基于BP神经网络的川气东送管道土壤腐蚀预测

通过现场埋片和土壤理化性质试验确定了影响川气东送管道腐蚀速率的主要土壤因素,对39个试验点的X70钢质试片的腐蚀数据进行分析,构建了X70钢材土壤腐蚀预测模型,利用该模型在BP神经网络中训练、模拟,并运用MATLAB软件对神经网络进行编程,将预测结果与现场X70埋片腐蚀实验结果对比。结果表明:运用BP神经网络可以建立稳定性好的土壤腐蚀预测模型,预测川气东送管道X70钢材在土壤中的腐蚀速率的准确度达到90%以上。     

灰色GM（1，1）模型在管道腐蚀预测中的应用

随着运营时间的增加,输气管道必然受到不同程度的腐蚀,如果不及时维修或更换,一旦发生泄漏引起爆裂,将会造成极大的损失。为了对输气管道的腐蚀程度进行预测,掌握输气管道腐蚀的基本规律,运用GM（1,1）模型对输气管道的腐蚀速度和腐蚀深度的原始数据进行了灰色动态拟合,建立了相应的灰色微分方程和灰色时间响应函数,应用于四川某气田输气管道未来6年的腐蚀情况预测。计算结果表明：建立的管道腐蚀预测模型GM（1,1）模型,与实测数据相比,误差较小,具有一定的实用价值,能为管道运营者采取相应防腐措施提供可靠的依据。     

浅析影响管道漏磁腐蚀检测器定位精度的因素

目前，我国管道漏磁腐蚀检测技术及设备不断得到应用和普及，为管道维护和管道管理提供了科学准确的检测数据。提高检测数据和维护开挖时的定位精度，可使管道腐蚀检测更好地为管道维护、大修服务。通过对管道磁腐蚀检测器在实际生产中的运用，本文简要地分析了影响管道漏腐蚀检测器定位精度的原因，并提出了提高检测器定位精度的方法。     

机场航班地面保障数据质量校验研究

近年来,国内机场的规模和业务量日益扩大,在运营过程中产生大量的航班地面保障数据。由于数据质量管理不完善,机场记录的航班地面保障数据存在缺失、错误等质量问题,进而影响机场的运营决策,也不利于对数据的挖掘。本文根据国内某机场航班地面保障数据质量校验需求和保障业务,设计数据质量校验指标及各指标的表达式。同时,基于IBM ODM运营决策平台实现航班地面保障数据质量校验系统,可以对机场的数据质量问题进行校验,从而推进大型机场数据质量管理的系统化。     

炼厂易腐蚀管线高温测厚技术的研究及应用

针对石油加工过程中高温管线腐蚀严重、易引发火灾事故的问题,通过对其腐蚀原因的系统分析,根据其腐蚀特征,进行了此类腐蚀有效监控手段—不停车高温测厚技术的研究与分析。最后,通过实验测试,建立了高温测厚数据的数学转换模型、腐蚀速率计算方法和剩余寿命评估方式,并在炼油厂进行了实际应用,有效地预测了腐蚀隐患。     

埋地输油管道腐蚀调查及改造设计

针对龙鞍埋地输油管道的腐蚀现状 ,通过检测数据 ,对管线的腐蚀环境、防腐层状况、管体腐蚀等情况进行分析和评价 ,探讨腐蚀原因和机理 ,并提出了管道改造的设计方案 ,对方案的优缺点及经济因素进行了分析和比较     

基于管道完整性管理的输气管道内腐蚀分析

为确认管道内检测发现的内部金属损失是否为内腐蚀缺陷并分析内腐蚀成因,基于管道完整性管理的大数据分析理念,将内检测数据、内腐蚀发生位置数据、开挖直接检测数据、腐蚀形貌3D建模分析数据、内腐蚀产物理化分析成果、超声导波监测数据等进行整合并分析了内腐蚀发生的原因。分析结果表明:内腐蚀是由于管道内壁与H_2S、CO_2和管道内部的水发生电化学腐蚀而形成的。依据腐蚀成因,开展了生产清管作业内腐蚀控制,并通过对比多轮超声导波监测数据,确认管道清管对内腐蚀控制的有效性。介绍了开展管道内腐蚀研究的重要性及研究方向。     

成品油长输管道的腐蚀分析及缺陷修复

文中分析了长输管道腐蚀形成的主要原因,采用数据对比的方式计算出腐蚀加深的趋势,采用保护措施处理腐蚀问题,对腐蚀部位进行修复并补强。在实际应用中,效果比较明显,降低了管道运行的风险。     

