DESIGN AND APPLICATION OF DYNAMIC MONITORING AND VISUALIZATION MANAGEMENT INFORMATION SYSTEM OF KARST LAND ROCKY DESERTIFICATION

In order to study the spatial-temporal change and environmental management of regional karst LUCC (land use and land cover change) and its causative environmental effect-rocky desertification by integrating qualitative analysis and quantitative analysis, and relying on RS, GIS and GPS (3S) techniques, karst land rocky derification dynamic monitoring and visualization management information system (KLRD.DMVM.IS) is framed, which includes design aim and structure model, function design, database design and model system design. The model system design gives priority to dynamic monitoring, drive force diagnosis, comprehensive evaluation and decision support of karst rocky desertification. From the viewpoint of model type, mathematic expression and its meaning, the dynamic monitoring models are concretely devised to reflect the spatial and temporal changing features and the trend of karst LUCC and rocky desertification. Taking Du'an Yao Autonomic County of Guangxi as an example, the KLRD.DMVM.IS is systematically analyzed in the application of the process and trend of karst LUCC and rocky desertification in Du'an County, and it provides the technical support for the study on karst land rocky desertification.

Visualization Research and Application of Water Quality Monitoring Data Based on ECharts

Water resources are one of the basic resources for human survival,and water protection has been becoming a major problem for countries around the world.However,most of the traditional water quality monitoring research work is still concerned with the collection of water quality indicators,and ignored the analysis of water quality monitoring data and its value.In this paper,by adopting Laravel and AdminTE framework,we introduced how to design and implement a water quality data visualization platform based on Baidu ECharts.Through the deployed water quality sensor,the collected water quality indicator data is transmitted to the big data processing platform that deployed on Tencent Cloud in real time through the 4G network.The collected monitoring data is analyzed,and the processing result is visualized by Baidu ECharts.The test results showed that the designed system could run well and will provide decision support for water resource protection.

Real-Time Data and Visualization Monitoring of Computer Numerical Control Machine Tools Based on Hyper Text Markup Language 5

In order to ensure the safety,quality and efficiency of computer numerical control(CNC)machine tool processing,a real-time monitoring and visible solution for CNC machine tools based on hyper text markup language(HTML)5 is proposed.The characteristics of the real-time monitoring technology of CNC machine tools under the traditional Client/Server(C/S)structure are compared and analyzed,and the technical drawbacks are proposed.Web real-time communication technology and browser drawing technology are deeply studied.A real-time monitoring and visible system for CNC machine tool data is developed based on Metro platform,combining WebSocket real-time communication technology and Canvas drawing technology.The system architecture is given,and the functions and implementation methods of the system are described in detail.The practical application results show that the WebSocket real-time communication technology can effectively reduce the bandwidth and network delay and save server resources.The numerical control machine data monitoring system can intuitively reflect the machine data,and the visible effect is good.It realizes timely monitoring of equipment alarms and prompts maintenance and management personnel.

Design and implementation of a visual monitoring system to ensure safety in the water surrounding a container vessel

Container vessels navigate among the world＇s ports, frequently passing through narrow and congested waters. Due to the many layers of containers on a container vessel＇s decks, it is difficult for the crew to be aware of all fishing vessels and other obstacles in a container vessel＇s radar observation blind zone. This greatly increases the risk of collisions and other accidents. Given such great challenges to safe navigation and safety management with container vessels, their security risks are severe. An effective visual monitoring system can improve the safety of the water area surrounding container vessel by eliminating a vessel＇s observation blind zone, providing an effective safety measure for vessels navigating fishing zones and other troublesome areas. The system has other functions, such as accident recording, ship security, and monitoring of loading and unloading operations, thus ensuring the ship operates safely. Six months＇ trial operation showed that the system facilitates safe navigation of container vessels.

Real-Time Grouting Monitoring and Visualization Analysis System for Dam Foundation Curtain Grouting

A real-time monitoring and 3D visualization analysis system is proposed for dam foundation curtain grouting. Based on the real-time control technology, the optimization method and the set theory, a mathematical model of the system is established. The real-time collection and transmission technology of the grouting data provides a data foundation for the system. The real-time grouting monitoring and dynamic alarming method helps the system control the grouting quality during the grouting process, thus, the abnormalities of grouting, such as jacking and hydraulic uplift, can be effectively controlled. In addition, the 3D grouting visualization analysis technology is proposed to establish the grouting information model(GIM). The GIM provides a platform to visualize and analyze the grouting process and results. The system has been applied to a hydraulic project of China as a case study, and the application results indicate that the real-time grouting monitoring and 3D visualization analysis for the grouting process can help engineers control the grouting quality more efficiently.

