基于超声导波的管道结构特性识别

文中分析了基于导波频散检测频率优化选择及限制频率等问题,研究了检测参数选择问题。根据不同换能器荷载施加方式、管道实际情况等对导波激励影响,就管道中存在的轴向连续单损及非连续性损伤,提出一种基于优化波形字典的追踪方法,分解损伤信号,评估损伤类型、大小等。文中研究了管道存在的变形损伤类型,分析了新导波检测可行性,为后续管道检测提供参考。     

管道超声导波腐蚀检测技术应用研究

介绍了导波的频散特性及相关的理论成果.从导波的结构出发,分析了导波在介质中能量与位移的分布.阐述了导波检测技术领域中数值分析方法和信号处理方面的一些新技术,根据超声导波现场检测存在缺陷及不能精确定量问题,推荐使用C扫描为缺陷定量.完成检测后,对管道强度进行了分析,指出存在的主要问题,对开展超声导波检测有重要指导作用.     

基于声发射技术的管道泄漏检测与定位方法研究

为提高管道无损检测中对小孔径泄漏检测灵敏度、泄漏信号判别准确率以及泄漏点定位精确度,提出一种基于声发射技术并结合信号频域特征提取算法的管道泄漏识别和定位方法。设计管道泄漏检测实验平台进行管道泄漏检测实验,采用经验模态分解方法和小波分解重构相结合的信号处理算法进行降噪并提取信号频域特征,研究不同孔径和不同管道压力下管道泄漏检测和泄漏点定位问题。验证了基于声发射技术并结合信号频域特征提取算法的管道泄漏检测方法的有效性。     

基于声发射波形分析的锦屏大理岩岩爆试验研究

岩爆破坏是一种非常复杂的非线性力学行为,影响岩爆的因素众多。文章通过对锦屏大理岩进行两例全程破坏和一例非全程破坏岩爆试验,采集试验过程中的应力和声发射参数,以应力曲线和声发射累计能量曲线为基础确定了关键点,并针对关键点对岩爆过程中的声发射波形进行分析,得到了锦屏大理岩发生岩爆的本质规律。结果表明,锦屏大理岩在单位时间内的声发射波形数分布与关键点有很大相关性,单波占绝大多数,双波、三波和四波在关键点处分布较为集中,多波只在岩爆时刻出现;锦屏大理岩在岩爆阶段与前期加载阶段相比,会有单位时间内波形数数不清的岩爆波产生,是其岩爆阶段的独有特征。     

工业管道声发射信号衰减测试及定位分析

简述了工业管道输送流体流动特性,以及声发射技术在管道检测中的应用。采用手持式声发射检测仪器配合不同频率传感器对在役工业管道进行检测,研究焊接有三通、法兰、阀门等外接接口的不规则管道的定位特征,对比分析规则管道与焊有外接接口的不规则管道衰减特征区别,通过对现场数据的分析,得到管道损伤定位与传播声速之间的相互关系以及不同传播速度条件下产生的定位误差,综合分析误差产生原因,作为对现场检测的经验。     

磁致伸缩导波技术在管道检测中的应用

介绍了磁致伸缩T模态导波技术检测管道缺陷的原理.实验研究了磁致伸缩导波技术检测管道缺陷的灵敏度和精度,实验结果证明该检测技术具有很高的灵敏度和精度.在此基础上应用该检测技术对在役管道进行在线检测,给出了数据分析结果和不同环境下磁致伸缩导波技术对管道缺陷检测的可靠灵敏度.实验和现场检测表明:磁致伸缩T模态导波技术在管道检测上具有较高的可靠性和快捷性.     

声发射检测技术在管道气压强度试验中的应用研究

声发射检测技术在工艺管道气压强度试验中的应用，能有效避免人员近距离检查存在的气体膨胀爆炸造成的安全风险。文中分析了声发射检测技术工作原理及处理模块主要功能；研究了声发射标准管道压力增长曲线及新安装管线增压要求。通过声发射系统在阿穆尔天然气加工厂某条管线回路中的应用，分析了传感器安装和几何布置、信号数据处理及定位要求。研究了信号衰减、降噪措施及定位方式对声源信号检测准确性的影响，为声发射检测技术在管道气压强度试验中的应用提供借鉴。     

小波变换在管道泄漏点定位中的应用

当管道发生泄漏时，泄漏诱发的负压波传播到管道上下游监测点时会使该点压力信号幅值产生瞬态下降，利用小波变换模极大值检测压力信号的突变点，从而计算出管道泄漏诱发的负压波传播到上下游监测点的时间差。在MATLAB6．1软件环境下，以某次实验数据为例进行管道泄漏点定位研究。在计算过程中小波基函数选取为Haar小波，尺度水平为6，计算结果表明该方法可以计算出管道泄漏点处诱发的负压波传播到管道上游监测点的时间差，从而为准确定位泄漏点提供了基础。     

基于傅里叶变换的管道杂散电流分析及应用

杂散电流严重威胁管道的安全运行,对其进行检测、分析和排流是管道防腐的重要工作.针对这一问题,提出了基于傅里叶变换杂散电流分析方法.傅里叶变换的基本思想是将时域的信号转换到频域进行分析.管道对地电位测试数据,通过傅里叶变换分析处理之后,可以得到其中的直流分量和不同频率的交流分量.对这些分量的幅值进行分析,可以判断管道上存...     