含水率对X70钢在滨海土壤中腐蚀行为的影响

X70钢作为新型管线钢,目前正大量地应用于输气管道的建设。对X70钢的土壤腐蚀问题进行了实验研究,采用极化曲线、交流阻抗技术对相对含水率在38％-100％（WHC）的青岛滨海土壤中的腐蚀行为进行研究,分析了含水率对土壤腐蚀的影响。结果表明：X70钢在不同含水率土壤中的腐蚀受阴极极化控制。土壤的密实程度和可溶性盐的离子化程度导致不同含水率的土壤腐蚀规律如下：中高含水率对腐蚀速率影响显著,相对含水率小于等于45％时腐蚀速率较小且变化不明显,高于45％时腐蚀速率呈现先迅速升高后降低的趋势,在65％时达到最大;高含水率的土壤中有中间腐蚀产物膜形成。     

原油长输管线腐蚀分析与防护

湛茂线是华南地区运营30多年的原油管线。针对湛茂线运营期间遇到的各类管线腐蚀问题,通过收集原油长输管线内检测腐蚀缺陷资料,深入剖析管线内腐蚀与外腐蚀产生机理,运用异常阴保电位排查、清理杂散电流、修复补强外防腐层等技术手段,对各腐蚀缺陷管段进行有针对性的防护补强和修复,有效防止管线出现异常腐蚀现象,并形成一套成熟的区域原油管线维护保养经验。     

Rationalizing Reliable Imputation Durations of Genetically Designed Time Delay Neural Network and Locally Weighted Regression Models

Abstract

Estimating missing values is known as data imputation. Previous research has shown that genetic algorithms (GAs) designed locally weighted regression (LWR) and time delay neural network (TDNN) models can generate more accurate hourly volume imputations for a period of 12 successive hours than traditional methods used by highway agencies. It would be interesting and important to further refine the models for imputing larger missing intervals. Therefore, a large number of genetically designed LWR and TDNN models are developed in this study and used to impute up to a week-long missing interval (168 hours) for sample traffic counts obtained from various groups of roads in Alberta, Canada. It is found that road type and functional class have considerable influences on reliable imputations. The reliable imputation durations range from 4–5 days for traffic counts with most unstable patterns to over 10 days for those with most stable patterns. The study results clearly show that calibrated GA-designed models can provide reliable imputations for missing data with ‘block patterns’, and demonstrate their further potentials in traffic data programs.     

基于形貌特征的CO2腐蚀速率预测方法

针对CO2腐蚀过程复杂，难以利用实测数据有效预测腐蚀速率问题，文中以腐蚀形貌图像为对象，利用支持向量机（SVM）构建预测模型，实现对CO2腐蚀速率的预测。对N80钢的CO2腐蚀图像进行灰度处理、灰度增强及二值化处理，提取蚀孔数目和孔蚀面积。经计算获得孔蚀密度及孔蚀率，结合工作温度及CO2分压作为腐蚀速率预测的四维特征向量。以SVM构建预测模型，经测试，可准确预测CO2腐蚀速率，并与神经网络预测结果进行对比，验证了该方法的优越性。     

辽河特石超稠油输油管线腐蚀预测与评价

以辽河油田埋地管道土壤腐蚀实测数据为例,同时引入灰关联分析原理及处理方法来描述土壤腐蚀因素对管道腐蚀的影响程度.通过计算各采样的关联度,可以知道管道的腐蚀轻重情况,沿途中的腐蚀情况为BB03＜Z001＜Y3＜Z010＜兴-转＜石材市场＜Z012.另外,又引用了侵蚀性指数法,通过计算侵蚀性指数来判断腐蚀液(除Z010外)的腐蚀倾向.结果表明腐蚀液有中等侵蚀性.     

Estimating vehicle miles traveled combined with ITS data

‘Vehicle miles traveled’ (VMT) is an important performance measure for highway systems. Currently, VMT [or ‘annual average daily traffic’ (AADT)] is estimated from a combination of permanent counting stations and short-term counts done at specified locations as part of the Highway Performance Monitoring System (HPMS) mandated by the US Federal Highway Administration. However, on some roadway sections, Intelligent Transportation Systems (ITS) such as detectors and cameras also produce traffic data. The question addressed in this paper is whether and under what conditions ITS systems data could be used instead of HPMS short-term counts (called ‘coverage counts’)? This paper develops a methodology for determining a threshold number of missing daily traffic counts, or alternatively, the number of valid ITS data observations needed, in order to confidently replace the HPMS coverage counts with ITS data.

