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Application of poly-harmonic signals to eddy-current metal detectors and to advanced classification of metals

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A limited ability to discriminate between different materials is the fundamental problem with all conventional eddy-current-based metal detectors. This paper presents the use, evaluation and classification of nontraditional excitation signals for eddy-current metal detectors to improve their detection and discrimination ability. The presented multi-frequency excitation signals are as follows: a step sweep sine wave, a linear frequency sweep and sin(x)/x signals. All signals are evaluated in the frequency domain. Amplitude and phase spectra and polar graphs of the detector output signal are used for classification and discrimination of the tested objects. Four different classifiers are presented. The classification results obtained with the use of poly-harmonic signals are compared with those obtained with a classical single-tone method. Multi-frequency signals provide more detailed information, due to the response function - the frequency characteristic of a detected object, than standard single-tone methods. Based on the measurements and analysis, a metal object can be better distinguished than when using a single-tone method.
Rocznik
Strony
387--402
Opis fizyczny
Bibliogr. 29 poz., rys., tab., wykr., wzory
Twórcy
autor
  • Czech Technical University in Prague, Department of Measurement, Prague 6, Technická 2, 16627, Czech Republic
  • Czech Technical University in Prague, Department of Measurement, Prague 6, Technická 2, 16627, Czech Republic
autor
  • Czech Technical University in Prague, Department of Measurement, Prague 6, Technická 2, 16627, Czech Republic
Bibliografia
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  • [2] Nováček, P., Roháč, J., Šimánek, J., Ripka, P. (2013). Metal detector signal imprints of detected objects. IEEE Trans. Magn., 49(1), 69-72.
  • [3] Connor, M., Scott, D.D. (1998). Metal Detector Use in Archaeology: An Introduction. Hist. Archaeol., 34(4), 76-85.
  • [4] Brooks, J.W. (2000). The Detection of Buried Non-Metallic Anti-Personnel Land Mines. The University of Alabama in Huntsville.
  • [5] Guelle, D., Smith, A., Lewis, A., Bloodworth, T. (2003). Metal detector handbook for humanitarian demining. Luxembourg: Luxembourg: Office for Official Publications of the European Communities.
  • [6] Bielecki, Z., Janucki, J., Kawalec, A., Mikolajczyk, J., Palka, N., Pasternak, M., Pustelny, T., Stacewicz, T., Wojtas, J. (2012). Sensors and systems for the detection of explosive devices - An overview. Metrol. Meas. Syst., 19(1), 3-28.
  • [7] Candy, B. (2010). Metal Detector Basics and Theory, Minleab. Available: http://www.minelab.com/_files/f/11043/kba_metal_detector_basics_&_theory.pdf.
  • [8] Bruschini, C. (2002). A Multidisciplinary Analysis of Frequency Domain Metal Detectors for Humanitarian Demining. Vrije Universiteit Brussel, 2002.
  • [9] Svatoš, J., Vedral, J., Fexa, P. (2011). Metal detector excited by frequency-swept signal. Metrol. Meas. Syst., 18(1), 57-68.
  • [10] Gao, J., et al. (2009). Simulation analysis of multi-frequency eddy current sensor impedance property. 2009 International Conference on Information Engineering and Computer Science, Wuhan, 1-4.
  • [11] Brojboiu, M., Popa, I.C., Ivanov, V. (2016). Numerical modeling of an eddy current sensor used in a metal separation device. 2016 International Conference on Applied and Theoretical Electricity, Craiova, 1-6.
  • [12] OToole, M., Karimian, N., Peyton, A.J. (2018). Classification of Non-ferrous Metals using Magnetic Induction Spectroscopy. IEEE Transactions on Industrial Informatics, 3203, 1-9.
  • [13] Grant, F.S., West, G.F. (1965). Interpretation Theory in Applied Geophysics . New York: McGrawHill.
  • [14] Svatos, J., Vedral, J. (2012). The Usage of Frequency Swept Signals for Metal Detection. IEEE Trans. Magn., 48(4), 1501-1504.
  • [15] Svatos, J., Vedral, J., Novacek, P. (2012). Metal object detection and discrimination using Sinc signal. 13th Biennial Baltic Electronics Conference, 307-310.
  • [16] Siegenfeld, A. (2003). ATMID - Technologie und Schaltungsbeschreibung. Schiebel.
  • [17] Schiebel, (2002). ATMID Maintenance Manual. Schiebel.
  • [18] Bruschini, C. (2004). On the low-frequency EMI response of coincident loops over a conductive and permeable soil and corresponding background reduction schemes. IEEE Trans. Geosci. Remote Sens., 42(8), 1706-1719.
  • [19] Matlab Pattern Recognition Toolbox. Delft University of Technology. http://prtools.org. (Sep. 2014).
  • [20] Svatoš, J., Vedral, J., Fexa, P. (2009). Methods for economical test of dynamic parameters adcs. Metrol. Meas. Syst., 16(1), 161-170.
  • [21] Kowalewski, M., Lentka, G. (2013). Fast High-Impedance Spectroscopy Method Using Sinc Signal Excitation. Metrol. Meas. Syst., 20(4), 645-654.
  • [22] Vedral, J., Fexa, P. (2012). DAC testing using impulse signals. Metrol. Meas. Syst., 19(1), 105-114.
  • [23] van der Heijden, F., Duin, R.P.W., de Ridder, D., Tax, D.M.J. (2004). Classification, Parameter Estimation and State Estimation. John Wiley & Sons, Ltd.
  • [24] Xiao, L., Deng, L. (2010). A geometric perspective of large-margin training of Gaussian models. IEEE Signal Process. Mag., 27(6), 118-23.
  • [25] Beleites, C., Neugebauer, U., Bocklitz, T., Krafft, C., Popp, J. (2013). Sample size planning for classification models. Anal. Chim. Acta, 760, 25-33.
  • [26] Kaski, J., Peltonen, S. (2011). Dimensionality reduction for data visualization. IEEE Signal Process. Mag. , 28(1), 100-104.
  • [27] Das, Y., McFee, J., Chesney, R. (1985). Determination of Depth of Shallowly Buried Objects by Electromagnetic Induction. IEEE Trans. Geosci. Remote Sens., GE-23(1), 60-66.
  • [28] Das, Y., McFee, J., Toews, J., Stuart, G.C. (1990). Analysis of an electromagnetic induction detector for real-time location of buried objects. IEEE Trans. Geosci. Remote Sens., 28(3), 278-288.
  • [29] Svatoš, J. (2015). Advanced Instrumentation for Polyharmonic Metal Detectors (Doctoral dissertation), CTU in Prague, Prague, Czechia, https://dspace.cvut.cz/handle/10467/61084.
Uwagi
EN
1. This research was supported by the SGS16/171/OHK3/2T/13 grant provided by the Grant Agency of the Czech Technical University in Prague.
PL
2. Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8ca9ead8-8b01-4662-ab1c-35e20d4f322d
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