A Remote Real-Time Monitoring System for Power Quality

An introduction is made to the composition, design method and engineering application of a remote real time monitoring system of power quality in substations based on internet. With virtual instrument and network technique adopted, this system is characterized by good real time property, high reliability, plentiful functions, and so on. It also can be used to monitor the load of a substation, such as electric locomotives.

Implementation of remote monitoring system for prediction of tool wear and failure using ART2

Remote monitoring of tools for prediction of tool wear in cutting processes was considered, and a method of implementation of a remote-monitoring system previously developed was proposed. Sensor signals were received and tool wear was predicted in the local system using an ART2 algorithm, while the monitoring result was transferred to the remote system via intemet. The monitoring system was installed at an on-site machine tool for monitoring three kinds of tools cutting titanium alloys, and the tool wear was evaluated on the basis of vigilances, similarities between vibration signals received and the normal patterns previously trained. A number of experiments were carried out to evaluate the performance of the proposed system, and the results show that the wears of finishing-cut tools are successfully detected when the moving average vigilance becomes lower than the critical vigilance, thus the appropriate tool replacement time is notified before the breakage.

Patient Centered Real-Time Mobile Health Monitoring System

In this paper, we introduce a system architecture for a patient centered mobile health monitoring (PCMHM) system that deploys different sensors to determine patients’ activities, medical conditions, and the cause of an emergency event. This system combines and analyzes sensor data to produce the patients’ detailed health information in real-time. A central computational node with data analyzing capability is used for sensor data integration and analysis. In addition to medical sensors, surrounding environmental sensors are also utilized to enhance the interpretation of the data and to improve medical diagnosis. The PCMHM system has the ability to provide on-demand health information of patients via the Internet, track real-time daily activities and patients’ health condition. This system also includes the capability for assessing patients’ posture and fall detection.

Monitoring of winter wheat distribution and phenological phases based on MODIS time-series： A case study in the Yellow River Delta, China

Accurate winter wheat identification and phenology extraction are essential for field management and agricultural policy making. Here, we present mechanisms of winter wheat discrimination and phenological detection in the Yellow River Delta（YRD） region using moderate resolution imaging spectroradiometer（MODIS） time-series data. The normalized difference vegetation index（NDVI） was obtained by calculating the surface reflectance in red and infrared. We used the Savitzky-Golay filter to smooth time series NDVI curves. We adopted a two-step classification to identify winter wheat. The first step was designed to mask out non-vegetation classes, and the second step aimed to identify winter wheat from other vegetation based on its phenological features. We used the double Gaussian model and the maximum curvature method to extract phenology. Due to the characteristics of the time-series profiles for winter wheat, a double Gaussian function method was selected to fit the temporal profile. A maximum curvature method was performed to extract phenological phases. Phenological phases such as the green-up, heading and harvesting phases were detected when the NDVI curvature exhibited local maximum values. The extracted phenological dates then were validated with records of the ground observations. The spatial patterns of phenological phases were investigated. This study concluded that, for winter wheat, the accuracy of classification is 87.07%, and the accuracy of planting acreage is 90.09%. The phenological result was comparable to the ground observation at the municipal level. The average green-up date for the whole region occurred on March 5, the average heading date occurred on May 9, and the average harvesting date occurred on June 5. The spatial distribution of the phenology for winter wheat showed a significant gradual delay from the southwest to the northeast. This study demonstrates the effectiveness of our proposed method for winter wheat classification and phenology detection.

基于静止气象卫星监测西太平洋火山活动

利用自主开发的静止气象卫星实时热点监测系统所积累的西太平洋2020~2023年卫星热点监测数据,结合全球火山活动计划(GVP)发布的全新世火山列表数据,在分析火山活动热辐射特征的基础上,提出一种基于静止气象卫星热点观测数据的火山活动监测算法,通过聚类识别技术从卫星热点数据中提取火山热点并计算火山热辐射指数。对比分析火山监测结果与GVP火山活动报告可知,该算法的火山活动识别率约为90%。漏报火山主要位于印度尼西亚地区,受火山活动类型和热带对流云系的影响。根据火山热点地理分布及其时间变化可以估算熔岩流蔓延方向、距离和速度。卫星火山热点监测数据在实时运行模式下可以作为输入因子之一驱动火山活动预报模型实时发布火山预警信息,其历史数据还可以作为高时间分辨率数据源支持火山活动研究。

