A. Dzipalski, J. A. Morton, N. Papachristou, R. R. Maier, W. MacPherson, A. Ristolainen, M. Kruusmaa, E. Reilent, B. Wolf, P. Pirih, S. van Netten, I. Shuhova, U. Lips, N. McFarlane, R. Macleod, M. Hendry, J. Sheehy, M. Almoghayer, N. Rojas, G. Davies, A. Hakim, A. Ng
In this paper a multiplexed multi-parameter marinized sensory array is described. This was deployed on the continental slope off the Keri Island marine observatory in the Gulf of Finland (Estonia). The sensor array is made up of 4 measurement stations which are connected in series. Across these measurement stations, a total of 16 temperature sensors, 4 attitude sensors (each consisting of 3 individual fiber sensors) and 16 flow sensors were successfully deployed. They were addressed over 1.1 km via 20 single-mode (SMF-28e) optical fibers contained in a single marine compliant ruggedized umbilical. The bio-inspired fiber optic flow sensors are designed to mimic the behavior of the superficial neuromasts naturally found as part of the lateral line sensory organ present in fish. The sensor is composed of optical fibers inscribed with Fiber Bragg Gratings glued together in a polymer matrix which are then encapsulated in a polyurethane shell. The sensors response has been tested in DC flows in a tow tank and have demonstrated the ability of measuring flow speed from 0.05 ms-1 to 2.5 ms-1. The main aim of the deployment was to demonstrate the capabilities of fiber sensor technology for long-term oceanographic applications. The measurement period described lasted over two months and the sensor system performed well in comparison with data was gathered from commercial instrumentation available.
An array of fluid flow sensors can be used to detect and track underwater objects via the fluid flow field these objects create. The sensed flows combine to a spatio-temporal velocity profile, which can be used to solve the inverse problem; determining the relative position and orientation of a moving source via a trained model. In this study, two training strategies are used: simulated data resulting from continuous motion in a path and from vibratory motion at discrete locations on a grid. Furthermore, we investigate two sensing modalities found in literature: 1D and 2D sensitive flow sensors; all while varying the sensor detection threshold via a noise level. Results show that arrays with 2D sensors outperform those with 1D sensors, especially near and next to the sensor array. On average, the path method outperforms the grid method with respect to estimating the location and orientation of a source.
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