火焰图像的张量平行因子分析识别法  

Tensor parallel factor analysis and recognition methodsof flame images

作　　者：郭旭凯 李海广[1] 龚志军[1] GUO Xukai;LI Haiguang;GONG Zhijun(School of Energy and Environment,Inner Mongolia University of Science and Technology,Baotou 014000,China)

机构地区：[1]内蒙古科技大学能源与环境学院,内蒙古包头014000

出　　处：《重庆理工大学学报（自然科学）》2023年第6期317-324,共8页Journal of Chongqing University of Technology：Natural Science

基　　金：国家自然科学基金项目(51666015);内蒙古自然科学基金项目(2020MS05045)。

摘　　要：正确识别火焰燃烧状态是维持稳定燃烧的前提条件,而现存方法智能化水平低、主观性强、燃烧状态识别困难。为提高识别的准确性,提出一种基于张量分解的火焰图像识别方法。根据RGB颜色空间模型中的火焰像素的分布特点,将图像序列升维构造成三维张量,并在此基础上使用平行因子分析法对火焰图像进行识别。分析结果表明:相对于传统单张火焰图像的区域识别和特征融合方法,对火焰图像构成张量直接进行分解不仅能找到火焰图像序列之间的联系,而且能更大程度上保留信息,提高图像识别精度。与理论值进行比较分析后发现,采用新方法后的平均误差在0.5%内,准确率达到99.5%以上,可为连续火焰图像的识别提供参考。The correct recognition of flame combustion state is a prerequisite for maintaining stable combustion.However,the existing methods have a low intellectual level,strong subjectivity and difficulty in the recognition of the combustion state.Therefore,in order to improve the accuracy of recognition,this paper proposes a flame image recognition method based on tensor decomposition.According to the distribution characteristics of the flame pixels in the RGB color space model,the ascending dimension of the image sequence is constructed into a three-dimensional tensor,and,on this basis,the parallel factor analysis method is used to identify the flame images.The analysis results show that,compared with the traditional regional recognition and feature fusion method of single flame images,the flame image tensor is decomposed directly,which not only finds the relationship between the flame image sequences,but also retains more information to a greater extent to improve the accuracy of image recognition.Compared with the theoretical value,the average error of the new method is within 0.5%,and the accuracy is more than 99.5%.It provides reference for continuous flame image recognition.

关 键 词：张量分解 图像识别 特征提取 平行因子分析 

分 类 号：TK16[动力工程及工程热物理—热能工程]