Investigating nonlinear dynamics in a mass-spring oscillator using real-time computer vision

Abstract

We present a low-cost laboratory for investigating the dynamics of a vertical mass-spring oscillator using real-time computer vision. The proposed system automatically tracks the motion of the oscillating mass with a smartphone camera, displays the displacement in real time, and exports the recorded data for further analysis. Representative experiments include damped oscillations, oscillation period measurements, spectral analysis, and phase-space reconstruction. The system also enables the investigation of nonlinear phenomena, including harmonic generation, frequency mixing, and energy exchange between coupled oscillation modes. Owing to its low cost, ease of construction, and automated data acquisition, the proposed apparatus extends the traditional mass-spring experiment to include topics in nonlinear dynamics that are rarely explored in undergraduate laboratories.