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Measurement of Biomass Moisture Content Distribution in a Fluidised Bed Dryer Through Electrostatic Sensing and Digital Imaging

Qi, Bojian, Yan, Yong, Zhang, Wenbiao, Wang, Xueyao (2021) Measurement of Biomass Moisture Content Distribution in a Fluidised Bed Dryer Through Electrostatic Sensing and Digital Imaging. Powder Technology, 388 . pp. 380-392. ISSN 0032-5910. (doi:10.1016/j.powtec.2021.04.096) (KAR id:87926)

Abstract

Accurate moisture content distribution measurement of biomass in a fluidised bed dryer is desirable to explore the complex drying characteristics, continuously monitor the operation and maximise the efficiency of the drying process. In this paper, electrostatic sensing and digital imaging techniques are combined to measure the moisture content distribution of biomass in a laboratory-scale fluidised bed dryer. The proposed method determines the biomass velocity by the cross correlation of the electrostatic sensor signals and establishes a measurement model that relates the root mean square of the sensor signals, the biomass velocity and the moisture content. Experimental tests are conducted under different inlet air velocities and temperatures to assess the electrostatic measurement method and investigate the moisture content distribution. The results demonstrate that the proposed method is capable of measuring the moisture content with a relative error within ±15%. Moreover, an optical digital imaging unit is used to record the positions of bubbles and the biomass in the fluidised bed. The mass transfer at the interface between the air and the biomass is determined by fusing the information from the moisture content and bubble positions.

Item Type: Article
DOI/Identification number: 10.1016/j.powtec.2021.04.096
Uncontrolled keywords: Fluidised bed dryer; moisture content distribution; biomass; electrostatic sensing; digital imaging; mass transfer
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA165 Engineering instruments, meters etc. Industrial instrumentation
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Yong Yan
Date Deposited: 05 May 2021 13:53 UTC
Last Modified: 02 May 2022 23:00 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/87926 (The current URI for this page, for reference purposes)

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