变形监测网平差分析系统设计

针对变形监测长期性、重复性、高精度性的特点,利用VB6开发了变形监测网平差分析子系统(DMAAS),系统集数据输入、计算、检验、查询、分析等功能于一体,为建筑物变形监测资料处理和分析提供了一种有效工具。

浅析数字电视监测系统

本文浅析数字电视传输监测系统的发展和实际应用

无线广播电视监测网及安全策略

随着生活水平的提高,越来越多人开始注重广播电视节目的播出质量和效果,而无线广播电视监测网正是节目收看效果的重要保障。本文简要介绍了无线广播电视网络,阐述了无线广播电视监测网系统的基本组成:包括广播数据处理系统和电视监测前端系统,最后从网络安全、主机系统安全、数据安全、安全管理等方面重点介绍了无线广播电视监测网的安全保障体系,希望能够减少广播电视播出故障,为广大观众提供更加优质的广播内容。

A Real-time Monitoring and Early Warning System for Landslides in Southwest China

Landslides not only cause property losses,but also kill and injure large numbers of people every year in the mountainous areas. These losses and casualties may be avoided to some extent by early warning systems for landslides. In this paper, a realtime monitoring network and a computer-aided automatic early warning system(EWS) are presented with details of their design and an example of application in the Longjingwan landslide, Kaiyang County, Guizhou Province. Then, according to principle simple method of landslide prediction, the setting of alarm levels and the design of appropriate counter-measures are presented. A four-level early warning system(Zero, Outlook, Attention and Warning) has been adopted, and the velocity threshold was selected as the main warning threshold for the landslide occurrence, but expert judgment is included in the EWS to avoid false alarms. A case study shows the applicability and reliability for landslide risk management, and recommendations are presented for other similar projects.

Analyses of Trawling Track and Fishing Activity Based on the Data of Vessel Monitoring System(VMS): A Case Study of the Single Otter Trawl Vessels in the Zhoushan Fishing Ground

The original purpose of Vessel Monitoring System(VMS) is for enforcement and control of vessel sailing. With the application of VMS in fishing vessels, more and more population dynamic studies have used VMS data to improve the accuracy of fisheries stock assessment. In this paper, we simulated the trawl trajectory under different time intervals using the cubic Hermite spline(c Hs) interpolation method based on the VMS data of 8 single otter trawl vessels(totally 36000 data items) fishing in Zhoushan fishing ground from September 2012 to December 2012, and selected the appropriate time interval. We then determined vessels' activities(fishing or non-fishing) by comparing VMS speed data with the corresponding speeds from logbooks. The results showed that the error of simulated trajectory greatly increased with the increase of time intervals of VMS data when they were longer than 30 minutes. Comparing the speeds from VMS with those from the corresponding logbooks, we found that the vessels' speeds were between 2.5 kn and 5.0 kn in fishing. The c Hs interpolation method is a new choice for improving the accuracy of estimation of sailing trajectory, and the VMS can be used to determine the vessels' activities with the analysis of their trajectories and speeds. Therefore, when the fishery information is limited, VMS can be one of the important data sources for fisheries stock assessment, and more attention should be paid to its construction and application to fisheries stock assessment and management.

Coal mine gas monitoring system based on wireless sensor network

Based on the nowadays＇ condition, it is urgent that the gas detection cable communication system must be replaced by the wireless communication systems. The wireless sensors distributed in the environment can achieve the intelligent gas monitoring system. Apply with multilayer data fuse to design working tactics, and import the artificial neural networks to analyze detecting result. The wireless sensors system communicates with the control center through the optical fiber cable. All the gas sensor nodes distributed in coal mine are combined into an intelligent, flexible structure wireless network system, forming coal mine gas monitoring system based on wireless sensor network.

