一种采用改进半桥主电路的有源滤波器

在分析双电感半桥电路的基础上,提出了一种基于改进半桥拓扑结构的新型有源电力滤波器,它消除了传统有源滤波器拓扑的桥臂直通故障隐患,且具有可高频、高效率运行的优点。文章详细分析了其工作原理,给出了相应的控制策略。仿真和实验结果验证了这种新型有源滤波器的可行性。     

列车网络控制系统时延特性研究

针对列车网络控制系统在列车运行中产生的时延问题,通过搭建列车网络控制系统时延测试模拟平台,研究列车通信过程中控制系统的时延特性。根据时延特性分析出TCN网络各子系统的时延影响因素。重点研究任务周期与源端口特征周期对网络控制系统时延的影响。利用TCN网络分析仪测出系统时延,结合所得数据归纳出系统时延的变化规律。通过分析任务周期与特征周期的匹配关系对系统时延的影响,获得减少时延抖动的方法,达到减小网络控制系统时延的目的。     

喷锚支护的时间效应与空间效应

喷锚支护是新奥法构筑隧道的主要支护手段，为使喷锚支护与围岩形成共同承载结构，必须在适宜的时机及根据适当的围岩变位量来确定恰当的喷锚支护结构。     

Time windows in workers' activity patterns: Empirical evidence from the Netherlands

This paper assumes that activities at the home and work location are important determinants of individuals' paths through time and space. Fixed activities at these locations determine to a large extent the duration and timing of time windows – blocks of time available for participation in travel and out-of-home non-work activities. Taking the time spent at home and at the workplace as a starting point, this paper classifies activity patterns on workdays into six groups with distinct home- and work-stay patterns. For this, data are used from the 1998 Netherlands National Travel Survey. The six clusters vary in terms of the duration and timing of time windows and some of the differences can be explained by commute characteristics, types of non-work activities performed, workers' sociodemographic attributes, and their spatiotemporal environment. However, the impact of sociodemographic and spatiotemporal variables on cluster membership is shown to be weak.     

徐宿高速公路碎石桩处理试验研究

主要结合睢宁三合同段中的碎石桩试验段研究碎石桩施工方案的可行性和处理的实际效果,完善碎石桩的施工工艺。通过室内土工试验、静力触探试验、标准贯入试验、动力触探试验、瞬态瑞利波试验等检测手段的对比研究,探讨碎石桩的检测方法和碎石桩加固效果检测的最佳检测时间。     

车载动态实时可视化交通信息服务系统

一种新型城市交通信息服务系统,它采用GPS接收机、数码像机、有线/无线智能传感器、辅以人工等方式完成路况信息采集,经控制中心处理后按1～3次/min频率生成全面、综合反映路况信息的实时、动态交通图,通过无线传输为公众提供实时、动态路况信息,并用全新概念的车载显示器Skipper显示路况信息,实现道路车辆均衡化、提高道路利用率。论述了其开发背景、系统构成及工作原理、核心产品开发与运用等。     

An Exploration of the Relationship between Timing and Duration of Maintenance Activities

The timing and duration of an activity episode are two important temporal aspects of activity-travel behavior. Understanding the causal relationship between these two variables would be useful in the development of activity-based travel demand modeling systems. This paper investigates the relationship between these two variables by considering two different causal structures – one structure in which time-of-day choice is determined first and influences duration and a second structure in which activity duration is determined first and affects time-of-day choice. These two structures are estimated within a discrete-continuous simultaneous equations framework employing a full-information maximum likelihood methodology that allows error covariance. The estimation is performed separately for commuter and non-commuter samples drawn from a 1996 household travel survey data set from the Tampa Bay area in Florida. The results of the model estimation effort show that the causal structure in which activity duration precedes or affects activity timing (time of day choice) performs better for the non-commuter sample. For the commuter sample, the findings were less conclusive with both causal structures offering equally good statistical measures of fit. In addition, for the commuter sample, all error correlations were found to be zero. These two findings suggest that time of day choice and activity episode duration are only loosely related for the commuter sample, possibly due to the relatively non-discretionary and inflexible work activity and travel.     

列车运行图可调整度评价系统研究

在详细分析了列车运行图缓冲时间的大小及其分布规律对列车晚点传播影响的基础上，通过建立列车运行图调整系统，对给定晚点程度的列车进行模拟调整，从而计算出列车晚点恢复率，晚点传播区大小，连带晚点时间和关键列车运行线等。指标来达到对列车运行图可高速程度优劣评判的目的。     

基于改进 BiLSTM 网络的地铁车轮磨耗预测模型

针对地铁车轮磨耗数据时间跨度较长引起的长期依赖问题,为了进一步提升预测精度,提出一种将麻雀搜索算法(sparrow search algorithm,SSA)优化双向长短期记忆网络(bidirectional long short term memory,BiLSTM)的改进 BiLSTM(SSA-BiLSTM)网络模型,用于地铁车轮磨耗预测。首先,利用麻雀搜索算法对双向长短期记忆网络算法的神经元个数、迭代次数、输入批量和学习率等超参数在给定范围内进行寻优,得到参数最优值;然后,以参数最优值来构建改进 BiLSTM 网络模型,对车轮磨耗进行预测分析;最后,以车轮踏面磨耗和轮缘磨耗作为研究对象,将某地铁 1 车厢 1 号车轮的现场实测历史磨耗数据作为输入,对该模型进行训练及验证分析,并与多层感知机(multilayer perceptron,MLP)、LSTM、BiLSTM 以及 SSA-LSTM 模型的预测结果进行对比。研究结果表明：SSA-Bi-LSTM 模型的车轮磨耗预测精度更高,与 LSTM、BiLSTM 以及 SSA-LSTM 网络模型相比,踏面磨耗的平均绝对百分误差(mean absolute percentage error,MAPE)分别降低了 13.28%、10.32%、1.47%,轮缘磨耗分别降低了 9.5%、0.46%、0.02%;分别对同一地铁 2 号、4 号车厢的 1 号位置车轮磨耗进行预测,并与磨耗实测数据进行对比,踏面磨耗的平均绝对百分比误差分别为 1.34%、1.42%,轮缘磨耗的平均绝对百分比误差分别为 0.18%、0.19%,验证了本文所提模型具有良好的泛化性,为地铁轮对智能化管理提供理论支持,延长车轮使用寿命。     

连续复利资金时间价值的使用研究

根据间断复利和连续复利之间的关系,结合技术经济学中资金时间价值的基本原理,研究连续复利条件下整收整付及等额收付系列资金时间价值计算的方法和特点.