Automatic Evaluation of Atomization Effect of Fiber Materials Based On Image Recognition

In order to improve the efficiency and accuracy of the evaluation of the atomization effect of the filament dosing material, image recognition technology combined with a high-resolution industrial camera was used to analyze the multi-dimensional data of atomization particle size distribution, spray coverage and uniformity. The results show that under the conditions of 5% material concentration and 3 MPa spray pressure, the average particle size is 50.3 μm, the coverage area reaches 120.8 cm², the uniformity of atomization reaches 96.5%, and the system evaluation accuracy can be maintained at more than 99%. The system effectively supports process optimization and production quality control, shows high stability and adaptability, and lays a technical foundation for the intelligent upgrading of filament dosing.

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Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.04.166
Primary Topic
Textile materials and evaluations
Type
article
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article

Automatic Evaluation of Atomization Effect of Fiber Materials Based On Image Recognition

Johan van der Lei, Jing Zeng, Jianfeng Chen, Jao J. Ou
Procedia Computer Science
Textile materials and evaluations
article

Automatic Evaluation of Atomization Effect of Fiber Materials Based On Image Recognition

Johan van der Lei, Jing Zeng, Jianfeng Chen, Jao J. Ou
article en

Abstract

In order to improve the efficiency and accuracy of the evaluation of the atomization effect of the filament dosing material, image recognition technology combined with a high-resolution industrial camera was used to analyze the multi-dimensional data of atomization particle size distribution, spray coverage and uniformity. The results show that under the conditions of 5% material concentration and 3 MPa spray pressure, the average particle size is 50.3 μm, the coverage area reaches 120.8 cm², the uniformity of atomization reaches 96.5%, and the system evaluation accuracy can be maintained at more than 99%. The system effectively supports process optimization and production quality control, shows high stability and adaptability, and lays a technical foundation for the intelligent upgrading of filament dosing.

Procedia Computer ScienceVol. 261
China Tobacco (CN)
Openalex Percentile: Top 91%
Textile materials and evaluations
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Automatic Evaluation of Atomization Effect of Fiber Materials Based On Image Recognition — Johan van der Lei, Jing Zeng, et al. · Procedia Computer Science (2025) | TGRS Research Map | TGRS