Energy optimal routing for long chain-type wireless sensor networks in underground mines

Wireless sensor networks are useful complements to existing monitoring systems in underground mines. They play an important role of enhancing and improving coverage and flexibility of safety monitoring systems.Regions prone to danger and environments after disasters in underground mines require saving and balancing energy consumption of nodes to prolong the lifespan of networks.Based on the structure of a tunnel,we present a Long Chain-type Wireless Sensor Network（LC-WSN）to monitor the safety of underground mine tunnels.We define the optimal transmission distance and the range of the key region and present an Energy Optimal Routing（EOR）algorithm for LC-WSN to balance the energy consumption of nodes and maximize the lifespan of networks.EOR constructs routing paths based on an optimal transmission distance and uses an energy balancing strategy in the key region.Simulation results show that the EOR algorithm extends the lifespan of a network,balances the energy consumption of nodes in the key region and effectively limits the length of routing paths,compared with similar algorithms.

Smart Cities as Cyber-Physical Social Systems

The emerging prototype for a Smart City is one of an urban environment with a new generation of inno- vative services for transportation, energy distribution, healthcare, environmental monitoring, business, commerce, emergency response, and social activities. Enabling the technology for such a setting re- quires a viewpoint of Smart Cities as cyber-physical systems （CPSs） that include new software platforms and strict requirements for mobility, security, safety, privacy, and the processing of massive amounts of information. This paper identifies some key defining characteristics of a Smart City, discusses some lessons learned from viewing them as CPSs, and outlines some fundamental research issues that remain largely open.

Digital Solution to Mining Image Monitor System

The thesis describes an advanced digital solution to mining digital image monitor system, which makes up the shortage of the traditional mining analog image monitor. It illustrates the system components and how to choose the encoder bandwidth of the system. The problem of image multicast and its solution in LAN are also discussed.

An Overlay Network for Monitoring Activities of Computer Viruses

To accurately track computer viruses,an overlay network that monitors the activities of viruses is constructed.Identifying and locating nodes infected by virus on network is achieved by a naming system in which a node in the network is mapped to a unique serial number of the hard-drive.By carefully monitoring and recording sensitive communication between local system and remote nodes on the network,and suspicious operations on files that originate from remote nodes and entered via some form of file transfer,activities of viruses in both local and network level are recorded and ready for future analysis.These data can also be used in analysis of the mechanism of a computer virus as well as its spreading mode and pattern.

Integrated real-time roof monitoring

CSIRO has recently developed a real-time roof monitoring system for under-groundcoal mines and successfully tried the system in gate roads at Ulan Mine.The systemintegrated displacement monitoring,stress monitoring and seismic monitoring in onepackage.It included GEL multianchor extensometers,vibrating wire uniaxial stress meters,ESG seismic monitoring system with microseismic sensors and high-frequency AE sensors.The monitoring system automated and the data can be automatically collected by acentral computer located in an underground nonhazardous area.The data are then transferredto the surface via an optical fiber cable.The real-time data were accessed at anylocation with an Internet connection.The trials of the system in two tailgates at Ulan Minedemonstrate that the system is effective for monitoring the behavior and stability of roadwaysduring Iongwall mining.The continuous roof displacement/stress data show clearprecursors of roof falls.The seismic data (event count and locations) provide insights intothe roof failure process during roof fall.

Design of intelligent transformer monitoring system based on GSM

This paper proposes a method for transformer fault detection system based on GSM network, through the current transformer, voltage sensor information, the known fault information attribute conditions, and the feedback weighted coefficient through the adaptive feed forward, that can obtain high fault information attributes, thus filtering interference factors and timely get fault information properties. It solves the traditional transformer can only judge general fault and fault real-time alarm by GSM network, the system also can measure the transformer oil temperature and oil temperature alarm in super high temperature, to detect the power transformer operation parameters, and the fault running state （over-current, over-voltage, under-voltage, warning）. The actual test system show that, diagnosis ability of fault signal separation ability and small signal identification increases 17%. also meet the requirements of real-time.

Human Errors Monitoring in Electrical Transmission Networks

The electrical transmission networks are complex systems that are commonly run near their operational limits. Such systems can undergo major disturbances that have serious consequences. Individually, these disturbances can be attributed to specific causes, such as lightning strikes, ice storms, equipment failure, shorts resulting from untrimmed trees, excessive customer demand, or human errors. In the paper, the human errors from electrical transmission networks of Romanian Power Grid Company over period of 10 years are analyzed. It is hoped that obtained results will provide engineers a better understanding so they can cater to the needs of the human operators when to implement new interfaces for network monitoring tasks, not for the other technical objectives.

