Characterization of gas–solid fluidized bed hydrodynamics by vibration signature analysis

Statistical diagnosis of a gas–solid fluidized bed using Electrical Capacitance Tomography

“…The influence of the small particles in the mix 2 powder can also be observe in Figure 6 as it produced larger skewness values than when just the 750−1000µm powder was used. Azizpour et al (2011) did experiments with acoustic signals and pressure measurements in fluidized beds filled with sand. They stated that the skewness will decrease as the average particle size is increased ).…”

“…The Geldart B powders had a flat curve while the Geldart D particles had a clear minimum point. According to Azizpour et al (2011) this minimum point in the kurtosis values is an indication of the change of the meso-structure of the bed and is not necessarily an indication of regime transition. As mentioned before, Lin and Wey (2004) stated that decreasing skewness values mainly occurs higher up in a fluidized bed when the bubbles have a long enough residence time in the bed to coalesce and form larger bubbles and thus large pressure fluctuations.…”

Early detection of agglomeration in a polyethylene fluidized bed at high temperature and pressure by vibration signature analysis

“…Analyzing the vibration signatures has been used for detecting minimum fluidization velocity and transition from bubbling to slugging in gas-solid fluidized beds (Abbasi et al, 2009), determining regime transition (Azizpour et al, 2011;Shiea et al, 2013) and characterizing the hydrodynamics of fluidized beds (Abbasi et al, 2010;Sheikhi et al, 2012).…”

“…Standard deviation of signals from fluidized beds have been used to identify regime transitions (Bi et al, 2000;Azizpour et al, 2011), determine the minimum fluidization velocity (Sobrino et al, 2008;Abbasi et al, 2009) and detect defluidization in industrial fluidized-bed reactors as an on-line tool . Standard deviation of time series x i shows the deviation of the distribution from a normal distribution in time interval of N and is defined as follows:…”

Non-intrusive characterisation of particle cluster behaviours in a riser through electrostatic and vibration sensing

“…In addition, accelerometers are desirable non-intrusive tools that enable the measurement of flow-induced vibrations experienced by fluidised beds and hence the characterisation of flow structure behaviours [4]. Accelerometers have been used for monitoring the bed fluidity [20], detecting the agglomerate occurrence [20], and characterising the particle motion [21] and the bulk and bubble dynamics [22][23][24][25]. As bubbles and particle clusters are both classified as mesoscale flow structures [22,26], accelerometers should also be applicable to cluster behaviour characterisation.…”