漏磁检测技术在管道检测中的应用及影响因素分析

阐述了漏磁检测的原理,介绍了基于漏磁原理的检测系统组成,以及在长输管道及工业管道检测中的工程应用。详细分析了漏磁检测技术的主要影响因素。指出国内漏磁检测技术领域与国外存在较大差距。国内管道内检测已进入立法阶段,相关标准的初稿已基本完成,未来漏磁检测技术将在维护管道安全生产上发挥越来越重要的作用。     

未连通闲置天然气管道内腐蚀评估

目前长输天然气管道内检测主要采用漏磁检测法,但漏磁检测要求管内有一定的介质流量,对于未连通管段并不适用。文中结合某天然气管网的特殊工况,提出了采用CCTV检测、导波检测、超声测厚、水样分析和垢样分析等方法综合分析评价管段的适用性,进而计算管道的剩余寿命,可用于未连通闲置天然气管道内腐蚀评估,具有借鉴意义。     

钢质管道外壁爬行漏磁检测技术在工程中的应用

文中介绍了漏磁的基本原理及漏磁检测系统在检测过程中信号的变化规律及实际应用中应注意问题。与利用管道内部压差作为动力的漏磁检测仪器不同,该仪器由主机、探头及信号传输电缆组成,探头通过永磁铁、固定轮固定于被测管道表面,手动操作探头以相应速率（标准速率应为0．5m／s）匀速运动,从而发现管道埋藏缺陷。通过实际应用发现影响检测精度、准确性的因素主要有样管制造、提离值调整、被检管道表面光滑程度及爬行速率等。     

漏磁腐蚀检测器测厚探头机械结构的设计

管道壁厚测量探头可以识别管道壁厚减薄所带来的安全隐患。基于电磁超声技术(EMAT),设计了一种管道壁厚测量探头的机械结构,详细地介绍了此探头机构的设计原则及设计难点,此探头可应用于油气管道壁厚的测量。该测厚探头采用浮动式结构,探头整体靠支撑轮支撑,与传统漏磁腐蚀检测器所用的探头结构相比,该测厚探头机械结构具有良好的抗冲击性、良好的密封性、优良的耐磨性和更长的使用寿命,同时,提高了探头与管壁的贴合程度。     

管道外壁爬行漏磁检测器的研制

漏磁检测方法可以实现对铁磁性材料缺陷的定位,对缺陷的物理性质进行定量化分析,逐渐在管道检测中受到重视。针对现有仪器存在的不足,开展管道漏磁检测器的研制,对于减少设备购置的成本具有重要意义。文中在理论研究的基础上,对管道外壁爬行漏磁检测器从磁路设计、样机研制及数据处理软件的开发开展工作。并分析了在设计过程中涉及到的关键问题以及技术难题,为其他相关研究提供指导性意见。     

管道缺陷与补板漏磁场识别技术研究

提出了管道漏磁检测过程中缺陷漏磁场与补板漏磁场的识别方法。根据微分形式的麦克斯韦方程组得出漏磁场动态数据模型。利用有限元方法建立管道漏磁检测的数值仿真模型,将缺陷、补板、缺陷与补板同时存在的漏磁场进行对比分析,并通过相邻补板漏磁场的分析,得出补板漏磁场与缺陷漏磁场的识别方法,为提高漏磁检测的精确度提供了重要的理论依据。     

长输油气管道金属损失漏磁内检测技术研究

以管道漏磁内检测器为载体,通过对管体进行在线的漏磁内检测,可以达到量化管道缺陷、避免事故发生的目的。文中介绍了管道金属损失漏磁内检测技术,分析了油气管道漏磁内检测技术原理及漏磁内检测系统组成,利用有限元分析方法研究了管道缺陷尺寸对于漏磁场信号的影响,验证了管道漏磁内检测技术的可靠性。     

气田集气站管线刺漏原因分析及改进方法

某气田集气管线的刺漏严重影响正常生产和平稳运行。为减少并防止集气管线刺漏情况的发生,需根据现场经验及相关资料,分析原因并提出改进方法。对该气田管线刺漏的原因进行分析,总结出天然气组分中含酸性气体CO2、管线布局不合理、管线腐蚀监测不到位、气井配产不合理等是造成管线刺漏的主要原因,提出更换管线材质、优化工艺流程、制定气田管线腐蚀监测机制等应对措施,实施结果表明改进措施有效。     

