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Determining the Coupling Source on a Set of Oscillators from Experimental Data

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  • Juan Carlos Jauregui-Correa
  • Carlos S. López-Cajun
  • Mihir Sen

Abstract

Complex systems are a broad concept that comprises many disciplines, including engineering systems. Regardless of their particular behavior, complex systems share similar behaviors, such as synchronization. This paper presents different techniques for determining the source of coupling when a set of oscillators synchronize. It is possible to identify the location and time variations of the coupling by applying a combination of analytical techniques, namely, the source of synchronization. For this purpose, the analysis of experimental data from a complex mechanical system is presented. The experiment consisted in placing a 24-bladed rotor under an airflow. The vibratory motion of the blades was recorded with accelerometers, and the resulting information was analyzed with four techniques: correlation coefficients, Kuramoto parameter, cross-correlation functions, and the recurrence plot. The measurements clearly show the existence of frequencies due to the foreground components and the internal interaction between them due to the background components (coupling).

Suggested Citation

  • Juan Carlos Jauregui-Correa & Carlos S. López-Cajun & Mihir Sen, 2017. "Determining the Coupling Source on a Set of Oscillators from Experimental Data," Complexity, Hindawi, vol. 2017, pages 1-10, May.
    • Handle: RePEc:hin:complx:8017138
    DOI: 10.1155/2017/8017138
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    References listed on IDEAS

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    1. Ray, Anirban & Roy Chowdhury, A. & Ghosh, Dibakar, 2013. "Effect of noise on chaos synchronization in time-delayed systems: Numerical and experimental observations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 4837-4849.
    2. Kim, Sang-Yoon & Lim, Woochang, 2015. "Thermodynamic order parameters and statistical–mechanical measures for characterization of the burst and spike synchronizations of bursting neurons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 544-559.
    3. F. Ghasemi & J. Peinke & M. Sahimi & M. R. Rahimi Tabar, 2005. "Regeneration of stochastic processes: an inverse method," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 47(3), pages 411-415, October.
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