Numeric Validation of the Inversion Model of Electrical Resistivity Imaging Method using the Levenberg-Marquardt Algorithm

Authors

  • Tuan Anh Nguyen STASD Research Group, Ho Chi Minh City University of Transport, Vietnam
Volume: 14 | Issue: 1 | Pages: 12806-12811 | February 2024 | https://doi.org/10.48084/etasr.6705

Abstract

This paper introduces a new application of the Electrical Resistivity Imaging (ERI) method within the realm of structural assessment, deviating from its conventional use in geology. The study presents an innovative inversion model that incorporates the Levenberg-Marquardt algorithm, representing a notable leap in seamlessly integrating ERI into structural analysis. Rigorous validation of the inversion methodology is conducted through extensive benchmarking against simulated reference data, focusing on 1D and 2D resistivity distributions within timber specimens. By utilizing known resistivity fields, the paper quantitatively validates the accuracy of reconstructed models obtained through numerical simulations. Notably, both longitudinal and transverse surveys exhibit exceptional outcomes, showcasing a high correlation with the actual resistivity profiles, achieved within a concise 10-13 iterations. This meticulous validation process conclusively underscores the effectiveness and precision of the proposed inversion approach. Beyond its scientific contribution, this research expands the conventional boundaries of ERI application and establishes it as an invaluable tool for structural monitoring.

Keywords:

ERI, resistivity, Levenberg-Marquardt, numeric validation, inversion model

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References

M. H. Loke, J. E. Chambers, D. F. Rucker, O. Kuras, and P. B. Wilkinson, "Recent developments in the direct-current geoelectrical imaging method," Journal of Applied Geophysics, vol. 95, pp. 135–156, Aug. 2013.

O. O. Osinowo and M. O. Falufosi, "3D Electrical Resistivity Imaging (ERI) for subsurface evaluation in pre-engineering construction site investigation," NRIAG Journal of Astronomy and Geophysics, vol. 7, no. 2, pp. 309–317, Dec. 2018.

C. Ungureanu, A. Priceputu, A. L. Bugea, and A. Chirică, "Use of electric resistivity tomography (ERT) for detecting underground voids on highly anthropized urban construction sites," Procedia Engineering, vol. 209, pp. 202–209, Jan. 2017.

S. Soto-Caban and E. Law, "Using Resistivity Measurements to Determine Anisotropy in Soil and Weathered Rock," Engineering, Technology & Applied Science Research, vol. 3, no. 4, pp. 483–487, Aug. 2013.

G. S. Solangi, A. A. Siyal, M. M. Babar, and P. Siyal, "Spatial Analysis of Soil Salinity in the Indus River Delta, Pakistan," Engineering, Technology & Applied Science Research, vol. 9, no. 3, pp. 4271–4275, Jun. 2019.

J. D. Ducut et al., "A Review of Electrical Resistivity Tomography Applications in Underground Imaging and Object Detection," Displays, vol. 73, Jul. 2022, Art. no. 102208.

J. F. Lataste, C. Sirieix, D. Breysse, and M. Frappa, "Electrical resistivity measurement applied to cracking assessment on reinforced concrete structures in civil engineering," NDT & E International, vol. 36, no. 6, pp. 383–394, Sep. 2003.

K. Karhunen, A. Seppänen, A. Lehikoinen, P. J. M. Monteiro, and J. P. Kaipio, "Electrical Resistance Tomography imaging of concrete," Cement and Concrete Research, vol. 40, no. 1, pp. 137–145, Jan. 2010.

T. A. Nguyen, "Approches expérimentales et numériques pour l’étude des transferts hygroscopiques dans le bois," Ph.D. dissertation, Université de Limoges, Limoges, France, 2014.

S. F. Yasir, J. Jani, and M. Mukri, "A dataset of visualization methods to assessing soil profile using RES2DINV and VOXLER software," Data in Brief, vol. 24, Jun. 2019, Art. no. 103821.

A. Kleefeld and M. Reißel, "The Levenberg–Marquardt method applied to a parameter estimation problem arising from electrical resistivity tomography," Applied Mathematics and Computation, vol. 217, no. 9, pp. 4490–4501, Jan. 2011.

X. Wang, P. Wang, X. Zhang, Y. Wan, W. Liu, and H. Shi, "Efficient and robust Levenberg–Marquardt Algorithm based on damping parameters for parameter inversion in underground metal target detection," Computers & Geosciences, vol. 176, Jul. 2023, Art. no. 105354.

T. Dridi, H. Jouini, A. Mami, A. E. Mhamedi, and E. M. Dafaoui, "Application of the Levenberg-Marquardt Algorithm in Solving the Economic Emission Dispatch Problem Integrating Renewable Energy," Engineering, Technology & Applied Science Research, vol. 12, no. 4, pp. 8850–8855, Aug. 2022.

A. Lemita, S. Boulahbel, and S. Kahla, "Gradient Descent Optimization Control of an Activated Sludge Process based on Radial Basis Function Neural Network," Engineering, Technology & Applied Science Research, vol. 10, no. 4, pp. 6080–6086, Aug. 2020.

G. Tomasi and R. Bro, "2.22 - Multilinear Models: Iterative Methods," in Comprehensive Chemometrics, S. D. Brown, R. Tauler, and B. Walczak, Eds. Oxford: Elsevier, 2009, pp. 411–451.

D. Constales, G. S. Yablonsky, D. R. D’hooge, J. W. Thybaut, and G. B. Marin, "Chapter 9 - Experimental Data Analysis: Data Processing and Regression," in Advanced Data Analysis & Modelling in Chemical Engineering, D. Constales, G. S. Yablonsky, D. R. D’hooge, J. W. Thybaut, and G. B. Marin, Eds. Amsterdam, Netherlands: Elsevier, 2017, pp. 285–306.

M. Meloun and J. Militký, "8 - Nonlinear Regression Models," in Statistical Data Analysis, M. Meloun and J. Militký, Eds. Woodhead Publishing India, 2011, pp. 667–762.

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How to Cite

[1]
Nguyen, T.A. 2024. Numeric Validation of the Inversion Model of Electrical Resistivity Imaging Method using the Levenberg-Marquardt Algorithm. Engineering, Technology & Applied Science Research. 14, 1 (Feb. 2024), 12806–12811. DOI:https://doi.org/10.48084/etasr.6705.

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