基于DSP的电压补偿算法及实现

为了保证对电压质量要求较高的敏感负载正常工作,需要及时补偿供电系统的电压波动以维持用户电压稳定.根据这一目的提出一种快速的电压补偿算法,该算法使控制电路能够迅速检测出电压波动并输出电压补偿信号.利用工业控制用高性能数字处理芯片TMS320F2812实现该算法,并进行了控制系统的相关设计.实验结果证明该算法以及采用的DSP控制器能够快速的检测出电压波动量,并驱动功率电路实现电压的及时补偿.     

The determinants of car ownership in England and Wales from anonymous 2001 census data

Within the transportation research literature, the attempt to understand and predict the level of car ownership is probably one of the most popular areas of study. The primary reason for this is understandable, having access to a vehicle increases an individual’s (or their household’s) travel options, leading to greater mobility. Secondary reasons for this scrutiny include the need to predict future transport investment in road infrastructure and the commercial demand for new vehicles. This paper attempts to predict the level of household car ownership as a function of the characteristics of the household and the individuals that make up the household. The primary data source for this study comes from the 2001 United Kingdom Census and the analysis methods used are from the discipline of data mining. The results of this study are in line with those from previous research but show a potential to predict the higher levels of household car ownership with greater accuracy than other similar studies.     

Passenger travel characteristics and bus operational states: a study based on IC card and GPS data in Yinchuan,China

ABSTRACT

In recent years, public transport has been developing rapidly and producing large amounts of traffic data. Emerging big data-mining techniques enable the application of these data in a variety of ways. This study uses bus intelligent card (IC card) data and global positioning system (GPS) data to estimate passenger boarding and alighting stations. First, an estimation model for boarding stations is introduced to determine passenger boarding stations. Then, the authors propose an innovative uplink and downlink information identification model (UDI) to generate information for estimating alighting stations. Subsequently, the estimation model for the alighting stations is introduced. In addition, a transfer station identification model is also developed to determine transfer stations. These models are applied to Yinchuan, China to analyze passenger flow characteristics and bus operations. The authors obtain passenger flows based on stations (stops), bus lines, and traffic analysis zones (TAZ) during weekdays and weekends. Moreover, average bus operational speeds are obtained. These findings can be used in bus network planning and optimization as well as bus operation scheduling.     

Not bored yet - Revisiting respondent fatigue in stated choice experiments

Stated choice surveys are used extensively in the study of choice behaviour across many different areas of research, notably in transport. One of their main characteristics in comparison with most types of revealed preference (RP) surveys is the ability to capture behaviour by the same respondent under varying choice scenarios. While this ability to capture multiple choices is generally seen as an advantage, there is a certain amount of unease about survey length. The precise definition about what constitutes a large number of choice tasks however varies across disciplines, and it is not uncommon to see surveys with up to twenty tasks per respondent in some areas. The argument against this practice has always been one of reducing respondent engagement, which could be interpreted as a result of fatigue or boredom, with frequent reference to the findings of Bradley and Daly (1994) who showed a significant drop in utility scale, i.e. an increase in error, as a respondent moved from one choice experiment to the next, an effect they related to respondent fatigue. While the work by Bradley and Daly has become a standard reference in this context, it should be recognised that not only was the fatigue part of the work based on a single dataset, but the state-of-the-art and the state-of-practice in stated choice survey design and implementation has moved on significantly since their study. In this paper, we review other literature and present a more comprehensive study investigating evidence of respondent fatigue across a larger number of different surveys. Using a comprehensive testing framework employing both Logit and mixed Logit structures, we provide strong evidence that the concerns about fatigue in the literature are possibly overstated, with no clear decreasing trend in scale across choice tasks in any of our studies. For the data sets tested, we find that accommodating any scale heterogeneity has little or no impact on substantive model results, that the role of constants generally decreases as the survey progresses, and that there is evidence of significant attribute level (as opposed to scale) heterogeneity across choice tasks.     

