Application of dynamic image analysis to the optical characterisation of fibrous bulk material--颗粒学报PARTICUOLOGY

Lunewski, J., & Schmidt, E. (2024). Application of dynamic image analysis to the optical characterisation of fibrous bulk material. Particuology, 90, 51-60. https://doi.org/10.1016/j.partic.2023.11.015

Application of dynamic image analysis to the optical characterisation of fibrous bulk material

Johannes Lunewski^*, Eberhard Schmidt

Institute of Particle Technology, University of Wuppertal, Germany

10.1016/j.partic.2023.11.015

Volume 90, July 2024, Pages 51-60

Received 23 May 2023, Revised 8 November 2023, Accepted 14 November 2023, Available online 25 November 2023, Version of Record 19 December 2023.

E-mail: lunewski@uni-wuppertal.de

Highlights

• Pre-dispersion step to singularise interlocking fibres.

• Dynamic image analysis to determine projection area, fibre length and diameter.

• Flow cell boundaries during wet dispersion minimise fibre orientation influence.

• Semi-automatic evaluation by ImageJ if automated image processing algorithms fail.

Abstract

Dynamic image analysis provides an automated evaluation method to determine the size and shape of multiple particles. This method represents a common application for ordinary bulk material. The latest draft of ISO 13322–2:2021 describes the state of the art, but lacks instructions for handling fibrous bulk material. Interlocking fibres complicate the measurement conditions and require a disentanglement of fibrous samples during a pre-dispersion step. A further error source includes the fibre orientation inside the measurement zone of the device. If the thresholding algorithm fails to differentiate between the fibre projection area and the background, a subsequent image optimisation solves the problem. This article addresses the mentioned problems by analysing cotton cellulose and polyacrylonitrile fibres. Besides the execution of a pre-dispersion step, the experiments compare the discrepancies between dry and wet dispersion. Here, the software packages PAQXOS and ImageJ perform the image evaluation. In this case, the wet dispersion setup with a subsequent image evaluation by ImageJ provides comprehensible results.

Graphical abstract

Keywords

Bootstrap method; Dynamic image analysis; Fibre diameter; Fibre length distribution; Natural fibres; Synthetic fibres

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