斜拉桥结构健康监测系统的设计与实现(Ⅱ):系统实现

采用"斜拉桥结构健康监测系统的设计与实现(Ⅰ)-系统设计"中所建立的设计方法,分别为两座大型斜拉桥设计并实现长期实时健康监测系统和定期实时健康监测系统滨州黄河公路大桥长期实时健康监测系统和哈尔滨松花江大桥定期实时健康监测系统.研究两座大型斜拉桥结构健康监测系统的总体设计方案、子系统的设计方案和硬软件设备及其实现、系统的集成技术及其实现方法;分析两套健康监测系统在成桥试验和运营中监测的桥梁结构荷载和静动力反应.结果表明,两座斜拉桥结构健康监测系统均能协调运行,实现了预期设计功能;系统中布设的光纤光栅应变和温度传感器测试精度高、耐久性好、抗电磁干扰性能强;系统中建立的远程无线微波通讯系统可以实时传输和再现监测信号.     

斜拉桥结构健康监测系统的设计与实现(II):系统实现

采用“斜拉桥结构健康监测系统的设计与实现(I)-系统设计”中所建立的设计方法,分别为两座大型斜拉桥设计并实现长期实时健康监测系统和定期实时健康监测系统:滨州黄河公路大桥长期实时健康监测系统和哈尔滨松花江大桥定期实时健康监测系统。研究两座大型斜拉桥结构健康监测系统的总体设计方案、子系统的设计方案和硬软件设备及其实现、系统的集成技术及其实现方法;分析两套健康监测系统在成桥试验和运营中监测的桥梁结构荷载和静动力反应。结果表明,两座斜拉桥结构健康监测系统均能协调运行,实现了预期设计功能;系统中布设的光纤光栅应变和温度传感器测试精度高、耐久性好、抗电磁干扰性能强;系统中建立的远程无线微波通讯系统可以实时传输和再现监测信号。     

基于动态测试的轧钢厂过桥结构损伤监测

宝钢梅山粗轧过桥结构主要是在施工轧机基础期问为辊道设备提供结构悬挂支撑、对宝钢梅山技改工作中的过桥结构进行实时状态监测，将采集到的结构信息与信息库中的数据相比较，实现结构运行状态实时监测与损伤定位，进而可采取应对措施。结构频率是较易测得的结构模态参数，利用结构频率的平方变化比是损伤位置的函数，据此作为损伤定位的依据简单可靠，具有较高的应用价值。     

雄安站屋盖钢结构无线健康监测系统设计与开发

雄安站屋盖呈椭圆形平面,长轴为450m,短轴为355.5m,其主体结构采用大跨度空间钢结构体系.为了探究该屋盖结构实际受力与变形状态,提高结构运营期间的安全性,设计并开发针对雄安站屋盖结构的无线健康监测系统.详细介绍传感器选型和测点布设方案,建立以应变、位移和温度传感器为基础的全方位结构健康监测感知层,构建以传感器节点、通信路由节点与基站进行数据信息交互的树形网络拓扑传输层,开发集成数据查询、设备管理和报警维护等多种功能的结构监测智慧平台分析层.现场实测数据的分析结果验证了该无线健康监测系统的有效性.该无线健康监测系统的应用,实现了对结构状态的实时掌握,有助于保障雄安站的安全运维.     

基于无线传感器网络的高层建筑健康监测系统

针对高层建筑健康监测困难的问题,提出了一套基于无线传感器网络的高层建筑健康监测系统,从集成通讯模块、数据汇总节点、网络数据通讯等方面,对整个系统的设计方法进行了论述,分析了C/S结构和B/S结构的特点,并结合实例对该监测系统的具体应用进行了说明,实现了高层建筑的实时动态监控。     

天津永和大桥健康监测系统集成与实现技术研究

文中以天津永和大桥为例,介绍了该桥在维修加固后,为了及时发现导致桥梁重大灾害的结构损伤,提高桥梁的安全性和可靠性,延长桥梁的使用寿命,提高桥梁的管理水平,设计和实现了桥梁健康监测系统,给出了系统的整体框架,分析了系统的功能构成.整个系统在天津永和大桥上进行了集成和实施,通过分析和处理实时采集的结构作用荷载数据和结构响应数据,对桥梁的运营状态进行安全评定,并通过互联网实现了大桥的远程监测与预警功能.     