A New Method for Visual Real-Time Monitoring of Low Frequency Oscillation

Visual real-time monitoring is the premise of low frequency oscillation control in power grids. This paper showed a visual method for the control center of power grids to monitor low frequency oscillation. It processed the PMU real-time data with incomplete S-transform, and converted the waveforms to two-dimensional time-frequency figures which showed the initial time, frequency and amplitude of each low frequency oscillation mode directly. GPU was used to show figures and calculate FFT with the purpose of improving calculation efficiency. The results of practical cases show that the real-time characters of low frequency oscillation can be identified availably by this visualization real-time monitoring method which is helpful and suitable for practical application.

Research on Dynamic Monitoring Algorithm of Visual Safety Distance in Highway

To develop the dynamic monitoring algorithm of visual safety distance in highway, by using the highway video traffic monitoring system, the research platform of four kinds of terrain environment in plateau, mountainous area, plain and coastal area is established. Results show that through the contrast between the sample data and visibility train of thought, based on the theory of mathematical morphology, expressway visibility dynamic monitoring image information system can be established. Based on the theory of the measurement of the basic formula of visibility, the dynamic model of the optimization is established, set up 200 meters distance visual observation target system, research visual range detection algorithm process.

Design of a Web Crawler for Water Quality Monitoring Data and Data Visualization

Many countries are paying more and more attention to the protection of water resources at present,and how to protect water resources has received extensive attention from society.Water quality monitoring is the key work to water resources protection.How to efficiently collect and analyze water quality monitoring data is an important aspect of water resources protection.In this paper,python programming tools and regular expressions were used to design a web crawler for the acquisition of water quality monitoring data from Global Freshwater Quality Database(GEMStat)sites,and the multi-thread parallelism was added to improve the efficiency in the process of downloading and parsing.In order to analyze and process the crawled water quality data,Pandas and Pyecharts are used to visualize the water quality data to show the intrinsic correlation and spatiotemporal relationship of the data.

Monitoring Information 3D Visualization for Super-Filling Loess Project

The construction of high-filled loess project has some engineering and technical challenges, such as excavation of earth and backfilling of earth are both large, complex construction environment, variety of influence factors. According to this situation, this paper presents a dynamic 3D visualization method for high-filled project based on volume rendering. Through comparative analysis and visual analysis, realized at different times of the Loess fill internal detection data visualization and analysis presented. The results show that this visualization method can directly and accurately display the construction process, help decision makers master construction information and process.

Remote Visualization of High-Speed Rail Power Quality Monitoring

The visualization techniques were explored for power quality monitoring.And remote visualization solutions were proposed for highspeed rail power quality monitoring.Taking the Beijing-Shanghai highspeed rail power monitoring as a study case,a remote visualization client,based on our proposed solutions,was developed for high-speed rail power quality monitoring to efficiently support power quality data analysis of the electricity business.The solutions collected data from monitoring stations deployed along the high-speed rail route and visualized the data set with a variety of visualization technologies to alert the specific stations of catastrophic events.The proposed solutions have been proved to be effective in supporting decision-making for the railway power scheduling and providing diagnosis information for quickly spotting any possible runtime failure in operation.

Colorimetric indicator based on zwitterionic anti-freezing hydrogel and alizarin for visual monitoring of salmon fillets freshness

Indicating hydrogels have shown the advantages of being fast, sensitive, and real-time in demonstrating the freshness of aquatic products due to their noticeable color change. In this work, an anti-freezing hydrogel embedded with pH-sensitive alizarin was developed as an original colorimetric indicator for monitoring the corruption of aquatic products at low temperatures. The anti-freezing hydrogel was prepared from 2-carboxyethyl acrylate, [2-(methacryloyloxy)ethyl]-trimethylammonium chloride, and 2-hydroxyethyl methacrylate monomers with triethylene glycol dimethacrylate as cross-linking agent. The hydrogel showed excellent anti-freezing capability, which was further incorporated with the pH-sensitive dye alizarin to gain the indicating capability. When applied in the indication of the freshness of salmon under low-temperature storage, it was found that the color changes of the indicator corresponded with the total volatile basic nitrogen contents of salmon, the correlation coefficient of which was 0.959 6. These results indicated the application potential of the hydrogels as freshness indicators during low-temperature storage or cold-chain transportation.