高密度电法地表探测在隧道施工地质预报中的应用

高密度电法是工程地质勘察中应用较多的地表物探技术之一,其对含水性地质病害具有较高的预报精度。文章依托岗头山隧道和叙岭关隧道项目,介绍了富水性区域病害、充填粘土型溶洞病害和断层破碎带等三类典型工程实例的成功经验,并且对漏测、检测结果的多解性和异常信息缺失等常见应用问题及其应对方法进行了总结分析。     

油气管道周向漏磁检测信号分析

用于检测管道腐蚀缺陷的漏磁检测方法已运用多年,但传统的轴向漏磁检测方法无法检测到狭长的轴向腐蚀缺陷,使用周向漏磁检测则能很好地弥补轴向漏磁检测的不足。周向漏磁检测及其信号分析在国内还处于起步阶段。采用ANSYS仿真软件建立了周向漏磁检测模型,并进行了电磁场模拟;对仿真模型提取的漏磁信号与腐蚀缺陷的尺寸信息进行了定性分析,提出应用BP神经网络定量分析油气管道腐蚀缺陷与漏磁信号的关系。结果表明：漏磁信号能定性地判断腐蚀缺陷,而使用BP神经网络方法可以定量地确定管道腐蚀缺陷尺寸,有助于提高检测的精度,同时也为油气管道安全评价提供了依据。     

Estimating travel times and vehicle trajectories on freeways using dual loop detectors

Recent research has investigated various means of measuring link travel times on freeways. This search has been motivated in part by the fact that travel time is considered to be more informative to users than local velocity measurements at a detector station. But direct travel time measurement requires the correlation of vehicle observations at multiple locations, which in turn requires new communications infrastructure and/or new detector hardware. This paper presents a method for estimating link travel time using data from an individual dual loop detector, without requiring any new hardware. The estimation technique exploits basic traffic flow theory to extrapolate local conditions to an extended link. In the process of estimating travel times, the algorithm also estimates vehicle trajectories. The work demonstrates that the travel time estimates are very good provided there are no sources of delay, such as an incident, within a link.     

Length-based vehicle classification using event-based loop detector data

Length-based vehicle classification is an important topic in traffic engineering, because estimation of traffic speed from single loop detectors usually requires the knowledge of vehicle length. In this paper, we present an algorithm that can classify vehicles passing by a loop detector into two categories: long vehicles and regular cars. The proposed algorithm takes advantage of event-based loop detector data that contains every vehicle detector actuation and de-actuation “event”, therefore time gaps between consecutive vehicles and detector occupation time for each vehicle can be easily derived. The proposed algorithm is based on an intuitive observation that, for a vehicle platoon, longer vehicles in the platoon will have relatively longer detector occupation time. Therefore, we can identify longer vehicles by examining the changes of occupation time in a vehicle platoon. The method was tested using the event-based data collected from Trunk Highway 55 in Minnesota, which is a high speed arterial corridor controlled by semi-actuated coordinated traffic signals. The result shows that the proposed method can correctly classify most of the vehicles passing by a single loop detector.     

Improved velocity estimation using single loop detectors

This paper develops an improved algorithm for estimating velocity from single loop detector data. Unlike preceding works, the algorithm is simple enough that it can be implemented using existing controller hardware. The discussion shows how the benefits of this work extend to automated tests of detector data quality at dual loop speed traps. Finally, this paper refutes an earlier study that found conventional single loop velocity estimates are biased.     

基于GPRS的采油井网远程监测防盗系统

针对以往油田监控方式和设备存在的弊端,设计了一种基于GPRS的采油井网远程监测防盗系统。介绍了系统的组成和各部分功能;详细阐述了数据采集终端的硬件结构、负压波原理以及将负压波技术应用于输油管道监测的方法;最后给出系统的软件设计。实验结果表明:该系统集采油井状态监测和防盗功能于一身,硬件投资小,运行稳定可靠,监测精度高,可满足工程应用要求,有广阔的应用前景。     

原油管道检测器通过能力评价方法

为了探明管道内部通过能力,保证管道内部腐蚀检测器的顺利投放,制定了由泡沫检测器到几何尺寸检测器的管道通过能力检测流程,并将此方法在多条原油管线上进行了验证。结果表明：该方法能准确地识别管线上的变形尺寸大小,并对变形部位进行定位。根据检测结果对管道通过能力进行评价,对不符合要求的管段及时进行修复,保证了后期检测的顺利进行。此外,在检测的过程中有效地清理了管道内部污物,提高检测器通过能力及管道的输油效率。     

Real-time estimation of lane-based queue lengths at isolated signalized junctions

