基于微控制器的脉宽调制编码器在轻轨车辆上的应用

脉宽调制编码器(PWM encoder)在铁路动车组和轻轨、地铁车辆上担负着牵引、制动指令传输的重要任务。文章主要阐述了基于微控制器的脉宽调制编码器的设计理念、硬件组成、软件实现及其内部控制逻辑关系。     

火箭弹发射时连接螺纹处强度的数值分析和研究

基于非线性有限元数值分析,研究了某型号火箭弹内连接螺纹在发射中的强度问题。计算中考虑了材料的非线性问题和螺纹间的接触问题。计算结果表明,接触部位存在着明显的应力集中现象,但螺纹部位总体的应力水平较低,能够保证火箭弹的发射安全。     

轿车白车身重量目标设定方法

文章探讨了影响轿车白车身重量的因素,包括总质量,车身扭转刚度,长、宽、高等尺寸参数,并通过最佳子集回归分析找到影响轿车白车身主要因素。最后,基于多元线性回归分析,研究最佳影响因素与白车身重量间的关系,并推导出一种用于轿车白车身重量目标设定方法,为项目研发过程中车身重量目标的开发设定提供重要参考。     

Integrated sequencing and merging aircraft to parallel runways with automated conflict resolution and advanced avionics capabilities

Congestion in Terminal Maneuvering Area (TMA) in hub airports is the main problem in Chinese air transportation. In this paper we propose a new system to integrated sequence and merge aircraft to parallel runways at Beijing Capital International Airport (BCIA). This system is based on the advanced avionics capabilities. Our methodology integrates a Multi-Level Point Merge (ML-PM) system, an economical descent approaches procedure, and a tailored heuristic algorithm to find a good, systematic, operationally-acceptable solution. First, Receding Horizontal Control (RHC) technique is applied to divide the entire 24 h of traffic into several sub-problems. Then in each sub-problem, it is optimized on given objectives (conflict, deviation from Estimated Time of Arrival (ETA) on the runway and makespan of the arrival flow). Four decision variables are designed to control the trajectory: the entry time, the entry speed, the turning time on the sequencing leg, and the landing runway allocation. Based on these variables, the real time trajectories are generated by the simulation module. Simulated Annealing (SA) algorithm is used to search the best solution for aircraft to execute. Finally, the conflict-free, least-delay, and user-preferred trajectories from the entry point of TMA to the landing runway are defined. Numerical results show that our optimization system has very stable de-conflict performance to handle continuously dense arrivals in transition airspace. It can also provide the decision support to assist flow controllers to handle the asymmetric arrival flows on different runways with less fuel consumption, and to assist tactical controllers to easily re-sequence aircraft with more relaxed position shifting. Moreover, our system can provide the fuel consumption prediction, and runway assignment information to assist airport and airlines managers for optimal decision making. Theoretically, it realizes an automated, cooperative and green control of routine arrival flows. Although the methodology defined here is applied to the airport BCIA, it could also be applied to other airports in the world.     

Critical assessment of five methods to correct for endogeneity in discrete-choice models

Endogeneity often arises in discrete-choice models, precluding the consistent estimation of the model parameters, but it is habitually neglected in practical applications. The purpose of this article is to contribute in closing that gap by assessing five methods to address endogeneity in this context: the use of Proxys (PR); the two steps Control-Function (CF) method; the simultaneous estimation of the CF method via Maximum-Likelihood (ML); the Multiple Indicator Solution (MIS); and the integration of Latent-Variables (LV). The assessment is first made qualitatively, in terms of the formulation, normalization and data needs of each method. Then, the evaluation is made quantitatively, by means of a Monte Carlo experiment to study the finite sample properties under a unified data generation process, and to analyze the impact of common flaws. The methods studied differ notably in the range of problems that they can address; their underlying assumptions; the difficulty of gathering proper auxiliary variables needed to apply them; and their practicality, both in terms of the need for coding and their computational burden. The analysis developed in this article shows that PR is formally inappropriate for many cases, but it is easy to apply, and often corrects in the right direction. CF is also easy to apply with canned software, but requires instrumental variables which may be hard to collect in various contexts. Since CF is estimated in two stages, it may also compromise efficiency and difficult the estimation of standard errors. ML guarantees efficiency and direct estimation of the standard errors, but at the cost of larger computational burden required for the estimation of a multifold integral, with potential difficulties in identification, and retaining the difficulty of gathering proper instrumental variables. The MIS method appears relatively easy to apply and requiring indicators that may be easier to obtain in various cases. Finally, the LV approach appears as the more versatile method, but at a high cost in computational burden, problems of identification and limitations in the capability of writing proper structural equations for the latent variable.     

