- Volume 24 Issue 8 Serial No. 179
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Design Optimization of Deep Groove Ball Bearing with Discrete Variables for High-Load Capacity
이산 설계변수를 포함하고 있는 깊은 홈 볼 베어링의 고부하용량 설계
- Published : 2000.08.01
A design method for maximizing fatigue life of the deep groove ball bearing without enlarging mounting space is proposed by using a genetic algorithm. The use of gradient-based optimization methods for the design of the bearing is restricted because this design problem is characterized by the presence of discrete design variables such as the number of balls and standard ball diameter. Therefore, the design problem of rolling element bearings is a constrained discrete optimization problem. A genetic algorithm using real coding is used to efficiently find the optimum discrete design values. To effectively deal with the design constraints, a ranking method is suggested for constructing a fitness function in the genetic algorithm. Constrains for manufacturing are applied in optimization scheme. Results obtained for several 63 series deep groove ball bearings demonstrated the effectiveness of the proposed design methodology by showing that the average basic dynamic capacities of optimally designed bearings increased about 9-34% compared with the standard ones.
Deep Groove Ball Bearing;High-Load Capacity;Fatigue life;Discrete Variable;Optimum Design;Genetic Algorithm
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