Robotics & Autonomous Systems

Find out more about our robotics and autonomous systems testing and validation facilities.

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Electrical Infrastructure Research Hub

The Catapult has appointed the University of Strathclyde and the University of Manchester to form the Electrical Infrastructure Research Hub.

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Automation & Engineering Solutions

Find out more about our work in robotics, autonomous systems and artificial intelligence.

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Stay Current

Dig deeper into the biggest issues facing offshore wind, wave and tidal energy with our series of Analysis & Insight papers.

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Live Innovation Opportunities

There are a number of programmes identifying the key technology innovation challenges faced by the offshore renewables industry. Solving these challenges will help drive down the cost of offshore renewable energy, with positive effects for the industry and UK economy. Visit our Live Innovation Opportunities page to find out if your technology has the answer.

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Dr Ampea Boateng

Dr Ampea Boateng

Senior Research Engineer, Intelligence Condition Monitoring

Dr Ampea Boateng is responsible for R&D activities related to data analysis for wind turbine mechanical drivetrain components. Ampea began his research career with the Industrial Doctoral Centre for Offshore Renewable Energy (IDCORE) where he worked with ORE Catapult to develop new ways of testing main bearings in wind and tidal turbines in an accelerated manner. After joining ORE Catapult, Ampea has worked as a research engineer in the drivetrain knowledge area, focusing on advanced drivetrain sensing, measurements, signal processing and data analysis.

Ampea has utilised his skills to developed tools for automatic analysis of test data from a 7MW wind turbine nacelle test stand. As part of the same project, Ampea successfully evaluated the performance of a novel shaft monitoring device by comparing its performance with FEA analyses. Furthermore, Ampea has applied novel data processing techniques on vibration data in many applications, including on a 6MW pitch and main bearing test bench, as well as prototype testing of a novel 500 kW generator.

Ampea has also researched how data from turbine mounted lidars can be used to reduce loads on a 7MW wind turbine by studying how measured wind speeds ahead of a turbine can be used to reduce the impact turbine loads by making controller modifications. More recently, Ampea has focused on applying advanced Artificial Intelligence (AI) techniques on wind turbine measurements for detecting and diagnosing faults. He has successfully applied Machine Learning (ML) techniques to monitor the health condition of operational 6MW wind turbines based on their SCADA signals.

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