机器学习增强的固体燃料燃烧多粒子追踪
Machine learning enhanced multi-particle tracking in solid fuel combustion
AI总结：
针对高粒子数密度燃烧场景，本文结合 YOLO、RT-DETR、SAHI 与 SORT 实现多粒子检测追踪，揭示 PND 对粒子速度及群燃烧行为的主导作用。
摘要：
粒子测速在固体燃料燃烧研究中至关重要，但在高粒子数密度（PND）燃烧场景下准确检测和追踪粒子仍具挑战性。本研究推进了用于固体粒子精确速度测量的机器学习方法。为此，对在层流反应器中燃烧的高挥发分烟煤粒子开展了激光成像实验。采用时间分辨米氏散射对粒子位置进行成像。研究使用并基准比较了多种检测方法，包括传统的斑点检测以及基于机器学习（ML）的 You Only Look Once（YOLO）和 Realtime Detection Transformer（RT-DETR）。粒子追踪采用 Simple Online Realtime Tracking（SORT）算法完成。结果表明，在低 PND 数据上训练的机器学习模型具备预测高 PND 数据的能力。Slicing Aided Hyper Inference（SAHI）算法对于提升所用模型的性能十分重要。通过评估速度统计量发现，平均粒子速度随 PND 增加而降低，主要原因是粒子间相互作用增强。粒子动力学与先前研究中观察到的燃烧区位置密切相关。因此，PND 被认为是影响高挥发分固体燃料粒子群燃烧行为的主导因素。
英文摘要：
Particle velocimetry is essential in solid fuel combustion studies, however, the accurate detection and tracking of particles in high Particle Number Density (PND) combustion scenario remain challenging. The current study advances the machine-learning approaches for precise velocity measurements of solid particles. For this, laser imaging experiments were performed for high-volatile bituminous coal particles burning in a laminar flow reactor. Particle positions were imaged using time-resolved Mie scattering. Various detection methods, including conventional blob detection and Machine Learning (ML) based You Only Look Once (YOLO) and Realtime Detection Transformer (RT-DETR) were employed and bench marked.~Particle tracking was performed using the Simple Online Realtime Tracking (SORT) algorithm. The results demonstrated the capability of machine learning models trained on low-PND data for prediction of high-PND data. Slicing Aided Hyper Inference (SAHI) algorithm is important for the better performance of the used models. By evaluating the velocity statistics, it is found that the mean particle velocity decreases with increasing PND, primarily due to stronger particle interactions. The particle dynamics are closely related to the position of combustion zone observed in the previous study. Thus, PND is considered as the dominant factor for the particle group combustion behavior of high-volatile solid fuels.
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