Automated fouling image analysis

Abstract: Fouling is a widely observed phenomenon during the operation of heat exchangers throughout different process industries and results in a significant loss of performance. Therefore, several research projects focus on different strategies to either mitigate, prevent or remove occurring deposits which requires both a profound knowledge about the underlying mechanisms, e.g. eposition of fouling layers, structural, mechanical and chemical characteristics, and a resilient method to detect fouling layers. To improve the understanding of relevant phenomena, especially for protein deposits, fouling was investigated in an optically accessible micro-structured heat exchanger. Occurring protein fouling layers were stained by supplying a blue dye into the heat exchanger channels and photographed with a DSLR for further evaluation. The image processing tool automatically detects the relevant image section, straightens it and creates a binary image, which contains colored and uncolored pixels for occupied and clean areas of the image section. Further details about the used setup can be found in Spiegel et al. 2022 (https://doi.org/10.1016/j.fbp.2022.05.010).

Data and Resources

This dataset has no data

Cite this as

Spiegel, Christoph (2023). Dataset: Automated fouling image analysis. https://doi.org/10.24355/dbbs.084-202212191320-0

DOI retrieved: 2023

Additional Info

Field Value
Imported on January 8, 2025
Last update January 8, 2025
License CC-BY-NC-SA-4.0
Source https://doi.org/10.24355/dbbs.084-202212191320-0
Author Spiegel, Christoph
Given Name Christoph
Family Name Spiegel
Source Creation 2023
Publication Year 2023
Resource Type Software - software
Subject Areas
Name: Python, Image, Fouling, Heat Exchanger

Name: 005

Related Identifiers
Identifier: https://leopard.tu-braunschweig.de/receive/dbbs_mods_00071805?XSL.Transformer=mods
Type: URL
Relation: HasMetadata