Because ITS counts, coverage counts, and actual ground counts (e.g. continuous counts) cannot be found coexisting on a roadway section, it is hard to compare them directly. In this paper, the Monte Carlo simulation method is employed to generate synthetic ITS counts and coverage counts from a set of relatively complete traffic counts collected at a continuous count station. Comparisons are made between simulated ITS counts, coverage counts, and actual ground counts. The simulation results indicate that when there are<330 daily traffic counts missing in a set of ITS counts in a year, that is, when there are at least 35 days of valid data, ITS counts can be used to derive a better AADT than using coverage counts. This result is applied to calculate the VMT for the Hampton Roads region in Virginia. The comparison between the VMTs derived with using and not using the threshold number indicates that these two VMTs are significantly different.     

Real-time traffic estimation using data expansion

This paper presents a method for estimating missing real-time traffic volumes on a road network using both historical and real-time traffic data. The method was developed to address urban transportation networks where a non-negligible subset of the network links do not have real-time link volumes, and where that data is needed to populate other real-time traffic analytics. Computation is split between an offline calibration and a real-time estimation phase. The offline phase determines link-to-link splitting probabilities for traffic flow propagation that are subsequently used in real-time estimation. The real-time procedure uses current traffic data and is efficient enough to scale to full city-wide deployments. Simulation results on a medium-sized test network demonstrate the accuracy of the method and its robustness to missing data and variability in the data that is available. For traffic demands with a coefficient of variation as high as 40%, and a real-time feed in which as much as 60% of links lack data, we find the percentage root mean square error of link volume estimates ranges from 3.9% to 18.6%. We observe that the use of real-time data can reduce this error by as much as 20%.     

Practical approach for travel time estimation from point traffic detector data

Accurate estimation of travel time is critical to the success of advanced traffic management systems and advanced traveler information systems. Travel time estimation also provides basic data support for travel time reliability research, which is being recognized as an important performance measure of the transportation system. This paper investigates a number of methods to address the three major issues associated with travel time estimation from point traffic detector data: data filling for missing or error data, speed transformation from time‐mean speed to space‐mean speed, and travel time estimation that converts the speeds recorded at detector locations to travel time along the highway segment. The case study results show that the spatial and temporal interpolation of missing data and the transformation to space‐mean speed improve the accuracy of the estimates of travel time. The results also indicate that the piecewise constant‐acceleration‐based method developed in this study and the average speed method produce better results than the other three methods proposed in previous studies. Copyright © 2011 John Wiley & Sons, Ltd.     

On the imputation of missing data for road traffic forecasting: New insights and novel techniques

Vehicle flow forecasting is of crucial importance for the management of road traffic in complex urban networks, as well as a useful input for route planning algorithms. In general traffic predictive models rely on data gathered by different types of sensors placed on roads, which occasionally produce faulty readings due to several causes, such as malfunctioning hardware or transmission errors. Filling in those gaps is relevant for constructing accurate forecasting models, a task which is engaged by diverse strategies, from a simple null value imputation to complex spatio-temporal context imputation models. This work elaborates on two machine learning approaches to update missing data with no gap length restrictions: a spatial context sensing model based on the information provided by surrounding sensors, and an automated clustering analysis tool that seeks optimal pattern clusters in order to impute values. Their performance is assessed and compared to other common techniques and different missing data generation models over real data captured from the city of Madrid (Spain). The newly presented methods are found to be fairly superior when portions of missing data are large or very abundant, as occurs in most practical cases.     

油气站场管道腐蚀检测方法及节点控制

通过引进先进的超声导波检测技术和借鉴现有标准的做法,提出了针对站场管道腐蚀缺陷、外防腐层、区域阴极保护、土壤腐蚀性、杂散电流干扰的综合检测与评价方法,建立了输油气站场管道的腐蚀检测方法体系,明确了油气站场管道腐蚀检测中的关键节点.现场应用表明：该方法体系能够帮助检测人员实现对站场管道的非开挖或局部开挖检测,帮助管理者及时掌握站场管道的腐蚀状况.     

核级管道腐蚀数据的概率统计分析

针对核级管道腐蚀环境的复杂性及腐蚀过程的随机性,提出了基于概率统计方法的最大腐蚀深度预测模型。首先对核级管道进行腐蚀失效分析;其次采用广义极值分布模型（GEV）拟合管道最大腐蚀深度数据,用L-矩法计算模型的参数值,分析核级管道腐蚀深度的统计规律;最后引用回归期的概念预测管道最大腐蚀深度。以某核级管道为例,预测其最大腐蚀深度为4.575 1 mm,超过最大腐蚀深度的概率为0.75%。计算结果证明：应用极值理论作统计分析时,广义极值分布模型具有更广的适用性,该研究对分析腐蚀管道的可靠性和安全性具有一定的意义。     

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。