摘要
火焰燃烧状态的正确识别与控制是维持稳定燃烧的前提条件,现存识别方法智能化化水平低、主观性强、燃烧状态识别困难,为了提高识别的准确性,提出了一种基于张量分解的火焰图像识别方法。该方法根据RGB颜色空间模型中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,而且能够更大程度上保留信息,提高图像识别精度,并与理论值进行比较,计算后平均误差在0.5%内,准确率达到99.5%以上,为连续火焰图像的识别提供了有效的方法。
The correct recognition of flame combustion state is a prerequisite for maintaining stable combustion.The existing methods have low intellectualization level,strong subjectivity and difficulty in the recognition of combustion state.Therefore,in order to improve the accuracy of recognition,a flame image recognition method based on tensor decomposition is proposed in this paper.The distribution characteristics of the flame pixels in the RGB color space model are used to construct a three-dimensional tensor for each channel image,and on this basis,the parallel factor analysis method is used to reduce the dimension and extract the relevant features of the flame image.The analysis results show that compared with the traditional single flame image region recognition and feature fusion method,the flame image tensor is decomposed directly,which not only can find the relationship between the flame image sequence,but also can retain more information to improve the accuracy of image recognition.Compared with the theoretical value,the average error after calculation is within 0.5%,and the accuracy is more than 99.5%.It provides an effective method for continuous flame image recognition.
作者
郭旭凯
李海广
龚志军
GUO Xukai;LI Haiguang;GONG Zhijun(School of Energy and Environment,Inner Mongolia University of Science&Tecnology,Baotou 014000,China)
出处
《重庆理工大学学报（自然科学）》
北大核心
2023年第8期326-333,共8页
Journal of Chongqing University of Technology：Natural Science
基金
国家自然科学基金项目(51666015)。
关键词
张量分解
图像识别
特征提取
平行因子分析
tensor decomposition
image recognition
feature extraction
parallel factor analysis