Seismic Health Monitoring of Foundations Using Artificial Neural Networks

Damage identification plays an important role in structural health monitoring systems. Despite variety in damage identification methods, little attention has been paid to the seismic damage identification of foundations. When shear walls serve as the lateral load resistance system of structures, foundations may subject to the high level of concentrated moment and shear forces. Consequently, they can experience severe damage. Since such damage is often internal and not visible, visual inspections cannot identify the location and the severity of damage. Therefore, a robust method is required for damage localization and quantification of foundations. According to the concept of performance-based seismic design of structures, the seismic behavior of foundations is considered as Force-Controlled. Therefore, for damage identification of foundation, internal forces should be estimated during ground motions. In this study, for real-time seismic damage detection of foundations, a method based on artificial neural networks was proposed. A feed-forward multilayer neural network with one hidden layer was selected to map input samples to output parameters. The lateral displacements of stories were considered as the input parameters of the neural network while moment and shear force demands at critical points of foundations were taken into account as the output parameters. In order to prepare well-distributed data sets for training the neural network, several nonlinear time history analyses were carried out. The proposed method was tested on the foundation of a five-story concrete shear wall building. The obtained results revealed that the proposed method was successfully estimated moment and shear force demands at the critical points of the foundation.

Design and Realization of Distribution Network Intelligent Monitoring based on GSM Network

the power network fault detection system can only analyze all kinds of fault signal in stationary sequence： the internal grid and external disturbance presents degeneration, tiny, signal intensity changes randomly fluctuate, that will cause the system to detect the fault isolation ability of confusion and small fault signal is not strong; The article propose a method of power network fault detection for based on GSM, Through the underlying sensing equipment acquisition abnormal information of current, voltage power in the network and GSM networking scheme can filter the interference factors in extraction of fault information from and attribute value. The embedded gateway take STM32 chip as the core to monitoring data processing, to achieve a unified data management and user remote access, realizing method of system software are given, to construct the monitor management information platform. The actual test system show that, identification diagnosis ability of fault signal separation ability and small signal increases 17%, also meet the requirements.

The Jinsha River Groundwater Observation Network and Discussion about Its Earthquake Precursor Monitoring Capability

A groundwater observational network for monitoring seismic precursors has been established at the reservoirs on the lower reaches of the Jinsha River in southwestern China, where a series of hydropower stations are under construction. It is the second network in China that is operated by enterprises with the purpose to observe and study earthquake precursors in reservoir areas. This paper presents the layout and technical constitution of the network, features of its observational wells and aquifers and the preliminary result of its experimental operation. Its capability to monitor seismic precursor is evaluated based on an analysis of the well-aquifer system as well as the multiple-monthly, monthly, daily and hourly variations of water levels and water temperatures observed by this network.

CForBio： a network monitoring Chinese forest biodiversity

China harbors a rich variety of forest types and forest-associated biodiversity, linked to both historical and contemporary environmental factors. However, being a country with a large population and rapid economic development, its diverse forest is facing unprecedent challenges. The Chinese Forest Biodiversity Network （CForBio） was initiated 12 years ago to study the mainte- nance of biodiversity in China＇s forest ecosystems. In this review, we first summarize research progress in CForBio, and then give suggestions for future research. In the past 12 years, the research based on CForBio mainly focused on local ecological factors, such as environment filtering, biotic interactions and small-scale dispersal limitation. We suggest that future studies in CForBio should （1） continue research on trees, but expand more on insects, birds, mammals, microbes and other organism groups; （2） investigate the effects of widespread defaunation on forest biodiversity, structure and functioning; （3） evaluate the diverse effects of climate change on forest composition,structure and functioning; （4） include new technologies, such as remote sensing, to better monitor and study forest biodiversity change and maintenance.