Better Ultrasonic Bearing Health Measurement Posted on 14 Jan 16:15

Engineers from the University of Sheffield have developed a novel technique to predict when bearings inside wind turbines will fail in an effort to make wind energy cheaper. This updated technology can also be applied to critical industrial processes. 

The method, published in the journal Proceedings of the Royal Society A and developed by Mechanical Engineering research student Wenqu Chen, uses ultrasonic waves to measure the load transmitted through a ball bearing in a wind turbine. The stress on the wind turbine is recorded and then engineers can accurately forecast its remaining service life. 

When a bearing is subject to a load, its dimensional  thickness is reduced by a very small amount due to elastic deformation and the speed of sound is affected by the stress level in the material. Both of these effects change the time of flight of an ultrasound wave through a bearing.

 The new method measures the transmitted load through the rolling bearing components. It uses a custom built piezoelectric sensor mounted in the bearing to measure the time of flight and determine the load. This sensor is less expensive and significantly smaller than others that are currently available, making it suitable for smaller turbines. It can also provide a better prediction of the bearing maintenance required, saving time and money in maintenance. 

Professor Rob Dwyer-Joyce, co-author of the paper and Director of the Leonardo Centre for Tribology at the University of Sheffield says: "This technique can be used to prevent unexpected bearing failures, which are a common problem in wind turbines. By removing the risk of a loss of production and the need for unplanned maintenance, it can help to reduce the cost of wind energy and make it much more economically competitive." 

The new technology has been validated in the lab and is currently being tested at the Barnesmore farm in Donegal, Ireland by the Ricardo company. It is hoped it will be used in monitoring systems for other turbines.

Provided by the University of Sheffield