Optimizing electric adjustment mechanism using the combination of multi-body dynamics and control
- Authors: Congyanga, Yu , Dequana, Zhu , Chaoxiana, Wang , Lin, Zhu , Tingting, Chu , Tien-Chien, Jen , Liao Juana
- Date: 2019
- Subjects: Collaborative optimization , Multi-objective , Hybrid algorithm
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/406451 , uj:34173 , Citation: Chongyang, Z.D., et al. 2019 : Optimizing electric adjustment mechanism using the combination of multi-body dynamics and control.
- Description: Abstract : Optimization was carried out on the electric adjustment mechanism for transplanter by using the multidisciplinary design with weight, transmission efficiency, vibration frequency, and control error as the optimization goals. Then, a collaborative optimization model for the multidisciplinary design of a mechanism system was constructed. Based on ISIGHT software, the multidisciplinary design integration platform for the electric adjustment mechanism was built. A hybrid algorithm comprising the dual sequential quadratic programming method and the multi-island genetic algorithm was used to calculate the model. Optimization results show that the weight of the electric adjustment mechanism drops by 13.10%, its vibration frequency decreases by 27.71%, its transmission efficiency increases by 20.26%, and the control error decreases by 36.98%. Under the mutual coordination and balance of all discipline goals, the optimal values of the design variables of the electric adjustment mechanism indicate overall optimal performance.
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Optimizing transplanting mechanism with planetary elliptic gears based on multi-body dynamic analysis and approximate models
- Authors: Tingting, Chu , Dequana, Zhu , Wei, Xiong , Lin, Zhu , Shun, Zhang , Tien-Chien, Jen , Juana, Liao
- Date: 2019
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/406491 , uj:34178 , Citation: Tingting, C., et al. 2019 : Optimizing transplanting mechanism with planetary elliptic gears based on multi-body dynamic analysis and approximate models.
- Description: Abstract : The multidisciplinary design optimization (MDO) strategy of the transplanting mechanism was determined, which was decomposed into three disciplines of kinematics, dynamics, and structural mechanics. The multidisciplinary design collaborative optimization models of the transplanting mechanism were established. The Latin hypercube design method was used to generate the initial sample points and construct the kriging model between the system-level variables and the discipline-level optimization. The MDO platform on the planetary elliptic gears transplanting mechanism was established on the basis of ISIGHT software and calculated by using the hybrid algorithm of multi-island genetic algorithm and sequential quadratic programming method. Optimization results showed that the width of the trajectory dynamic hole of the seedling needle tip, the frame vibration peak force, and the overall quality of the transplanting mechanism decreased by 55.6%, 20.5%, and 9.33%, respectively. The optimum overall performance of the transplanting mechanism was obtained by using the MDO based on approximation technique to meet the agronomic requirements of rice transplanting under high-accuracy computation and low computation time.
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