CRH动车组临修作业中的U2000型不落轮镟床

CRH动车组在运行过程中由于其速度快,自重大等原因,轮对踏面擦伤与剥离现象较严重,在不满足三级以上修程时,需要对其进行临修作业,主要的镟轮设备是不落轮镟床.从软、硬件及其基本原理方面介绍U2000型不落轮镟床,旨在学习掌握U2000型不落轮镟床的原理,以提高对其的维护保养以及维修技能.     

基于机器视觉的非接触式螺纹参数测量系统

文中采用光机电一体化的思想,将光源、CCD、计算机等有机结合,开发了一种基于面阵CCD技术的石油管螺纹参数智能化测量系统。生产现场测量结果表明：该系统具有重复性好、精度高、检测速度快等优点,此外,此系统具有抗环境光及振动干扰,可操作性强等特点,适用于各种规格钢管外螺纹参数的在线测量。     

Fluid forces acting on three and four long side-by-side flexible cylinders undergoing flow-induced vibration(FIV)

Multiple side-by-side cylinders are widely employed in many engineering applications. Consequently, flow-induced vibrations (FIV), which have a significant influence on structural reliability, have drawn considerable concern from many investigators. Due to the complicated wake interactions behind the cylinders, the hydrodynamic characteristics of multiple side-by-side cylinders subject to FIV are obviously different from those of a single cylinder. Hydrodynamic force coefficients play an important role in evaluating structural reliability and predicting fatigue damage. However, few relevant investigations have been performed on hydrodynamic force coefficients of multiple side-by-side flexible cylinders, which require further research. In this paper, the hydrodynamic force coefficients of three and four side-by-side flexible cylinders with a spacing ratio of 6.0 are obtained by an inverse analysis method based on the oscillation displacements. In the resonance regions, the hydrodynamic force coefficients of multiple cylinders exhibit variation trends similar to those of a single cylinder, especially at higher reduced velocities. In the mode switch regions, relatively large deviations exist between the coefficients of multiple cylinders and single cylinder. The inner cylinder in the three-cylinder system shows prominently distinctive behaviour compared with the outer two cylinders. For the four-cylinder system in a side-by-side arrangement, the outer two cylinders show relatively slight differences between each other compared with the inner two cylinders.     

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.     

动力分散型电动车组车载微机网络的功能划分与接口设想

从车载微机网络的拓扑结构、网络组成单元及功能划分、接口与控制逻辑、故障处理几个方面提出了动力分散型电动车组车载微机网络的功能划分与接口设想。     

动车组ATP软件升级后问题处理

阐述动车组ATP车载软件升级后遇到的典型问题并对产生原因进行分析,提出了有效的解决方案,确保了行车安全,现场应用效果良好。     

南京地铁二号线信号系统多级后备控制模式

后备控制模式是提高信号系统可靠性,保证其正常运营的重要手段之一。南京地铁二号线在西门子Trainguard MTA TC系统原有后备控制模式的基础上,又引入了中国电子科技集团公司第十四研究所研发的后备控制模式,使整个系统的可靠性得以提高。通过对多级后备控制模式的设计及原理进行分析,为今后进一步完善后备系统提供参考。     

动荷载下钢筋接头直螺纹连接研究

北京南站轨道层板为地下室顶板,钢筋接头总量约为50万个,轨道层直接承受动荷载(列车轨道)。研究动荷载下直螺纹连接的可行性,对连接HRB335级钢筋的接头进行了应力为100 N/mm2,最大应力为180 N/mm2,最小应力为80 N/mm2的200万次循环加载试验。然后进行深化设计直螺纹连接接头和连接套筒,连接方案经过专家论证后在本工程成功应用,达到良好效果,结合该工程,为钢筋直螺纹连接技术在国内桥梁,特别是在铁路桥梁施工中的广泛应用提供了借鉴。     

螺纹数控车削方法的研究

本文主要从螺纹相关基础知识、数控加工指令及应用、螺纹加工注意事项等四个方面,讲述了螺纹的数控车削学习方法和要点。     

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.