Design of Integrated Monitoring and Early Warning System of Urban Rail Transit Train Running State

The monitoring and warning of urban rail transit is the core of operation management, and the breadth and depth of the monitoring range directly affect the quality of urban rail transit operation. For the current domestic monitoring system, most of the critical equipments and technologies are introduced from abroad;it is diseconomy, and also causes hidden danger. Realizing the localization of monitoring and early warning system is imperative. Based on the analysis of the present situation of urban rail transit operation safety at home and abroad, the paper proposes to use integrated technology to design basic framework of monitoring and warning system of urban rail train, and puts forward the critical technologies to realize the system. Compared with the existing monitoring system, the integrated monitoring system has the characteristics of wide monitoring range, clear division of labor, centralized management, coordination and integration operation and intelligent management, and embodies the concept of people-oriented. It has scientific significance for future construction of domestic Integrated Monitoring and Early Warning System (IMEWS) of urban rail transit.

China agricultural outlook for 2015–2024 based on China Agricultural Monitoring and Early-warning System(CAMES)

The primary goal of Chinese agricultural development is to guarantee national food security and supply of major agricultural products. Hence, the scientiifc work on agricultural monitoring and early warning as wel as agricultural outlook must be strengthened. In this study, we develop the China Agricultural Monitoring and Early-warning System (CAMES) on the basis of a comparative study of domestic and international agricultural outlook models. The system is a dynamic and multi-market partial equilibrium model that integrates biological mechanisms with economic mechanisms. This system, which includes 11 categories of 953 kinds of agricultural products, could dynamical y project agricultural market supply and demand, assess food security, and conduct scenario analysis at different spatial levels, time scale levels, and macro-micro levels. Based on the CAMES, the production, consumption, and trade of the major agricultural products in China over the next decade are projected. The fol owing conclusions are drawn:i) The production of major agricultural products wil continue to grow steadily, mainly because of the increase in yield. i ) The growth of agricultural consumption wil be slightly higher than that of agricultural production. Meanwhile, a high self-sufifciency rate is expected for cereals such as rice, wheat, and maize, with the rate being stable at around 97%. i i) Agricultural trade wil continue to thrive. The growth of soybean and milk im-ports wil slow down, but the growth of traditional agricultural exports such as vegetables and fruits is expected to continue.

The Project Monitoring and Early Warning System of Mould and Die

The article simply describes the difficulties of the Mould and Die project control,and then put forward the thoughts of developing the Monitoring and Early Warning System for the Mould and Die manufacturing.Afterwards,the main three constructing principles and the goals of the system are explained carefully.Based on those,the theory and the classifications of the Monitoring and Early Warning are expounded.With the assistance of the use case diagram of UML(the United Modeling Language),the main functions of the system are analyzed;and with the activity diagram of the UML,the work flows of the monitoring and early warning are expressed clearly.Finally,the classes and the architectures of the system are designed by making use of the class diagram of UML.

Research on Monitoring and Earlywarning System of Marine Organisms for the Intake of Nuclear PowerPlants

An monitoring and earlywarning system is proposed for marine organisms and the cause of water intake blockage is analyzed. Based onthe intelligent sensing technology, computer software and hardware technology and digital signal processing technology, the buoy monitoring platformsystem is developed by internet of things technology, cloud computing and the application of large data. Remote realtime monitoring of aquatic organisms and foreign bodies is realized based on underwater acoustic detection and low light imaging technology. Data processing center is established to store, analyze and process monitoring information and display it in real time, and provide emergency decision support. Through development and test of relevant key equipments, the reliability of cold source system of nuclear power plants is improved, which effectively reduces theinfluence of marine biological invasion on security and economic operation of the units.

Design and Availability Research of a Flammable and Explosive Volatiles Monitoring and Early Warning System (FEVMEW) for the Bus Crowded Places

In order to reduce the arson or accidental fire losses, we developed a gas sensitive detector used for the rapid detection and early warning of flammables in crowded places such as buses. A MEMS (Micro-Electro-Mechanical System) based thin film semiconductor was fabricated as the gas sensor. To obtain the target gas selective response, the surface of the sensitive film was modified with highly active metal catalytic nano-particles. Thus the anti-interference ability was improved and the false alarm rate was effectively reduced. Furthermore, the modular embedded system for information acquisition and transmission was developed. Supported by the Airflow Precision control system (APs), the rapid warning of volatile gas of flammable substances was realized. Experiments showed that RAs has satisfied selectivity to volatiles of usual flammable liquid, such as the output voltage reaches 3 V (0 - 3.3 V). With simulation about the actual installation state in bus, MWs sounds an alarm at 2 minutes after splashing 50 mL 92# petrol to the floor. For the last two years, FEVMEW has been integrated into more than 4000 buses in Hefei. This design has been proved feasible according to the actual operation.

