基于虚拟现实技术的数字孪生系统,用于远程监控采矿设备:架构和案例研究

Q1 Computer Science Virtual Reality Intelligent Hardware Pub Date : 2024-04-01 DOI:10.1016/j.vrih.2023.12.002
Jovana Plavšić, Ilija Mišković
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引用次数: 0

摘要

背景传统的采矿设备监控方法主要依靠目视检查,这种方法耗时长、效率低且危险。本文介绍了一种通过整合虚拟现实(VR)和数字孪生(DT)技术来监控采矿业关键任务系统和服务的新方法。方法本文介绍了基于虚拟现实技术的数字孪生技术开发架构,包括开发阶段、活动和所涉及的利益相关者。使用所提出的方法,对使用实时合成振动传感器数据进行传送带状态监测的案例进行了研究。该研究展示了该方法在远程监控中的应用,并确定了在主动采矿作业中实施该方法所需的进一步开发。文章还讨论了跨学科性、工具选择、计算资源、时间和成本、人工参与、用户接受度、检测频率、多用户环境、潜在风险以及采矿业以外的应用。
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VR-based digital twin for remote monitoring of mining equipment: Architecture and a case study

Background

Traditional methods for monitoring mining equipment rely primarily on visual inspections, which are time-consuming, inefficient, and hazardous. This article introduces a novel approach to monitoring mission-critical systems and services in the mining industry by integrating virtual reality (VR) and digital twin (DT) technologies. VR-based DTs enable remote equipment monitoring, advanced analysis of machine health, enhanced visualization, and improved decision making.

Methods

This article presents an architecture for VR-based DT development, including the developmental stages, activities, and stakeholders involved. A case study on the condition monitoring of a conveyor belt using real-time synthetic vibration sensor data was conducted using the proposed methodology. The study demonstrated the application of the methodology in remote monitoring and identified the need for further development for implementation in active mining operations. The article also discusses interdisciplinarity, choice of tools, computational resources, time and cost, human involvement, user acceptance, frequency of inspection, multiuser environment, potential risks, and applications beyond the mining industry.

Results

The findings of this study provide a foundation for future research in the domain of VR-based DTs for remote equipment monitoring and a novel application area for VR in mining.

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来源期刊
Virtual Reality  Intelligent Hardware
Virtual Reality Intelligent Hardware Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
6.40
自引率
0.00%
发文量
35
审稿时长
12 weeks
期刊最新文献
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