A hybrid of ensemble empirical mode decomposition and empirical mode decomposition (EEMD-EMD) is introduced to diagnose the valve-slap vibration signal,which is relative to the dominant combustion knock vibration sign...A hybrid of ensemble empirical mode decomposition and empirical mode decomposition (EEMD-EMD) is introduced to diagnose the valve-slap vibration signal,which is relative to the dominant combustion knock vibration signal given out by a diesel engine around the top dead center (TDC).The time-frequency representations of intrinsic mode functions (IMFs) decomposed by EEMD-EMD are obtained by adaptive generalized S transform (AGST).A type 493 diesel engine was used for the experiment,and the result indicates that the valve-slap of the diesel engine is serious,and the vibration frequencies are higher than the combustion knock.With EEMD-EMD-AGST approach,the valve-slap can be identified by the vibration analysis of the diesel engine.展开更多
Aesthetic anthropology is a new paradigm of the modem aesthetic research of China. Professor Wang Jie and his research team put forward the concept of local aesthetic experience in the process of research. The concept...Aesthetic anthropology is a new paradigm of the modem aesthetic research of China. Professor Wang Jie and his research team put forward the concept of local aesthetic experience in the process of research. The concept is used to summarize and refer to the existing way and existing form of non-westem mainstream culture in aesthetic dimension under global context. Local aesthetic experience converges many important problems in the research on aesthetic anthropology展开更多
Using the high-speed camera the time sequences of the classical flow patterns of horizontal gas-liquid pipe flow are recorded, from which the average gray-scale values of single-frame images are extracted. Thus obtain...Using the high-speed camera the time sequences of the classical flow patterns of horizontal gas-liquid pipe flow are recorded, from which the average gray-scale values of single-frame images are extracted. Thus obtained gray-scale time series is decomposed by the Empirical Mode Decomposition (EMD) method, the various scales of the signals are processed by Hurst exponent method, and then the dual-fractal characteristics are obtained. The scattered bubble and the bubble cluster theories are applied to the evolution analysis of two-phase flow patterns. At the same time the various signals are checked in the chaotic recursion chart by which the two typical characteristics (diagonal average length and Shannon entropy) are obtained. Resulting term of these properties, the dynamic characteristics of gas-liquid two-phase flow patterns are quantitatively analyzed. The results show that the evolution paths of gas-liquid two-phase flow patterns can be well characterized by the integrated analysis on the basis of the gray-scale time series of flowing images from EMD, Hurst exponents and Recurrence Plot (RP). In the middle frequency section (2nd, 3rd, 4th scales), three flow patterns decomposed by the EMD exhibit dual fractal characteristics which represent the dynamic features of bubble cluster, single bubble, slug bubble and scattered bubble. According to the change of diagonal average lengths and recursive Shannon entropy characteristic value, the structure deterministic of the slug flow is better than the other two patterns. After the decomposition by EMD the slug flow and the mist flow in the high frequency section have obvious peaks. Anyway, it is an effective way to understand and characterize the dynamic characteristics of two-phase flow patterns using the multi-scale non-linear analysis method based on image gray-scale fluctuation signals.展开更多
This paper focuses on how to extract physically meaningful information from climate data,with emphases placed on adaptive and local analysis. It is argued that many traditional statistical analysis methods with rigoro...This paper focuses on how to extract physically meaningful information from climate data,with emphases placed on adaptive and local analysis. It is argued that many traditional statistical analysis methods with rigorous mathematical footing may not be efficient in extracting essential physical information from climate data;rather,adaptive and local analysis methods that agree well with fundamental physical principles are more capable of capturing key information of climate data. To illustrate the improved power of adaptive and local analysis of climate data,we also introduce briefly the empirical mode decomposition and its later developments.展开更多
基金Supported by National Key Technology Research and Development Program of China (No.2011BAE22B05)
文摘A hybrid of ensemble empirical mode decomposition and empirical mode decomposition (EEMD-EMD) is introduced to diagnose the valve-slap vibration signal,which is relative to the dominant combustion knock vibration signal given out by a diesel engine around the top dead center (TDC).The time-frequency representations of intrinsic mode functions (IMFs) decomposed by EEMD-EMD are obtained by adaptive generalized S transform (AGST).A type 493 diesel engine was used for the experiment,and the result indicates that the valve-slap of the diesel engine is serious,and the vibration frequencies are higher than the combustion knock.With EEMD-EMD-AGST approach,the valve-slap can be identified by the vibration analysis of the diesel engine.
文摘Aesthetic anthropology is a new paradigm of the modem aesthetic research of China. Professor Wang Jie and his research team put forward the concept of local aesthetic experience in the process of research. The concept is used to summarize and refer to the existing way and existing form of non-westem mainstream culture in aesthetic dimension under global context. Local aesthetic experience converges many important problems in the research on aesthetic anthropology
基金Supported by the National Natural Science Foundation of China （50976018） the Natural Science Foundation of JilinProvince （20101562）
文摘Using the high-speed camera the time sequences of the classical flow patterns of horizontal gas-liquid pipe flow are recorded, from which the average gray-scale values of single-frame images are extracted. Thus obtained gray-scale time series is decomposed by the Empirical Mode Decomposition (EMD) method, the various scales of the signals are processed by Hurst exponent method, and then the dual-fractal characteristics are obtained. The scattered bubble and the bubble cluster theories are applied to the evolution analysis of two-phase flow patterns. At the same time the various signals are checked in the chaotic recursion chart by which the two typical characteristics (diagonal average length and Shannon entropy) are obtained. Resulting term of these properties, the dynamic characteristics of gas-liquid two-phase flow patterns are quantitatively analyzed. The results show that the evolution paths of gas-liquid two-phase flow patterns can be well characterized by the integrated analysis on the basis of the gray-scale time series of flowing images from EMD, Hurst exponents and Recurrence Plot (RP). In the middle frequency section (2nd, 3rd, 4th scales), three flow patterns decomposed by the EMD exhibit dual fractal characteristics which represent the dynamic features of bubble cluster, single bubble, slug bubble and scattered bubble. According to the change of diagonal average lengths and recursive Shannon entropy characteristic value, the structure deterministic of the slug flow is better than the other two patterns. After the decomposition by EMD the slug flow and the mist flow in the high frequency section have obvious peaks. Anyway, it is an effective way to understand and characterize the dynamic characteristics of two-phase flow patterns using the multi-scale non-linear analysis method based on image gray-scale fluctuation signals.
基金US National Science Foundation Grant(No.AGS-1139479)
文摘This paper focuses on how to extract physically meaningful information from climate data,with emphases placed on adaptive and local analysis. It is argued that many traditional statistical analysis methods with rigorous mathematical footing may not be efficient in extracting essential physical information from climate data;rather,adaptive and local analysis methods that agree well with fundamental physical principles are more capable of capturing key information of climate data. To illustrate the improved power of adaptive and local analysis of climate data,we also introduce briefly the empirical mode decomposition and its later developments.
