Parameters estimation of horizontal multilayer earth based on Kriging model updating method

被引:0
|
作者
Chen, Yuhao [1 ]
Wang, Xinyang [1 ]
Liu, Minzhou [1 ]
Xie, Yanzhao [1 ]
机构
[1] Xi An Jiao Tong Univ, Sch Elect Engn, State Key Lab Elect Insulat & Power Equipment, Xian 710049, Peoples R China
关键词
Horizontal multilayer earth model; Parameters estimation; Kriging model updating method; Genetic algorithm; Computational efficiency; APPARENT RESISTIVITY; SOIL PARAMETERS;
D O I
10.1016/j.epsr.2024.110465
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
A Kriging model updating method combined with Kriging surrogate model and genetic algorithm is proposed in this paper, helping to improve the computational efficiency of parameters estimation for horizontal multilayer earth model around electrical substation. Based on the theory of widely used Wenner configuration method for apparent resistivity measurement, the optimization model for horizontal multilayer earth model parameters is built up. To avoid time-consuming calculation, Kriging surrogate model is introduced to replace the complicated optimization model using small amount of data samples. Then genetic algorithm is adopted to update this Kriging model and estimate the earth model parameters until the criterion achieved. The accuracy and efficiency of the proposed method are analyzed. And several cases of multilayer earth model are studied furtherly and compared with traditional genetic algorithm to verify its feasibility.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] Estimation of horizontal multilayer soil parameters using Newton interpolation polynomial and h-DETLBO method
    Sengar, Kaushal Pratap
    Chandrasekaran, Kandasamy
    ELECTRICAL ENGINEERING, 2020, 102 (04) : 2083 - 2094
  • [22] Estimation of horizontal multilayer soil parameters using Newton interpolation polynomial and h-DETLBO method
    Kaushal Pratap Sengar
    Kandasamy Chandrasekaran
    Electrical Engineering, 2020, 102 : 2083 - 2094
  • [23] Frequency response function-based model updating using Kriging model
    Wang, J. T.
    Wang, C. J.
    Zhao, J. P.
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 87 : 218 - 228
  • [24] Using maximum likelihood estimation to estimate kriging model parameters
    Martin, Jay D.
    PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE 2007, VOL 6, PTS A AND B, 2008, : 663 - 673
  • [25] Multi-Resolution Complex Image Method of Horizontal Multilayer Earth
    Ruan, Ling
    Zhou, You-bing
    Quan, Jiang-tao
    Yang, Qi
    Pan, Zhuo-hong
    Wen, Xi-shan
    2014 6TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND ELECTRICAL ENGINEERING (ICITEE), 2014, : 301 - 306
  • [26] Bayesian model updating in an active Kriging-based metamodeling framework
    Sengupta, Partha
    Chakraborty, Subrata
    APPLIED MATHEMATICAL MODELLING, 2025, 142
  • [27] The Using of Kriging Method in DBD Model Parameters Identification
    Yu, Jia-Ning
    Song, Yan-Ping
    Yu, Jian-Yang
    Jin, Jia-Hui
    Kung Cheng Je Wu Li Hsueh Pao/Journal of Engineering Thermophysics, 2019, 40 (02): : 282 - 288
  • [28] Bayesian model updating for bridge engineering applications based on DREAMKZS algorithm and Kriging model
    Qin, Shiqiang
    Song, Renxian
    Li, Ning
    STRUCTURES, 2023, 58
  • [29] Identification of structural boundary conditions based on the Kriging model and the hierarchical model updating technique
    Wang Y.
    Peng Z.
    Zhendong yu Chongji/Journal of Vibration and Shock, 2023, 42 (06): : 134 - 142
  • [30] A Super-Harmonic Feature Based Updating Method for Crack Identification in Rotors Using a Kriging Surrogate Model
    Lu, Zhiwen
    Lv, Yong
    Ouyang, Huajiang
    APPLIED SCIENCES-BASEL, 2019, 9 (12):