Energy Harvesting IoT Systems for Predictive Maintenance in Marine Diesel Engines

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< Project Overview >

Rapid changes in the marine industry due to the introduction and advancements within telecommunications are predicted, and it has been suggested that the vast majority of commercial vessels will be broadband capable within the near future.

Increased data transfer rates at a decreased cost is expected to lead to a change in the industry’s approach to, and desired for, optimised Prognostics and Health Management (PHM) systems for fault detection, isolation and prediction of marine diesel engines. Currently IoT PHM systems are available for the larger commercial shipping vessels, however small to medium size vessels are yet to exploit this technology. An optimised stand-alone PHM solution for small to medium sized marine diesel engines could provide improved energy efficiency, which could result in cost and environmental benefits.

This project will look to enable the introduction of IoT predictive maintenance in diesel generators for medium-sized vessel used in the offshore, ferry and tug marine industries. IoT energy harvesting, vibration sensors positioned on a test engine could be used to monitor vibrational outputs and relay the data for analysis to a centralised hub. The results would be incorporated into a wireless, battery-less system connected to a cloud based management system in an IoT application.

This project will lead the design and development of a predictive maintenance system demonstrator product. Research will focus on exploring vibration energy harvesting to enable the development of a battery-less wireless predictive maintenance system. The proposed design will also require a dedicated energy management unit to optimise the usage of the harvested energy.

Project Lead:

Dr Domenico Balsamo – Newcastle University


Royston Power Generation Ltd