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Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
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Nonlinear damping and quasi-linear modelling.

S J Elliott1, M Ghandchi Tehrani2, R S Langley3

  • 1Institute of Sound and Vibration Research, University of Southampton, Southampton SO17 1BJ, UK s.j.elliott@soton.ac.uk.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|August 26, 2015
PubMed
Summary
This summary is machine-generated.

Nonlinear damping significantly impacts mechanical systems. This study models nonlinear damping using an equivalent linear system, simplifying analysis for various excitations and providing physical insight.

Keywords:
nonlinear dampingquasi-linearstatistical linearization

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Area of Science:

  • Mechanical Engineering
  • Nonlinear Dynamics
  • Vibration Analysis

Background:

  • Nonlinear damping is a primary source of nonlinearity in many mechanical systems.
  • Analysis of these systems is often simplified by representing them with a quasi-linear model.
  • The nonlinear damping force is assumed to be proportional to the nth power of velocity.

Purpose of the Study:

  • To review diverse sources of nonlinear damping.
  • To analyze systems with nonlinear damping under sinusoidal and random excitation.
  • To present methods for calculating system response and equivalent linear damping parameters.

Main Methods:

  • Harmonic balance method (related to describing function method) for sinusoidal excitation.
  • Equivalent linear damper calculation for random excitation, often requiring iterative methods.
  • Analysis of power dissipation for validation of the quasi-linear model.

Main Results:

  • System response to sinusoidal excitation is often nearly sinusoidal.
  • Equivalent linear damper values depend on system response and require iterative calculation for random excitation.
  • Power dissipation of the equivalent linear damper accurately matches that of the nonlinear damper.

Conclusions:

  • The quasi-linear model provides a theoretically sound and physically insightful approach to analyzing systems with nonlinear damping.
  • This modeling simplifies the analysis of complex mechanical systems.
  • Applications include microspeakers, vibration isolation, energy harvesting, and the cochlea's mechanical response.