Fuzzy Optimization Design on Stranded Wire Helical Spring of High-Frequency Vibration Sieve

2010 ◽  
Vol 97-101 ◽  
pp. 4066-4070 ◽  
Author(s):  
Xiao Xin Gong ◽  
Yan Nian Rui ◽  
Ying Ping He
Keyword(s):  
High Frequency ◽  
Optimization Design ◽  
Fuzzy Theory ◽  
Fuzzy Optimization ◽  
Helical Spring ◽  
High Frequency Vibration ◽  
Vibration Resistance ◽  
Design Variables ◽  
The Common ◽  
Optimum Solution

When the common cylindrical helical spring is used in high-frequency vibration sieve for slime dewatering, there are many problems such as poor vibration resistance, easy happening fatigue fracture, etc. In order to solve these problems, this paper uses the stranded wire helical spring as a support instead, and applies fuzzy theory method to get the optimization design. By selecting the design variables correlated with spring and determining the objective function together with the constraint conditions, the fuzzy optimization mathematical model is built and the optimum solution is obtained so as to achieve the perfect results of optimization.

The Finite Element Analysis and the Multi-Objective Optimization Design of Spindle Systems of CNC Gantry Machine Tools

2016 ◽  
Vol 693 ◽  
pp. 243-250
Author(s):  
Zhi Zhong Guo ◽  
Yun Shun Zhang ◽  
Shi Hao Liu
Keyword(s):  
Machine Tools ◽  
Optimization Design ◽  
Multi Objective Optimization ◽  
Element Analysis ◽  
Multi Objective ◽  
Vibration Resistance ◽  
Design Variables ◽  
Force Coupling ◽  
The Finite Element Analysis ◽  
Spindle Structure

It is discovered that the vibration resistance of spindle systems needs to be improved based on the statics analysis, modal analysis and heating-force coupling analysis of spindle systems of CNC gantry machine tools. The design variables of optimization are set according to sensitivity analysis, multi-objective and dynamic optimization design is realized and its designing scheme is gained for spindle structure. The research results show that vibration resistance can be improved without change of the quality and static property of spindle systems of CNC gantry machine tools.

Fuzzy optimization design-based multi-level response surface of bogie frame

2019 ◽  
Vol 10 (2) ◽  
pp. 134-148 ◽  
Author(s):  
Pengpeng Zhi ◽  
Yonghua Li ◽  
Bingzhi Chen ◽  
Meng Li ◽  
Guannan Liu
Keyword(s):  
Boundary Conditions ◽  
Response Surface ◽  
Optimization Algorithm ◽  
Optimization Design ◽  
Fuzzy Optimization ◽  
Optimal Solution ◽  
Content Type ◽  
Design Variables ◽  
Multi Level ◽  
Response Surface Function

Purpose In a structural optimization design-based single-level response surface, the number of optimal variables is too much, which not only increases the number of experiment times, but also reduces the fitting accuracy of the response surface. In addition, the uncertainty of the optimal variables and their boundary conditions makes the optimal solution difficult to obtain. The purpose of this paper is to propose a method of fuzzy optimization design-based multi-level response surface to deal with the problem. Design/methodology/approach The main optimal variables are determined by Monte Carlo simulation, and are classified into four levels according to their sensitivity. The linear membership function and the optimal level cut set method are applied to deal with the uncertainties of optimal variables and their boundary conditions, as well as the non-fuzzy processing is carried out. Based on this, the response surface function of the first-level design variables is established based on the design of experiments. A combinatorial optimization algorithm is developed to compute the optimal solution of the response surface function and bring the optimal solution into the calculation of the next level response surface, and so on. The objective value of the fourth-level response surface is an optimal solution under the optimal design variables combination. Findings The results show that the proposed method is superior to the traditional method in computational efficiency and accuracy, and improves 50.7 and 5.3 percent, respectively. Originality/value Most of the previous work on optimization was based on single-level response surface and single optimization algorithm, without considering the uncertainty of design variables. There are very few studies which discuss the optimization efficiency and accuracy of multiple design variables. This research illustrates the importance of uncertainty factors and hierarchical surrogate models for multi-variable optimization design.

