Holistic evaluation of involute gear surfaces using 3D point cloud inversion

Abstract

Abstract Gear users desire increased performance from their products and are interested in predicting the behavior (vibration, loss, service life, etc), and gear manufacturers are interested in adjusting machining parameters to manufacture even better gears. Both require proficient metrology. The evaluation standards were originally written to classify the manufacturing capability of machine tools and as tolerances tighten they may not provide enough insight into the functional performance of the manufactured parts. Furthermore, the advantage of modern coordinate and gear measuring machines is not fully taken into account when applying standardized measurement and evaluation strategies. Improved analysis tools can increase the relevant information gained from current measurement capabilities and enable more useful functional characteristics to be specified by designers and manufacturers. A key improvement is to move from profile and helix line traces to flank surfaces and corresponding fitted form elements. This is achieved by the introduced method. We present an inversion algorithm that fits dimension, form, and pose, and is applicable with current methods through freezing of specific fitting parameters. The method fits a synthetic point cloud with output results that are accurate to the 7th digit, or in practical terms are numerically equal. The inversion method can increase the understanding of error contributions and the functional performance of gears.