摘要
应用一种将视频信号的每一帧图像分块成小的区域,每相邻两帧图像的相邻两区域进行灰度相似值计算,组成时间序列的新方法,对时间序列分别求取最大李亚普诺夫指数,组成最大李亚普诺夫指数矩阵。利用李亚普诺夫指数的特征将气液两相流视频划分为混沌特性不同的区域,分别采用0、1分布图谱以及三维图谱,对其从整体以及细节两部分进行分析。结合最大李亚普诺夫指数矩阵的分形盒维数与香农熵两个特征,对气液两相流型流动机制进行辅助分析。实验结果表明,由于气液两相流视频图像的背景与变化相界面具有强度不同的混沌特性,图像小区域分块灰度相似值序列结合最大李亚普诺夫指数的方法能够区别出不同流型的流动特性,是一种有效的分析气液两相流图像信号的新方法。
Each frame of the video signal was divided into smaller areas by a new method for extracting time series. The gray similar values of each two adjacent frame were calculated, then formed the time series. The largest Lyapunov exponents of time series were respectively extracted, and the largest Lyapunov exponent matrix was composed. The videos of gas-liquid two-flow patterns were divided into different chaotic characteristic areas by the characteristics of Lyapunov exponent. Then they were respectively analyzed from overall and details by zero and one distribution map and 3D map. The flowing mechanism of gas-liquid two-phase flow was analyzed, combined the fractal box dimension and Shannon entropy of the largest Lyapunov exponent matrix. The results show that the method of the gray similar values series of small areas combined extracting the largest Lyapunov exponent can distinguish the flowing characteristics of different flow patterns; the background and changed phase interface of gas-liquid two-phased flow video have chaotic charateristics of different intensity, which is an effective method for analyzing the gasliquid two-phase flow signals.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2011年第20期88-94,共7页
Proceedings of the CSEE
基金
国家自然科学基金项目(50976018)
吉林省自然科学基金项目(20101562)~~
关键词
气液两相流
图像序列
最大李亚普诺夫指数
分形盒维数
熵
gas-liquid two-phase flow
image squence
the largest Lyapunov exponent
fractal box dimension
Shannon