Optimization Design of Cantilever Supporting Structure

2013 ◽  
Vol 357-360 ◽  
pp. 2410-2413
Author(s):  
Wei Xu ◽  
Jian Sheng Feng ◽  
Fei Fei Feng
Keyword(s):  
Genetic Algorithm ◽  
Optimization Design ◽  
Design Method ◽  
Optimal Solution ◽  
Optimization Method ◽  
Original Design ◽  
Supporting Structure ◽  
Primary Object ◽  
Design Variables ◽  
Optimum Solution

The primary object of this fundamental research is to reveal the application of genetic algorithm improved on the optimization design of cantilever supporting structure. In order to meet the strength of pile body and pile top displacement as well as design variables subjected to constraint, an algorithm is carried on to seek the optimum solution and relevant examples by means of comprehensively considering the effects on center-to-center spacing between piles,pile diameter and quantity of distributed steel, which is taken the lowest engineering cost as objective function. Through the comparison of the optimized scheme and original design, this fruitful work provides explanation to the effectiveness of genetic algorithm in optimization design. These findings of the research lead to the conclusion that the shortcomings of traditional design method is easy to fall into local optimal solution. The new optimization method can overcome this drawback.

Multi-Objective Fuzzy Optimization Design of Gear Drive

2014 ◽  
Vol 533 ◽  
pp. 68-73
Author(s):  
Xiao Xing Liu ◽  
Qi Ying Pan
Keyword(s):  
Fuzzy Sets ◽  
Optimization Design ◽  
Comprehensive Evaluation ◽  
Fuzzy Theory ◽  
Fuzzy Optimization ◽  
Optimal Level ◽  
Optimal Solutions ◽  
Membership Functions ◽  
Design Data ◽  
Multi Objective

fuzzy factors in the gear reducer design are analyzed, and a multi-objective optimization model with minimum volume and maximum bearing capacity is established in this paper. Optimal level cut-set method is introduced to conduct comprehensive evaluation on constraining fuzziness and convert the fuzzy constraint into general constraint according to the actual conditions and requirements; for multi-objectives, single-objective optimal solutions are fuzzified to form fuzzy sets to establish the membership functions of the fuzzy sets by taking the fuzziness between the single objectives and between the single objectives and multiple objectives into consideration, and multi-objective optimal solutions are obtained by maximizing the membership functions of the fuzzy set intersection. For an actual gear reducer, the fuzzy theory and method are applied to obtain results, and the validness of the method is demonstrated by comparing such results with the conventional design data.

The Fuzzy Reliability Optimum Design of Offshore Jacket Platforms

2002 ◽  
Author(s):  
Gangjun Zhai ◽  
Haigui Kang ◽  
Facong Xu
Keyword(s):  
Optimum Design ◽  
Structural Reliability ◽  
Fuzzy Optimization ◽  
Optimization Method ◽  
Optimum Level ◽  
Design Variables ◽  
Fuzzy Constraint ◽  
Cut Set ◽  
Optimum Model ◽  
Optimum Solution

In consideration of the fuzzy constraint boundary and through analysis of structural reliability, a model of structural fuzzy optimum design is established based on reliability for offshore jacket platforms. According to the characteristics of offshore jacket platforms, the tolerance coefficient of the constraint boundary is determined with the fuzzy optimization method. The optimum level cut set λ*, which is the intersection of the fuzzy constraint set and fuzzy objective set, is determined with the bound search method, and then the fuzzy optimum solution of fuzzy optimization problem is obtained. The center offshore platform SZ36-1 is designed with the fuzzy optimum model based on reliability above; the results are compared with those from deterministic optimum design and fuzzy optimum design. The tendency of design variables and its reasons in the above three methods are analyzed. The results of an example show that the fuzzy optimum design based on reliability is stable and reliable.

scholarly journals Roof-Crush Protection Design of Automotive Bodies Using Clustering and Pattern Recognition

2019 ◽  
Vol 9 (7) ◽  
pp. 1437
Author(s):  
Yong-Sang Shin ◽  
Hyo-Jun Eun ◽  
Yong-Ju Chu ◽  
Seung-Yop Lee
Keyword(s):  
Pattern Recognition ◽  
Response Surface ◽  
Optimization Design ◽  
Large Scale ◽  
Optimization Technique ◽  
Surface Model ◽  
Automotive Body ◽  
Design Variables ◽  
Vehicle Rollover ◽  
Optimum Solution

