Particle size monitoring in a fluidized bed using pressure fluctuations

Davies, Clive E; Carroll, Alison; Flemmer, Rory C.

doi:10.1016/j.powtec.2007.02.026

Cited by 22 publications

(8 citation statements)

References 7 publications

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“…In particular, the useful information about the operation status and abnormalities in the system can be detected by changes in the average pressure and standard deviation. [25][26][27][28] Therefore, changes in the average pressure according to the sludge feed rate during combustion were determined (Figure 7(a)). Of note, the average pressure at the top of the chamber increased and then decreased after sludge was added and the height of the fluidized bed increased.…”

Section: Pressure Fluctuationmentioning

confidence: 99%

RETRACTED ARTICLE: Combustion characteristics of paper and sewage sludge in a pilot-scale fluidized bed

Chung

2015

Environmental Technology

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This study characterizes the combustion of paper and sewage sludge in a pilot-scale fluidized bed. The highest temperature during combustion within the system was found at the surface of the fluidized bed. Paper sludge containing roughly 59.8% water was burned without auxiliary fuel, but auxiliary fuel was required to incinerate the sewage sludge, which contained about 79.3% water. The stability of operation was monitored based on the average pressure and the standard deviation of pressure fluctuations. The average pressure at the surface of the fluidized bed decreased as the sludge feed rate increased. However, the standard deviation of pressure fluctuations increased as the sludge feed rate increased. Finally, carbon monoxide (CO) emissions decreased as oxygen content increased in the flue gas, and nitrogen oxide (NOx) emissions were also tied with oxygen content.

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Section: Pressure Fluctuationmentioning

confidence: 99%

RETRACTED ARTICLE: Combustion characteristics of paper and sewage sludge in a pilot-scale fluidized bed

Chung

2015

Environmental Technology

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“…Examples of gradual changes are small changes in size of bubbles, number of bubbles and clusters, rise velocity of bubbles and, etc. These changes are important in applications like conditional monitoring of drying process of food or pharmaceutical particles in fluidized beds, detecting gradual particle size changes and monitoring granulation of particles in fluidized beds …”

Section: Resultsmentioning

confidence: 99%

“…Many researchers have shown that pressure fluctuations can be used to detect sharp and gradual changes [5,[22][23][24][25][26] are small changes in size of bubbles, number of bubbles and clusters, rise velocity of bubbles and, etc. These changes are important in applications like conditional monitoring of drying process of food or pharmaceutical particles in fluidized beds, [6,14] detecting gradual particle size changes [27] and monitoring granulation of particles in fluidized beds. [28] Figure 7a and b shows variation of total power of the inherent vibration signal and pressure fluctuations, respectively, against superficial gas velocity at various aspect ratios.…”

Section: Characterization Of Bed Hydrodynamicsmentioning

confidence: 99%

Wall vibration for characterizing fluidization hydrodynamics

et al. 2014

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Wall vibration of a lab‐scale fluidized bed was measured at various gas velocities (0.4–1.4 m/s) and aspect ratios (L/D: 0.5, 1.0 and 1.5), filled with 1500‐μm particles, as well as that of the empty bed. For comparison with the vibration signals, pressure fluctuations inside the bed were simultaneously collected. It was shown that the vibration intensity of the empty bed is significant compared to that of the fluidized bed. Thus, the original vibration signal was decomposed into coherent signal (reflecting the vibration arises from the empty bed) and inherent signal (reflecting the vibration arises from the bed hydrodynamics). The analysis of inherent signal showed that this measuring technique in conjunction with signal components decomposition are robust enough for detecting sharp changes (such as de‐fluidization) in the bed hydrodynamics. The same results were obtained from pressure fluctuations. The vibration signal analysis showed that the de‐fluidization velocity falls within the range of 0.44 and 0.47 m/s and this value is within the range of 0.44 and 0.46 m/s for pressure fluctuations. The frequency range of different length‐scale phenomena was determined. The frequency ranges of macro‐, meso‐, and micro‐structures were, respectively, 0–5, 5–40, and 40–200 Hz for pressure fluctuations. These frequency ranges were 0–9500, 9500–12 000, and 12 000–32 500 Hz for vibration signal. The vibration of bed wall qualitatively reflects the gradual changes in bed hydrodynamics, like changes in the relative energy of bubbles and clusters. However, it was shown that pressure fluctuations are more sensitive to these gradual changes.

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“…It confirms the existence of non-uniform distribution among different measured regions. However, the standard deviation is influenced by many factors, for example the dynamics of the flow, the distribution of bed material, and even particle size (Davies et al, 2008;Qiu et al, 2014;van Ommen et al, 2011). Therefore, the difference of standard deviation values should be applied with great care.…”

Section: Non-uniform Distribution Of Gas-solids Flowmentioning

confidence: 99%