Three-Dimensional Bubbly Flow Measurement Using Event-based Vision Sensor Cameras

Abstract

A three-camera Event-Based Vision Sensor (EVS) system is employed to perform three-dimensional measurements of bubble motion, morphology, and bubble{\DH}bubble interactions. The multi-EVS configuration mitigates the absence of direct depth information inherent to binary event-based imaging while preserving key advantages, including high temporal resolution, low latency, and reduced data throughput. The experimental configuration consisted of an octagonal tank equipped with a controlled particle release mechanism and an air diffuser. Camera synchronization and pulsed LED illumination were achieved using a dedicated signal generator and driver circuitry, while calibration was performed using pulsed-illumination recordings of a target acquired at multiple depths. A comprehensive, inhouse computational framework was developed to process the event data for three-dimensional motion trajectory reconstruction. The validation of the developed tracking framework followed a rigorous multi-stage pipeline to ensure reconstruction fidelity. The framework was initially benchmarked against synthetic rendering cases of increasing kinematic complexity to evaluate 3D trajectory reconstruction accuracy under controlled conditions, achieving sub-millimeter global accuracy with root-mean-square error (RMSE) values ranging from 0.015 to 0.36 mm. Following numerical validation, physical baseline experiments were conducted using precisely manufactured particle releases through both a gated chamber and a single-particle claw opening mechanism. Subsequently, dynamic bubble plumes generated via multiple inlets across various compressed air flow rates were evaluated. The EVS framework successfully resolved dense bubble-bubble interactions, producing smooth, physically consistent three-dimensional trajectories across all tested conditions. Quantitative results showed strong agreement, yielding an overall velocity consistency exceeding 97% between conventional centroid tracking and independent velocity estimates derived from continuous-illumination event streaks. Overall, this methodology demonstrates a robust framework for high-speed volumetric tracking and bubble flow measurement. However, event oversaturation remains a key hardware limitation in ultra-dense regimes, as oversaturation in a single camera can cause system desynchronization.