Radiated Susceptibility Analysis of Multiconductor Transmission Lines Based on Polynomial Chaos

Authors

  • Tianhao Wang College of Instrumentation and Electrical Engineering Jilin University, Changchun, 220000, 130061 China
  • Quanyi Yu College of Instrumentation and Electrical Engineering Jilin University, Changchun, 220000, 130061 China
  • Xianli Yu College of Geo-Exploration Science and Technology Jilin University, Changchun, 220000, 130061 China
  • Le Gao College of Instrumentation and Electrical Engineering Jilin University, Changchun, 220000, 130061 China
  • Huanyu Zhao College of Instrumentation and Electrical Engineering Jilin University, Changchun, 220000, 130061 China

Keywords:

Adaptive Hyperbolic Truncation (AHT), Least Angle Regression (LAR), Multiconductor Transmission Lines (MTLs), polynomial chaos, radiated susceptibility

Abstract

To address the uncertainties of the radiated susceptibility of multiconductor transmission lines (MTLs), a surrogate model of the MTLs radiated susceptibility is established based on generalized polynomial chaos (gPC), and the gPC is made sparser by combining the adaptive hyperbolic truncation (AHT) scheme and the least angle regression (LAR) method. The uncertainties of the radiated susceptibility of transmission lines are calculated using the adaptive-sparse polynomial chaos (AS-PC) scheme. The parameters related to the incident field, such as elevation angle θ, azimuth angle ψ, polarization angle η, and field amplitude E, are inevitably random. Therefore, these four variables are taken as random input variables, and each of them is subject to different variable distributions. The MTLs model with infinite ground as the reference conductor is adopted, different impedances are used and the AS-PC scheme is combined with transmission line theory to calculate the average, standard deviation and probability distribution of the radiated susceptibility of MTLs. Sobol global sensitivity analysis based on variance decomposition is adopted to calculate the influence of random input variables on the MTLs radiated susceptibility model. The calculation results are compared with the results of the Monte Carlo (MC) method, proving that the proposed method is correct and feasible.

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References

C. Taylor, R. Satterwhite and C. Harrison, “The response of a terminated two-wire transmission line excited by a nonuniform electromagnetic field,” IEEE Trans. Antennas Propagat., vol. 13, no. 6, pp. 987-989, Nov. 1965.

C. R. Paul, “Frequency response of multiconductor transmission lines illuminated by an electromagnetic field,” IEEE Trans. on Electromagn. Compat., vol. EMC-18, no. 4, pp. 183-190, Nov. 1976.

C. R. Paul, Analysis of Multiconductor Transmission Lines, 2nd ed., New York, NY, USA: Wiley, 2008.

Z. Fei, Y. Huang, J. Zhou, and C. Song, “Numerical analysis of a transmission line illuminated by a random plane-wave field using stochastic reduced order models,” IEEE Access, vol. 5, pp. 8741-8751, 2017.

D. Bellan and S. Pignari, “A probabilistic model for the response of an electrically short two-conductor transmission line driven by a random plane wave field,” IEEE Trans. on Electromagn. Compat., vol. 43, no. 2, pp. 130-139, May 2001.

S. Pignari and D. Bellan, “Statistical characterization of multiconductor transmission lines illuminated by a random plane-wave field,” IEEE International Symposium on Electromagnetic Compatibility Symposium Record, Washington, DC, vol. 2, pp. 605-609, 2000.

M. Omid, Y. Kami, and M. Hayakawa, “Field coupling to nonuniform and uniform transmission lines,” IEEE Trans. on Electromagn. Compat., vol. 39, no. 3, pp. 201-211, Aug. 1997.

G. S. Shinh, N. M. Nakhla, R. Achar, M. S. Nakhla, A. Dounavis, and I. Erdin, “Fast transient analysis of incident field coupling to multiconductor transmission lines,” IEEE Trans. on Electromagn. Compat., vol. 48, no. 1, pp. 57-73, Feb. 2006.

X. Zhang, Z. Zhao, Y. Qin, J. Luo, and G. Ni, “Transient analytic solutions of lossless multiconductor transmission line excited by plane-wave,” Proceedings of the 9th International Symposium on Antennas, Propagation and EM Theory, Guangzhou, pp. 1073-1076, 2010.

B. Ravelo, Y. Liu, and A. K. Jastrzebski, “PCB near-field transient emission time-domain model,” IEEE Trans. Electromagn. Compat., vol. 57, no. 6, pp. 1320-1328, Dec. 2015.

