Structural optimization of pitch bearings for offshore wind turbines

Pitch bearings are key components for the pitch system of wind turbines, and their reliability is closely associated with normal operation of wind turbines. In this paper, to solve the low efficiency problem of the GH Bladed and MATLAB software in design and analysis due to its operation in a single-user, stand-alone and single-key mode, GH bladed and MATLAB were combined based on Python for the integrated load spectrum calculation of pitch bearings through the full life cycle. Based on theories of contact strength analysis and fatigue life, finite element analysis and sub-modelling refinement techniques are established to investigate the relation between structural parameters and raceway stress of the bearings. Based on the Artificial Fish Swarm Algorithm (AFSA), the structural parameters are optimized to minimize the maximum contact stress on the bearing raceways and maximize the fatigue life of the bearings. The results show that the maximum contact load and the maximum contact stress on the pitch bearing raceways are significantly reduced and the bearing fatigue life is notably increased by 8.7%. The method proposed in the present study applies not only to pitch bearings, but also to other large four-point contact ball bearings.

Automated summary

In this study, GH Bladed and MATLAB software were combined on Python to solve the low efficiency problem in design and analysis. The relation between structural parameters and raceway stress of the bearings was investigated using finite element analysis and sub-modelling refinement techniques. The structural parameters were optimized using the Artificial Fish Swarm Algorithm (AFSA) to reduce maximum contact stress and increase fatigue life of the bearings.