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.

The integrated monitoring system for running parameters of key mining equipment based on condition monitoring technology

An integrated monitoring system for running parameters of key mining equipmenton the basis of condition monitoring technology and modern communication networktechnology was developed.The system consists of a client computer with functions ofsignal acquisition and processing, and a host computer in the central control room.Thesignal acquisition module of the client computer can collect the running parameters fromvarious monitoring terminals in real-time.The DSP high-speed data processing system ofthe main control module can quickly achieve the numerical calculation for the collectedsignal.The signal modulation and signal demodulation are completed by the frequencyshift keying circuit and phase-locked loop frequency circuit, respectively.Finally, the signalis sent to the host computer for logic estimation and diagnostic analysis using the networkcommunication technology, which is helpful for technicians and managers to control therunning state of equipment.

On-line monitoring of insulation quality of high voltage electric power equipment

Discusses on-line monitoring of electric parameters, such as dielectric loss, divulging current, equivalent capacitance and running voltage, and presents an on-line monitoring system of insulation quality, based on monitoring divulging current and dielectric loss of high voltage equipment, and its advantages, such as helping people to discover the hidden problems in a timely manner, to reduce power cut and overhaul and to improve security of power supply.

An in situ monitoring method for PECVD process equipment condition

A key to successful consistent plasma processing is maintaining a consistent process chamber condition over a certain production period.To alleviate the concern,in situ process monitoring sensors are employed to investigate the plasma chamber conditions of both the deposition step with direct plasma and the cleaning step with a remote plasma system.In situ sensors are optical emission spectroscopy (OES),optical plasma monitoring sensors (OPMS),voltage current probes (Ⅵ-probes),and self-plasma OES (SP-OES).During the deposition,we perform the monitoring of a plasma condition associated with the applied RF power via OES,OPMS,and a Ⅵ-probe.In the chamber cleaning step using a remote plasma system does not allow plasma monitoring through the sidewall because the plasma is not formed in the process chamber,thus we employed SP-OES to monitor the by-product gas chemistry during the chamber cleaning process step.Successful monitoring results with some useful applications,such as arc detection,part failure detection,and cleaning process chemistry analysis,are presented in this paper.The use of in situ sensors with proper combination can help to understand the plasma process better,to achieve more precise control of plasma processing.

Analysis and Application of the Synthetic Relative Measuring Method in On-Line Monitoring for Capacitive Equipment in Power Systems

On-line measurement for dielectric loss angle can effectively monitor the insulation condition of capacitive equipment in power systems. Synthetic relative measuring methods not only markedly overcome the shortcomings of traditional absolute measuring methods but also greatly improve the accuracy of dielectric loss angle measurement. However, synthetic relative measuring methods based on two or three pieces of capacitive equipment do not have the characteristic of generality. In this paper, a principle of synthetic relative measuring method is presented. The example of application for synthetic relative methods based on three and four pieces of capacitive equipment running in the same phase is taken to present the failure judgment matrices for N pieces of equipment. According to these matrices, the fault condition of N pieces of capacitive equipment can be watched, which is more general. Then some problems needing to be concerned along with two diagnostic methods used in diagnostic system are introduced. Finally, two programmable flow charts for the two methods are given and corresponding examples demonstrate their feasibility in practice.

Real-time parameters monitoring system for underground equipment based on panoramic images

Complex terrain and working equipment in coal mine underground need a way to ensure coal mine safety. In this paper, the way to monitor the real-time status of underground equipment was put forward, and it was proved to be effective as commanding and dispatching system. Monitoring system for underground equipment based on panoramic images was effectively combined with real-time sensor data and static panoramic images of underground surrounding, which not only realizes real-time status monitoring for underground equipment, but also gets a direct scene for underground surrounding. B/S mode was applied in the monitoring system and this is convenient for users to monitor the equipment. Meantime, it can reduce the waste of the data resource.

Dynamic Control System of Automatic Monitoring Equipment for Waste Gas Pollution Source

In order to improve the quality of automatic monitoring data of pollution sources and apply the automatic monitoring data to verify the environmental tax,Shandong Province took the lead in adopting the Internet of Things technology and drawing on the successful experience of air automatic monitoring stations and surface water automatic monitoring stations in management,and developed a dynamic management and control system for automatic monitoring equipment of pollution sources to improve and strengthen the quality audit of automatic monitoring data,further improve the quality of automatic monitoring data and better provide a basis for environmental management and decision making.The system realizes the simultaneous monitoring of monitoring data,running state and parameters of the automatic monitoring equipment,eliminates the phenomenon of falsification by modifying equipment parameters,and judges the validity of the collected data by acquiring the working state of the equipment remotely and randomly.After the actual operation test of the Department of Ecological Environment of Shandong Province,the system is proved to have the characteristics of practicality,real time and high efficiency,and be able to make up for low frequency and narrow coverage of manual inspection,with good application prospect in the field of environment and pollution source monitoring.