油气管道局部管体损伤导波检测研究与应用

文中对磁致伸缩超声导波检测原理进行了研究,通过对长输管道建模分析,得到长输管道的导波传输特性。实验室样管与现场管道的导波实测数据表明,导波检测具有单点激励、长距离传输的特点,对长输管道重点区域检测具有适宜性和局限性。     

Applications of wavelet transform for analysis of freeway traffic: Bottlenecks, transient traffic, and traffic oscillations

This paper demonstrates the capabilities of wavelet transform (WT) for analyzing important features related to bottleneck activations and traffic oscillations in congested traffic in a systematic manner. In particular, the analysis of loop detector data from a freeway shows that the use of wavelet-based energy can effectively identify the location of an active bottleneck, the arrival time of the resulting queue at each upstream sensor location, and the start and end of a transition during the onset of a queue. Vehicle trajectories were also analyzed using WT and our analysis shows that the wavelet-based energies of individual vehicles can effectively detect the origins of deceleration waves and shed light on possible triggers (e.g., lane-changing). The spatiotemporal propagations of oscillations identified by tracing wavelet-based energy peaks from vehicle to vehicle enable analysis of oscillation amplitude, duration and intensity.     

A reliability‐based traffic assignment model for multi‐modal transport network under demand uncertainty

In densely populated and congested urban areas, the travel times in congested multi‐modal transport networks are generally varied and stochastic in practice. These stochastic travel times may be raised from day‐to‐day demand fluctuations and would affect travelers' route and mode choice behaviors according to their different expectations of on‐time arrival. In view of these, this paper presents a reliability‐based user equilibrium traffic assignment model for congested multi‐modal transport networks under demand uncertainty. The stochastic bus frequency due to the unstable travel time of bus route is explicitly considered. By the proposed model, travelers' route and mode choice behaviors are intensively explored. In addition, a stochastic state‐augmented multi‐modal transport network is adopted in this paper to effectively model probable transfers and non‐linear fare structures. A numerical example is given to illustrate the merits of the proposed model. Copyright © 2012 John Wiley & Sons, Ltd.     

油气管道泄漏检测技术发展现状

简单说明了油气长输管道泄漏的原因和泄漏的危害,详细介绍了声发射技术法、GPS时间标签法、负压波法、压力点分析法、压力梯度法、状态估计法、神经网络法和统计检漏法等几种管道泄漏检测技术方法,最后指出了存在的问题和发展的趋势。     

Assessment of schedule-based and frequency-based assignment models for strategic and operational planning of high-speed rail services

Despite some substantial limitations in the simulation of low-frequency scheduled services, frequency-based (FB) assignment models are by far the most widely used in practice. They are less expensive to build and less demanding from the computational viewpoint with respect to schedule-based (SB) models, as they require neither explicit simulation of the timetable (on the supply side), nor segmentation of OD matrices by desired departure/arrival time (on the demand side).The objective of this paper is to assess to what extent the lack of modeling capabilities of FB models is acceptable, and, on the other hand, the cases in which such approximations are substantial and more detailed SB models are needed. This is a first attempt to shed light on the trade-off between (frequency-based) model inaccuracy and (scheduled-based) model development costs in the field of long-distance (e.g. High-speed Rail, HSR) service modeling.To this aim, we considered two modeling specifications estimated using mixed Revealed Preferences (RP) and Stated Preferences (SP) surveys and validated with respect to the same case study. Starting from an observed (baseline) scenario, we artificially altered the demand distributions (uniform vs. time-varying demand) and the supply configuration (i.e. train departure times), and analyzed the differences in modal split estimates and flows on individual trains, using the two different model specifications.It resulted that when the demand distribution is uniform within the period of analysis, such differences are significant only when departure times of trains are strongly unevenly spaced in time. In such cases, the difference in modal shares, using FB w.r.t. SB, is in the range of [0%, +5%] meaning that FB models tend to overestimate HSR modal shares. When the demand distribution is not uniform, the difference in modal shares, using FB w.r.t. SB, is in the range of [−10%, +10%] meaning that FB models can overestimate or underestimate HSR modal shares, depending on timetable settings with respect to travelers’ desired departure times. The differences in on-board train flow estimates are more substantial in both cases of uniform and not uniform demand distribution.     