Energy evolution and structural health monitoring of coal under different failure modes:An experimental study

Structural instability in underground engineering,especially in coal-rock structures,poses significant safety risks.Thus,the development of an accurate monitoring method for the health of coal-rock bodies is crucial.The focus of this work is on understanding energy evolution patterns in coal-rock bodies under complex conditions by using shear,splitting,and uniaxial compression tests.We examine the changes in energy parameters during various loading stages and the effects of various failure modes,resulting in an innovative energy dissipation-based health evaluation technique for coal.Key results show that coal bodies go through transitions between strain hardening and softening mechanisms during loading,indicated by fluctuations in elastic energy and dissipation energy density.For tensile failure,the energy profile of coal shows a pattern of “high dissipation and low accumulation” before peak stress.On the other hand,shear failure is described by “high accumulation and low dissipation” in energy trends.Different failure modes correlate with an accelerated increase in the dissipation energy before destabilization,and a significant positive correlation is present between the energy dissipation rate and the stress state of the coal samples.A novel mathematical and statistical approach is developed,establishing a dissipation energy anomaly index,W,which categorizes the structural health of coal into different danger levels.This method provides a quantitative standard for early warning systems and is adaptable for monitoring structural health in complex underground engineering environments,contributing to the development of structural health monitoring technology.

Identification of Monitoring Organ in Bivalves for Early Warning of Paralytic Shellfish Toxins Accumulation

Bivalve farming plays a dominant role in mariculture in China.Paralytic shellfish toxins(PSTs)can be accumulated in bivalves and cause poisoning the consumers.A sensitive detection of PSTs can provide early warning to decrease poisoning events in bivalve consuming.PSTs are traditionally examined using the whole soft-tissues.However,PSTs accumulation varies dramatically in different tissues of bivalves.Some tough tissues/organs(such as mantle),which account for a large proportion of the total soft body,exhibit a lower accumulation of PSTs and make the toxin extraction time-and reagent-consuming,potentially decreasing the accuracy and sensitivity of PSTs monitoring in bivalves.To develop a sensitive and cost-effective approach for PSTs examination in massively farmed bivalves,we fed three commercially important bivalves,Yesso scallop Patinopecten yessoensis,Pacific oyster Crassostrea gigas,and blue mussel Mytilus edulis with PSTs-producing dinoflagellate Alexandrium catenella,and detected PSTs concentration in different tissues.For all three bivalve species,the digestive gland accumulated much more PSTs than other tissues,and the digestive gland’s toxicity was significantly correlated with the PSTs toxicity of the whole soft-tissues,with r^(2)=0.94,0.92,and 0.94 for Yesso scallop,Pacific oyster,and blue mussel,respectively.When the toxicity of the whole soft-tissues reached 80μgSTXeq(100g)^(−1),the regulatory limit for commercial shellfish,the digestive gland’s toxicity reached 571.48,498.90,and 859.20μgSTXeq(100g)^(−1) in Yesso scallop,Pacific oyster,and blue mussel,respectively.Our results indicate that digestive gland can be used for the sensitive and cost-effective monitoring of PSTs in bivalves.

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.

Disaster reduction stick equipment: A method for monitoring and early warning of pipeline-landslide hazards

Oil and gas pipelines are of great importance in China,and pipeline security problems pose a serious threat to society and the environment.Pipeline safety has therefore become an integral part of the entire national economy.Landslides are the most harmful type of pipeline accident,and have directed increasing public attention to safety issues.Although some useful results have been obtained in the investigation and prevention of pipeline-landslide hazards,there remains a need for effective monitoring and early warning methods,especially when the complexity of pipeline-landslides is considered.Because oil and gas pipeline-landslides typically occur in the superficial soil layers,monitoring instruments must be easy to install and must cause minimal disturbance to the surrounding soil and pipeline.To address the particular characteristics of pipelinelandslides,we developed a multi-parameter integrated monitoring system called disaster reduction stick equipment.In this paper,we detail this monitoring and early warning system for pipeline-landslide hazards based on an on-site monitoring network and early warning algorithms.The functionality of our system was verified by its successful application to the Chongqing Loujiazhuang pipeline-landslide in China.The results presented here provide guidelines for the monitoring,early warning,and prevention of pipeline geological hazards.

