Small-Capacity Liquid Density Detection Device Based on Computer Vision

To address the challenge of density detection for small-volume unit-labeled quantitative packaged products, a computer vision-based density detection device suitable for small-volume liquids was designed. The device integrates image processing technology with an automatic injection system and micro-volume constant-volume control technology to achieve automatic weighing and volume acquisition of volumetric flasks, thereby enabling automated density measurement of samples. Additionally, a data acquisition and processing software system was developed to minimize human reading and operational errors, improving detection efficiency and measurement accuracy. Experimental results demonstrate that the device achieves a relative expanded uncertainty of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$0.00069 \mathrm{g} / \text{cm}^3$</tex> and a measurement repeatability of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$0.0005 \text{g/cm}^{3}$</tex>, ensuring high detection precision.

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Published
2025-03-21
DOI
https://doi.org/10.1109/icaace65325.2025.11019802
Primary Topic
Advanced Computing and Algorithms
Type
article
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article

Small-Capacity Liquid Density Detection Device Based on Computer Vision

Jie Chen, Bin Li, Rui Liu, Renda Xing
Advanced Computing and Algorithms
article

Small-Capacity Liquid Density Detection Device Based on Computer Vision

Jie Chen, Bin Li, Rui Liu, Renda Xing
article en

Abstract

To address the challenge of density detection for small-volume unit-labeled quantitative packaged products, a computer vision-based density detection device suitable for small-volume liquids was designed. The device integrates image processing technology with an automatic injection system and micro-volume constant-volume control technology to achieve automatic weighing and volume acquisition of volumetric flasks, thereby enabling automated density measurement of samples. Additionally, a data acquisition and processing software system was developed to minimize human reading and operational errors, improving detection efficiency and measurement accuracy. Experimental results demonstrate that the device achieves a relative expanded uncertainty of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$0.00069 \mathrm{g} / \text{cm}^3$</tex> and a measurement repeatability of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$0.0005 \text{g/cm}^{3}$</tex>, ensuring high detection precision.

Shanghai University (CN), Shanghai Institute of Quality Inspection and Technical Research (CN)
Affordable and clean energy
Openalex Percentile: Top 83%
Advanced Computing and Algorithms
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