It has been shown that much dynamic information is hidden in the pressure fluctuation signals of a gas-solid fluidized bed. Unfortunately, due to the random and capricious nature of this signal, it is hard to realize ...It has been shown that much dynamic information is hidden in the pressure fluctuation signals of a gas-solid fluidized bed. Unfortunately, due to the random and capricious nature of this signal, it is hard to realize reliable analysis using traditional signal processing methods such as statistical analysis or spectral analysis, which is done in Fourier domain. Information in different frequency band can be extracted by using wavelet analysis. On the evidence of the composition of the pressure fluctuation signals, energy of low frequency (ELF) is proposed to show the transition of fluidized regimes from bubbling fluidization to turbulent fluidization. Plots are presented to describe the fluidized bed's evolution to help identify the state of different flow regimes and provide a characteristic curve to identify the fluidized status effectively and reliably.展开更多
A time-frequency signal processing method for two-phase flow through a horizontal Venturi based on adaptive optimal-kernel （AOK） was presented in this paper.First,the collected dynamic differential pressure signal o...A time-frequency signal processing method for two-phase flow through a horizontal Venturi based on adaptive optimal-kernel （AOK） was presented in this paper.First,the collected dynamic differential pressure signal of gas-liquid two-phase flow was preprocessed,and then the AOK theory was used to analyze the dynamic differ-ential pressure signal.The mechanism of two-phase flow was discussed through the time-frequency spectrum.On the condition of steady water flow rate,with the increasing of gas flow rate,the flow pattern changes from bubbly flow to slug flow,then to plug flow,meanwhile,the energy distribution of signal fluctuations show significant change that energy transfer from 15-35 Hz band to 0-8 Hz band;moreover,when the flow pattern is slug flow,there are two wave peaks showed in the time-frequency spectrum.Finally,a number of characteristic variables were defined by using the time-frequency spectrum and the ridge of AOK.When the characteristic variables were visu-ally analyzed,the relationship between different combination of characteristic variables and flow patterns would be gotten.The results show that,this method can explain the law of flow in different flow patterns.And characteristic variables,defined by this method,can get a clear description of the flow information.This method provides a new way for the flow pattern identification,and the percentage of correct prediction is up to 91.11%.展开更多
To ensure efficient operation of metallurgical gas-liquid reactors, the gas bubbles must be uniformly distributed. For high temperature metallurgical reactors, it is impractical and unsafe to carry out visual observat...To ensure efficient operation of metallurgical gas-liquid reactors, the gas bubbles must be uniformly distributed. For high temperature metallurgical reactors, it is impractical and unsafe to carry out visual observations. An air-water model was used to study the relationship between the bubble flow patterns and the pressure fluctuation signals. The fluctuation signals captured in the time domain were transformed into the frequency domain. Various parameters obtained from the transformed data were analysed for their suitability for delineating the bubble flow patterns observed. These parameters and the flow patterns were found to be well-correlated using the gas flow number.展开更多
文摘It has been shown that much dynamic information is hidden in the pressure fluctuation signals of a gas-solid fluidized bed. Unfortunately, due to the random and capricious nature of this signal, it is hard to realize reliable analysis using traditional signal processing methods such as statistical analysis or spectral analysis, which is done in Fourier domain. Information in different frequency band can be extracted by using wavelet analysis. On the evidence of the composition of the pressure fluctuation signals, energy of low frequency (ELF) is proposed to show the transition of fluidized regimes from bubbling fluidization to turbulent fluidization. Plots are presented to describe the fluidized bed's evolution to help identify the state of different flow regimes and provide a characteristic curve to identify the fluidized status effectively and reliably.
基金Supported by the Natural Science Foundation of Zhejiang Province（Y1100842） the Planning Projects of General Administration of Quality Supervision Inspection and Quarantine of the People＇s Republic of China（2006QK23）
文摘A time-frequency signal processing method for two-phase flow through a horizontal Venturi based on adaptive optimal-kernel （AOK） was presented in this paper.First,the collected dynamic differential pressure signal of gas-liquid two-phase flow was preprocessed,and then the AOK theory was used to analyze the dynamic differ-ential pressure signal.The mechanism of two-phase flow was discussed through the time-frequency spectrum.On the condition of steady water flow rate,with the increasing of gas flow rate,the flow pattern changes from bubbly flow to slug flow,then to plug flow,meanwhile,the energy distribution of signal fluctuations show significant change that energy transfer from 15-35 Hz band to 0-8 Hz band;moreover,when the flow pattern is slug flow,there are two wave peaks showed in the time-frequency spectrum.Finally,a number of characteristic variables were defined by using the time-frequency spectrum and the ridge of AOK.When the characteristic variables were visu-ally analyzed,the relationship between different combination of characteristic variables and flow patterns would be gotten.The results show that,this method can explain the law of flow in different flow patterns.And characteristic variables,defined by this method,can get a clear description of the flow information.This method provides a new way for the flow pattern identification,and the percentage of correct prediction is up to 91.11%.
文摘To ensure efficient operation of metallurgical gas-liquid reactors, the gas bubbles must be uniformly distributed. For high temperature metallurgical reactors, it is impractical and unsafe to carry out visual observations. An air-water model was used to study the relationship between the bubble flow patterns and the pressure fluctuation signals. The fluctuation signals captured in the time domain were transformed into the frequency domain. Various parameters obtained from the transformed data were analysed for their suitability for delineating the bubble flow patterns observed. These parameters and the flow patterns were found to be well-correlated using the gas flow number.
