An adhesive wear prediction method for double helical gears based on enhanced coordinate transformation and generalized sliding distance model

An adhesive wear prediction method for double helical gears is proposed according to enhanced coordinate transformation and generalized sliding distance model in conjunction with Archard's wear equation. To describe transient contact ellipse and identify the contact point pairs conveniently, a transform coordinate plane is set in coincidence with the plane of action and a coordinate axe parallels to the contact line. The contact pressure distribution is determined by contact line length, contact width and normal force, and a modified sliding distance model is proposed by generalized moving distance replacement of Hertz contact width. As the wear coefficient, contact pressure and sliding distance are given, the tooth wear depths are predicted by a developed numerical procedure. Effects of major geometrical and working parameters on the wear depth are investigated. The results show that the wear depth becomes smaller, which is mainly determined by the contact force per unit length, equivalent curvature radius and sliding distance as normal module, normal pressure angle, helix angle, tooth width or transmission ratio increases. However, the wear depth becomes larger when input torque is improved. It is indicated that rational parameters match in gear design and uniform wear distribution are beneficial for wear resistance. (C) 2018 Elsevier Ltd. All rights reserved.