Complex Virtual Instrument Model for Ocean Sensor Networks

Hu, Keyong; Ma, Guobing; Zhou, Wei; Sun, Zhongwei

doi:10.1109/access.2018.2828322

Cited by 5 publications

(3 citation statements)

References 20 publications

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“…We define T as the localization period in which each node needs to estimate its location. Note that, the localization period can be tuned according to practical requirements (e.g., in a UASN that observing ocean phenomena, it can be set to be equal to an hour [1]). For simplicity, the superscript for the n-th localization period is suppressed in what follows.…”

Section: Network Model and Problem Definitionmentioning

confidence: 99%

“…Underwater Acoustic Sensor Networks (UASNs) have been widely applied in many fields such as underwater surveillance, pollution detection and disaster prevention [1,2]. Generally, an UASN is comprised of different types of nodes, which can be floating sensor nodes, surface buoys, Autonomous Underwater Vehicles (AUVs) and other application specific devices [3,4].…”

Section: Introductionmentioning

confidence: 99%

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Localization Based on MAP and PSO for Drifting-Restricted Underwater Acoustic Sensor Networks

Song

Sun

et al. 2018

Sensors

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Localization is a critical issue for Underwater Acoustic Sensor Networks (UASNs). Existing localization algorithms mainly focus on localizing unknown nodes (location-unaware) by measuring their distances to beacon nodes (location-aware), whereas ignoring additional challenges posed by harsh underwater environments. Especially, underwater nodes move constantly with ocean currents and measurement noises vary with distances. In this paper, we consider a special drifting-restricted UASN and propose a novel beacon-free algorithm, called MAP-PSO. It consists of two steps: MAP estimation and PSO localization. In MAP estimation, we analyze nodes’ mobility patterns, which provide the priori knowledge for localization, and characterize distance measurements under the assumption of additive and multiplicative noises, which serve as the likelihood information for localization. Then the priori and likelihood information are fused to derive the localization objective function. In PSO localization, a swarm of particles are used to search the best location solution from local and global views simultaneously. Moreover, we eliminate the localization ambiguity using a novel reference selection mechanism and improve the convergence speed using a bound constraint mechanism. In the simulations, we evaluate the performance of the proposed algorithm under different settings and determine the optimal values for tunable parameters. The results show that our algorithm outperforms the benchmark method with high localization accuracy and low energy consumption.

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Section: Network Model and Problem Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Localization Based on MAP and PSO for Drifting-Restricted Underwater Acoustic Sensor Networks

Song

Sun

et al. 2018

Sensors

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“…These approaches have limited perspectives and concepts connected to oceanic observation, understanding and development. To explore and understand the ocean and promote the development of marine science [9], [10], the marine science community has proposed a third platform for observing the ocean [11], that is, cabled underwater information networks (CUINs).…”

Section: Introductionmentioning

confidence: 99%

A Novel Diagnosis and Location Method of Short-Circuit Grounding High-Impedance Fault for a Mesh Topology Constant Current Remote Power Supply System in Cabled Underwater Information Networks

et al. 2019

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Cabled underwater information networks (CUINs) have evolved over the last decade to provide abundant power and broad bandwidth communication to enable marine science. To ensure reliable operation of CUINs, it is essential to have the technology for high-impedance fault diagnosis and isolation with high reliability and accuracy. The short-circuit grounding high-impedance fault status of mesh topology constant current remote supply system was diagnosed by analyzing the variation difference of equivalent current in the Laplace transform domain. Shore power feeding equipment (SPFE) supplied the power for underwater system individually from both terminals, and the fault location was located by calculating the shunt loss of the current in the trunk before and after the fault. Thus, the fault was isolated to maintain normal operation of the rest of the system and improve the reliability of CUINs. According to the established typical mesh topology constant current remote supply system circuit model, the fault location scheme was designed to simulate the faults of the cable sections in the different links in the constant current remote supply system, and the changes of current located at the primary nodes (PNs) in the Laplace transform domain before and after the fault were analyzed. The results show that the equivalent current of each PN changes when a fault occurs in the system, and the location of the fault point can be analyzed by comparing the shunt loss of the current in the trunk before and after the fault. The designed method of short-circuit grounding high-impedance fault diagnosis and location for a constant current remote supply system is suitable for the fault monitoring and judgment of CUINs with high feasibility and practicality. Furthermore, it provides technical support for the resulting effective determination of faults, isolation of faults, protection of equipment, and improvement of the system reliability.INDEX TERMS Cabled underwater information networks (CUINs), constant current, short-circuit grounding high-impedance fault, fault diagnosis, point location, reliability.

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