工程车辆运行参数实时监测报警系统设计与开发

介绍了工程车辆运行参数实时监测报警系统的总体结构、主要硬件电路设计和软件开发,并简要介绍了系统所采取的抗电磁干扰措施。该系统实现了对工程车辆运行参数的实时监测、故障诊断与报警、故障参数的记录与查询等功能。     

大型桥梁结构智能健康监测系统集成技术研究

首先分析研究了桥梁健康监测系统的各个子系统的功能、特点、实现方法与硬软件系统,研究了完成桥梁健康监测任务对各个子系统协同工作的要求。提出了以LabW indows/LabVIEW为桥梁健康监测系统的核心软件,由它“指挥”、调用和驱动各个子系统的运行和数据的交互与通讯;以数据管理子系统的数据库作为桥梁健康监测系统的中心数据库,它不仅存储桥梁结构及其监测数据的全部信息,同时所有的数据交互均通过该数据库完成。建议采用B rower/Server系统模式将桥梁结构健康监测的各子系统相互结合,建立基于网络平台的开放式的实时在线智能健康监测系统。最后,为一座实际的三塔斜拉桥集成了一套健康监测系统。     

深基坑无线实时监测系统

为确保深基坑修建过程安全质量,结合深基坑现场修建情况,引入了无线实时监测系统.首先,阐释了深基坑无线实时监测系统的运行原理;其次,讨论了深基坑无线实时监测系统的设计结构和功能组成;最后,结合深基坑工程项目,介绍了深基坑无线实时监测系统布点方案以及监测指标,希望为深基坑开挖、降水安全管理提供一些参考.     

深圳平安金融中心结构健康监测系统应用

以深圳平安金融中心为平台,设计了一套集成的健康监测系统对塔楼在施工阶段和使用阶段的施工环境、结构荷载和响应进行连续实时监测。本文从项目简介、模块化设计、设备空间布置和硬软件组织架构四个方面介绍了深圳平安健康监测系统的总体概况;详细阐述了监测系统的组成和六个子结构系统的功能,包括传感器系统、数据采集和传输系统、数据处理与评估系统、数据管理系统、结构健康评估系统和支持保护系统,并对监测系统的开发和应用情况进行了简介;模块化的设计思想使各个子结构系统在独立运行的同时,又与其他子结构系统协同工作,并保证了监控体系具有充分的可扩充性和升级能力。最后描述了监测系统在现场施工过程中的注意事项,为其他工程结构健康监测系统的开发和实际应用提供宝贵经验。     

Investigation concerning structural health monitoring of an instrumented cable-stayed bridge

In Hong Kong, a sophisticated long-term structural health monitoring system has been devised by the Highways Department of HKSAR Government to monitor the structural performance and health conditions of three cable-supported bridges. On-structure instrumentation systems for two new long-span bridges are also being implemented. The implementation of these monitoring systems highlights the necessity for developing a monitoring-based structural health evaluation paradigm for long-span bridges. This paper describes the research directed towards this that has been conducted in the Hong Kong Polytechnic University. Taking the instrumented cable-stayed Ting Kau Bridge as a paradigm, the research covers the development of an index system and a database system for monitoring data management, the modelling of the environmental variability of measured modal properties with the intention of eliminating environmental effects in vibration-based damage detection, and the feasibility of using measured modal properties from the deployed vibration sensors for structural damage identification.     

