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Intelligent identification of concrete uniformity based on dynamic mixing

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Abstract

The uniformity of concrete is an important reference for the maturity of concrete, and is also closely related to the quality and safety of the product. In order to analyze the performance of concrete during the mixing process, in view of the problem that there is no scientific and effective method to detect the uniformity of concrete during the mixing process, this paper proposes an intelligent identification method for the uniformity of concrete based on dynamic mixing. The method measures the surface of concrete fluid through computer graphical modeling, applies mathematical and computational models to the interaction of fluid dynamics, and uses the computer to independently judge the characteristics of the concrete fluid state under non-artificial conditions, thereby obtaining the state of concrete uniformity. The experimental results show that the average accuracy of the intelligent identification method of concrete uniformity based on dynamic mixing is 97.14%, and the real-time monitoring speed reaches 12FPS/S, which has important reference significance for the real-time state detection of concrete. The identification accuracy and monitoring speed can both meet the actual monitoring needs of the concrete mixing station.

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The data that support the findings of this study are available on request from the corresponding author, [initials], upon reasonable request.

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Funding

The funding is largely from Henan Province Major Science and Technology Project (201110210300); Zhengzhou Major Science and Technology Innovation Special Project (2019CXZX0050); Henan Province Key Scientific Research Project Plan (21A510007). Part of financial support is from [Zhengzhou Sanhe Hydraulic Machinery Co., Ltd.]

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Authors and Affiliations

  1. North China University of Water Resources and Electric Power, Zhengzhou, China

    Mingtang Liu, Bin Li, Shuang Yue, Yuying Du & Jie Xu

Authors
  1. Mingtang Liu
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  2. Bin Li
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  3. Shuang Yue
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  4. Yuying Du
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  5. Jie Xu
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Contributions

ML: Conceptualization, methodology. BL: data curation, writing- original draft preparation. SY: investigation. YD: supervision. JX: writing- reviewing and editing. All authors reviewed the manuscript.

Corresponding author

Correspondence to Bin Li.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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The written-formed consent for publishing this paper was obtained from the North China University of Water Resources and Electric Power and all authors.

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Liu, M., Li, B., Yue, S. et al. Intelligent identification of concrete uniformity based on dynamic mixing. SIViP 18, 427–436 (2024). https://doi.org/10.1007/s11760-023-02738-1

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  • DOI: https://doi.org/10.1007/s11760-023-02738-1

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