Mechanism and monitoring and early warning technology for rockburst in coal mines

On the basis of the massive amount of published literature and the long-term practice of our research group in the field of prevention and control of rockburst,the research progress and shortcomings in understanding the rockburst phenomenon have been comprehensively in-vestigated.This study focuses on the occurrence mechanism and monitoring and early warning technology for rockburst in coal mines.Results showed that the prevention and control of rockburst had made significant progress.However,with the increasing mining depth,several unre-solved concerns remain challenging.From the in-depth research and analysis,it can be inferred that rockburst disasters involve three main problems,i.e.,the induction factors are complicated,the mechanism is still unclear,and the accuracy of the monitoring equipment and multi-source stereo monitoring technology is insufficient.The monitoring and warning standards of rockburst need to be further clarified and im-proved.Combined with the Internet of Things,cloud computing,and big data,a study of the trend of rockburst needs to be conducted.Further-more,the mechanism of multiphase and multi-field coupling induced by rockburst on a large scale needs to be explored.A multisystem and multiparameter integrated monitoring and early warning system and remote monitoring cloud platform for rockburst should be explored and developed.High-reliability sensing technology and equipment and perfect monitoring and early warning standards are considered to be the de-velopment direction of rockburst in the future.This research will help experts and technicians adopt effective measures for controlling rock-burst disasters.

Construction of multi-factor identification model for real-time monitoring and early warning of mine water inrush

As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.Due to the many factors affecting water inrush and the complicated water inrush mechanism,many factors close to water inrush may have precursory abnormal changes.At present,the existing monitoring and early warning system mainly uses a few monitoring indicators such as groundwater level,water influx,and temperature,and performs water inrush early warning through the abnormal change of a single factor.However,there are relatively few multi-factor comprehensive early warning identification models.Based on the analysis of the abnormal changes of precursor factors in multiple water inrush cases,11 measurable and effective indicators including groundwater flow field,hydrochemical field and temperature field are proposed.Finally,taking Hengyuan coal mine as an example,6 indicators with long-term monitoring data sequences were selected to establish a single-index hierarchical early-warning recognition model,a multi-factor linear recognition model,and a comprehensive intelligent early-warning recognition model.The results show that the correct rate of early warning can reach 95.2%.

Research and application of real-time monitoring and early warning thresholds for multi-temporal agricultural products information

Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.

Development and Application of Meteorological Disaster Monitoring and Early Warning Platform for Characteristic Agriculture in Huzhou City Based on GIS

Based on the needs of characteristic agricultural production for meteorological services in Huzhou City,we use C# programming language to develop the meteorological disaster monitoring and early warning platform for characteristic agriculture in Huzhou City. This platform integrates the functions of meteorological and agricultural information monitoring,disaster identification and early warning,fine weather forecast product display,and data query and management,which effectively enhances the capacity of meteorological disaster monitoring and early warning for characteristic agriculture in Huzhou City,and provides strong technical support for the meteorological and agricultural departments in the agricultural meteorological services.

A new early-warning prediction system for monitoring shear force of fault plane in the active fault

The most common method used to describe earthquake activity is based on the changes in physical parameters of the earth＇s surface such as displacement of active fault and seismic wave.However,such approach is not successful in forecasting the movement behaviors of faults.In the present study,a new mechanical model of fault activity,considering the shear strength on the fault plane and the influence of the resistance force,is established based on the occurrence condition of earthquake.A remote real-time monitoring system is correspondingly developed to obtain the changes in mechanical components within fault.Taking into consideration the local geological conditions and the history of fault activity in Zhangjiakou of China,an active fault exposed in the region of Zhangjiakou is selected to be directly monitored by the real-time monitoring technique.A thorough investigation on local fault structures results in the selection of two suitable sites for monitoring potential active tectonic movements of Zhangjiakou fault.Two monitoring curves of shear strength,recorded during a monitoring period of 6 months,turn out to be steady,which indicates that the potential seismic activities hardly occur in the adjacent region in the near future.This monitoring technique can be used for early-warning prediction of the movement of active fault,and can help to further gain an insight into the interaction between fault activity and relevant mechanisms.

Study on video intelligent early warning and tracking system based on ARM

The protrusion of the planning of numerical intelligent early-warning and tracking system in this study which can ease triggerman's work strength,lay the next generation intelligence supervision system foundation and expand effectively the video resources use etc. In the numerical intelligent early-warning matrix sub-system,the authors have designed a kind dual-core system which includes both ARM and DSP,and designed detailedly traffic dynamics affairs early-warning arithmetic which bases on that system. And then,this system will carry quickly on fixing the right position of license plate,correcting the inclination degree of license plate,and thinning it to get the number of this license and severity grade. Secondly,in the rotated dome camera sub-system,the authors have designed three-dimensional trajectory mathematical model which makes use of a fuzzy PID controller to achieve the high- speed track. At last,Simulation shows that the proposed control method has high profile tracking precision,accuracy and robustness of the disturbance.