铁路轨道打磨电动机远程监测系统设计

针对铁路轨道打磨电动机运行故障率较高,故障后对轨道打磨工作质量影响较大,且传统的人工巡检方式无法及时发现故障的问题,文中设计了一套能实时采集铁路轨道打磨电动机运行状态数据的远程监测系统,采用分层设计的理念,实现了对打磨电动机运行状态数据进行数据采集、数据存储、数据传输以及数据展示等相关处理的功能,并以此为基础对电动机进行故障诊断,在电动机发生故障时进行报警并推送故障诊断结果,从而极大地提高了铁路轨道打磨电动机的工作运行效率。

基于“5G+AI”技术的远程心电监测系统研究

为解决心血管疾病防控的难题,提高心血管疾病预防、诊断及治疗的时效性和精准性,基于5G通信和人工智能技术,搭建一个远程心电监测系统,包括患者心电数据采集和自动识别、医生远程诊疗等功能。此监测系统可远程不间断地实时采集并识别分析患者的心电数据,并将识别结果、结论反馈给医生和患者,为患者及时就医和医生诊疗提供意见和建议。该系统在心脏病患者的管理、突发心脏事件监测和早期心脏疾病筛查等方面具有一定的实用价值。

基于数据驱动的重症监护病房脱机拔管预测模型的研究

目的 开发并评估一种基于数据驱动的重症监护病房脱机拔管预测模型。方法 收集重症监护病房有创机械通气患者的非时序数据、低频生命体征时序数据和高频机械通气时序数据,采用决策树、朴素贝叶斯、支持向量机、分类集成、广义线性模型和神经网络等算法构建预测模型,并进行性能评估。结果 共纳入204例患者,其中脱机成功患者122例,失败患者82例。含有163例高频机械通气时序数据的深度神经网络模型在预测脱机拔管成功率方面表现最佳,准确度94.2%,AUC值0.81,灵敏度100%,特异性80%。其他模型表现相对逊色,分类集成模型的准确率75%,AUC值0.76,灵敏度83.3%,特异性62.5%。结论 利用远程高频时序数据建立的深度神经网络模型在预测重症监护病房患者脱机拔管成功率上展现出卓越性能,明显超越未采用此类数据的模型。

基于时序遥感数据的城市国土空间动态监测方法研究

随着航空航天技术的发展,对地观测变得便捷、高效,使得建立时序遥感数据集开展连续的国土空间变化监测逐渐成为一种有效手段。本文通过固定的卫星平台、采用1个季度为间隔,获取连续的遥感数据,近地采取无人机摄影的方式进行补充,建立连续、完整的时序遥感数据,并进行人机交互式的解译、识别和分析,对研究城市区域开展4个季度时相的不间断获取和识别,并连续国土空间变化监测,对比分析新城区域和市中心区域的街镇变化图斑数量及组成占比,总结浦东新区建设用地变化图斑的周期性规律和趋势特点,为“上海2035”总规专题评估提供有效支撑。

深海无人遥控潜水器水面监控软件的设计与实现

针对深海无人遥控潜水器(ROV)实时远程监控的需求以及传统ROV水面监控软件人机交互性差的问题,详细研究软件的实时性策略和虚拟仪表开发等关键技术,基于海龙系列ROV平台设计开发一套水面监控软件。软件采用三层架构的体系结构,实现串口通信、数据处理、状态监视、设备控制、警报显示等主要功能。经测试,该水面监控软件可在Windows系统下稳定运行,具有良好的实时性以及友好的人机交互性。

Monitoring paddy rice phenology using time series MODIS data over Jiangxi Province,China