Structural Health Monitoring System for the Shandong Binzhou Yellow River Highway Bridge

Abstract:   Structural health monitoring (SHM) provides a useful tool for ensuring safety and detecting the evolution of damage and performance deterioration of civil infrastructures. A great number of civil infrastructures under construction can be used as test beds for SHM systems. The Binzhou Yellow River Highway Bridge is a cable-stayed bridge in Shandong Province, China. An SHM system has been implemented on this bridge during its construction for monitoring its health status and assessing its safety for long-term services. The system includes a sensor module, a data acquisition module, a wired and wireless data transmit module, a structural analysis module, a database module, and a warning module. It is integrated by using LabVIEW software and can be remotely operated via Internet. The database is available freely to all scientists and engineers in the SHM research area. This article introduces the deployment and functions of this system, and presents the measured responses of the bridge subjected to moving vehicle loads.     

A scalable cloud-based cyberinfrastructure platform for bridge monitoring

Cloud computing is a computing paradigm wherein computing resources, such as servers, storage and applications, can be provisioned and accessed in real time via advanced communication networks. In the era of Internet of Things (IoT) and big data, cloud computing has been widely developed in many industrial applications involving large volume of data. Appropriate use of cloud computing infrastructure can enhance the long-term deployment of a structural health monitoring (SHM) system which would incur significant amount of data of different types. This paper presents a cloud-based cyberinfrastructure platform designed to support bridge monitoring. The cyberinfrastructure platform enables scalable management of SHM data and facilitates effective information sharing and data utilisation. A cloud-based platform comprises of virtual machines, distributed database and web servers. The peer-to-peer distributed database architecture provides a scalable and fault-tolerant data management system. Platform-neutral web services designed in compliant with the Representational State Transfer (REST) standard enables easy access to the cloud resources and SHM data. For data interoperability, a bridge information model for bridge monitoring applications is adopted. For demonstration, the scalable cloud-based platform is implemented for the monitoring of bridges along the I-275 corridor in the State of Michigan. The results show that the cloud-based cyberinfrastructure platform can effectively manage the sensor data and bridge information and facilitate efficient access of the data as well as the bridge monitoring software services.     

基于改进YOLOv3 的无人机林火监测系统设计与实现

以无人机为飞行平台，基于目标检测技术设计并实现了一套林火监测系统，针对原生态YOLOv3 算法在烟雾与火焰检测时表现不佳，从增加NMS 和重新聚类Anchors 两个方面对算法进行改进，检测准确率和召回率分别提高了6.8% 、11.92%。该系统无论昼夜都可实时监测森林火灾，提高了森林防火安全防范的能力和林火预警的自动化、数字化水平。     

Frontier of continuous structural health monitoring system for short & medium span bridges and condition assessment

It is becoming an important social problem to make maintenance and rehabilitation of existing short and medium span(10-20 m) bridges because there are a huge amount of short and medium span bridges in service in the world. The kernel of such bridge management is to develop a method of safety(condition) assessment on items which include remaining life and load carrying capacity. Bridge health monitoring using information technology and sensors is capable of providing more accurate knowledge of bridge performance than traditional strategies. The aim of this paper is to introduce a state-of-the-art on not only a rational bridge health monitoring system incorporating with the information and communication technologies for lifetime management of existing short and medium span bridges but also a continuous data collecting system designed for bridge health monitoring of mainly short and medium span bridges. In this paper, although there are some useful monitoring methods for short and medium span bridges based on the qualitative or quantitative information, mainly two advanced structural health monitoring systems are described to review and analyse the potential of utilizing the long term health monitoring in safety assessment and management issues for short and medium span bridge. The first is a special designed mobile in-situ loading device(vehicle) for short and medium span road bridges to assess the structural safety(performance) and derive optimal strategies for maintenance using reliability based method. The second is a long term health monitoring method by using the public buses as part of a public transit system (called bus monitoring system) to be applied mainly to short and medium span bridges, along with safety indices, namely, “characteristic deflection” which is relatively free from the influence of dynamic disturbances due to such factors as the roughness of the road surface, and a structural anomaly parameter.     

