2016
DOI: 10.1051/meca/2016025
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Optimal design of tapered roller bearings for maximum rating life under combined loads

Abstract: Using the relationships of the ISO 281 standard, this paper optimizes the internal dimensions of tapered roller bearings for maximum rating life. The bearing system addressed contains two identical bearings subjected to an arbitrary combination of centred radial and axial forces. It is shown that the basic rating life increases more than quadratically with the roller infill and the aspect ratio of the rollers, increases with the sixth power of the pitch diameter of the roller set and decreases with the third p… Show more

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Cited by 8 publications
(3 citation statements)
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“…Dragoni (2016) developed an optimization procedure for tapered roller bearings by considering maximum rating life [15]. The rollers are supported by inner and outer rings as in the cylindrical rolling elements.…”
Section: Waghole Et Al (mentioning
confidence: 99%
“…Dragoni (2016) developed an optimization procedure for tapered roller bearings by considering maximum rating life [15]. The rollers are supported by inner and outer rings as in the cylindrical rolling elements.…”
Section: Waghole Et Al (mentioning
confidence: 99%
“…Zhang et al [2] established a multi-objective optimal design model for cross roller bearings, and obtained the optimal parameters to significantly improve the rated dynamic load of bearings by adopted genetic algorithm. Eugenio [3] proposed an optimization model of tapered roller bearing system with arbitrary combination of radial force and axial force, and obtained the optimal matching among internal structure sizes of bearings under the maximum dynamic load and static load bearing capacity. Rajiv and Jat [4] took spherical roller bearings as the research object, established a three-objective optimization model of maximum dynamic bearing capacity, minimum elastic fluid dynamic oil film thickness and minimum bearing temperature, and obtained the optimal structural parameter values significantly improved bearing life by solving the genetic algorithm.…”
Section: Introductionmentioning
confidence: 99%
“…Some investigations were therefore concerned with maximizing the load carrying capacity, fatigue, stiffness, load distribution and dynamics. In particular, analytical and numerical approaches for the design of geometrical bearing features have been applied [2][3][4][5]. Thereby, machine learning and data mining methods as well as optimization algorithms were also employed [6][7][8].…”
Section: Introductionmentioning
confidence: 99%