Multi-Objective Optimization of Fine-Pitch Gear Based on Variable-Grain Strategy

2010 ◽  
Vol 44-47 ◽  
pp. 4191-4195
Author(s):  
Fu Qiang Zhao ◽  
Tie Wang
Keyword(s):  
Optimization Design ◽  
Optimal Solution ◽  
Complex Problem ◽  
Friction Torque ◽  
Coarse Grained ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Fine Grained ◽  
Fine Pitch ◽  
Tooth Flank

A variable-grain strategy is proposed to tackle the complex problem of optimization design of fine-pitch gear with multiple objectives and restrictions involved. Multi-objective optimization mathematical models of various grains are established, in order to ensure the tooth profile optimal and reduce the noise generated by the slide of tooth flank meshing and the mutation of friction torque as criteria to evaluate different schemes. The coarse-grained model is utilized in the early design to efficiently determine the direction to the globally optimal solution. Then more accurate model can be utilized and finally the optimal scheme can be acquired on the basis of the fine-grained model. Based on the theory of meshing noise and the superiority criteria, the algorithm is put forward for the fine-pitch gear design problem, and the Pareto optimal sets are obtained.

Variable-Grain Optimization Design of High-Speed Transmission Helical Gear

2011 ◽  
Vol 346 ◽  
pp. 179-183
Author(s):  
Fu Qiang Zhao ◽  
Tie Wang ◽  
Rui Liang Zhang ◽  
Yu Juan Li ◽  
Jun Shen
Keyword(s):  
High Speed ◽  
Optimization Design ◽  
Optimal Solution ◽  
Objective Evaluation ◽  
Friction Torque ◽  
Evaluation Index System ◽  
Coarse Grained ◽  
Contact Ratio ◽  
Helical Gears ◽  
Multi Objective

A variable-grain strategy is proposed to solve the complicated problem of optimization design on high-speed transmission helical gears with multiple objectives and restrictions. Based on the theory of gear meshing noise and the superiority criteria, a multi-objective evaluation index system is brought forward which gives consideration to the increase of the contact ratio and the decrease of the noise generated by the slide ratio of the tooth flank meshing and the mutation of friction torque, and then the variable-grain multi-objective optimization models of high-speed helical gears are established. The coarse-grained model is utilized in the early design to efficiently determine the direction to the optimal solution. Then the grain is refined and the fine-grained model can be utilized to acquire the optimal result.

Multi-Objective Optimization Design of Steel Frames Based on Multiple Attribute Decision-Making Method

2013 ◽  
Vol 368-370 ◽  
pp. 830-837
Author(s):  
Mao Qiao Cui ◽  
Hai Yan Huang ◽  
Fu Lai Wang ◽  
Yong Qiu
Keyword(s):  
Decision Making ◽  
Optimization Design ◽  
Intuitionistic Fuzzy Set ◽  
Optimal Solution ◽  
Multiple Attribute Decision Making ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Multiple Attribute ◽  
High Level

This paper describes in detail a multi-objective optimization strategy and decision-making method in the process of steel frame optimization design. A step-by-step analysis process integrating optimization algorithm and model analysis is proposed to solve the present problem. A multi-objective algorithm method using fast Non-dominated Sorting Genetic Algorithm is employed to obtain the Pareto-optimal solution set through an evolutionary optimization process. A high-level multiple attribute decision-making method based on intuitionistic fuzzy set theory is adopted to rank these solutions from the best to worst, and to determine the best solution. An example is used to demonstrate the proposed optimization model and decision-making method.

A Closeness Degree Method for Multi-Objective Optimization of Belt Transmission

1992 ◽  
Author(s):  
Lin Qun ◽  
Wu Meijuan
Keyword(s):  
Mathematical Model ◽  
Objective Function ◽  
Optimization Design ◽  
Optimal Solution ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Objective Function Values ◽  
Belt Transmission ◽  
Fuzzy Subsets ◽  
The Ideal

Abstract A mathematical model for multi objective optimization design of belt transmission is proposed in this paper. The normal fuzzy distribution is used to convert the ideal and non-inferior solutions into fuzzy subsets over the space of objective function values. The optimal solution which is closest to the ideal one could then be found on the basis of closeness degree method.

Study on Multi-Objective Optimization Design of Planetary Gear Reducer

2011 ◽  
Vol 199-200 ◽  
pp. 1180-1184
Author(s):  
Han Zhang ◽  
Xiao Qin Shen ◽  
Fu Sheng Yu ◽  
Jian Hua Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Optimal Solution ◽  
Planetary Gear ◽  
Minimum Volume ◽  
Discrete Variables ◽  
Multi Objective Optimization ◽  
Contact Ratio ◽  
Multi Objective ◽  
Maximum Contact

Various elements in planetary gear reducer design are discussed. A multi-objective optimization model is created. The model requires the minimum volume and the maximum contact ratio. The method of multiplication and division is used to solve the multi-objective problem, and the method of feasibility enumeration is used to handle the discrete variables. The results show that the optimal solution meets the actual requirements.

The Multi-Objective Optimization Design of Leaf Spring of few Piece Variable Cross-Section

2011 ◽  
Vol 213 ◽  
pp. 231-235
Author(s):  
Qin Man Fan ◽  
Qin Man Fan
Keyword(s):  
Cross Section ◽  
Optimization Design ◽  
Optimal Solution ◽  
Variable Cross Section ◽  
Leaf Spring ◽  
Variable Cross ◽  
Multi Objective Optimization ◽  
Solution Quality ◽  
Front Suspension ◽  
Multi Objective

Being the ability of global optimization, MOPSO algorithm have some virtue such as high calculate velocity, good solution quality, great robustness, and so on. In allusion to a leaf spring of few piece variable cross-section, its multi-objective optimization mathematical model was built regarding minimum mass and minimum stiffness deviation as sub-objective functions. Taking the leaf spring of front suspension of a light truck as an example, the Pareto optimal solution set of optimization problem was obtained by using MOPSO algorithm. The optimization results show that the mass of the leaf spring reduced by 24.2% and the stiffness deviation is only 0.32% after optimization by using MOPSO algorithm.

scholarly journals Multi-objective optimization design of spur gear based on NSGA-II and decision making

2019 ◽  
Vol 11 (3) ◽  
pp. 168781401882493 ◽  
Author(s):  
Qizhi Yao
Keyword(s):  
Decision Maker ◽  
Optimization Design ◽  
Optimal Solution ◽  
Spur Gear ◽  
Optimal Solutions ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Deviation Index ◽  
Decision Variables

Optimization design of spur gear is a complicated work because the performance characteristics depend on different types of decision variables and objectives. Traditional single-objective optimization design of the spur gear always results in poor outcomes relative to other objectives due to objectives’ competition with each other. Therefore, this study works on the spur gear design based on the multi-objective optimization model of elitist non-dominated sorting genetic algorithm (NSGA-II). In the model, gear module, teeth number, and transmission ratio are decision variables, while center distance, bearing capacity coefficient, and meshing efficiency are objectives. Final optimal solutions are picked out from Pareto frontier calculated from NSGA-II using the decision makers of Shannon Entropy, linear programming technique for multidimensional analysis of preference (LINMAP), and technique of order preference by similarity to an ideal solution (TOPSIS). Meanwhile, a deviation index is used to evaluate the reasonable status of the optimal solutions. From triple-objective and dual-objective optimization results, it is found that the optimal solution selected from LINMAP decision maker shows a relatively small deviation index. It indicates that LINMAP decision maker may yield better optimal solution. This study could provide some beneficial information for spur design.

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

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