Online Fault Detection Configuration on Equipment Side of a Variable-Air-Volume Air Handling Unit

With the development of the technology of the Internet of Things,more and more operational data can be collected from air conditioning systems.Unfortunately,the most of existing air conditioning controllers mainly provide controlling functions more than storing,processing or computing the measured data.This study develops an online fault detection configuration on the equipment side of air conditioning systems to realize these functions.Modbus communication is served to collect real-time operational data.The calculating programs are embedded to identify whether the measured signals exceed their limits or not,and to detect if sensor reading is frozen and other faults in relation to the operational performance are generated or not.The online fault detection configuration is tested on an actual variable-air-volume(VAV)air handling unit(AHU).The results show that the time ratio of fault detection exceeds 95.00%,which means that the configuration exhibits an acceptable fault detection effect.

Intelligent Examination Monitoring and Maintenance for the Safety of Operation of Flexible Manufacturing Systems

Based on the system of electric power supply for flexible manufacturing systems (FMS), a study has been carried out on the intelligent safety examination, monitoring and maintenance of its running environment. On the basis of the specific feature of the power supply network of an FMS, real time monitoring system of the power supply network and the fault diagnostic expert system for the power equipment have been designed. This system can diagnose not only definite fault phenomena, but also fuzzy, uncertain fault phenomena as well. Fault diagnostic knowledge base for the power equipment has been founded hierarchy architecture model and the method of fault tree analysis. Feasibility of this system has been proved by computer simulation.

Fault diagnosis and analysis of main sea water pump based on vibration monitoring in offshore oil field

The main sea water pump is the key equipment for the floating production storage and offloading （FPSO）. Affected by some factors such as hull deformation, sea water corrosion, rigid base and pipeline stress, the vibration value of main sea water pump in the horizontal direction is abnormally high and malfunctions usually happen. Therefore, it is essential to make fault diagnosis of main sea water pump, By conventional off-line monitoring and vibration amplitude spectrum analysis, the fault cycle is found and the alarm value and stop value of equipment are set, which is helpful to equipment maintenance and accident prevention.

An Automated Detection Approach of Protective Equipment Donning for Medical Staff under COVID-19 Using Deep Learning

Personal protective equipment(PPE)donning detection for medical staff is a key link of medical operation safety guarantee and is of great significance to combat COVID-19.However,the lack of dedicated datasets makes the scarce research on intelligence monitoring of workers’PPE use in the field of healthcare.In this paper,we construct a dress codes dataset for medical staff under the epidemic.And based on this,we propose a PPE donning automatic detection approach using deep learning.With the participation of health care personnel,we organize 6 volunteers dressed in different combinations of PPE to simulate more dress situations in the preset structured environment,and an effective and robust dataset is constructed with a total of 5233 preprocessed images.Starting from the task’s dual requirements for speed and accuracy,we use the YOLOv4 convolutional neural network as our learning model to judge whether the donning of different PPE classes corresponds to the body parts of the medical staff meets the dress codes to ensure their self-protection safety.Experimental results show that compared with three typical deeplearning-based detection models,our method achieves a relatively optimal balance while ensuring high detection accuracy(84.14%),with faster processing time(42.02 ms)after the average analysis of 17 classes of PPE donning situation.Overall,this research focuses on the automatic detection of worker safety protection for the first time in healthcare,which will help to improve its technical level of risk management and the ability to respond to potentially hazardous events.

New “Intellectual Networks” (Smart Grid) for Detecting Electrical Equipment Faults, Defects and Weaknesses

The most important elements of “intellectual networks” (Smart Grid) are the systems of monitoring the parameters of electrical equipment. Information-measuring systems (IMS), which described in this paper, were proposed to use together with rapid digital protection against short-circuit regimes in transformer windings. This paper presents an application’s experience of LVI-testing, some results of the use of Frequency Response Analysis (FRA) to check the condition of transformer windings and infra-red control results of electrical equipment. The LVI method and short-circuit inductive reactance measurements are sensitive for detecting such faults as radial, axial winding deformations, a twisting of low-voltage or regulating winding, a losing of winding’s pressing and others.

A Study on a Remote Monitoring and Diagnosis System and Its Application

Remote monitoring and diagnosis （RMD） is a new kind of monitoring and diagnosis technology that combines computer science, communication technology and fault diagnosis technology. Via the Internet a remote monitoring and diagnosis system can be established. In this paper, the model of an Internet based remote monitoring and diagnosis system is presented; the function of every part of the RMD system is discussed. Then, we introduce a practical example of a remote monitoring and diagnosis system that we established in a factory; its traits and functions are described.

