Processing time-series of randomly forced self-oscillators: the example of beer bottle whistling

Abstract

We present a model-based, output-only parameter identification method for self-sustained oscillators forced by dynamic noise, which we illustrate experimentally with an aeroacoustic setup: a turbulent jet impinging a beer bottle and producing a whistling tone in a finite range of jet angles and velocities. Given a low-order model of the system, the identification analyzes stationary time series of a single observable: acoustic pressure fluctuations in the bottle. As this observable exhibits the characteristics of weakly non-linear self-oscillations, we choose as a minimal model the Van der Pol (VdP) oscillator: a linear acoustic oscillator (bottle) subject to stochastic forcing and non-linear deterministic forcing (turbulent jet). Although very simple, the VdP oscillator driven by random noise proves to be a sufficient phenomenological description of the aeroacoustic limit cycle for model-based linear growth rate identification. The associated stochastic amplitude equation allows us to describe the stochastic fluctuations of the acoustic amplitude resulting from a competition between (i) linear growth rate from the coherent unsteady vortex force, (ii) random forcing from the turbulence, (iii) non-linear saturation of the coherent flapping of the jet. Finally, the associated adjoint Fokker-Planck equation reveals the deterministic potential well and the stochastic forcing intensity governing these random fluctuations. Additional experiments with an external control validate the identification results. We observe that different operating conditions can yield similar statistics but different dynamics, showing that the identification method can disentangle deterministic and stochastic effects in systems forced stochastically. This output-only identification approach can be used in a wide range of phenomena exhibiting stationary self-sustained oscillations in the presence of random forcing.

arXiv comment17 pages, 9 figures, to appear in the Journal of Sound and Vibration

References in corpus (11)

• Discovering governing equations from data: Sparse identification of nonlinear dynamical systems
• How to quantify deterministic and random influences on the statistics of the foreign exchange market
• On the proper reconstruction of complex dynamical systems spoilt by strong measurement noise
• On the universality of small scale turbulence
• Estimation of Kramers-Moyal coefficients at low sampling rates
• Turbulent-Like Behavior of Seismic Time Series
• Output-only parameter identification of a colored-noise-driven Van der Pol oscillator -- Thermoacoustic instabilities as an example
• Effect of wall thermal inertia upon transient thermoacoustic dynamics of a swirl-stabilized flame
• Reconstruction of dynamical equations for traffic flow
• Finite sampling interval effects in Kramers-Moyal analysis
• Quantifying acoustic damping using flame chemiluminescence

Cited by in corpus (5)

• Nonlinear stochastic modeling with Langevin regression
• Stochastic modelling of a noise driven global instability in a turbulent swirling jet
• A real-time digital twin of azimuthal thermoacoustic instabilities
• A numerically efficient output-only system-identification framework for stochastically forced self-sustained oscillators
• Steady State Statistics of Emergent Patterns in a Ring of Oscillators