COVID-19 Public Opinion and Emotion Monitoring System Based on Time Series Thermal New Word Mining

With the spread and development of new epidemics,it is of great reference value to identify the changing trends of epidemics in public emotions.We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining.A new word structure discovery scheme based on the timing explosion of network topics and a Chinese sentiment analysis method for the COVID-19 public opinion environment are proposed.Establish a“Scrapy-Redis-Bloomfilter”distributed crawler framework to collect data.The system can judge the positive and negative emotions of the reviewer based on the comments,and can also reflect the depth of the seven emotions such as Hopeful,Happy,and Depressed.Finally,we improved the sentiment discriminant model of this system and compared the sentiment discriminant error of COVID-19 related comments with the Jiagu deep learning model.The results show that our model has better generalization ability and smaller discriminant error.We designed a large data visualization screen,which can clearly show the trend of public emotions,the proportion of various emotion categories,keywords,hot topics,etc.,and fully and intuitively reflect the development of public opinion.

Sound-Environment Monitoring Method Based on Computational Auditory Scene Analysis

Monitoring techniques are a key technology for examining the conditions in various scenarios, e.g., structural conditions, weather conditions, and disasters. In order to understand such scenarios, the appropriate extraction of their features from observation data is important. This paper proposes a monitoring method that allows sound environments to be expressed as a sound pattern. To this end, the concept of synesthesia is exploited. That is, the keys, tones, and pitches of the monitored sound are expressed using the three elements of color, that is, the hue, saturation, and brightness, respectively. In this paper, it is assumed that the hue, saturation, and brightness can be detected from the chromagram, sonogram, and sound spectrogram, respectively, based on a previous synesthesia experiment. Then, the sound pattern can be drawn using color, yielding a “painted sound map.” The usefulness of the proposed monitoring technique is verified using environmental sound data observed at a galleria.

Visualization and early warning analysis of damage degree of surrounding rock mass in underground powerhouse

Based on the underground powerhouse of Shuangjiangkou hydropower station,Octree theory is adopted to define the indices of the microseismic(MS)spatial aggregation degree and the deviation values of MS count and energy.The relationship between the MS multiple parameters and surrounding rock mass instability is established from three aspects:time,space,and strength.Supplemented by the center frequency of the signal evolution characteristics,A fuzzy comprehensive evaluation model and the evolution trend of the MS event center frequency are constructed to quantitatively describe the early warning state of the surrounding rock mass instability.The results show that the multilevel tree structure and voxels generated based on the Octree theory fit relatively well with the set of MS points in threedimensional space.The fuzzy comprehensive evaluation model based on MS spatial aggregation and MS count and energy deviation values enables three-dimensional visualization of the potential damage area and damage extent of the surrounding rock mass.The warning time and potential damage zone quantified are highly consistent with the characteristics of MS precursors,with wide recognition and field investigation results,which fully validate the rationality and applicability of the proposed method.These findings can provide references for the early warning of surrounding rock mass instability in similar underground engineering.

基于计算机视觉的电力作业人员行为分析研究现状与展望

电力作业人员的有效监管是保障电力安全生产的基础。该文对电力视频中作业人员的行为识别研究进行了归类总结,涵盖静态行为分析(穿戴分析、动作分析和组合分析)和动态行为分析(复杂动作、时序行为和行为预测等);详细综述了电力作业行为分析中的核心算法模块,包括目标检测、姿态估计和视频跟踪等;论述了电力作业行为识别在算法高效性、鲁棒性、灵活性等方面所面临的应用难点和挑战,并展望了电力作业行为智能监控领域的未来发展方向,特别强调了在软硬件结合、通用大模型、生成式人工智能方面进行技术创新和改进所蕴含的潜在机会。

