基于互联网的电网监测诊断系统

为了实现远程监测诊断，在TCP／IP协议下，利用有效的网络资源，ASP和socket技术，采用易于扩展的客户／服务器结构模型来设计系统，并在Internet和Windows环境下，实现远程电网监测诊断系统。     

基于CORBA的远程诊断系统模型

介绍了三层C／S结构及CORBA的概念和特点，根据远程诊断活动的技术需求，提出一个基于CORBA的远程诊断系统模型，并讨论了其组成部分、功能及所涉及的关键实现技术。     

基于B/S结构的远程故障诊断系统的研究

分析了基于Internet的远程故障诊断系统的可行性，优越性．介绍了诊断系统的Browser／Server体系结构，简述了远程故障诊断的系统框架和主要功能模块，同时指出了诊断系统的自学能力特点．系统自我完善、自我更新的智能化功能。     

基于C／S模式的远程虚拟仪器测控系统及其实现

基于客户／服务器Ｃ／Ｓ模式的远程虚拟仪器系统是在现有基础上将虚拟仪器技术与客户／服务器技术相结合,构造出一种灵活的测控系统结构。论述了Ｃ／Ｓ模式测控系统原理及结构,并结合实例进行了讨论。     

基于B/S模型的设备远程诊断系统的研究

针对某测量船所开发的远程诊断的原型系统,讨论了其于B／S结构模型远程故障诊断系统的组成、结构,介绍了其逻辑三层结构,以及各个组成部分的内容、功能和相互之相的关系,研究了系统开发实现技术。     

水轮发电机组振动监测及其在远程故障诊断中的应用

本文介绍了基于虚拟仪器技术研究而用实时嵌入式操作系统实现的水轮发电机组振动的监测系统．该智能实时远程故障诊断系统具有推广应用的价值。     

快速构建基于Web的远程测控系统

文章分析了测控领域中两种类型的远程测控系统,论述了利用虚拟仪器和Internet技术快速构建基于Web的远程测控系统的方法。利用该方法构建了基于Web的远程在线监测诊断系统,并深入讨论了减少网路流量的途径。     

基于DataSocket的远程故障诊断数据传输

海军电子设备的发展向自动测试系统提出了更高的要求,基于NI公司的虚拟仪器开发平台LabVIEW及DataSocket技术构建的监测和诊断系统,可以使数据进行实时传输.文中介绍了DataSocket技术的特点以及其在组建电子设备远程故障诊断系统中的应用实例.     

基于虚拟仪器的电能质量网络监测系统的实现

基于虚拟仪器的电能质量网络监测系统是把网络技术与虚拟仪器相结合，构成的网络虚拟仪器系统，本文介绍了系统的网络结构，虚拟仪器的总体设计，论述了部分电能质量参数监测的软件设计，最后论述了实现远程监测的方法。     

基于虚拟仪器技术的谐波在线监测系统的设计与实现

一种基于虚拟仪器技术的谐波在线监测系统的设计方法，可以用于电力系统谐波在线远程监测。文中论述了监测系统的硬件结构、软件平台及应用软件的工作模式。通过应用虚拟仪器技术和网络技术进行谐波测量和数据传输处理，并得出实验结果，从而实现了电力系统谐波远程监测的目的。     

Identification of coexistent load and damage

Load reconstruction and damage identification are crucial problems in structural health monitoring. However, it seems there is not much investigation on identification of coexistent load and damage, although in practice they usually exist together. This paper presents a methodology to solve this problem based on the Virtual Distortion Method. A damaged structure is modeled by an equivalent intact structure subjected to the same loads and to virtual distortions which model the damages. The measured structural response is used to identify the loads, the distortions and to recover the stress-strain relationship of the damaged elements. This way both the damage type and extent are identified. The approach can be used off-line and online by repetitive applications in a moving time window. A numerical experiment of a truss with 5% measurement error validates that the two tested damage types (constant stiffness reduction and breathing crack) can be identified along with the loads.     

基于HHT的复合材料层合板结构损伤识别

针对航空飞行器复合材料层合板结构的健康监测,提出一种基于HHT的新型损伤特征量提取方法.利用结构动态响应信号的Hilbert能量谱构造了损伤特征量,用以表征信号的能量变化,从而对带损伤结构进行损伤识别.通过光纤布拉格光栅(FBG)加速度传感器采集数据,比较复合材料层合板在完好和带损伤两种情况下的信号能量变化,实现了对结构小损伤的识别.试验结果表明,构造的结构损伤特征量可以应用于复合材料层合板的结构健康监测,具有良好的灵敏度和实用性.     

Degradation evaluation of lateral story stiffness using HLA-based deep learning networks

Hysteresis loop analysis (HLA) has proven an effective indicator of damage detection in civil engineering structural health monitoring (SHM). In this paper, the histogram of stiffness (HOS) features are extracted from segregated half cycles of hysteresis loops reconstructed from measured response. A deep learning network (DLN) is proposed with the use of the HOS to classify the damage index (DI) based on stiffness degradation for damage identification. Training data are obtained using numerical simulations of 30,000 realistic, randomly created hysteresis loops, including a wide range of typical linear and nonlinear structural behaviours. Performance of the trained DLN model is assessed using both 1800 additional simulated 3-story “virtual” buildings and experimental data from a 3-story full-scale real building. Results are compared to the validated HLA method.Validation on simulated virtual building data yields prediction accuracy for 97.2% and 91.6% samples without and with 10% added noise, respectively. The comparison shows a good match of trend and percentage stiffness drop between DLN and HLA identification with the average difference for all cases within 1.1–4.6%, indicating a good accuracy of the proposed DLN prediction model for real structures. The overall results show its potential to provide a rapid, and real-time alarm or other notice on damage states and mitigation to emergency response using DLN and thus without detailed engineering analysis.     

