Acoustic chemometric at-line characterization for monitoring particle size fractions in pneumatically conveyed biomass

Felicia Nkem Ihunegbo*, Claas Wagner, Kim H. Esbensen, Maths Halstensen

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Reliable on-line/at-line prediction of particle size fractions of biomass material is a process monitoring concern owing to inherent variation in particle size and difficulty in sampling of pneumatically ducted biomass material. A feasibility study on application of acoustic chemometrics for at-line prediction of size fractions of biomass material has been performed, with all models subjected to independent test set validation. This study serves as a platform for at-line characterization of biomass samples from a sampling device extracting biomass samples from pneumatic conveying systems (based on theory of sampling). A prestudy using complex biomass/plastic pellets mixtures was used to test reliability and robustness of the experimental setup. Promising prediction results were achieved (slope, relative root mean square error of prediction (RMSEPrel), and correlation coefficient (r2) were 1.08, 24.94%, and 0.90, respectively). The same experimental setup was adapted for quantitative prediction of coarse versus fine biomass mixtures (the main objective) with satisfactory results; slope = 0.96, r2 = 0.97, RMSEP(rel) = 11%. A case study was also performed showing the adverse effect of using nonrepresentative coarse versus fine biomass samples for calibration. It is concluded that acoustic chemometrics is a viable technique for at-line prediction of size fractions of representative biomass materials.

Original languageEnglish
JournalParticulate Science and Technology
Volume32
Issue number1
Pages (from-to)70-79
Number of pages10
ISSN0272-6351
DOIs
Publication statusPublished - 2 Jan 2014

Keywords

  • Acoustic chemometrics
  • biomass
  • fine-fraction estimation
  • partial least squares regression (PLS-R)
  • process analytical technology (PAT)
  • theory of sampling (TOS)

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