Predictive maintenance in wind turbines with Bonfiglioli and Schaeffler

Posted 25 June 2020
manutenzione predittiva eolico Bonfiglioli Scaheffler

Italian Bonfiglioli and Schaeffler collaborated to develop a compact Industry 4.0 solution package for wind turbine azimuth drives, aimed to implement predictive maintenance for yaw drive gearboxes in wind turbines.

Schaeffler Torque Sense and SmartCheck sensors record torque, speed, vibration and temperature information. These data are transmitted through a gateway, combined and processed using algorithms developed by Bonfiglioli and based on company’s more than 60 years know-how in gearmotors and dedicated specifically for the application. Subsequently, the data will be made available for the users on the Bonfiglioli Cloud platform. The Bonfiglioli Dashboard provides a clear overview of the collected information for the operator. Maintenance measures can be carried out in a load-oriented manner and the unplanned downtimes of the system can be minimized, more than halving operating costs.

Concrete figures show that about 50% of the operating and maintenance costs of wind turbines are attributable to unplanned interventions. Specifically, this means that for a 2.3 megawatt wind generator in 20 years operating costs of approximately € 1.6 million are estimated, of which up to € 1.1 million are due to unscheduled repair and maintenance. With the help of the relatively small investment in the system from the cooperation between Bonfiglioli and Schaeffler, operating costs can be reduced by up to 60%.

On the Bonfiglioli dashboard, the operator can carry out a continuous control of the state of the geared motor based on the data situation, even an estimation of the remaining service life of the drive takes place. Abnormal behavior of the azimuth drive is reported as naturally as critical conditions. On this basis, the maintenance intervals can be optimized to the actual needs and necessary repairs can be made at favorable times. At the same time, the control of the drives can be optimized, whereby overloading can be avoided. Valuable result is the drastic reduction of unplanned downtime or vice versa, the significant increase in the profitability of a plant.

The available amount of data allows indeed many other important advantages, even if difficult to quantify. Further improvements result from the possibility of adapting the electronic drives to environmental and operating conditions (eg temperatures, wind hours / year, etc.), which has a direct and positive effect on the productivity of the wind generator.



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