Intelligent decision-making system for mineral processing production indices based on digital twin interactive visualization

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Visualization Pub Date : 2024-03-28 DOI:10.1007/s12650-024-00964-4
Kesheng Zhang, Quan Xu, Changxin Liu, Tianyou Chai
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Abstract

The multi-layer indices decision-making of complex industrial processes is the key to reducing costs and improving production efficiency. With the development of the Industrial Internet, a large number of industrial streaming data and intelligent algorithms have brought opportunities for optimizing plant-wide production indices. However, due to the strong dynamic and coupling of the production process, the intelligent system based only on the optimization algorithm cannot give practical data analysis suggestions and decision results, so a human–computer interactive visual analysis and index decision system are urgently needed. This paper combines multi-layer indices decision-making algorithms with 3D digital twin visual analysis technology to propose an intelligent decision-making system for mineral processing production indices based on 3D digital twin interactive visualization (DTIV). The DTIV system provides users a 3D digital twin modeling view from the production park, workshop, and equipment scenes. It adopts visualization technology that seamlessly integrates 3D and 2D to help users obtain indices decision input information and hidden data features from real-time stream data with different spatiotemporal data characteristics. In addition, the DTIV system also combines a multi-layer indices optimization decision-making algorithms engine and designs a human–machine interaction indices decision interface and indices decision execution visual analysis interface to improve users’ production perception and decision-making ability. Through our collaboration with domain experts, carefully designed interviews, and prototype system evaluation in a beneficiation plant, the effectiveness and usability of the system have been proven.

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基于数字孪生互动可视化的矿物加工生产指数智能决策系统
摘要 复杂工业流程的多层指数决策是降低成本、提高生产效率的关键。随着工业互联网的发展,大量工业流数据和智能算法为优化全厂生产指标带来了机遇。然而,由于生产过程具有很强的动态性和耦合性,仅基于优化算法的智能系统无法给出切实可行的数据分析建议和决策结果,因此迫切需要一种人机交互的可视化分析和指标决策系统。本文将多层指标决策算法与三维数字孪生可视化分析技术相结合,提出了基于三维数字孪生交互可视化(DTIV)的选矿生产指标智能决策系统。DTIV 系统为用户提供了从生产园区、车间到设备场景的三维数字孪生建模视图。它采用三维和二维无缝集成的可视化技术,帮助用户从具有不同时空数据特征的实时数据流中获取指数决策输入信息和隐藏数据特征。此外,DTIV 系统还结合多层指数优化决策算法引擎,设计了人机交互指数决策界面和指数决策执行可视化分析界面,以提高用户的生产感知和决策能力。通过与领域专家的合作、精心设计的访谈以及在选矿厂的原型系统评估,该系统的有效性和可用性得到了验证。
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来源期刊
Journal of Visualization
Journal of Visualization COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY
CiteScore
3.40
自引率
5.90%
发文量
79
审稿时长
>12 weeks
期刊介绍: Visualization is an interdisciplinary imaging science devoted to making the invisible visible through the techniques of experimental visualization and computer-aided visualization. The scope of the Journal is to provide a place to exchange information on the latest visualization technology and its application by the presentation of latest papers of both researchers and technicians.
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