Abstract
Transient signals are universally characterized by a short duration and a broad spectrum which are often present in various phenomena such as sudden acoustic pressure changes, seismic waves, electrical discharges, etc. In order to efficiently monitor the systems where they happen, it is very important that the signals generated by transient phenomena be detected, located and characterized. This significantly helps to better understand their effects in the given application context. This chapter presents new tools derived from the concept of Recurrence Plot Analysis (RPA) and applied on three real applications. Two of the applications concern the detection, localization and characterization of the electrical partial discharges (measured from photovoltaic panels and on electrical cables, respectively). Another application refers to the quantification of the water hammer effect using two acoustic sensors placed on a pipe line.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
J. Gao, Y. Cao, W.W. Tung, J. Hu, Multiscale Analysis of Complex Time Series: Integra-tion of Chaos and Random Fractal Theory, and Beyond (Wiley, New Jersey, 2007)
A. Serbanescu, L. Cernaianu, C. Ivan, New approaches in nonlinear dynamics analysis of complex systems and processes, in International Symposium of Electronics Computers and Artificial Intelligence, Pitesti, 2009
C. Ioana, A. Digulescu, A. Serbanescu, I. Candel, F.-M. Birleanu, in Recent Advances in Non-Stationary Signal Processing Based on the Concept of Recurrence Plot Analysis, Springer Proceedings in Mathematics and Statistics, ed. by M. Marwan et al. Translational Recurrences, pp. 75–93. Cham, Switzerland, 2014
I. Candel, A. Digulescu, A. Serbanescu, E. Sofron, Partial discharge detection in high voltage cables using polyspectra and recurrence plot analysis, in 9th International Conference on Communications (COMM). Bucharest, Romania, 2012
S.A. Boggs, G.C. Stone, Fundamental limitations in the measurement of corona effect and partial discharges, in Ontario Hydro Research, Toronto, Canada IEEE Transactions on Electrical Insulation, vol. EI–17, no.2, (1982), p. 143
A. Digulescu, M. Paun, C. Vasile, T. Petrut, D. Deacu, C. Ioana, R. Tamas, in Electrical Arc Surveillance and Localization System Based on Advanced Signal Processing Techniques IEEE International Energy Conference (ENERGYCON) (Dubrovnik, Croatia, 2014)
C. Strobl, P. Meckler, Arc Faults in photovoltaic systems, in Proceedings of 25th ICEC and 56th IEEE Holm Conference on Electrical Contacts, Charleston, 2010, pp. 216–222
F.M. Birleanu, I. Candel, C. Ioana, C. Gervaise, A. Serbanescu, G. Serban, A vector approach to transient signal processing, in The 11th Conference on Information Science, Signal Processing and their Applications, Montreal, Canada, 3–5 July 2012
N. Marwan, J. Kurths, Nonlinear analysis of bivariate data with cross recurrence plots. Phys. Lett. A 302, 299–307 (2002)
F. Popescu, F. Enache, I.C. Vizitiu, P. Ciotîrnae, Recurrence plot analysis for characterization of appliance load signature, in 10th International Conference on Communications, Bucharest, Romania, 2014
H. Yang, Multiscale recurrence quantification analysis of spatial cardiac vectorcardiogram (VCG) signals. IEEE Trans. Biomed. Eng. 58(2), 339–347 (2011)
Y. Chen, H. Yang, Multiscale recurrence analysis of long-term nonlinear and nonstationary time series. Chaos, Solitons Fractals 45(7), 978–987 (2012)
G.M. Ramirez Avila, A. Gapelyuk, N. Marwan, H. Stepan, J. Kurths, T. Walther, N. Wessel, Classifying healthy women and preeclamptic patients from cardiovascular data using recurrence and complex network methods, Auton. Neurosci. Basic Clin. 178(1–2), 103–110 (2013)
