

Qi Liu (Q)

College of Electrical Engineering, Naval University of Engineering, Wuhan 430033, China.

Zhaolong Sun (Z)

College of Electrical Engineering, Naval University of Engineering, Wuhan 430033, China.

Runxiang Jiang (R)

College of Electrical Engineering, Naval University of Engineering, Wuhan 430033, China.

Jiawei Zhang (J)

College of Weaponry Engineering, Naval University of Engineering, Wuhan 430033, China.

Kui Zhu (K)

College of Electrical Engineering, Naval University of Engineering, Wuhan 430033, China.

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Classifications MeSH