Computer-aided engineering (CAE) tools play an indispensable role in the vehicle development process. However, it is difficult to accurately predict the relationships and behavior of automotive bodies in vehicle crashes owing to high-order nonlinearity and numerous design variables of the automotive body structure. In this study, clustering and pattern recognition techniques were used to develop a novel optimization design of an automotive body considering roof crushing by vehicle rollover. The large-scale data were clustered to find the strong and weak clusters, and new response surface models were acquired by clustering analysis to achieve better performance than the response surface model of traditional optimization. For an efficient robust design, clusters with weak performance were excluded from the optimum solution. Finally, it was confirmed that the solutions by the proposed optimization technique were better than those obtained by the traditional optimum method based on a comparative analysis by various cluster combinations.

Multi-Objective Fuzzy Optimization Design of Worm Drive

2013 ◽  
Vol 753-755 ◽  
pp. 1503-1509
Author(s):  
Xiao Xing Liu ◽  
Qi Ying Pan
Keyword(s):  
Fuzzy Sets ◽  
Optimization Design ◽  
Comprehensive Evaluation ◽  
Fuzzy Theory ◽  
Fuzzy Optimization ◽  
Optimal Level ◽  
Optimal Solutions ◽  
Membership Functions ◽  
Design Data ◽  
Multi Objective

Fuzzy factors in the worm reducer design are analyzed, and a multi-objective optimization model with minimum volume and maximum bearing capacity is established in this paper. Optimal level cut-set method is introduced to conduct comprehensive evaluation on constraining fuzziness and convert the fuzzy constraint into general constraint according to the actual conditions and requirements; for multi-objectives, single-objective optimal solutions are fuzzified to form fuzzy sets to establish the membership functions of the fuzzy sets by taking the fuzziness between the single objectives and between the single objectives and multiple objectives into consideration, and multi-objective optimal solutions are obtained by maximizing the membership functions of the fuzzy set intersection. For an actual worm reducer, the fuzzy theory and method are applied to obtain results, and the validness of the method is demonstrated by comparing such results with the conventional design data.

Multi-Objective Robust Design of Loader Transmission Based on Genetic Algorithm

2013 ◽  
Vol 325-326 ◽  
pp. 223-227
Author(s):  
Jian Bin Wang ◽  
Ji Shu Yin
Keyword(s):  
Genetic Algorithm ◽  
Robust Optimization ◽  
Robust Design ◽  
Optimization Design ◽  
High Efficiency ◽  
Design Method ◽  
Fuzzy Theory ◽  
Fuzzy Optimization ◽  
Optimal Method ◽  
Robust Optimization Design

The fuzzy theory and robust design is applied to the optimization design of the loader transmission, and put forward the fuzzy optimization design method of loader Transmission based on the robust idea. It is established the fuzzy robust optimization design model of loader transmission which has the goal of small size and high efficiency, and finally shows the optimal method and calculation example.

Multi-Objective Fuzzy Optimization Design of Truck Differential

2014 ◽  
Vol 722 ◽  
pp. 84-88
Author(s):  
Er Zhong An ◽  
Yun Chao Wang
Keyword(s):  
Optimization Design ◽  
Fuzzy Theory ◽  
Fuzzy Optimization ◽  
Multi Objective Optimization ◽  
Gear Teeth ◽  
Multi Objective ◽  
Section Modulus ◽  
Planet Gear ◽  
Fuzzy Solution ◽  
Set Up

Multi-objective optimization technology and Fuzzy theory were applied to design truck differential based on consideration on its force condition. The mathematical model for the multi-objective optimization design was set up under the objective of the minimum volume of the differential, maximal strength of planet gear, with the design variable of planet gear teeth number Z1, axle shaft gear teeth number Z2, section modulus ms and working width b. Then, the fuzzy solution of multi-objective optimization were use to solve the model. Practical example of calculation shows that, the fuzzy optimization result is superior to that of regular optimization and traditional design, differential volume deceased by 32.73% and 1.92% respectively. Comparing with nominal design, the load of planet gear increases 17%, but is far below its permissible value, and also reduced by 9.04% than that of regular optimization.

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