Multi-objective design optimisation of deep groove ball bearing for wind turbine generator Online publication date: Thu, 20-Apr-2023
by Prasun Bhattacharjee; Rabin K. Jana; Somenath Bhattacharya
International Journal of Design Engineering (IJDE), Vol. 11, No. 2, 2022
Abstract: Although installed wind power capacity has expanded globally at an unprecedented rate over the past few decades, a substantial portion of wind turbine operational time is wasted each year due to the unplanned breakdown of mechanical components like generator bearings. This paper employs artificial intelligence techniques like the multi-objective genetic algorithm (MOGA) and multi-objective whale optimisation algorithm (MOWOA) simultaneously for design optimisation of deep groove ball bearing engaged in wind turbine generator for improved performance. The maximisation of static capacity, dynamic capacity, elastohydrodynamic minimum film thickness, and minimisation of frictional power loss of the generator bearings have been considered as the optimisation objectives. The proposed MOGA is found to be more efficient in offering better design solutions compared with MOWOA and industrial quiet running wind turbine generator bearing standards.
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