Paddy rice is one of the most important crops in the world.Accurate estimation and monitoring of paddy rice phenology is necessary for management and yield prediction.Remotely sensed time-series data are essential for estimation of crop phenology stages across large areas.Here,the paddy rice phenological stages(i.e.,transplanting,tillering,heading,and harvesting)were detected in Jiangxi Province,China.A comparison study was conducted using ground observation data from 10 agricultural meteorological stations,collected between 2006 and 2008.The phenological stages were detected using Moderate Resolution Imaging Spectroradiometer(MODIS)time-series enhanced vegetation index(EVI)data.Savitzky-Golay filter and wavelet transform were used to reduce the noise in the time-series EVI data and reconstruct the smoothed EVI time-series profile.Key phenological stages of double-cropping rice were detected using the characteristics of the smoothed EVI profile.The root mean square errors(RMSEs)for each stage were ±10 days around the ground observation data.The results suggest that Savitzky-Golay filter and wavelet transform are promising approaches for reconstructing high-quality EVI time-series data.Moreover,the phenological stages of double-cropping rice could be detected using time-series MODIS EVI data smoothed by Savitzky-Golay filter and wavelet transform.

心脏远程实时监护系统在心血管疾病患者中的应用效果分析

目的:探讨心脏远程实时监护系统在心血管疾病患者中的应用效果。方法:选取2022年9-12月于上海市第一人民医院嘉定医院使用心脏远程实时监护系统救治的207例心血管疾病患者作为研究对象,均进行常规12导联心电图(ECG)检查、12导联24 h动态心电图(Holter)检查、心脏远程监护仪(Holter 5000)检查,以临床综合诊断结果为“金标准”,比较三种检测方法心血管疾病检出情况以及对心血管疾病的诊断效能。结果:Holter 5000心肌缺血检出率高于ECG、 Holter,传导阻滞、心房扑动或心房颤动、室性早搏或室性心动过速检出率Holter 5000>Holter>ECG,Holter 5000、Holter房性早搏或房性心动过速高于ECG,差异有统计学意义(P<0.05);ECG、Holter心肌缺血检出率,Holter 5000、Holter房性早搏或房性心动过速检出率比较,差异无统计学意义(P>0.05)。Holter 5000诊断心血管疾病的灵敏度、特异度高于ECG、Holter,Holter诊断心血管疾病的特异度高于ECG,差异有统计学意义(P<0.05);ECG、Holter诊断心血管疾病的灵敏度比较,差异无统计学意义(P>0.05)。结论:心脏远程实时监护系统在心血管疾病患者中的应用效果显著,具有较高的灵敏度、特异度。

海上平台无人值守智能化井口装置及采油树的设计与应用

探讨海上平台无人值守智能化井口装置及采油树的应用情况和存在问题。在明确无人值守智能化井口的总体方案,确定智能化井口必备的实时监测、故障诊断、远程控制三大主要功能和改造、升级方向的基础上,设计平台的井口布局图,对智能化井口进行结构设计、仿真测试、尺寸优化,研发满足无人平台空间布局要求的井口装置及采油树。为确定主要模块的功能和改造要求,根据其特点和需求,对智能化井口进行详细设计和分析,并针对当前无人井口平台的技术特点,提出增强远程监测和控制技术的改进方向。

基于RSEI和地理探测器的西昌市生态环境质量时空演变特征及其驱动力分析

生态环境保护对于推动社会经济可持续发展非常重要,对生态环境质量进行及时有效的监测可为城市发展规划提供依据。本文选取西昌市2001-2020年5期Landsat TM/ETM+/OLI时间序列影像为研究数据,耦合绿度、湿度、干度、热度构建遥感生态指数RSEI,并结合研究区气候、降水量、人口密度等驱动因素探究西昌市生态环境质量变化规律。结果表明:20年间,西昌市生态环境质量得到了有效改善;生态环境质量恶化区域主要位于中部流域耕作区、主城区周边及西部山脉,改善区域主要分布在海拔稍低的山区;由单因子探测分析可知,土地利用、年平均气温、年平均降水量对RSEI影响较大;由多因子探测分析可知,各因子交互作用对RSEI均有增强效果,其中年平均气温在土地利用交互作用下表现出了更强的解释力。

