Machine Learning Model-Based Minimization of Roughness Variations after Profile Grinding of Wind Power Gears

KAPP NILES

This white paper explores how machine learning can enhance the surface quality of gears in wind turbine gearboxes. As nominal power of turbines significantly increases, higher torque densities of the gearbox are required. To produce highly precise gears with a high surface quality profile grinding is applied as one of the last manufacturing steps. However, the larger the teeth of the gear become, inconsistent grinding conditions cause roughness variations along the tooth flanks.

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