Fault Detection and Isolation Methods in Subsea Observation Networks

Abstract

Subsea observation networks have gradually become the main means of deep-sea exploration. The reliability of the observation network is greatly affected by the severe undersea conditions. This study mainly focuses on theoretical research and the experimental platform verification of high-impedance and open-circuit fault detection for an underwater observation network. With the aid of deep learning, we perform the fault detection and prediction of the network operation. For the high-impedance and open-circuit fault detection of submarine cables, the entire system is modeled and simulated, and the voltage and current values of the operating nodes under different fault types are collected. Numerous calibrated data samples are supervised by a deep learning algorithm, and a fault location system model is built in the laboratory to verify the feasibility and superiority of the scheme. This paper also studies the fault isolation of the observation network, focusing on the communication protocol and the design of the fault isolation system. Experimental results verify the effectiveness of the proposed algorithm for the location and prediction of high-impedance and open-circuit faults, and the feasibility of the fault isolation system has also been verified. Moreover, the proposed methods greatly improve the reliability of undersea observation network systems.

Technology Review of Cabled Ocean Observatories

“…With the rapid development of related technologies, especially circuit fault isolation and protection, remote intelligent monitoring, and operation health management [24][25][26][27][28][29][30][31], it has become increasingly feasible to design and construct grid networks. However, the growing network scale potential increases the possibility of system failure.…”

Attitude-Independent Route Tracking for Subsea Power Cables Using a Scalar Magnetometer under High Sea Conditions

“…Time-frequency domain reflectometry is a traditional method [20]. To solve the difficulty of high-impedance fault location, a deep learning algorithm [21] and a novel method by analyzing the variation difference in the equivalent current in the Laplace transform domain [22] have been proposed. When using electrical methods to locate the fault points of the subsea cables, precise cable route information is essential.…”

Design and Implementation for the High Voltage DC-DC Converter of the Subsea Observation Network

“…The subsea observation network has received increasing attention worldwide as a new and revolutionary means of ocean observation. The cabled submarine observation network has become a research hotspot in the past decade because of its powerful power supply capacity and ultra-high data transmission rate [1][2][3][4]. The basic idea is to connect the observation instruments and seabed or ocean equipment with the power grid and information network on the land through the submarine cable to extend the land observation to the depth of the ocean.…”