Chinese public participation monitoring and warning system for geological hazards

In China,many geological hazards occurred in remote mountainous regions,and it was time-consuming to disseminate disaster information for the responsible parties to make timely judgements.Besides,only relying on professionals to monitor and manage disasters was demanding and costly.The Chinese government created a system to engage residents in the process of disaster risk management,namely’Public Participation Monitoring and Warning’(PPMW),to disseminate timely disaster information and bring down management costs.The objective of this system was to reduce casualties with minimum cost by organizing residents to evacuate from disasters in advance.This paper introduced the PPMW system,including its structure,operation mechanism by reviewing government documents and research articles,and its implementation by a case study of a landslide at Boli village(E 101°01’,N 27°29’),Yanyuan County,Sichuan Province,China on July 19th 2018.Further,this paper analyzed the strengths and limitations of the system and discussed its future development.It had the potential to become an affordable disaster risk management tool for other countries facing similar situations to China.

Research on Technology Early-Warning System Based on Dynamic Information Monitoring

Relying on the advanced information technologies, such as information monitoring, data mining, natural language processing etc., the dynamic technology early-warning system is constructed. The system consists of technology information automatic retrieval, technology information monitoring, technology threat evaluation, and crisis response and management subsystem, which implements uninterrupted dynamic monitoring, trace and crisis early-warning to the specific technology. Empirical study testifies that the system improves the accuracy, timeliness and reliability of technology early-warning.

An Early Warning System for Regional Rain-Induced Landslide Hazard

Landslide in alpine regions often causes heavy losses of both human lives and properties, most of the landslides are induced by heavy rainfall. In this paper, we put forward an early warning system of rain-induced landslide. From 2002, we carried on the demonstrative work of landslide monitoring and early warning in Yaan, Sichuan Province, China, and constructed the first county-scale landslide monitoring and early warning region. Yucheng District of Yaan City is located in the west of the Sichuan Basin, right in the intersection of SichuanBasin and the Tibetan Plateau. The slopes are made of Mesozoic sedimentary rock, sandstone inter-bedded with mudstone. Yucheng District has the title “sky funnel” because of the high precipitation, the annual precipitation is about 1750 mm. We carried out detailed landslide survey, and obtained the location, scale, characteristics, influence and triggering factors of the landslides. Then we assessed the regional landslide susceptibility. Based on the evolution law of the landslides, we selected ten factors to study the relationship between the factors and landslide. Using the bi-variate statistics method, we calculated the contribution to landslide from each factor, classified the susceptibility into four categories. We set up the regional rainfall monitoring network with 13 automatic CAWS600R rain gauges. Using the landslide survey data, we studied the rainfall influencing of the regional landslides. The one-day and three-day rainfall controls the occurrence of regional landslide. We also classified the triggering effect of rainfall into four categories. We presented a method to calculate the landslide danger degree using the susceptibility and triggering category. Utilizing the predicted rainfall data and real-time monitored rainfall data, together with the landslide susceptibility map, we developed a WebGIS-based landslide warning system, which greatly strengthened the capability for geohazard control.

Probabilistic rainfall thresholds in Chibo, India: estimation and validation using monitoring system

The Himalayan region has been severely affected by landslides especially during the monsoons. In particular, Kalimpong region in Darjeeling Himalayas has recorded several landslides and has caused significant loss of life, property and agricultural land. The study region, Chibo has experienced several landslides in the past which were mainly debris and earth slide. Globally, several types of rainfall thresholds have been used to determine rainfall-induced landslide incidents. In this paper, probabilistic thresholds have been defined as it would provide a better understanding compared to deterministic thresholds which provide binary results, i.e., either landslide or no landslide for a particular rainfall event. Not much research has been carried out towards validation of rainfall thresholds using an effective and robust monitoring system. The thresholds are then validated using a reliable system utilizing Microelectromechanical Systems(MEMS) tilt sensor and volumetric water content sensor installed in the region. The system measures the tilt of the instrument which is installed at shallow depths and is ideal for an early warning system for shallow landslides. The change in observed tilt angles due to rainfall would give an understanding of the applicability of the probabilistic model. The probabilities determined using Bayes' theorem have been calculated using the rainfall parameters and landslide data in 2010-2016. The rainfall values were collected from an automatic rain gauge setup near the Chibo region. The probabilities were validated using the MEMS based monitoring system setup in Chibo for the monsoon season of 2017. This is the first attempt to determine probabilities and validate it with a robust and effective monitoring system in Darjeeling Himalayas. This study would help in developing an early warning system for regions where the installation of monitoring systems may not be feasible.