基于量子滤光及跟踪算法的火箭发动机尾焰粒子测速方法研究

Research on velocity measurement method of rocket engine tail flame particle based on quantum filter and tracking algorithm

粒子喷射速度的测速是火箭发动机结构改进设计极其重要的依据。但是由于火箭发动机尾焰喷射速度快、背景辐射强,传统的滤光器件(滤光片)与运动目标检测算法无法适用。针对上述问题,本文采取新型量子滤光技术,利用量子高信噪比,低背景噪声的特点,以原子滤光器为核心,将超窄带量子滤光技术应用到粒子图像测速法(Particle Image Ve⁃locimetry,PIV)中,组成量子滤光PIV系统,滤光带宽可窄至GHz量级。同时基于量子滤光PIV系统提出了一种新的基于图像灰度互相关的虚拟粒子图像示踪算法,该算法通过对虚拟粒子的标记跟踪而表征实际粒子的运动轨迹,达到测量粒子速度的目的。经外场试验表明:量子滤光技术抑制复杂背景干扰强,相较于传统滤光器件信噪比提高了30 dB,滤光效果明显;该算法准确性高,粒子测速误差低于0.5 m/s,计算测量精度优于0.06%。同时,相关系统已经在国家相关研究单位获得应用。

Measuring the ejected particle’s velocity is crucial for rocket motor development design.Be⁃cause of the intense light background radiation of the rocket motor flame,the conventional filter device and moving object detection algorithm cannot be used.To address these problems,this study presents a novel quantum filter technology.Considering the characteristics of quantum high signal-to-noise ratio and low background noise,taking the atomic filter as the core,the ultra-narrow band quantum filter technology is applied to particle image velocimetry(PIV),which makes up the quantum filter PIV system.The filter bandwidth is on the order of magnitude of MHz to GHz.Simultaneously,based on the quantum filter PIV system,a new virtual particle image tracer algorithm based on image gray cross-correlation is proposed.This algorithm obtains the trajectory of particle motion by tracking and marking to characterize the particle motion in the flow field.The results indicate that the quantum filter technology exhibited strong suppres⁃sion of complex background interference,the signal-to-noise ratio was improved by 30 dB compared with the conventional filter device,and the filtering effect was significant.The algorithm had high accuracy,the particle velocity measurement error was less than 0.5 m/s,and the calculation measurement accuracy was better than 0.06%.The relevant system had already been used in national research institutes.