A joint bottom-up solution methodology for system-level pavement rehabilitation and reconstruction

We present a methodology for the joint optimization of rehabilitation and reconstruction activities for heterogeneous pavement systems under multiple budget constraints. The proposed bottom-up approach adopts an augmented condition state to account for the history-dependent properties of pavement deterioration, and solves for steady-state policies for an infinite horizon. Genetic algorithms (GAs) are implemented in the system-level optimization based on segment-specific optimization results. The complexity of the proposed algorithm is polynomial in the size of the system and the policy-related parameters. We provide graphical presentations of the optimal solutions for various budget situations. As a case study, a subset of California’s highway system is analyzed. The case study results demonstrate the economic benefit of a combined rehabilitation and reconstruction budget compared to separate budgets.     

Improving rail network velocity: A machine learning approach to predictive maintenance

Rail network velocity is defined as system-wide average speed of line-haul movement between terminals. To accommodate increased service demand and load on rail networks, increase in network velocity, without compromising safety, is required. Among many determinants of overall network velocity, a key driver is service interruption, including lowered operating speed due to track/train condition and delays caused by derailments. Railroads have put significant infrastructure and inspection programs in place to avoid service interruptions. One of the key measures is an extensive network of wayside mechanical condition detectors (temperature, strain, vision, infrared, weight, impact, etc.) that monitor the rolling-stock as it passes by. The detectors are designed to alert for conditions that either violate regulations set by governmental rail safety agencies or deteriorating rolling-stock conditions as determined by the railroad.Using huge volumes of historical detector data, in combination with failure data, maintenance action data, inspection schedule data, train type data and weather data, we are exploring several analytical approaches including, correlation analysis, causal analysis, time series analysis and machine learning techniques to automatically learn rules and build failure prediction models. These models will be applied against both historical and real-time data to predict conditions leading to failure in the future, thus avoiding service interruptions and increasing network velocity. Additionally, the analytics and models can also be used for detecting root cause of several failure modes and wear rate of components, which, while do not directly address network velocity, can be proactively used by maintenance organizations to optimize trade-offs related to maintenance schedule, costs and shop capacity. As part of our effort, we explore several avenues to machine learning techniques including distributed learning and hierarchical analytical approaches.     

多重化双向DC-DC变换器在DCM状态下电感电流纹波研究

本文首先分析了多重化双向DC-DC变换器的工作原理。在频域内分别对单个DC-DC变换器和多重化双向DC-DC变换器在电流断续状态下的电流用Fourier级数展开,导出了电流各次标准化谐波幅值及其比值与占空比的定量表达式。在时域内依据基于多重化结构的双向DC-DC变换器合成总电感电流波形特征导出了多重化双向DC-DC变换器与单个DC—DC变换器电感电流的脉动率比与占空比的定量表达式。定量表达式表明,多重化双向DC-DC变换器与单个DC—DC变换器相比,电感电流纹波及其谐波明显减小。这些定量表达式为大功率DC-DC变换器拓扑结构和工作点的选择提供依据。     

浅埋偏压连拱隧道中隔墙合理厚度的确定

以在建大跨、浅埋偏压高速公路连拱隧道具体项目为研究对象,采用基于地层结构的有限单元数值分析方法,对不同厚度的中隔墙进行受力状态分析,提出了该浅埋偏压连拱隧道中隔墙的合理厚度,研究思路可为类似工程提供借鉴。     

快速管接头在商用车管路系统中的应用

介绍一种新型快速管接头在商用车管路系统的产业化应用。分析了传统卡套式管接头与快速管接头的结构性能与特点,快速管接头改进现有卡套式管接头的结构型式和装配方式,提高了产品性能和工作效率、降低了综合成本,且具有密封性好、耐压高、连接牢固、安全可靠等性能。结合快速管接头的工作原理和结构形式,阐述了快速管接头在卡车管路系统中的应用前景和技术优势。