Optimization of Shearer Drum Based on Multi-Objective Bat Algorithm with Grid (MOBA/G)

被引:7
|
作者
Duan, Mingyu [1 ,2 ]
Huang, Qibai [1 ]
Xu, Ren [1 ]
Wang, Chenlin [1 ]
Xu, Jing [3 ]
机构
[1] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Peoples R China
[2] Henan Dayou Energy Co Ltd, Yima 472300, Peoples R China
[3] Jiangsu Univ Sci & Technol, Marine Equipment & Technol Inst, 2 Mengxi Rd, Zhenjiang 212008, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
comprehensive performance; pick; drum; multi-objective optimization; multi-objective bat algorithm with grid; PERFORMANCE; INTELLIGENT;
D O I
10.3390/machines10090733
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The shearer drum undertakes the main function of coal falling and loading, and picks distributed on it have a great impact on the performance of the drum. However, few studies have optimized the pick and drum at the same time. In this paper, parameters of pick and drum are considered as design variables, and the response functions of design variables are established based on the central composite experiment method. The optimal structural and working parameters of the pick and the drum of MG500/1130-WD shearer are obtained by using the multi-objective bat algorithm and multi-objective bat algorithm with grid, respectively. Comparing results of the two algorithms, the multi-objective bat algorithm with grid is more effective in improving the comprehensive performance of the drum. According to the optimized design variables, a coal mining test is carried out to verify the optimization effect of the algorithm. The result provides some theoretical references for the design and production of the drum and has some engineering application value.
引用
收藏
页数:18
相关论文
共 50 条
  • [41] A multi-objective optimization algorithm based on gradient information
    Qi, Rongbin
    Liu, Chenxia
    Zhong, Weimin
    Qian, Feng
    Huagong Xuebao/CIESC Journal, 2013, 64 (12): : 4401 - 4409
  • [42] Multi-objective optimization problem based on genetic algorithm
    Heng, L., 1600, Asian Network for Scientific Information (12):
  • [43] Portfolio analysis based on multi-objective optimization algorithm
    Chen Juan
    Ji Mengla
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MECHATRONICS, ROBOTICS AND AUTOMATION (ICMRA 2015), 2015, 15 : 809 - 812
  • [44] A Multi-Objective Memetic Algorithm Based on Chaos Optimization
    Ammaruekarat, Paranya
    Meesad, Phayung
    MECHANICAL AND ELECTRONICS ENGINEERING III, PTS 1-5, 2012, 130-134 : 725 - 729
  • [45] A New Algorithm based on PSO for Multi-objective Optimization
    Leung, Man-Fai
    Ng, Sin-Chun
    Cheung, Chi-Chung
    Lui, Andrew K.
    2015 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2015, : 3156 - 3162
  • [46] An improved multi-objective optimization algorithm based on decomposition
    Wang, Wanliang
    Wang, Zheng
    Li, Guoqing
    Ying, Senliang
    2019 TENTH INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROL AND INFORMATION PROCESSING (ICICIP), 2019, : 327 - 333
  • [47] Multi-objective optimization of reservoir flood dispatch based on multi-objective differential evolution algorithm
    Qin, Hui
    Zhou, Jian-Zhong
    Wang, Guang-Qian
    Zhang, Yong-Chuan
    Shuili Xuebao/Journal of Hydraulic Engineering, 2009, 40 (05): : 513 - 519
  • [48] Personalised Multi-Objective Travel Route Recommendation Based on Super Multi-Objective Optimization Algorithm
    Zhang, Xiang-Rong
    Wang, Xue-Ying
    Ebara, Takeshi
    Journal of Network Intelligence, 2024, 9 (03): : 1625 - 1640
  • [49] Research on Grid Workflow Scheduling Based on the Discrete Multi-objective Particle Swarm Optimization Algorithm
    Li Jinzhong
    Xia Jiewu
    Wei Simin
    Huang Chuanlian
    PROCEEDINGS OF 2009 CONFERENCE ON COMMUNICATION FACULTY, 2009, : 662 - 666
  • [50] A Novel Opposition-Based Multi-objective Differential Evolution Algorithm for Multi-objective Optimization
    Peng, Lei
    Wang, Yuanzhen
    Dai, Guangming
    ADVANCES IN COMPUTATION AND INTELLIGENCE, PROCEEDINGS, 2008, 5370 : 162 - +