C.L. Webber Jr., J.P. Zbilut, in Recurrence Quantification Analysis of Nonlinear Dynamical Systems, ed. by M.A. Riley, G.C. Van Orden. Tutorials in Contemporary Nonlinear Methods for the Behavioral Sciences Web Book (National Science Foundation, U.S., 2005), pp. 26–94
J.P. Zbilut, C.L. Webber Jr., in Recurrence Quantification Analysis, ed. by M. Akay. Wiley Encyclopedia of Biomedical Engineering, Wiley, 2006
J. Fan, Q. Yao, Nonlinear Time Series: Nonparametric and Parametric Methods (Springer, New York, 2005)
J.C. Sprott, Chaos and Time-Series Analysis (Oxford University Press, New York, 2003)
J. Gao, Y. Cao, L. Gu, J. Harris, J. Principe, Detection of weak transitions in signal dynamics using recurrence time statistics. Phys. Lett. A 317, 64–72 (2003)
J. Gao, Y. Cao, W.W. Tung, J. Hu, Multiscale Analysis of Complex Time Series: Integration of Chaos and Random Fractal Theory, and Beyond (Wiley, New Jersey, 2007)
N. Marwan, S. Schinkel, J. Kurts, Recurrence plots 25 years later—Gaining confidence in dynamic transitions. Europhys. Lett. 101, 20007 (2013)
N. Marwan, M.C. Romano, M. Thiel, J. Kurths, Recurrence plots for the analysis of complex systems. Phys. Rep. 438(5–6), 237–329 (2007)
H. Kantz, T. Schreiber, Nonlinear Time Series Analysis (University Press, Cambridge, 1997)
J.P. Eckmann, S.O. Kamphorst, D. Ruelle, Recurrence plots of dynamical systems. Europhys. Lett. 5(9), 973–977 (1987)
F.-M. Birleanu, C. Ioana, C. Gervaise, J. Chanussot, A. Serbanescu, G. Serban, On the recurrence plot analysis method behaviour under scaling transform, in 2011 IEEE Workshop on Statistical Signal Processing (SSP2011) (2011), pp. 789–792
S. Mallat, S. Zhong, Characterization of signals from multiscale edges. IEEE Trans. Pattern Anal. Mach. Intell. 14(7), 710–732 (1992)
S. Mallat, A Wavelet Tour of Signal Processing, 2nd edn, Academic Press, 1999
S. Mallat, A Theory for Multiresolution Signal Decomposition: The Wavelet Representation. IEEE Trans. Pattern Anal. Mach. Intell. 11(7), 674–693 (1989)
M. Misiti, Y. Misiti, G. Oppenheim, J-M. Poggi, Wavelets Toolbox Users Guide, the MathWorks, Wavelet Toolbox, for use with MATLAB (2000)
C. Bernard, T. Petrut, G. Vasile, C. Ioana, Multi-lag phase space representations for transient signal characterization, in Europeean Signal Processing Conference, Portugal, 2014, pp. 2115–2119
M. Casdagli, S. Eubank, J. Doyne Farmer, J. Gibson, State space reconstruction in the presence of noise. Phys. D 51(1–3), 52–98 (1991)
E.B. Wylie, L.V. Streeter, Fluid Transients in Systems (Prentice-Hall Inc., 1993)
F.E. Hachem, A.J. Schleiss, Effect of drop in pipe wall stiffness on water-hammer speed and attenuation. J. Hydraul. Res. 50(2) (2012)
N.H.C. Hwang, R.J. Houghtalen, Fundamentals of Hydraulic Engineering Systems, 3rd edn (Prentice Hall Inc., 1996)
Acknowledgement
This work has been supported in part by the Dema’Loc project funded by Institut Carnot “Energies du futur” and by the “Smart Hydro Monitoring” project (Rhone Alpes “Tenerrdis” and “Minalogic” research clusters).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Digulescu, A., Murgan, I., Ioana, C., Candel, I., Serbanescu, A. (2016). Applications of Transient Signal Analysis Using the Concept of Recurrence Plot Analysis. In: Webber, Jr., C., Ioana, C., Marwan, N. (eds) Recurrence Plots and Their Quantifications: Expanding Horizons. Springer Proceedings in Physics, vol 180. Springer, Cham. https://doi.org/10.1007/978-3-319-29922-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-29922-8_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-29921-1
Online ISBN: 978-3-319-29922-8
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)