In this study, we develop a real-time estimation approach for lane-based queue lengths. Our aim is to determine the numbers of queued vehicles in each lane, based on detector information at isolated signalized junctions. The challenges involved in this task are to identify whether there is a residual queue at the start time of each cycle and to determine the proportions of lane-to-lane traffic volumes in each lane. Discriminant models are developed based on time occupancy rates and impulse memories, as calculated by the detector and signal information from a set of upstream and downstream detectors. To determine the proportions of total traffic volume in each lane, the downstream arrivals for each cycle are estimated by using the Kalman filter, which is based on upstream arrivals and downstream discharges collected during the previous cycle. Both the computer simulations and the case study of real-world traffic show that the proposed method is robust and accurate for the estimation of lane-based queue lengths in real time under a wide range of traffic conditions. Calibrated discriminant models play a significant role in determining whether there are residual queued vehicles in each lane at the start time of each cycle. In addition, downstream arrivals estimated by the Kalman filter enhance the accuracy of the estimates by minimizing any error terms caused by lane-changing behavior.     

基于MSP430的铁路货运车厢温湿度信息采集系统设计

文章设计了基于MSP430的铁路货运车厢温湿度信息采集系统,介绍了该系统软件和硬件的结构组成与功能原理,指出该系统具有处理速度快、实时性强、精确度和集成度高、携带方便等优点,可为铁路货运系统提供基础数据,并能提高铁路货物运输的安全性和质量,有着广泛的应用前景。     

Vehicle reidentification and travel time measurement across freeway junctions using the existing detector infrastructure

Conventional vehicle detectors are capable of monitoring discrete points along the freeway but do not provide information about conditions on the link between detectors. Knowledge of conditions on the link is useful to operating agencies for enabling timely decisions in response to various delay causing events and hence to reduce the resulting congestion of the freeway system. This paper presents an approach that matches vehicle measurements between detector stations to provide information on the conditions over the link between the detectors rather than relying strictly on the aggregate point measurements from the detectors. In particular this work reidentifies measurements from distinct vehicles using the existing loop detector infrastructure. Here the distinct vehicles are the long vehicles, but depending on the vehicle population or type of detector used, one might chose to use some other reproducible feature.This new methodology represents an important advancement over preceding loop based vehicle reidentification, as illustrated herein, it enables vehicle reidentification across a major diverge and a major merge. The examples include a case where the reidentification algorithm responded to delay between two detector stations an hour before the delay was locally observable at either of the stations used for reidentification. While previous loop based reidentification work was limited to dual loop detectors, the present effort also extends the methodology to single loop detectors; thereby making it more widely applicable. Although the research uses loop detector data, the algorithm would be equally applicable to data obtained from many other traffic detectors that provide reproducible vehicle features.     

An Adaptive Neuro-Fuzzy Inference System for estimating the number of vehicles for queue management at signalized intersections

Queue management is a valuable but underutilized technique which could be used to minimize the negative impacts of queues during oversaturated traffic conditions. One of the main obstacles of applying queue management techniques along signalized arterials is the unavailability of a robust and sufficiently accurate method for measuring the number of vehicles approaching a signalized intersection. The method based on counting vehicles as they enter and exit a specific detection zone with check-in and check-out detectors is unreliable because of the likely systematic under or over counting and the resulting cumulative errors. This paper describes the application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) in the development of a new fuzzy logic-based approach for estimating the Number of Vehicles in a Detection Zone (NVDZ) by using detector time-occupancy data (instead of detector counts). Microscopic simulation results are used to evaluate the accuracy of the NVDZ estimates. Tests were carried out to determine the transferability of a tuned Fuzzy Inference System (FIS) and to check the sensitivity of the calibrated FIS to detection coverage, the location of the detection zone relative to the signalized (bottleneck) intersection, the length of the detection zone, and different signal timings at the bottleneck intersection. Results show that the NVDZ estimation based on fuzzy logic seems to be a feasible approach. Although the primary objective of developing the NVDZ estimation technique has been queue management, other applications such as ramp metering and incident detection could potentially use the same technique.     

Increasing the accuracy of loop detector counts using adaptive neural fuzzy inference system and genetic programming

Loop detectors are devices that are most commonly used for obtaining data at intersections. Multiple detectors are usually required to monitor a location, and this reduces the accuracy of detectors for collecting traffic volumes. The purpose of this paper is to increase the accuracy of loop detector counts using Adaptive Neural Fuzzy Inference System (ANFIS) and Genetic Programming (GP) based on detector volume and occupancy. These methods do not need microscopic analysis and are easy to employ. Four approaches for one intersection are used in a case study. Results show that the models can improve intersection detector counts significantly. Results also show that ANFIS produces more accurate counts compared to regression and GP.