用于超燃流场羟节标记示踪背景抑制的逐步逼近特征窗口滤波

邵珺; 叶景峰; 胡志云; 李景银

doi:10.3788/OPE.20152313.0221

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用于超燃流场羟节标记示踪背景抑制的逐步逼近特征窗口滤波

更新时间：2020-08-13

- 用于超燃流场羟节标记示踪背景抑制的逐步逼近特征窗口滤波
- Progressive approach characteristic window filtering for HTV background suppression in supersonic combustion field
- 光学精密工程 2015年23卷第10z期页码：221-228
- 作者机构：
  
  1. 西北核技术研究所激光与物质相互作用国家重点实验室,陕西西安,710024
  2. 西安交通大学能源与动力学院,陕西西安,710049
- 作者简介：
- 基金信息：
  
  激光与物质相互作用国家重点实验室基金资助项目(No.SKLLIM1306)()
- DOI：10.3788/OPE.20152313.0221
  中图分类号： TP391
- 收稿日期：2015-05-26，
  
  修回日期：2015-06-18，
  
  纸质出版日期：2015-11-14
- 稿件说明：
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邵珺, 叶景峰, 胡志云等. 用于超燃流场羟节标记示踪背景抑制的逐步逼近特征窗口滤波[J]. 光学精密工程, 2015,23(10z): 221-228

SHAO Jun, YE Jing-feng, HU Zhi-yun etc. Progressive approach characteristic window filtering for HTV background suppression in supersonic combustion field[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 221-228
邵珺, 叶景峰, 胡志云等. 用于超燃流场羟节标记示踪背景抑制的逐步逼近特征窗口滤波[J]. 光学精密工程, 2015,23(10z): 221-228 DOI： 10.3788/OPE.20152313.0221.

SHAO Jun, YE Jing-feng, HU Zhi-yun etc. Progressive approach characteristic window filtering for HTV background suppression in supersonic combustion field[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 221-228 DOI： 10.3788/OPE.20152313.0221.

摘要

针对复杂特殊超声燃流场背景下HTV(羟基分子标记示踪)测量精度的提高

提出了逐步逼近特征窗口滤波的背景抑制方法

开展了HTV精细化测量。分析了超音速燃烧流场强背景噪声对HTV测量中图像处理的干扰;在窗口滤波背景抑制的基础上

针对燃流场某些位置流速明显变化造成HTV标记线变形

扭曲、模糊等情况

采取了分区处理并逐步缩小滤波窗口策略

使得每个分区窗口内的标记线图像沿轴向逼近高斯分布;最后结合中值滤波的图像分析方法

获得了一种应用于燃烧流场的HTV背景去除方法。分析讨论了该方法的可行性

确定了实验参数并对实验数据进行处理。对比实验表明:优化处理后提高了图像信噪比

测速精度提高了18.8%

基本满足了HTV技术应用中对信噪比和测量精度的要求。

Abstract

To improve speed measuring accuracy of Hydroxyl Tagging Velocimetry(HTV)in a complex and special supersonic combustion flow field

a progressive approach characteristic window filtering was proposed to do the meticulous measurement. Firstly

the influence of background noise of the supersonic combustion flow field on the image processing of the HTV measurement was analyzed. Then

on the basis of the background suppression by the window filtering

the deformation

distortion

blur of HTV tag line caused by the flow rate change in fuel flow field significantly in some locations were processed by taking the partition processing method

the filter window was gradually narrowed

and the tag line along the width direction of the image within the window for each partition was approached to Gaussian distribution. By combined with image analysis methods in median filtering

the HTV background removal method was achieved for the combustion flow field. The feasibility of the method was analyzed and discussed

and corresponding parameters were determined by the experimental processing. Comparison of experimental data shows that after optimization

the Signal to Noise Ratio(SNR) is greatly improved

the accuracy has increased by 18.8%

which satisfies the system requirements of the HTV application for the SNR and measurement precision.

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Keywords

references

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