MicEMD: Open-source toolbox for electromagnetic modeling, inversion, and classification in underground metal target detection

被引：0
作者：
Wang, Xiaofen [1 ]
Shi, Haodong [1 ]
Zhang, Xiaotong [1 ]
Wan, Yadong [1 ]
Wang, Peng [2 ]
机构：
[1] Univ Sci & Technol, Sch Comp & Commun Engn, Beijing, Peoples R China
[2] China Unicorn Smart City Res Inst, Beijing, Peoples R China
来源：
SOFTWAREX | 2024年 / 27卷
关键词：
Open-source; Underground metal target detection; Inversion; Classification; Electromagnetic induction (EMI); Extensibility; DIMENSIONALITY REDUCTION; IDENTIFICATION;
D O I：
10.1016/j.softx.2024.101812
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
The development and improvement of electromagnetic underground metal target detection methods can be implemented by a framework that is experimental supporting, modular, and extensible. In this paper, we organize the components of electromagnetic underground metal target detection in a comprehensive, modular, and extensible framework. Furthermore, we present an open-source toolbox in Python called MicEMD (Modeling, Inversion, and Classification in ElectroMagnetic Detection, https://github.com/UndergroundDetection/ MICEMD). The graphical user interface (GUI) and the library with a Python application programming interface (API) are contained in MicEMD. Included in MicEMD are staggered frequency-domain and time-domain electromagnetic forward modeling, least-squares inversion, and data-based classification methods at present. MicEMD's capabilities are presented by two synthetic case studies. The first example shows the application of frequency-domain inversion. The second example shows the application of time-domain classification. It is anticipated that MicEMD offers a flexible tool in electromagnetic underground metal target detection.
引用
收藏
页数：8
相关论文
共 42 条
  • [11] Feller Joseph, 2000, PROC ICIS 00, P58
  • [12] Fernandez JP, 2011, Detection and sensing of mines, explosive objects, and obscured targets XVI, V8017, P67
  • [13] A Man-Portable Vector Sensor for Identification of Unexploded Ordnance
    Fernandez, Juan Pablo
    Barrowes, Benjamin E.
    Grzegorczyk, Tomasz M.
    Lhomme, Nicolas
    O'Neill, Kevin
    Shubitidze, Fridon
    [J]. IEEE SENSORS JOURNAL, 2011, 11 (10) : 2542 - 2555
  • [14] A framework for simulation and inversion in electromagnetics
    Heagy, Lindsey J.
    Cockett, Rowan
    Kang, Seogi
    Rosenkjaer, Gudni K.
    Oldenburg, Douglas W.
    [J]. COMPUTERS & GEOSCIENCES, 2017, 107 : 1 - 19
  • [15] A Hybrid Method for UXO vs. Non-UXO Discrimination
    Kappler, Karl N.
    Gasperikova, Erika
    [J]. JOURNAL OF ENVIRONMENTAL AND ENGINEERING GEOPHYSICS, 2011, 16 (04) : 177 - 189
  • [16] ModEM: A modular system for inversion of electromagnetic geophysical data
    Kelbert, Anna
    Meqbel, Naser
    Egbert, Gary D.
    Tandon, Kush
    [J]. COMPUTERS & GEOSCIENCES, 2014, 66 : 40 - 53
  • [17] A new algorithm for redundancy minimisation in geo-environmental data
    Laib, Mohamed
    Kanevski, Mikhail
    [J]. COMPUTERS & GEOSCIENCES, 2019, 133
  • [18] Locating Underground Pipe Using Wideband Chaotic Ground Penetrating Radar
    Li, Jingxia
    Guo, Tian
    Leung, Henry
    Xu, Hang
    Liu, Li
    Wang, Bingjie
    Liu, Yang
    [J]. SENSORS, 2019, 19 (13):
  • [19] 2D marine controlled-source electromagnetic modeling: Part 1 - An adaptive finite-element algorithm
    Li, Yuguo
    Key, Kerry
    [J]. GEOPHYSICS, 2007, 72 (02) : WA51 - WA62
  • [20] Three-dimensional object location and inversion of the magnetic polarizability tensor at a single frequency using a walk-through metal detector
    Marsh, Liam A.
    Ktistis, Christos
    Jarvi, Ari
    Armitage, David W.
    Peyton, Anthony J.
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2013, 24 (04)
12345