The experimental signals analysis for bubbly oil-in-water flow using multi-scale weighted-permutation entropy
The experimental signals analysis for bubbly oil-in-water flow using multi-scale weighted-permutation entropy
复制标题
基于多尺度加权排列熵的气泡水包油流实验信号分析
DOI：
10.1016/j.physa.2014.09.058
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发表时间：
2015-01-01
影响因子：
3.3
通讯作者：
Sun, Bin
中科院分区：
文献类型：
--
作者：
Chen, Xin;Jin, Ning-De;Sun, Bin
首次将联合收割机多尺度方法（MS）与加权置换熵（WPE）相结合，对混沌、噪声和分形时间序列进行分析，发现多尺度置换熵（MSPE）不能区分不同的非线性时间序列，并且在噪声较大的情况下表现出较好的鲁棒性。然后，我们应用MSWPE从垂直向上的水包油两相流实验的信号进行分析。研究结果表明，MSWPE的变化率可以表征流型的转变，多尺度加权排列熵可以表征油水两相流复杂性的差异。(C)2014爱思唯尔有限公司版权所有。
We firstly combine multi-scale method (MS) and weighted-permutation entropy (WPE) to analyze chaotic, noisy, and fractal time series, and find that MSWPE can distinguish different nonlinear time series and exhibit a better robustness in the presence of higher levels of noise, a task that multi-scale permutation entropy (MSPE) fails to work. We then apply MSWPE to analyze the signals from vertical upward oil-in-water two-phase flow experiments. Our results suggest that the change rate of MSWPE enables to characterize the transition of flow patterns and multi-scale weighted-permutation entropy allows indicating the discrepancy of complexity of oil-in-water two-phase flow. (C) 2014 Elsevier B.V. All rights reserved.