2009
DOI: 10.1115/1.4000645
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An Ease-Off Based Optimization of the Loaded Transmission Error of Hypoid Gears

Abstract: Loaded transmission error (LTE) is one of the primary sources of gear noise and vibration. While ease-off topography has been shown to be powerful in improving the contact properties of a gear drive, its optimization to minimize LTEs has been an open problem in the gear literature. Through the formulation of an appropriate nonlinear optimization problem, this study proposes a novel methodology to systematically define optimal ease-off topography to simultaneously minimize LTEs and contact pressures, while conc… Show more

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Cited by 102 publications
(48 citation statements)
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“…Because of the limited lebgth of this presentation, only small part of the corresponding publications can be referenced [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16].…”
Section: Simon Vilmos Budapest University Of Technology and Economicsmentioning
confidence: 99%
“…Because of the limited lebgth of this presentation, only small part of the corresponding publications can be referenced [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16].…”
Section: Simon Vilmos Budapest University Of Technology and Economicsmentioning
confidence: 99%
“…Artoni [15] then works on the minimization of the quasi-static transmission error. The maximum contact pressure is minimized simultaneously.…”
Section: Gear Topography Optimizationmentioning
confidence: 99%
“…2. Maximum contact pressure optimization [15]. pressure by setting himself the different designs to be evaluated is Fig.…”
Section: Mastering the Gearbox Deflectionmentioning
confidence: 99%
“…Some studies had been proved that through modifying addendum and dedendum, teeth meshing performance could be effectively improved, meshing impact being decreased, noise being reduced, and loading capacity being increased because of teeth surface load uniformly distributing. [16][17][18][19][20] Therefore, from a practical point of view, the minimum of flash temperature and vibration acceleration RMS is of great necessary when evaluating the optimization effects.…”
Section: Introductionmentioning
confidence: 99%