Jin Ningde

Multi-Scale Permutation Entropy: A Complexity Measure for Discriminating Two-Phase Flow Dynamics

We propose an improved permutation entropy method, i.e., multi-scale permutation entropy (MSPE), for discriminating two-phase flow dynamics. We first take the signals from different typical dynamical systems as examples to demonstrate the effectiveness of the methods. In particular, we compute the MSPE values of sinusoidal signal, logistic, Lorenz and Chen chaotic signals and their signals with white Gaussian noise added. We find that the MSPE method can be an effective tool for analyzing the time series with distinct dynamics. We finally calculate the multi-scale permutation entropy and rate of MSPE from 66 groups of conductance fluctuating signals and find that these two measures can be used to identify different flow patterns and further explore dynamical characteristics of gas-liquid flow patterns. These results suggest that the MSPE can potentially be a useful tool for revealing the dynamical complexity of two-phase flow on different scales.

Complex network analysis in inclined oil–water two-phase flow

Complex networks have established themselves in recent years as being particularly suitable and flexible for representing and modelling many complex natural and artificial systems. Oil–water two-phase flow is one of the most complex systems. In this paper, we use complex networks to study the inclined oil–water two-phase flow. Two different complex network construction methods are proposed to build two types of networks, i.e. the flow pattern complex network (FPCN) and fluid dynamic complex network (FDCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K-means clustering, useful and interesting results are found which can be used for identifying three inclined oil–water flow patterns. To investigate the dynamic characteristics of the inclined oil–water two-phase flow, we construct 48 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of the inclined oil–water two-phase flow. In this paper, from a new perspective, we not only introduce a complex network theory into the study of the oil–water two-phase flow but also indicate that the complex network may be a powerful tool for exploring nonlinear time series in practice.

Multi-scale complexity entropy causality plane: An intrinsic measure for indicating two-phase flow structures

We extend the complexity entropy causality plane (CECP) to propose a multi-scale complexity entropy causality plane (MS-CECP) and further use the proposed method to discriminate the deterministic characteristics of different oil-in-water flows. We first take several typical time series for example to investigate the characteristic of the MS-CECP and find that the MS-CECP not only describes the continuous loss of dynamical structure with the increase of scale, but also reflects the determinacy of the system. Then we calculate the MS-CECP for the conductance fluctuating signals measured from oil—water two-phase flow loop test facility. The results indicate that the MS-CECP could be an intrinsic measure for indicating oil-in-water two-phase flow structures.

Bubble Image Segmentation of Gas/Liquid Two-Phase Flow Based on Improved Canny Operator

Image segmentation is the foundation of multi-flow high speed video analysis. Based on improved canny operator, we provide a method to bubble gas/liquid two-phase flow image segmentation, which takes the more gray distribution information into account, uses gauss sigma smooth filter to maintain edges and eliminate noise, then by non-maximum control of grads and lag-threshold process, the clear bubble edge image is obtained. The method is very effective for the analysis and recognition of bubble multi-flow.

Application of chaotic recurrence plot analysis to identification of oil/water two-phase flow patterns

Recurrence quantification analysis method was employed to study the identification of oil/water two-phase flow patterns. The results showed recurrence plot appeared different textures for the transitional oil/water two phase flow patterns, and was special for different flow pattern. That indicated the texture of recurrence plot was sensitive to the changes of oil/water two flow patterns, and the recurrence quantification analysis is a useful diagnosis tool in identifying of two phase flow patterns.

Attractor comparison analysis for characterizing vertical upward oil—gas—water three-phase flow

We investigate the dynamic characteristics of oil—gas—water three-phase flow in terms of chaotic attractor comparison. In particular, we extract a statistic to characterize the dynamical difference in attractor probability distribution. We first take time series from Logistic chaotic system with different parameters as examples to demonstrate the effectiveness of the method. Then we use this method to investigate the experimental signals from oil—gas—water three-phase flow. The results indicate that the extracted statistic is very sensitive to the change of flow parameters and can gain a quantitatively insight into the dynamic characteristics of different flow patterns.

Multi-Scale Time Asymmetry for Detecting the Breakage of Slug Flow Structure

We first employ multi-scale time asymmetry (MSA) to analyze typical chaotic signals from Schuster maps and indicate that the MSA method can characterize the distinct time asymmetry of chaotic time series. Then we propose a modified MSA method, i.e., multi-scale weighted time asymmetry, and a novel time asymmetry index to investigate fractal Brownian motion signals and demonstrate its effects on discriminating between fractal signals with different Hurst exponents. Considering that the dynamic behavior of slug flow exhibits chaotic features, we apply the MSA method to analyze experimental signals from a gas-liquid two-phase flow and find that slug flow presents a unique time asymmetric structure. In addition, we further explore the mechanism leading to the formation of time asymmetry in terms of adaptive optimal kernel time-frequency representation. The results suggest that the MSA method can be a useful tool for detecting the complex flow structure underlying a gas-liquid two-phase flow.

Improved Local Binary Pattern Based Gas/Liquid Two-Phase Flow Regimes Analysis

A method to analyze gas/liquid two-phase flow regimes based on the Improved Local Binary Patterns (ILBP) is proposed in this paper. The method constructs Texture Pattern Matrix (TPM) based on the ILBP, and five statistic features are extracted from the TPM for the flow regimes analysis. Experimental results demonstrate that the proposed method improves performance both in efficiency and effectiveness in the analysis of flow regimes. It can provide reliable reference for other indirect measurement information used to analyze flow patterns by right of its own physical objectivity.

Chinese text watermarking based on occlusive components

Based on the idea of the mathematical expression of a Chinese character and its automatic generation, a novel watermarking technique for Chinese text is presented in this paper. The proposed method embeds the watermarking signals into some Chinese characters with occlusive components by adjusting the size of the closed rectangular regions in these components, so it is totally based on the content. Experiments show that the proposed text watermarking technique is more robust and transparent than the counterpart methods. It will play an important role in protecting Chinese information security such as authenticity, integrality, confidentiality over the Internet.Based on the idea of the mathematical expression of a Chinese character and its automatic generation, a novel watermarking technique for Chinese text is presented in this paper. The proposed method embeds the watermarking signals into some Chinese characters with occlusive components by adjusting the size of the closed rectangular regions in these components, so it is totally based on the content. Experiments show that the proposed text watermarking technique is more robust and transparent than the counterpart methods. It will play an important role in protecting Chinese information security such as authenticity, integrality, confidentiality over the Internet.

Characterization of oil/water two-phase flow patterns based on symbolic time series analysis

The flow patterns of oil/water two-phase flow in vertical upward pipes have been characterized by the analysis of symbolic time series based on the conductance fluctuating signals. It is shown that the temporal irreversibility and chi-square statistics have little changes with oil-in-water flow pattern variations for flow conditions of 61% /spl les/ K/sub W/ /spl les/ 91% and are sensitive to transitional flow pattern variations of K/sub W/ = 51%. The characterization of flow patterns is strongly supported by the flow map of our previous study based on Kinematic wave theory. The symbolic time series analysis can be a new tool for flow pattern identification in vertical upward oil/water two-phase flow pipes.