Characterisation of Flow Intermittency and Coherent Structures in a Gas-Solid Circulating Fluidised Bed through Electrostatic Sensing

Flow intermittency and coherent structures are important hydrodynamic phenomena in a gas–solid circulating fluidized bed (CFB). In this work, an electrostatic measurement system based on arc-shaped sensing electrodes is designed and implemented on a CFB test rig. Cross correlation, statistical analysis, wavelet transform, and probability density function (PDF) are applied to the electrostatic signal processing, providing a comprehensive description of the solids velocity, solids holdup, flow intermittency, and coherent structure behaviors. A conditional sampling method is used to extract the coherent structure signals from the electrostatic signals. By comparing the extended self-similarity (ESS) scaling law curves before and after the extraction, the effects of coherent structures on the flow intermittency are further confirmed. Experimental results have demonstrated that the electrostatic signals contain important information about the intermittent hydrodynamic behaviors in a CFB, and the analysis of electrostatic signals through appropriate methods results in an in-depth understanding of the fluidization process

Non-intrusive Characterisation of Particle Cluster Behaviours in a Riser through Electrostatic and Vibration Sensing

Particle clusters are important mesoscale flow structures in gas-solid circulating fluidised beds (CFBs). An electrostatic sensing system and two accelerometers are installed on the riser of a CFB test rig to collect signals simultaneously. Cross correlation, Hilbert-Huang transform (HHT), V-statistic analysis, and wavelet transform are applied for signal identification and cluster characterisation near the wall. Solids velocities are obtained through cross correlation. Non-stationary and non-linear characteristics are distinctly exhibited in the Hilbert spectra of the electrostatic and vibration signals, and the cluster dynamic behaviours are represented by the energy distributions of the signal intrinsic mode functions (IMFs). The cycle feature and main cycle frequency of cluster motion are characterised through V-statistic analysis of the vibration signals. Consistent characteristic information about particle clusters is extracted from the electrostatic and vibration signals. Furthermore, a cluster identification criterion for electrostatic signals is proposed, including a fixed and a wavelet dynamic thresholds, based on which the cluster time fraction, average cluster duration time, cluster frequency, and average cluster vertical size are quantified. Especially, the cluster frequency obtained from this criterion agrees well with that from the aforementioned V-statistic analysis. Results from this 3 work provide a new non-intrusive approach to the characterisation of cluster dynamic behaviours and their effects on the flow field

Monitoring of particle motions in gas-solid fluidized beds by electrostatic sensors

Gas-solid fluidized beds are widely applied in numerous industrial processes. Particle motions significantly affect the performance of fluidized bed reactors and the characterization of particle movements is therefore important for fluidization quality monitoring and scale-up of reactors. Electrostatic charge signals in the fluidized bed contain much dynamic information on particle motions, which are poorly understood and explored. In this work, correlation velocities of Geldart B and D particles were measured, analyzed and compared by induced electrostatic sensors combined with cross-correlation method in the fluidized bed. The results indicated that the average correlation velocity of particle clouds increased and the normalized probability density distributions of correlation velocities broadened when the superficial gas velocity increased in the dense-phase region. Both upward and downward correlation velocities could be acquired in the dynamic bed level region. Under the same excess gas velocity, the average correlation velocity of Geldart D particles was significantly smaller than that of Geldart B particles, which was caused by the smaller bubble sizes caused by the dominant bubble split over coalescence and less volume of gas forming bubbles for Geldart D particles. The experimental results verified the reliability and repeatability of particle correlation velocity measurement by induced electrostatic sensors in the gas-solid fluidized bed, which provides definite potential in monitoring of particle motions

Non-intrusive Characterisation of Particle Cluster Behaviours in a Riser through Electrostatic and Vibration Sensing

Particle clusters are important mesoscale flow structures in gas-solid circulating fluidised beds (CFBs). An electrostatic sensing system and two accelerometers are installed on the riser of a CFB test rig to collect signals simultaneously. Cross correlation, Hilbert-Huang transform (HHT), V-statistic analysis, and wavelet transform are applied for signal identification and cluster characterisation near the wall. Solids velocities are obtained through cross correlation. Non-stationary and non-linear characteristics are distinctly exhibited in the Hilbert spectra of the electrostatic and vibration signals, and the cluster dynamic behaviours are represented by the energy distributions of the signal intrinsic mode functions (IMFs). The cycle feature and main cycle frequency of cluster motion are characterised through V-statistic analysis of the vibration signals. Consistent characteristic information about particle clusters is extracted from the electrostatic and vibration signals. Furthermore, a cluster identification criterion for electrostatic signals is proposed, including a fixed and a wavelet dynamic thresholds, based on which the cluster time fraction, average cluster duration time, cluster frequency, and average cluster vertical size are quantified. Especially, the cluster frequency obtained from this criterion agrees well with that from the aforementioned V-statistic analysis. Results from this 3 work provide a new non-intrusive approach to the characterisation of cluster dynamic behaviours and their effects on the flow field

Non-intrusive measurement and hydrodynamics characterization of gas–solid fluidized beds: a review

Gas-solid fluidization is a well-established technique to suspend or transport particles and has been applied in a variety of industrial processes. Nevertheless, our knowledge of fluidization hydrodynamics is still limited for the design, scale-up and operation optimization of fluidized bed reactors. It is therefore essential to characterize the two-phase flow behaviours in gas-solid fluidized beds and monitor the fluidization processes for control and optimization. A range of non-intrusive techniques have been developed or proposed for measuring the fluidization dynamic parameters and monitoring the flow status without disturbing or distorting the flow fields. This paper presents a comprehensive review of the non-intrusive measurement techniques and the current state of knowledge and experience in the characterization and monitoring of gas-solid fluidized beds. These techniques are classified into six main categories as per sensing principles, electrostatic, acoustic emission and vibration, visualization, particle tracking, laser Doppler anemometry and phase Doppler anemometry as well as pressure fluctuation methods. Trend and future developments in this field are also discussed