Optimal design of main girder structure of bridge crane based on equal life concept driven by data

被引:0
|
作者
Yannan Yu
Zhiping Liu
Yao Lu
Peng Zhang
Hui Liu
机构
[1] Wuhan University of Technology,College of Transportation and Logistics Engineering
关键词
Crane; Equal life; Fatigue life; Structural optimization; Optimization algorithm; Finite element;
D O I
暂无
中图分类号
学科分类号
摘要
In traditional structural crane design, the fatigue strength of the structure is qualitatively evaluated, only depending on the steel type, working level and joint form, which leads to the excessive service life of some parts of the existing main girder structure, resulting in a waste of industrial resources and manufacturing costs. Based on the concept of equal life design, this paper obtained the service information of the crane in the scheduled inspection period through the rapid prediction method of “field collection+machine learning.” Combined with the bearing capacity evaluation method and the fatigue life assessment method of “S-N curve+fracture mechanics,” a nonlinear mixed integer equal life optimization model of crane girder structure was established, and the multi-specular reflection optimization algorithm was used to optimize the life distribution at different positions and overall weight of the main girder. The structural design parameters of the crane main girder which meet the bearing capacity and have the characteristics of “equal life+lightweight” were obtained. The performance of the optimized main girder structure was verified by finite element simulation. The results show that this method can realize the quantitative control of the life distribution of each position of the crane main girder structure and the lightweight design of the whole structure, and provides a scientific reference for the equal life and lightweight design of large construction machinery products.
引用
收藏
页码:4767 / 4786
页数:19
相关论文
共 42 条
  • [21] Optimal Control Design for Traffic Flow Maximization Based on Data-Driven Modeling Method
    Nemeth, Balazs
    Fenyes, Daniel
    Bede, Zsuzsanna
    Gaspar, Peter
    ENERGIES, 2022, 15 (01)
  • [22] Data-Driven Sparse Sensor Selection Based on A-Optimal Design of Experiment With ADMM
    Nagata, Takayuki
    Nonomura, Taku
    Nakai, Kumi
    Yamada, Keigo
    Saito, Yuji
    Ono, Shunsuke
    IEEE SENSORS JOURNAL, 2021, 21 (13) : 15248 - 15257
  • [23] Development of a BIM-Based Master Digital Model Using Data-Driven Design for the Suspension Bridge
    NgocSon Dang
    Rho, GiTae
    Shim, ChangSu
    CIGOS 2021, EMERGING TECHNOLOGIES AND APPLICATIONS FOR GREEN INFRASTRUCTURE, 2022, 203 : 1805 - 1813
  • [24] An approach to the selection of target reliability index of Cable-stayed bridge's main girder based on optimal structural parameter ratio from cost-benefit analysis
    Zhang, Zhenhao
    Li, Wenbiao
    Ding, Zhouxiang
    Wu, Xueyan
    STRUCTURES, 2020, 28 : 2221 - 2231
  • [26] Data-Driven Optimal Test Selection Design for Fault Detection and Isolation Based on CCVKL Method and PSO
    Li, Yang
    Chen, Hongtian
    Lu, Ningyun
    Jiang, Bin
    Zio, Enrico
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
  • [27] A Data-Driven Method for Lithium-Ion Batteries Remaining Useful Life Prediction Based on Optimal Hyperparameters
    Zhu, Yuhao
    Shang, Yunlong
    Duan, Bin
    Gu, Xin
    Li, Shipeng
    Chen, Guicheng
    2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 7388 - 7392
  • [28] An Online Data-Driven Evolutionary Algorithm-Based Optimal Design of Urban Stormwater-Drainage Systems
    Li, Xuan
    Hou, Jingming
    Chai, Jie
    Du, Ying'en
    Han, Hao
    Yang, Shaoxiong
    Gao, Xujun
    Yang, Xiao
    JOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING, 2022, 148 (11)
  • [29] Data-Driven Coordinated Attack Policy Design Based on Adaptive L2-Gain Optimal Theory
    An, Liwei
    Yang, Guang-Hong
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2018, 63 (06) : 1850 - 1857
  • [30] Parameter Optimal Iterative Learning Control Design: from Model-based, Data-driven to Reinforcement Learning *
    Zhang, Yueqing
    Chu, Bing
    Shu, Zhan
    IFAC PAPERSONLINE, 2022, 55 (12): : 494 - 499