L. Gao, Q. Yu, D. Wu, T. Wang, X. Yu, Y. Chi, and T. Zhang, “Probabilistic distribution modeling of crosstalk in multi-conductor transmission lines via maximum entropy method,” in IEEE Access, vol. 7, pp. 103650-103661, 2019.

Y. Chi, B. Li, X. Yang, T. Wang. K. Yang, and Y. Gao, “Research on the statistical characteristics of crosstalk in naval ships wiring harness based on polynomial chaos expansion method,” Nephron. Clin. Pract., vol. 24, no. s2, pp. 205-214, 2017.

P. Manfredi and F. G. Canavero, “Polynomial chaos representation of transmission-line response to random plane waves,” International Symposium on Electromagnetic Compatibility - EMC Europe, Rome, pp. 1-6, 2012.

P. Manfredi and F. G. Canavero, “Polynomial Chaos for Random Field Coupling to Transmission Lines,” in IEEE Trans. Electromagn. Compat., vol. 54, no. 3, pp. 677-680, June 2012.

T. Bdour and A. Reineix, “Global sensitivity analysis and uncertainty quantification of radiated susceptibility in PCB using nonintrusive polynomial chaos expansions,” IEEE Trans. Electromagn. Compat., vol. 58. no. 3, pp. 939-942, June 2016.

B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani, “Least angle regression,” The Annals of Statistics, vol. 32, no. 2, pp. 407-451, 2004.

G. Blatman and B. Sudret, “Adaptive sparse 1565 ACES JOURNAL, Vol. 35, No. 12, December 2020 polynomial chaos expansion based on least angle regression,” J. Comput. Phys., vol. 230, no. 6, pp. 2345-2367, Dec. 2011.

G. Spadacini, F. Grassi, F. Marliani, and S. A. Pignari, “Transmission-line model for field-to-wire coupling in bundles of twisted-wire pairs above ground,” IEEE Trans. Electromagn. Compat., vol. 56, no. 6, pp. 1682-1690, Dec. 2014.

G. Spadacini and S. A. Pignari, “Numerical assessment of radiated susceptibility of twistedwire pairs with random nonuniform twisting,” IEEE Trans. Electromagn. Compat., vol. 55, no. 5, pp. 956-964, Oct. 2013.

H. Y. Xie, Y. Li, and H. L. Qiao, “Analysis of field coupling to transmission lines with random rotation over the ground,” Chin. Phys. B., vol. 24, no. 6, pp. 171-176, Apr. 2015.

I. M. Sobol, “Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates,” Math. Comput. Simul., vol. 55, no. 1-3, pp. 271-280, 2001.

A. Kouassi, J. Bourinet, S. Lalléchère, P. Bonnet, and M. Fogli, “Reliability and sensitivity analysis of transmission lines in a probabilistic EMC context,” IEEE Trans. Electromagn. Compat., vol. 58, no. 2, pp. 561-572, Apr. 2016.

N. Wiener, “The homogeneous chaos,” Am. J. Math., vol. 60, pp. 897-936, 1938.

N. Wiener, Nonlinear Problems in Random Theory. MIT Technology Press and John Wiley and Sons, 1958.

D. Xiu and G. E. Karniadakis, “Modeling uncertainty in flow simulations via generalized polynomial chaos,” J. Comput. Phys., vol. 187, no. 1, pp. 137-167, 2003.

R. Mukerjee and C. F. J. Wu, A Modern Theory of Factorial Designs. Springer New York, 2006.

M. Larbi, I. S. Stievano, F. G. Canavero, and P. Besnier, “Identification of main factors of uncertainty in a microstrip line network,” Prog. Electromagn. Res., vol. 162, pp. 61-72, 2018.

B. Sudret, “Global sensitivity analysis using polynomial chaos expansions,” Reliability Engineering and System Safety, vol. 93, no. 7, pp. 964- 979, Apr. 2008.

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Published

2020-12-05

How to Cite

[1]
Tianhao Wang, Quanyi Yu, Xianli Yu, Le Gao, and Huanyu Zhao, “Radiated Susceptibility Analysis of Multiconductor Transmission Lines Based on Polynomial Chaos”, ACES Journal, vol. 35, no. 12, pp. 1556–1566, Dec. 2020.

Issue

2020: Vol 35 Iss 12

Section

Articles