Measurement of the extremely low frequency (ELF) magnetic field emission from a ship

Birsan, Marius

doi:10.1088/0957-0233/22/8/085709

Cited by 15 publications

(10 citation statements)

References 8 publications

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“…24 Underwater moving vehicles generate an extremely low frequency (ELF) electric field due to galvanic currents flowing in the water around the hull. 25 The fundamental frequency of the ELF emissions is related to the speed of the vessel, which means that a frequency analysis can reveal information about the vessel movements. 26 However, as with the MADs, the signal diminishes quickly with distance from the object.…”

Section: Electromagnetic Signaturesmentioning

confidence: 99%

The non-acoustic signatures of underwater vehicles

Slimming,

Beniwal,

Devrelis

et al. 2023

Ocean Sensing and Monitoring XV

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Submersible vehicles, such as Uncrewed Underwater Vehicles (UUVs), can be lost underwater and it is desirable to locate them before they go missing or collide with other vehicles. These objects generate inherent signatures when they move in the ocean. With a better understanding of these signatures, more information regarding the motion of underwater vehicles can be inferred using LiDAR technology. In this paper, the authors review existing literature on various non-acoustic signatures of a submerged body, namely, the electromagnetic, biological and thermal signatures, turbulent wake patterns, internal waves and vortex structures. The authors discuss how these signatures evolve both spatially and temporally. Furthermore, the review investigates how environmental and operational parameters such as the stratification of the medium, vehicle speed, shape and depth affect the non-acoustic signatures. Underwater vehicles operating at low speeds and large depths have bioluminescent, Kelvin wake and Bernoulli hump signatures that are difficult to detect on the surface. Thermal signatures, vortex wakes and far wakes are only likely to be detected at the vehicle’s depth. This is primarily due to the ocean stratification which suppresses the vertical motion of underwater turbulent signatures. Thermal signatures appear to be most likely to be detected. The study concludes that relying on a single signature to detect submersibles is not advisable and future methods for underwater vehicle detection should use multiple sensors to detect complementary signatures.

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Section: Electromagnetic Signaturesmentioning

confidence: 99%

The non-acoustic signatures of underwater vehicles

Slimming,

Beniwal,

Devrelis

et al. 2023

Ocean Sensing and Monitoring XV

View full text Add to dashboard Cite

show abstract

“…Galvanic currents flowing in the water around the hull generate an underwater electric field. This field is responsible for the extremely low frequency emission [ 18 ]. The electric field emitted by the ships had advantages such as low frequency (1–7 Hz), long transmission distance and remarkable characteristics of the line spectrum [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

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

Liu

Sun

Jiang

et al. 2022

Sensors

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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.

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“…Wavelet transform becomes an effective tool for joint time-frequency analysis and has a broader application in the diagnosis of mechanical faults and the evaluation of non-destructive testing (NDT) signals [37,38,39]. Marius Birsan et al [40] presents an underwater detection of ELF electromagnetic field signals from ships using the cross wavelet transform and wavelet coherence method for high SNR situations. Qin et al [41] present transient weak fault feature extraction based on an optimized Morlet wavelet transform and kurtosis index.…”

Section: Introductionmentioning

confidence: 99%

High-Sensitivity Real-Time Tracking System for High-Speed Pipeline Inspection Gauge

Piao

Guo

et al. 2019

Sensors

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Real-time tracking of pipeline inspection gauges (PIGs) is an important aspect of ensuring the safety of oil and gas pipeline inline inspections (ILIs). Transmitting and receiving extremely low frequency (ELF) magnetic signals is one of the preferred methods of tracking. Due to the increase in physical parameters of the pipeline including transportation speed, wall thickness and burial depth, the ELF magnetic signals received are short transient (1-second duration) and very weak (10 pT), making the existing above-ground-marker (AGM) systems difficult to operate correctly. Based on the short transient very weak characteristics of ELF signals studied with a 2-D finite-element method (FEM) simulation, a data fusion model was derived to fuse the envelope decay rates of ELF signals by a least square (LS) criterion. Then, a fast-decision-tree (FDT) method is proposed to estimate the fused envelope decay rate to output the maximized orthogonal signal power for the signal detection through a determined topology and a fast calculation process, which was demonstrated to have excellent real-time detection performance. We show that simulation and experimental results validated the effectiveness of the proposed FDT method, and describe the high-sensitivity detection and real-time implementation of a high-speed PIG tracking system, including a transmitter, a receiver, and a pair of orthogonal search coil sensors.

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Measurement of the extremely low frequency (ELF) magnetic field emission from a ship

Cited by 15 publications

References 8 publications

The non-acoustic signatures of underwater vehicles

The non-acoustic signatures of underwater vehicles

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

High-Sensitivity Real-Time Tracking System for High-Speed Pipeline Inspection Gauge

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