An analysis of the factors influencing differences in survey-reported and GPS-recorded trips

Recent advances in global positioning systems (GPS) technology have resulted in a transition in household travel survey methods to test the use of GPS units to record travel details, followed by the application of an algorithm to both identify trips and impute trip purpose, typically supplemented with some level of respondent confirmation via prompted-recall surveys. As the research community evaluates this new approach to potentially replace the traditional survey-reported collection method, it is important to consider how well the GPS-recorded and algorithm-imputed details capture trip details and whether the traditional survey-reported collection method may be preferred with regards to some types of travel. This paper considers two measures of travel intensity (survey-reported and GPS-recorded) for two trip purposes (work and non-work) as dependent variables in a joint ordered response model. The empirical analysis uses a sample from the full-study of the 2009 Indianapolis regional household travel survey. Individuals in this sample provided diary details about their travel survey day as well as carried wearable GPS units for the same 24-h period. The empirical results provide important insights regarding differences in measures of travel intensities related to the two different data collection modes (diary and GPS). The results suggest that more research is needed in the development of workplace identification algorithms, that GPS should continue to be used alongside rather than in lieu of the traditional diary approach, and that assignment of individuals to the GPS or diary survey approach should consider demographics and other characteristics.     

A Bayesian approach for modeling origin-destination matrices

The majority of origin destination (OD) matrix estimation methods focus on situations where weak or partial information, derived from sample travel surveys, is available. Information derived from travel census studies, in contrast, covers the entire population of a specific study area of interest. In such cases where reliable historical data exist, statistical methodology may serve as a flexible alternative to traditional travel demand models by incorporating estimation of trip-generation, trip-attraction and trip-distribution in one model. In this research, a statistical Bayesian approach on OD matrix estimation is presented, where modeling of OD flows derived from census data, is related only to a set of general explanatory variables. A Poisson and a negative binomial model are formulated in detail, while emphasis is placed on the hierarchical Poisson-gamma structure of the latter. Problems related to the absence of closed-form expressions are bypassed with the use of a Markov Chain Monte Carlo method known as the Metropolis-Hastings algorithm. The methodology is tested on a realistic application area concerning the Belgian region of Flanders on the level of municipalities. Model comparison indicates that negative binomial likelihood is a more suitable distributional assumption than Poisson likelihood, due to the great degree of overdispersion present in OD flows. Finally, several predictive goodness-of-fit tests on the negative binomial model suggest a good overall fit to the data. In general, Bayesian methodology reduces the overall uncertainty of the estimates by delivering posterior distributions for the parameters of scientific interest as well as predictive distributions for future OD flows.     

危险品物流园区消防设施与总平面关系

针对危险品仓储物流园区内数以千计种危险品,论述危险品内危险品在装箱堆场、危险品拆装箱场地和危险品仓库内的布置原则及采取的消防措施,研究常见危险品最广泛采用的3种消防灭火剂,提出灭火剂相应的消防设施与总平面的关系。通过工程实例,明确危险品集装箱堆场、危险品拆装箱场地和危险品仓库的布置方法,为危险品物流园区平面和消防安全设计提供借鉴。     

智慧船厂概念模型研究

针对智慧船厂的功能概念、智慧生产流程、智慧化进程等方面的研究不足,提出智慧船厂的系统性功能定义,并进行了详细的定义分解分析,建立了智慧船厂的生产流程模型和智慧化进程模型,通过案例分析,对功能定义、生产流程模型和智慧化进程概念模型的有效性进行了验证。     

水平荷载作用下两种桩土模拟算法对高桩码头横向排架的影响

以某码头工程为例,横向排架按柔性桩台考虑,将实际结构图简化得到其计算简图;基于m法和假想嵌固点法,分别采用弹性嵌固和固端约束模拟桩土相互作用,利用ANSYS建立2种有限元模型计算水平力作用下横向排架的内力和变形;采用SPSS对计算结果进行数据统计分析。结果显示:当显著水平α取0.05时,采用m法和假想嵌固点法计算桩土相互作用对水平力作用下横向排架的内力和变形的影响无显著差异。     

洋山四期全自动集装箱码头设计创新

自动化码头在装卸作业的稳定高效、安全节能、绿色环保等方面具有显著优势,已成为我国实现港口转型升级发展的必由之路。但我国自动化港口建设起步晚,技术经验积累少,缺少相应的技术标准和规范指导。而洋山四期工程是我国首座拥有安全自主技术打造的当前全球单项规模最大、技术最先进的全自动化集装箱码头工程,其设计经验对于推动我国港口的技术进步具有重要的借鉴意义。对洋山四期工程自动化集装箱码头设计所涉及的平面、工艺、结构、控制、供电、给排水等多方面设计成果进行总结和梳理,为同类工程设计提供参考。