Multi-Objective Parametric Optimization of an Equilibrator Mechanism

被引:0
|
作者
Kurtulmus, Ergin [1 ]
机构
[1] FNSS Savunma Sistemleri AS, TR-06830 Ankara, Turkey
关键词
Moment unbalance; Nonlinear systems; Optimization; Pareto optimality; Pareto fronts;
D O I
10.1007/978-3-319-53841-9_3
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In order to eliminate the moment unbalance of rotary systems, a certain type of equilibrator mechanism which is able to perfectly balance is utilized. It includes helical spring(s), a pulley and a cable attached to a certain hinge point on the rotary body. Actual implementations of the mechanism may not allow realization of the conditions for perfect balancing. Then, the problem is transformed into a multi objective constrained optimization, which includes multiple parameters and multiple objectives like minimizing the residual moment unbalance, minimizing the diameter and the length of the spring( s), maximizing the spring fatigue life as well necessity to satisfy some geometrical layout constraints and operational constraints on the springs. The system has been modeled in a quasi-static manner and optimized parametrically around the regions of operation. Pareto optimal fronts have been determined and the optimized parameters have been used as design parameters for realization of the actual system. The design of the mechanism has been algorithmically automated based on the requirements and constraints.
引用
收藏
页码:25 / 40
页数:16
相关论文
共 50 条
  • [41] A multi-objective optimization design for a new linear compliant mechanism
    Minh Phung Dang
    Hieu Giang Le
    Ngoc Le Chau
    Thanh-Phong Dao
    OPTIMIZATION AND ENGINEERING, 2020, 21 (02) : 673 - 705
  • [42] A study on distribution preservation mechanism in evolutionary multi-objective optimization
    Khor, EF
    Tan, KC
    Lee, TH
    Goh, CK
    ARTIFICIAL INTELLIGENCE REVIEW, 2005, 23 (01) : 31 - 56
  • [43] Multi-objective boxing match algorithm for multi-objective optimization problems
    Tavakkoli-Moghaddam, Reza
    Akbari, Amir Hosein
    Tanhaeean, Mehrab
    Moghdani, Reza
    Gholian-Jouybari, Fatemeh
    Hajiaghaei-Keshteli, Mostafa
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 239
  • [44] Hyper multi-objective evolutionary algorithm for multi-objective optimization problems
    Guo, Weian
    Chen, Ming
    Wang, Lei
    Wu, Qidi
    SOFT COMPUTING, 2017, 21 (20) : 5883 - 5891
  • [45] MOCSA: A Multi-Objective Crow Search Algorithm for Multi-Objective Optimization
    Nobahari, Hadi
    Bighashdel, Ariyan
    2017 2ND CONFERENCE ON SWARM INTELLIGENCE AND EVOLUTIONARY COMPUTATION (CSIEC), 2017, : 60 - 65
  • [46] Multi-Objective A* Algorithm for the Multimodal Multi-Objective Path Planning Optimization
    Jin, Bo
    2021 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC 2021), 2021, : 1704 - 1711
  • [47] Multi-Objective Factored Evolutionary Optimization and the Multi-Objective Knapsack Problem
    Peerlinck, Amy
    Sheppard, John
    2022 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2022,
  • [48] Hyper multi-objective evolutionary algorithm for multi-objective optimization problems
    Weian Guo
    Ming Chen
    Lei Wang
    Qidi Wu
    Soft Computing, 2017, 21 : 5883 - 5891
  • [49] Hybrid Multi-Objective Genetic Algorithm for Multi-Objective Optimization Problems
    Zhang, Song
    Wang, Hongfeng
    Yang, Di
    Huang, Min
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 1970 - 1974
  • [50] Splitting for Multi-objective Optimization
    Qibin Duan
    Dirk P. Kroese
    Methodology and Computing in Applied Probability, 2018, 20 : 517 - 533