Journal of Jilin University(Engineering and Technology Edition) ›› 2019, Vol. 49 ›› Issue (6): 1969-1976.doi: 10.13229/j.cnki.jdxbgxb20180924

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Optimal design of two degrees of freedom dynamic vibration absorber based on multi-objective genetic algorithm

Fu-chun JIA1(),Xian-jie MENG2,Yu-long LEI1()   

  1. 1. State Key Laboratory of Automotive Simulation and Control, Jinlin University, Changchun 130022, China
    2. School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China
  • Received:2018-09-10 Online:2019-11-01 Published:2019-11-08
  • Contact: Yu-long LEI E-mail:jiafc1992@163.com;leiyl@jlu.edu.cn

Abstract:

This paper presents a 2-DOF dynamic vibration absorber to reduce the vibration of 2-DOF main system which possesses translation and rotation around the centroiding. The main system obtains a good damping effect by optimizing the stiffness and damping of the dynamic vibration absorber. The evaluation and optimization indexes are displacement, acceleration, angular displacement and angular acceleration. The nondominated sorting genetic algorithm (NSGA-Ⅱ) is used to solve the multi-objective optimization problem including four optimization objectives and three design variables. The 60 Pareto optimal solutions are ordered by entropy weight TOPSIS. The optimal solution is selected as the dynamic vibration absorber optimization design solution and a simulation analysis is carried out to obtain the frequency domain simulation results and time domain simulation results. The results show that the dynamic vibration absorber with optimized parameters greatly reduce the four vibration evaluation indexes of the main system and the vibration control effect of the two-DOF dynamic vibration absorber is good. The NSGA-Ⅱ and Entropy TOPSIS joint optimization method is suitable for optimal design of two-DOF dynamic vibration absorber.

Key words: mechanical design, two-DOF dynamic vibration absorber, multi-objective optimization, genetic algorithm, multi-attribute decision making

CLC Number: 

  • TH113.1

Fig.1

Schematic of two degrees of freedom DVA"

Fig.2

Flow chart of multi-objective genetic algorithm"

Fig.3

Optimization results distribution"

Table1

Decision results"

序 数 方 案
1 2 3 4 5
sum(max|x 1/f|)/(10-4 m·N-1 1.88 1.78 1.96 2 1.74
sum(max|θ 1/f|)/(10-4 rad·N-1 6.17 6.43 5.98 5.87 6.55
sum(max| x ¨ 1/f|)/(10-2 m·s-2·N-1 6.43 6.25 6.58 6.64 6.2
sum(max| θ ¨ 1 /f |)/(rad·s-2·N-1 1.217 1.31 1.146 1.107 1.35
k 3/(104 N·m-1) 2.865 2.47 3.074 3.335 2.387
k 4/(104 N·m-1) 1.019 1.015 1.019 1.015 1.014
c/(103 N·s·m-1) 1.296 1.291 1.443 1.438 1.241
综合评价指数方正汇总行C 0.153 0.154 0.155 0.156 0.162

Fig.4

Relationship between each solution"

Fig.5

Amplitude-frequency characteristic curves"

Table 2

Amplitude-frequency characteristic peak"

幅频特性 幅频特性峰值/dB
主系统 附加DVA 降幅
max|x 1/f | 1 -85.5 -172.1 86.6
2 -197.7 -242.1 45
max|θ 1/f | 1 -85.4 -107.9 22
2 -154.7 -172.3 17.6
max| x ¨ 1/f | 1 29.42 -59.9 88.9
2 -39.50 -84.7 45.2
max| θ ¨ 1 /f | 1 29.5 -60.2 89.7
2 50.2 3.1 46.9

Fig.6

Random motivation"

Fig.7

Simulation results"

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