基于红外成像的乙烯气体泄漏检测

王建平; 李俊山; 杨亚威; 孙胜永; 王蕊

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基于红外成像的乙烯气体泄漏检测

成像技术与图像处理 | 更新时间：2020-08-12

- 基于红外成像的乙烯气体泄漏检测
- Ethylenegas leaking detection based on infrared imaging
- 液晶与显示 2014年29卷第4期页码：623-628
- 作者机构：
  
  1. 第二炮兵工程大学信息工程系,陕西西安,710025
  2. 第二炮兵工程大学一系,陕西西安,710025
- 作者简介：
- 基金信息：
  
  国家自然科学基金（No.61175120）()
- DOI：
  中图分类号： TP391
- 收稿日期：2013-12-25，
  
  修回日期：2014-01-20，
  
  纸质出版日期：2014-08-05
- 稿件说明：
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王建平, 李俊山, 杨亚威, 孙胜永, 王蕊. 基于红外成像的乙烯气体泄漏检测[J]. 液晶与显示, 2014,29(4): 623-628

WANG Jian-ping, LI Jun-shan, YANG Ya-wei, SUN Sheng-yong, WANG Rui. Ethylenegas leaking detection based on infrared imaging[J]. , 2014,29(4): 623-628
王建平, 李俊山, 杨亚威, 孙胜永, 王蕊. 基于红外成像的乙烯气体泄漏检测[J]. 液晶与显示, 2014,29(4): 623-628 DOI：

WANG Jian-ping, LI Jun-shan, YANG Ya-wei, SUN Sheng-yong, WANG Rui. Ethylenegas leaking detection based on infrared imaging[J]. , 2014,29(4): 623-628 DOI：

摘要

针对传统乙烯气体泄漏检测和定位方法存在效率低、检测范围小和实时性差等问题，提出了一种基于红外成像的泄漏检测方法。该方法利用红外摄像机获取乙烯生产车间内各设备工作时的红外视频图像，将其转化为灰度图像序列后，利用逻辑运算融合多幅帧间差分和背景差分后的图像信息，并利用形态学滤波消除噪声干扰，最终获得气体泄漏疑似区域的准确位置。实验结果表明，该方法高效、准确且具备实时性，能够获得完整、清晰的泄漏疑似区域，实现了无色气体泄露区域的初步定位。

Abstract

Becasue the traditional ethylene gas leak detection and localization method has the problem of low efficiency

small detection area and poor real-time performance

a leakage detection method based on infrared imaging was proposed. The method uses infrared camera to acquire infrared video image of ethylene production workshop when equipments are working

and converts it to grayscale image sequence. The image information after multi frame diffe rence and background difference was cumulated together through the use of logic operation

and noise interference was eliminated through morphological filtering. At last

the accurate position of suspected gas leak area was obtained. The experimental results indicate that this method is efficient

accurate and real-time

and can obtain a complete

clear leakage suspected areas.The purpose of preliminary localization of the colorless gas leakage area has been achieved.

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references

李俊山,杨威,张雄美. 红外图像处理、分析与融合 [M]. 北京:科学出版社,2009. Li J S,Yang W,Zhang X M. Infrared Image Processing,Analysis and Fusion [M].Beijing:Science Press,2009. (in Chinese)[2] 吴君钦,刘昊,罗勇. 静态背景下的运动目标检测算法[J]. 液晶与显示,2012,27(5):682-686. Wu J Q,Liu H,Luo Y. Algorithm of moving object detection in static background [J]. Chinese Journal of Liquid Crystals and Displays,2012,27(5):682-686. (in Chinese)[3] Yuan F N. A fast accumulative motion orientation model based on integral image for video smoke detection [J]. Pattern Recognition Letters,2008(29):925-932.[4] 胡以静,李政访,胡跃明. 基于光流的运动分析理论及应用[J]. 计算机测量与控制,2007,15(2):219-221. Hu Y J,Li Z F,Hu Y M. Theories and applications of motion analysis based on optical flow [J]. Computer Measurement & Control,2007,15(2):219-221. (in Chinese)[5] 李林,卢焕章,肖山竹,等. 基于分级自适应背景差分的运动目标检测[J]. 电视技术,2013,37(7):164-166. Li L,Lu H Z,Xiao S Z,et al. Moving object detection based on differentiated Self-adaptive background difference [J]. Video Engineering,2013,37(7):164-166.(in Chinese)[6] 刘火平,孟维平,宋立维,等. 红外图像序列中不均匀背景消除新方法[J]. 液晶与显示,2012,27(4):539-544. Liu H P,Meng W P,Song L W,et al. New method for eliminating non-uniformity background of IR images [J]. Chinese Journal of Liquid Crystals and Displays,2012,27(4):539-544. (in Chinese)[7] 帅师,周平,汪亚明,等. 基于小波的实时烟雾检测[J]. 计算机应用研究,2007,24(3):309-311. Shuai S,Zhou P,Wang Y M,et al. Wavelet based real-time smoke detection [J]. Application Research of Computers,2007,24(3):309-311.(in Chinese)[8] 夏永泉,宁少辉,李卫丽. 一种简单有效的运动目标检测算法[J]. 计算机测量与控制,2011,19(2):356-358. Xia Y Q,Ning S H,Li W L. A simple and effective moving objects detection algorithm [J]. Computer Measurement & Control,2011,19(2):356-358. (in Chinese)[9] Ho C C,Chen M C. Nighttime fire smoke detection system based on machine vision[J]. International Journal of Precision and Manufacturing,2012,13(8):1369-1376.[10] 靳永亮,王延杰,丁南南,等. 改进的红外弱小目标检测方法[J]. 液晶与显示,2011,26(4):555-560. Jin Y L,Wang Y J,Ding N N,et al. Improved method for small infrared target detection [J]. Chinese Journal of Liquid Crystals and Displays,2011,26(4):555-560. (in Chinese)[11] 邱家涛,李玉山,初秀琴,等. 稳定运动物体视频的特征方法[J]. 光学精密工程,2012,20(10):2300-2307. Qiu J T,Li Y S,Chu X Q,et al. Feature-based approach for stabilizing videos moving objects [J]. Opt. Precision Eng.,2012,20(10):2300-2307. (in Chinese)[12] 穆治亚,魏仲慧,何昕,等. 采用稀疏表示的红外图像自适应杂波抑制[J]. 光学精密工程,2013,21(7):1850-1857. Mu Z Y,Wei Z H,He X,et al. Adaptive clutter suppression of infrared images by using sparse representation [J]. Opt. Precision Eng.,2013,21(7):1850-1857. (in Chinese)

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