利用CVI进行虚拟仪器友好界面的开发

首先介绍了虚拟仪器及其软件开发平台，然后，通过与传统仪器应用面板的比较，着重阐述了利用LabWindows／CVI对虚拟仪器友好界面的开发。     

Structural damage identification by adding virtual masses

This paper presents a method for damage identification by adding virtual masses to the structure in order to increase its sensitivity to local damages. The main concept is based on the Virtual Distortion Method (VDM), which is a fast structural reanalysis method that employs virtual distortions or pseudo loads to simulate structural modifications. In this paper, the structure with an added virtual mass is called the virtual structure. First, the acceleration frequency response of the virtual structure is constructed numerically by the VDM using local dynamic data measured only by a single excitation sensor and a single acceleration sensor. Second, the value of the additional mass is determined via sensitivity analysis of the constructed frequency responses of the virtual structure with respect to damage parameters; only the natural frequencies with high sensitivity are selected. This process is repeated for all the considered placements of the virtual mass. At last, the selected natural frequencies of all the virtual structures are used together for damage identification of the real structure. A finite element (FE) model of a plane frame is used to introduce and verify the proposed method. The damage can be identified precisely and effectively even under simulated 5 % Gaussian noise pollution.     

基于CRIO和无线传输的结构损伤主动监测系统设计

飞机结构损伤监测技术是确保其结构完整性、可靠性和安全性的关键技术。为了实现飞机大面积曲面结构的主动损伤监测，利用柔韧性良好的0-3型压电涂层复合材料和Lamb波传播距离远及对细微缺陷的高敏感性，基于CRIO(Compact RIO)平台和LabVIEW环境设计了结构损伤监测的软硬件系统。系统由激励探头、压电涂层传感器阵列、CRIO数据采集平台、WiFi无线传输网络、监测中心上位机及软件等部分组成，研制的压电涂层传感器能够较好地贴合于机翼等曲面结构，应用CRIO技术实现了测试设备的可重复配置与快速测试，无线数据传输能够克服大量传感器布置带来的布线复杂问题。将该系统应用于曲面铝板损伤监测模拟实验，验证了该系统测试信号的有效性和损伤定位结果的准确性。     

网络化学虚拟仪器系统的构建与应用

基于LabVIEW 8.0的C/S、B/S两种网络通信模式,构建网络化学虚拟仪器系统,以C/S模式实现远程实时监控多个以常规带串行口的WZZ-2B旋光仪、精密数字温差仪组建的现场测试虚拟仪器;以B/S模式,在Web中实现远程实时动态操控测试现场电导率虚拟仪器。应用结果表明:应用LabVIEW 8.0的C/S和B/S模式,可快捷构建用于不同测试目的远程监控的网络化学虚拟仪器,实现远程共享的化学虚拟仪器。     

Two-stage structural damage detection using fuzzy neural networks and data fusion techniques

It is proposed in this paper a novel two-stage structural damage detection approach using fuzzy neural networks (FNNs) and data fusion techniques. The method is used for structural health monitoring and damage detection, particularly for cases where the measurement data is enormous and with uncertainties. In the first stage of structural damage detection, structural modal parameters derived from structural vibration responses are fed into an FNN as the input. The output values from the FNN are defuzzified to produce a rough structural damage assessment. Later, in the second stage, the values output from three different FNN models are input directly to the data fusion center where fusion computation is performed. The final fusion decision is made by filtering the result with a threshold function, hence a refined structural damage assessment of superior reliability. The proposed approach has been applied to a 7-degree of freedom building model for structural damage detection, and proves to be feasible, efficient and satisfactory. Furthermore, the simulation result also shows that the identification accuracy can be boosted with the proposed approach instead of FNN models alone.     

Agent-based artificial immune system approach for adaptive damage detection in monitoring networks

This paper presents an agent-based artificial immune system approach for adaptive damage detection in distributed monitoring networks. The presented approach establishes a new monitoring paradigm by embodying desirable immune attributes, such as adaptation, immune pattern recognition, and self-organization, into monitoring networks. In the artificial immune system-based paradigm, a group of autonomous mobile monitoring agents mimic immune cells (such as B-cells) in the natural immune system, interact locally with monitoring environment, and respond to emerging problems through simulated immune responses. The presented immune-inspired monitoring paradigm has been applied to structural health monitoring. The “antibody” of a mobile monitoring agent is a pattern recognition algorithm tuned to a certain type of structural damage pattern. The mobile monitoring agent performs damage diagnosis based on structural dynamic response data. Mobile monitoring agents communicate with each other and collaborate with network components based on agent interaction protocols defined in agent standards, the Foundation for Intelligent Physical Agents standards. A mobile agent system embedded in sensor nodes supports the selective generation, migration, communication, and management of mobile monitoring agents automatically. The active structural health monitoring is achieved by distributing mobile monitoring agents to the sites where they are needed. The structural damage diagnosis using mobile monitoring agents and artificial immune pattern recognition method has been tested using a scaled steel bridge structure. The test result shows the feasibility of using this approach for real-time structural damage diagnosis.     

基于两种网络模式的虚拟核子仪器的研制

本文分析了两种常用核子仪器的软、硬件实现,并对实现该虚拟仪器网络功能的两种网络模式的不同实现方法进行了探讨。