Published July 2019 | Version v1
Journal article

Probabilistic response of an electromagnetic transducer with nonlinear magnetic coupling under bounded noise excitation

  • 1. Laboratory of Mechanics, Department of Physics, Faculty of sciences, University of Yaounde I, P.O. Box 812, Yaounde (Cameroon)

Description

The response in terms of probability density function (PDF) of a vibration transducer, whose mechanical and electrical parts are respectively subjected to stochastic force and bounded noise excitation, is revisited in this report, both analytically and numerically. We discuss the phenomenological transitions exhibited by the PDFs as the noisy excitations parameters evolve and analyze the dependence of the mean output power (MOP) on the parameters of noisy excitations. In the weak parameter regime, using the stochastic averaging method, we show that the MOP of the transducer increases with the intensity of the electrical oscillator additive noise; however, it is independent of the mechanical oscillator additive noise intensity. Conversely, in the hard coupling regime, we show, by Monte Carlo simulations, that the PDFs and the MOP are also affected by the mechanical oscillator additive noise parameters. In particular, we find that the system exhibits the stochastic P-bifurcation only for large damping and coupling parameters. The simulations and the approximate analytical treatment are consistent in the weak parameter regime, as expected.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.chaos.2019.04.030

Additional details

Identifiers

DOI
10.1016/j.chaos.2019.04.030;
PII
S0960077919301390;

Publishing Information

Journal Title
Chaos, Solitons and Fractals
Journal Volume
124
Journal Page Range
p. 26-35
ISSN
0960-0779

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54120713
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Descriptors DEI
APPROXIMATIONS; COMPUTERIZED SIMULATION; MONTE CARLO METHOD; NONLINEAR PROBLEMS; OSCILLATORS; PROBABILISTIC ESTIMATION; PROBABILITY DENSITY FUNCTIONS; STOCHASTIC PROCESSES
Descriptors DEC
CALCULATION METHODS; ELECTRONIC EQUIPMENT; EQUIPMENT; FUNCTIONS; SIMULATION

Optional Information

Copyright
Copyright (c) 2019 Elsevier Ltd. All rights reserved.