Deep learning for data anomaly detection and data compression of a long‐span suspension bridge

As intelligent sensing and sensor network systems have made progress and low‐cost online structural health monitoring has become possible and widely implemented, large quantities of highly heterogeneous data can be acquired during the monitoring. This has resulted in exceeding the capacity of traditional data analytics techniques, especially in monitoring large‐scale or critical civil structures. In particular, data storage has become a big challenge, hence, resulting in the emergence of data compression and reconstruction as a new area in structural health monitoring (SHM) of large infrastructure systems. SHM data generally include anomalies that can disturb structural analysis and assessment. The fundamental reasons for the abnormality of data are extremely complex. Therefore, reconstruction of the abnormal data is generally difficult and poses serious challenges to achieve high‐accuracy after data has been compressed. Considering these significant challenges, in this paper, a novel deep‐learning‐enabled data compression and reconstruction framework is proposed that can be divided into two phases: (a) a one‐dimensional Convolutional Neural Network (CNN) that extracts features directly from the input signals is designed to detect abnormal data with validated high accuracy; (b) a new SHM data compression and reconstruction method based on Autoencoder structure is further developed, which can recover the data with high‐accuracy under such a low compression ratio. To validate the proposed approach, acceleration data from the SHM system of a long‐span bridge in China are employed. In the abnormal data detection phase, the results show that the proposed method can detect anomaly with high accuracy. Subsequently, smaller reconstruction errors can be achieved even by using only 10% compression ratio for the normal data.     

Development and application of a multi-channel monitoring system for near real-time VOC measurement in a hazardous waste management facility

This paper describes the development and application of a multi-channel monitoring system for recording, processing, and analyzing volatile organic compound (VOC) levels discharged to the atmosphere from a walk-in hood in a hazardous waste management facility. The monitoring system consists of an array of PID (photo ionization detector) sensors and a networked control program that provides operational schematic diagram, performs data analyses, and illustrates real-time graphical displays. Furthermore, the system records potential worker exposures, exhaust filtration efficiency and environmental release levels. Multi-channel continuous monitoring of VOCs is successfully implemented during chemical bulking operations. It is shown that a real-time monitoring system is effective for early warning detection of hazardous chemicals and for predicting the performance of adsorption filters used for VOC removal. In addition, a connected local weather visualization system supports efforts to minimize potential health and environmental impacts of VOC emissions to surrounding areas.     

FRPFP模型滑坡监测预警关联规则挖掘分析——以三峡库区江津到奉节段为例

采用传统的关联规则用于岩土工程监测预警领域的知识发现,在数据庞大情形下单机机器学习实时性差,无法获得多因素综合作用的规则。由于未对前后部项进行约束,得到的关联规则冗余度高,含有大量不符因果逻辑的规则。基于此,提出一种前后部项约束关联规则并行化FRPFP (fore-part and rear-part parallel FP-growth)算法,并在大数据分布式处理平台Spark下进行实现。通过对三峡库区奉节至江津库段滑坡的孕灾因子统计分类,采用7个滑坡发育基础因子和4个滑坡诱导因子作为前部集合,滑坡前缘、中部、后缘监测点位移参数为后部集合,采集研究区25个滑坡11年监测数据。以FRPFP算法为模型架构基于关联规则的滑坡监测预警大数据系统,设计区域滑坡危险性规则挖掘、典型滑坡危险性规则挖掘、滑坡发生原因分析挖掘3个功能,用于库岸滑坡稳定性预测和分析,为认清库岸滑坡的破坏机制和提升其预报水平提供新的思路。     

国家体育馆安全监测系统研究

国家体育馆屋盖结构为双向张弦网格结构体系.为保证屋盖结构在奥运期间和今后正常使用期间安全服役,在屋盖结构系统中引入了永久健康监测系统.该监测系统包括监测仪器、数据采集系统和数据分析与处理软件三部分,可以随时对屋盖结构的受力性能、变形状态进行监测.此外,介绍健康监测系统性能,包括稳定性、抗干扰性和远程监控.并分析钢结构变形、索力和应力监测结果.监测结果表明国家体育馆健康监测系统技术先进,稳定可靠.     

兰华国际大厦工程圆柱形天桥钢结构安装技术

北京兰华国际大厦天桥采用全钢结构,施工中通过采用合理的预设起拱、安装技术、焊接工艺及施工监测等措施,圆满完成了施工任务。