Digitalisation remains a critical new initiative of the wind industry. Through the use of new types of data on critical sub-components, life extension of complex machinery like wind assets now has a proven record of improving financial outcomes for operators and suppliers.

Wind turbine bearings, for instance, can cause up to 64% of drivetrain failures. Bearing failure is nearly impossible to detect until it’s too late, wreaking havoc on secondary components within the drive systems. The reason can be attributed to bearings’ long failure initiation and then short propagation to catastrophic failure, once a crack reaches a bearing surface. Gearbox bearings and main-bearing failure are high on most operators' watch lists.

Digitalisation of bearings using both materials science and physics-based modeling, however, can simulate bearings within drive systems computationally and under broad operational loads and conditions, to provide a more accurate understanding of when bearings fail and why.

Understanding why and how bearings fail becomes extremely important in the quest for drivetrain life extension, which is good for both OEMs and the operators. The performance of bearings, lubrication and how sub-components interact can vary from turbine to turbine, especially at different physical locations and wind regimes. These differences will affect the performance of bearings.

By upgrading bearings proactively, by understanding where bad bearings are, in what machine, from what subcontractor or batch, operators will have the chance to extend the life of their drivetrains well beyond the projected design life and proformas.

Jill Szpylman is director of IR, PR & communications at Sentient Science