基于环境声识别的工业设备状态监测实验系统设计

为了实现低成本的工业设备故障检测,设计了一套基于环境声识别的设备状态监测实验系统。基于Arduino开源硬件开发低成本的智能传感器,并部署限制感受野的深度学习模型RFL-MobileNet。通过在边缘端进行智能数据处理,系统为工厂设备提供了实时且准确的状态监测,以减少传统方法中数据传输到云端所带来的延迟以及数据泄露风险。基于公开数据集和实际数据集的实验结果表明,系统运行良好,电动机故障检测准确率达95.4%。

南极长城站哨声波监测仪设备及其初步观测

在子午工程二期项目的支持下,武汉大学(Wuhan University,WHU)联合中国极地研究中心研制了一套甚低频(very low frequency,VLF)波动探测系统,并在2022年由中国极地研究中心部署于南极洲的中国长城站(Great Wall Station,GWS,62.22°S,58.96°W).该探测系统的动态范围为~110 dB,时间精度为~100 ns,可为空间物理和空间天气研究提供高分辨率的波动观测数据.本文详细介绍了WHU VLF(子午工程编码:OCHCH_WHWM01)波动探测系统在GWS的初步观测结果,充分验证了系统的优越性能和稳定性.在过去一年的常规运行中,此系统能精确探测北美和欧洲等区域内各种地基VLF台站信号的动态变化.初步分析结果表明,在多次X级太阳耀斑爆发期间,GWS观测到的人工VLF台站信号特性与以往的研究结果高度一致.由于HWU-GWS(HWU为发射台站的名称)路径穿过南大西洋异常(south Atlantic anomaly,SAA)区域,观测结果同时表明,在磁暴期间,HWU VLF信号的扰动与磁层电子沉降在时空关系上具有很强的关联性.此外,此设备也能观测到闪电激发的宽频带哨声波,在频谱图上呈现特有的清晰色散结构.因此,在南极独特的地理位置,地基哨声波监测仪的观测结合其它仪器的观测,有利于深入开展与极区哨声波传播、低电离层扰动、地面闪电放电和辐射带粒子沉降等相关的空间天气学研究,对开展全天时空间环境监测具有重要意义.

基于单片机负载控制的无人机电气设备监测系统设计研究

为了实现电气化负载环境下,实时监测无人机电气设备,避免电子负载性能持续受限。将引入单片机负载控制思路,设计无人机电气设备监测系统,通过系统硬件选型与软件设计两方面,从构建无人机电气设备运行负载环境,采用PCB设备监控板建立PLC扩展负载模块,成功连接监测系统的监控主机设备。利用STM32单片机移植协议,根据提前预设的电气设备监控优先级条件,搭设系统程序执行环境。

轨道打磨电动机监测管理系统设计与实现

打磨电动机是铁路轨道打磨作业的重要设备。但其工作环境较为恶劣,故障率较高。文中从实际需求出发,研究并构建1套轨道打磨电动机监测管理系统,以实现对电动机实时状态进行监测和相关数据的采集。系统针对海量数据的高效采集存储、故障诊断方面进行了深入研究和设计,同时构建友好的用户交互界面。该系统对于推动铁路轨道打磨的实际应用和设备的智能化有一定的促进作用。

对“水利测雨雷达”的新质生产力研究

高精准降雨监测预报对于支撑水旱灾害防御等水利业务预报、预警、预演、预案“四预”工作至关重要。水利测雨雷达系统主要观测近地面2 km高度范围内大气中的液态水,能够实现无缝隙、精细化监测并生成高精度实况定量降雨产品,具有较为精准的外推1~3 h降雨临近预报能力,是水利新质生产力的典型代表。系统梳理了我国降雨监测发展历程,包括无器具测量、雨量器萌芽、标准化人工雨量器、自动记录式雨量器和现代自动测雨五个阶段。在此基础上,从雨量站业务应用、天气雷达业务应用、气象卫星业务应用角度,分析当前“四预”业务中降雨监测现状与问题,进而梳理了水利测雨雷达发展进程并分析其技术优势,包括:能够实时生成超精细化的网格降雨实况数据,能够实现精细化网格化降雨预报,以及系统运行稳定高效。结合水利测雨雷达在河北省大清河流域以及湖南省捞刀河、浏阳河流域的良好应用成效,指出其作为水利新质生产力在赋能“四预”方面具有应用前景。

炼化装置老旧设备安全保障一体化技术应用研究

针对当前国内炼化装置设备存在的“老龄化”趋势,以及由此引起的安全隐患问题,基于当前所存在的不足,提出基于损伤模式识别、安全评估并结合全面完备的在线检测(监测)等手段的炼化装置老旧设备安全保障一体化的技术路线,并将此技术路线应用于某大型石化企业中。结果表明:应用该技术路线可找出老旧设备的安全隐患,可提升企业针对老旧设备的管理水平。该技术路线可为当前炼化装置老旧设备所面临的困难提供技术指导。