Research project


The domain of Industrial Internet of Things (IIoT) provides a great promise to revolutionize all aspects of human professional engagement. The wind energy industry can particularly benefit from IIoT solutions, especially for wind farms located at sea or other remote locations that require effective monitoring systems to reduce the Levelized Cost of Electricity (LCOE). The key aspect of IIoT is the integration between the physical and digital worlds, which is generally difficult and expensive. Within a typical IIoT project, 80% of the total project cost is spent on integration and only 20% is spent on the true value-added functionality. The obvious solution is to make the integration simpler. Instead of deploying multiple sensors, which require power, communication infrastructure and maintenance, Netico’s technologies offer a pre-integrated system, with few sensors that emulate as many other sensors as possible, through the use of smart software.

The aim of this project is to develop an innovative, non-intrusive, sensor box and cloud-connected diagnostic system that will help asset owners/operators improve their workflow and maximise their revenues. The system will be based on Netico’s existing technology that uses acoustic sensors and will be enhanced with novel machine learning approaches. The focus will be on wind turbines, but the solution will not be specific to this technology, and it will be applicable to other industrial machines such as compressors. The project consists of (a) designing and testing a diagnostic system in the laboratory, (b) developing novel machine learning approaches for increasing the efficiency and effectiveness of the measurements, (c) combing these results into a prototype system and carrying out a proof of concept on a running wind turbine, and (d) developing recommendations for applying the solution to industrial machines in general.

Funded by Innosuisse.

Duration: 04.10.2021 - 04.10.2023