基于网络的磁力仪台站远程实时监测方法

磁法勘探中,磁力仪台站仪器采集地磁静日变化数据用于探区的地磁场数据的日变改正。为避开电磁干扰,磁力台站通常设置在偏远位置,很难实时监测仪器状况和数据质量,一旦出现问题会导致所有流动站的数据无法进行日变改正而作废。针对此问题,本文提出一种基于移动网络的远程实时监测磁力台站工作状况的方案,具有实时回传台站数据和状态异常警报功能,能够实时进行台站远程监测,解决了台站监测离不开人的难题。

遥感监测下城市主要大气污染物环流聚类时空分布特征研究

针对日益严重的城市大气污染问题,提出遥感监测下的城市主要大气污染物环流聚类时空分布特征分析方法。确认区域监测点数量,形成监测网,分析各个区域城市主要大气污染物的关联性与相似性,联合污染物对应的因子荷载与遥感监测数据属性信息,对主要大气污染物展开环流聚类分析,获得大气污染物的时间分布特征和空间分布特征。实验结果表明,以山东省为例,其大气污染最为严重区域为鲁西地区,空气质量最高区域为胶东半岛;山东省大气污染物在夏季的浓度值相对较低,在冬季的浓度值最高。

传统法与深度学习级联结合的近实时火点监测

针对山火监测精度和时效性不足的问题,提出一种级联传统法的多通道卷积神经网络(Multichannel Convolutional Neural Network,MCNN)近实时火点监测算法。首先,结合最大类间方差和空间上下文法,利用背景亮温空间信息差异筛选出潜在火点。然后,采用集成学习思想构建三个卷积神经网络通道,各通道分别输入光谱信息、空间上下文信息及时间地理信息特征的不同组合,同时,通过粒子群优化算法搜索各通道的最佳权重,获取三个通道的火点联合预测概率,实现火点准确识别。结果表明,相比于单通道卷积神经网络(Convolutional Neural Network,CNN)模型,MCNN精确度达到0.88,漏报率降低0.16,并且较日本气象厅官方产品漏报率降低0.06,且实验中模型运行平均耗时172 s。因此,文章提出的MCNN模型可实现较高精度的近实时火点监测,为火灾应急处理提供科学依据。

一种遥测智能终端设备双CPU架构系统软件升级的方案研究

针对双CPU架构的遥测智能终端设备提出了一种基于Inotify机制与NFS文件系统的系统软件升级方案。Inotify是Linux操作系统中一种实时监控文件系统变化的机制,NFS(Network File System)文件系统是一种网络文件系统,允许用户在不同的计算机或者各节点之间共享文件和存储资源。详细介绍了该方案的设计和实现,并对方案的性能进行了分析和评估。实验结果表明,该方案具有较高的实时性和可靠性,可有效提高遥测智能终端设备多CPU架构的升级效率。

高校高危实验数字孪生预案分析与遥操作安全技术

在高校化学化工等高危实验的教学、科研与管理工作中,很少从新技术应用层面研究其安全性保障问题。数字化、智能化、信息化是未来化学化工高危实验教学与实验室建设的必然技术趋势。从实验教学安全性角度出发,提出高校化学化工高危实验数字孪生技术、遥操作技术与实时操作监控预警系统的安全保障综合技术体系。其中,数字孪生技术在科技创新中用于探索性或前期实验教学的预案分析,人机交互遥操作技术是高风险实验现场操作规避人员安全性问题的新技术,实时操作监控预警系统提供教学环节监测与安全预警,以期根除化学化工高危实验教学与科研中事故频发的痼疾。

无人值守变电站监控系统设计

随着电网建设的快速发展,无人值守变电站成为电力系统的重要组成部分。文章主要设计一套无人值守变电站监控系统,以满足实时监测、远程控制以及故障检测的需求。该系统包括数据采集与处理、远程控制与操作、故障检测与报警、数据存储与管理以及用户界面与交互5个功能模块。经功能、性能及稳定性测试,验证了系统设计的有效性与可行性。