SCOTTISH scientists have imitated sensor technology used by bottlenose dolphins to develop new signal processing techniques that could improve subsea detection in a range of applications.
The initiative involves Heriot-Watt University’s Ocean Systems Laboratory, in collaboration with Hydrason Solutions, a sonar and underwater systems company and the Scottish Innovation Centre for Sensor and Imaging Systems (Censis).
Using signal processing techniques from previous research on the mammals, the project enables users to accurately locate underwater objects, as well as identifying their structure and composition, without making direct contact. Existing sensor devices only provide the image of an outline and cannot penetrate objects.
The technology could have a variety of applications, from helping surveyors to find blockages in pipelines, to determining whether oil rig supports are still structurally sound.
Dr Keith Brown, associate professor at the university’s School of Engineering & Physical Sciences, said: “Bottlenose dolphins are extremely good at detecting objects in the water – using sonar they can detect fish in the sand which can’t be seen by the eye. Earlier research also showed that dolphins can differentiate between the contents of a variety of filled aluminium bottles using signal processing.
“We analysed the characteristics of these signals and, using transducers, have reproduced frequencies within the same parameters, as close as possible to those created by dolphins.”
The new system can also be used on range of nautical vehicles, including autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). Multiple surveys can be conducted from one ship, making the device an economic way of collecting marine data.
Hydrason already has a strong presence in the military and energy sectors, while the new system could also be used for applications in fisheries and surveying across the globe.
Chris Capus, chief executive of Hydrason Solutions, said: “This system will set a new standard in acoustic object detection and identification in complex subsea environments.”
The 10-month project is being backed with a £40,000 grant from Censis.
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