成品油管道泄漏监测与定位系统的研制

研制一套有效的成品油管道泄漏监测与定位系统,对于输油管道的安全运行及环境保护,减少企业经济损失具有重要的意义。根据现场实际工况,提出一种与SCADA系统相结合的成品油管道泄漏监测与定位系统方案,给出了系统的组成与工作原理。基于GPS授时与中断技术的异地同步采集保证了异地数据采集设备的精确同步。系统使用基于负压波的分段斜率法准确判断泄漏;采用小波变换精确检测负压波传到首末站的时间差,并给出了小波基函数的选取原则及定位方法。实际应用表明：系统报警响应时间短、误报率低、泄漏定位精度高。     

Predictive path following with arrival time awareness for waterborne AGVs

Large ports are seeking innovative logistical ways to improve their competitiveness world-wide. This article proposes waterborne AGVs, inspired by conventional automated guided vehicles and autonomous surface vessels, for transport over water. A predictive path following with arrival time awareness controller is proposed for such waterborne AGVs. The controller is able to achieve smooth tracking and energy efficiency with arrival time awareness for transport oriented applications. Tracking errors are conveniently formulated with vessel dynamics modeled in connected reference path coordinate systems and a coordinate transformation at switching coordinate systems. Binary decision variables and logic constraints based on an along-track state are proposed for modeling switches in the framework of Model Predictive Control (MPC) so that overshoots are avoided. Moreover, timing-aware along-track references are generated by a two-level double integrator scheme. The lower level is embedded in online MPC optimizations for smooth tracking. The higher level solves a mixed-integer quadratic programming problem considering distance-to-go and time-to-go before each MPC optimization. References over the next prediction horizon are generated being aware of the requirements on arrival time. Furthermore, successive linearizations of nonlinear vessel dynamics about a shifted previous optimal system trajectory are implemented to maintain a trade-off between computational complexity and optimality. Simulation results of two industrially relevant Inter Terminal Transport case studies illustrate the effectiveness of the proposed modeling and control design for waterborne AGVs.     

Impact of license plate restriction policy on emission reduction in Hangzhou using a bottom-up approach

Many emission models have been developed for estimating the impact of transport policies on vehicle emissions. Macroscopic models, such as MOBILE and COPERT, are used for area analysis, while microscopic models, such as CMEM, are applied for corridor analysis. It is well known that driving dynamics are critical for estimating vehicle emissions. MOVES can be used for both macroscopic and microscopic emission analysis, and its advantage lies in the consideration of driving dynamics. Using a bottom-up approach, we study the impact of license plate restriction policy on vehicle emission reduction by localizing the emission rates in MOVES according to the vehicle emission standards in China. We implement the approach to evaluate the impact on the total vehicle emissions in Hangzhou, China before and after the implementation of license plate restriction policy. In the restricted region, the reductions of total Vehicle Kilometer Traveled (VKT) and total emissions are 9.6% and 6.9%, respectively. The result shows that the license plate restriction policy is effective in achieving the targeted emission reduction.     

Application of wavelet technique to freeway incident detection

This paper presents an application of the wavelet technique to freeway incident detection because wavelet techniques have demonstrated superior performance in detecting changes in signals in electrical engineering. Unlike the existing wavelet incident detection algorithm, where the wavelet technique is utilized to denoise data before the data is input into an algorithm, this paper presents a different approach in the application of the wavelet technique to incident detection. In this approach, the features that are extracted from traffic measurements by using wavelet transformation are directly utilized in detecting changes in traffic flow. It is shown in the paper that the extracted features from traffic measurements in incident conditions are significantly different from those in normal conditions. This characteristic of the wavelet technique was used in developing the wavelet incident detection algorithm in this study. The algorithm was evaluated in comparison with the multi-layer feed-forward neural network, probabilistic neural network, radial basis function neural network, California and low-pass filtering algorithms. The test results indicate that the wavelet incident detection algorithm performs better than other algorithms, demonstrating its potential for practical application.     

Equilibrium at a bottleneck when long-run and short-run scheduling preferences diverge

We consider the use of a Vickrey road bottleneck in the context of repetitive scheduling choices, distinguishing between long-run and short-run scheduling preferences. The preference structure reflects that there is a distinction between the (exogenous) ‘long-run preferred arrival time’, which would be relevant if consumers were unconstrained in the scheduling of their activities, and the ‘short-run preferred arrival time’, which is the result of an adaptation of travel routines in the face of constraints caused by, in particular, time-varying congestion levels. We characterize the unpriced equilibrium, the social optimum as well as second-best situations where the availability of the pricing instruments is restricted. All of them entail a dispersed distribution of short-run preferred arrival times. We obtain the intriguing results that the dispersion is lower in the social optimum than in the unpriced equilibrium, and that the application of first-best short-run tolls does not induce efficient long-run choices of travel routines.     

Hybrid model for prediction of bus arrival times at next station

Effective prediction of bus arrival times is important to advanced traveler information systems (ATIS). Here a hybrid model, based on support vector machine (SVM) and Kalman filtering technique, is presented to predict bus arrival times. In the model, the SVM model predicts the baseline travel times on the basic of historical trips occurring data at given time‐of‐day, weather conditions, route segment, the travel times on the current segment, and the latest travel times on the predicted segment; the Kalman filtering‐based dynamic algorithm uses the latest bus arrival information, together with estimated baseline travel times, to predict arrival times at the next point. The predicted bus arrival times are examined by data of bus no. 7 in a satellite town of Dalian in China. Results show that the hybrid model proposed in this paper is feasible and applicable in bus arrival time forecasting area, and generally provides better performance than artificial neural network (ANN)–based methods. Copyright © 2010 John Wiley & Sons, Ltd.