Synergistic Event-SVE Imaging for Quantitative Propellant Combustion Diagnostics

TL;DR

This paper introduces a novel imaging system combining HDR and neuromorphic event cameras for real-time, 3D, microsecond-resolution diagnostics of high-energy propellant combustion, overcoming traditional imaging challenges caused by smoke and high dynamic range.

Contribution

A closed-loop hybrid imaging system integrating SVE and neuromorphic cameras with smoke-aware fusion for accurate, real-time combustion diagnostics under challenging conditions.

Findings

Achieved maximum calibration error of 0.56% in 3D measurements.

Successfully captured transient separation events in propellant combustion.

Produced multimodal particle size statistics from high-speed imaging.

Abstract

Real-time monitoring of high-energy propellant combustion is difficult. Extreme high dynamic range (HDR), microsecond-scale particle motion, and heavy smoke often occur together. These conditions drive saturation, motion blur, and unstable particle extraction in conventional imaging. We present a closed-loop Event--SVE measurement system that couples a spatially variant exposure (SVE) camera with a stereo pair of neuromorphic event cameras. The SVE branch produces HDR maps with an explicit smoke-aware fusion strategy. A multi-cue smoke-likelihood map is used to separate particle emission from smoke scattering, yielding calibrated intensity maps for downstream analysis. The resulting HDR maps also provide the absolute-intensity reference missing in event cameras. This reference is used to suppress smoke-driven event artifacts and to improve particle-state discrimination. Based on the cleaned event observations, a stereo event-based 3D pipeline estimates separation height and equivalent particle size through feature extraction and triangulation (maximum calibration error 0.56%). Experiments on boron-based propellants show multimodal equivalent-radius statistics. The system also captures fast separation transients that are difficult to observe with conventional sensors. Overall, the proposed framework provides a practical, calibration-consistent route to microsecond-resolved 3D combustion measurement under smoke-obscured HDR conditions.