基于GIS与大数据分析的矿压监测预警平台

为响应国家关于加快煤矿智能化发展的号召,针对煤矿GIS“一张图”中巷道路径不能实现精确计算,矿压数据不能实现高效甄别、有效提取的问题,以及矿压预警需要实现在线推演、可视化展示的需求,提出建立基于GIS与大数据分析的矿压监测预警平台。采用GIS“一张图”、巷道结点-路径拓扑算法、多源异构监测数据处理技术、矿压大数据分析技术,搭建成能够实现矿井下复杂情况切实反映、矿压监测数据有效提取、采掘风险在线预测、可视化程度高的矿压监测预警平台。通过在李雅庄矿的实际应用,表明该系统运行稳定可靠,可有效提升煤矿的矿压风险监测预警。

面向流程制造的数字孪生车间可视化监控系统研究

为了解决流程制造过程监控实时性差、准确性不足的问题,在数字孪生技术迅速发展且与制造业结合愈发紧密的背景下,提出基于生产要素数据、生产工艺流程与多工序设备实体对象的数字孪生车间可视化监控系统架构。从要素、状态、运行逻辑等多个维度对多工序耦合生产线实体对象进行孪生建模,基于OPC UA统一架构的数据采集传输,虚拟车间的实时驱动等关键技术,实现了流程制造设备状态、生产要素工艺全流程三维可视化监控。基于某流程制造企业制丝生产试验线开展了应用验证,为提升流程制造过程中全生产要素的预见性、联动性、自治性提供了方法和实现途径。

基于数字孪生的工业机器人建模及监测方法

针对工业机器人数据不透明、监测存在死角等问题,通过对实体工业机器人分析和研究,构建数字孪生机器人监测系统。首先从几何、物理、逻辑3个维度完成虚拟机器人的建模;其次基于开放平台通信联合架构(open platform communications united architecture,OPC UA),实现机器人的数据采集和通信,设计用户显示界面,达到数据实时可视化的效果;最后,通过机器人仿真实验得出机器人末端执行器X、Y、Z坐标的相对位置误差分别为0.48%、0.32%、0.27%,通过数字孪生机器人监测同步实验验证机器人关节角度误差最大值为0.31°。实验结果表明:该方法能够实现数字孪生工业机器人的运动数据监测,减少工业机器人在生产过程中发生意外和故障的风险,为智能工业机器人的发展提供思路和方向。

基于PySide的时序InSAR处理可视化及形变监测实验

基于PySide等Python开源扩展包设计了时序InSAR处理可视化软件,用于实验教学。软件集成了影像搜索、像对组合、干涉解缠、时序处理、结果展示等功能。以山东省菏泽市郓城县城区地表沉降监测为例,进行实验处理,并与PSDS-InSAR方法进行精度对比。相较于传统命令行操作方式,该可视化软件极大地简化数据处理的复杂性,软件处理结果与PSDS-InSAR所得结果的相关性为0.9866。软件提高实验效率,降低实验难度,改善了实验效果,结果精度表明该软件也可直接应用于工程实践。

基于无人机及YOLOX视觉算法的大跨度钢结构吊装过程位移监测

在大跨度钢结构吊装施工过程中,节点位移及结构变形关系到吊装施工的安全和质量。对于传统接触式监测方法存在的耗时、耗力且维护费用高等问题,提出了一种以无人机为载体的非接触式监测方式。首先,针对大跨度钢结构吊装过程中无人机近距采集视角受限的问题,采用Harris图像拼接算法进行全景拼接,并与图像加权融合相结合,消除图像拼接中产生的不利光标及拼接缝,实现整体、高精度的大跨度结构图像的无缝拼接;其次,采用加入卷积块注意力机制(convolutional block attention module, CBAM)的YOLOX视觉算法解决复杂背景下不同像素面积的小目标图像识别、坐标提取和位移监测;最后,对四种不同检测模型进行对比评估,并通过对比实验室不同工况试验和实际工程验证该方法在施工环境下对大跨度钢结构测点位移监测的可行性。试验结果表明,加入CBAM注意力机制的YOLOX检测模型的平均精度及置信度均优于其他三种网络模型,且视觉识别的位移信息与Leica全站仪的误差均在亚毫米级内,满足实际工程精度的要求,实现了复杂背景下的小目标位移监测,具备较高的经济效益和广泛的应用前景。