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A Neural Network Approach to Predicting Car Tyre Micro-Scale and Macro-Scale Behaviour 汽车轮胎微观和宏观行为预测的神经网络方法
Pub Date : 2014-01-27 DOI: 10.4236/JILSA.2014.61002
Xiaoguang Yang, M. Behroozi, O. Olatunbosun
Finite Element (FE) analysis has become the favoured tool in the tyre industry for virtual development of tyres because of the ability to represent the detailed lay-up of the tyre carcass. However, application of FE analysis in tyre design and development is still very time-consuming and expensive. Here, the application of various Artificial Neural Network (ANN) architectures to predicting tyre performance is assessed to select the most effective and efficient architecture, to allow extensive parametric studies to be carried out inexpensively and to optimise tyre design before a much more expensive full FE analysis is used to confirm the predicted performance.
有限元分析由于能够反映轮胎胎体的详细分层结构,已成为轮胎行业进行轮胎虚拟开发的首选工具。然而,在轮胎设计和开发中应用有限元分析仍然是非常耗时和昂贵的。在这里,评估各种人工神经网络(ANN)体系结构在预测轮胎性能方面的应用,以选择最有效和最高效的体系结构,从而允许以低成本进行广泛的参数研究,并在使用更昂贵的完整有限元分析来确认预测性能之前优化轮胎设计。
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引用次数: 20
SOMS: A Subway Operation and Maintenance System Based on Planned Maintenance Model with Train State 基于列车状态计划维修模型的地铁运维系统
Pub Date : 2013-11-12 DOI: 10.4236/JILSA.2013.54021
Jianlong Ding, Yong Qin, L. Jia, Shiyou Zhu, Bo Yu
This paper aims to propose a modeling framework for subway operation and maintenance system (SOMS), which analyzes the train condition data based on both train sensor network data and basis train maintenance plan. The system is formulated into five function modules, and the research problem is to determine one auxiliary maintains plan, including the time allocation and frequency of maintenance. The case of Guangzhou metro is conducted to illustrate the applicability of SOMS, and the results reveal a number of interesting insights into subway maintenance system, i.e., the worksheet can reduce duplication of redundant maintenance work, the repair cost, and the damage caused by frequent disassembly.
本文旨在提出一种基于列车传感器网络数据和基础列车维护计划的地铁运维系统(SOMS)建模框架,对列车状态数据进行分析。系统分为五个功能模块,研究的问题是确定一个辅助维护计划,包括维护的时间分配和频率。本文以广州地铁为例,对SOMS的适用性进行了分析,结果揭示了地铁维修系统的一些有趣的见解,即工作表可以减少重复的冗余维修工作,减少维修成本,减少频繁拆卸造成的损坏。
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引用次数: 8
Design of Integrated Monitoring and Early Warning System of Urban Rail Transit Train Running State 城市轨道交通列车运行状态综合监测预警系统设计
Pub Date : 2013-11-12 DOI: 10.4236/JILSA.2013.54022
Ting Yun, Gang Chen, F. Zhou, Y. Lu, Haiyu Li, Qian Li
The monitoring and warning of urban rail transit is the core of operation management, and the breadth and depth of the monitoring range directly affect the quality of urban rail transit operation. For the current domestic monitoring system, most of the critical equipments and technologies are introduced from abroad; it is diseconomy, and also causes hidden danger. Realizing the localization of monitoring and early warning system is imperative. Based on the analysis of the present situation of urban rail transit operation safety at home and abroad, the paper proposes to use integrated technology to design basic framework of monitoring and warning system of urban rail train, and puts forward the critical technologies to realize the system. Compared with the existing monitoring system, the integrated monitoring system has the characteristics of wide monitoring range, clear division of labor, centralized management, coordination and integration operation and intelligent management, and embodies the concept of people-oriented. It has scientific significance for future construction of domestic Integrated Monitoring and Early Warning System (IMEWS) of urban rail transit.
城市轨道交通的监控预警是运营管理的核心,监控范围的广度和深度直接影响着城市轨道交通的运营质量。目前国内监控系统的关键设备和技术大多是从国外引进的;这是不经济的,也会造成隐患。实现监测预警系统的本地化势在必行。在分析国内外城市轨道交通运行安全现状的基础上,提出采用集成技术设计城市轨道交通列车监控预警系统的基本框架,并提出了实现该系统的关键技术。综合监控系统与现有的监控系统相比,具有监控范围广、分工明确、集中管理、协调一体化运作、智能化管理等特点,体现了以人为本的理念。这对未来国内城市轨道交通综合监测预警系统(IMEWS)的建设具有重要的科学意义。
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引用次数: 2
Research on the Prediction Model for the Security Situation of Metro Station Based on PSO/SVM 基于PSO/SVM的地铁车站安全态势预测模型研究
Pub Date : 2013-11-12 DOI: 10.4236/JILSA.2013.54028
Yong Qin, Zhenyu Zhang, Bo Chen, Z. Xing, Jing Liu, Jun Li
Security situation awareness is a new technology about security. This paper brings it to the assessment of security situation of metro station which serves as a new way to secure the security of passengers as well as the operation of the metro station. This paper sets up an index system for assessing the security situation awareness and makes a prediction model for the security situation of metro station based on PSO/SVM after doing lots of researches and analyses. Furthermore, through case studies, we find that the model has high accuracy and ability to accurately predict the security situation of metro station in the future and a certain practical value.
安全态势感知是一种新的安全技术。本文将其引入地铁车站安全态势评估,为保障乘客安全和地铁车站运营提供了一种新的途径。本文通过大量的研究和分析,建立了安全态势感知评价指标体系,并建立了基于粒子群算法/支持向量机的地铁车站安全态势预测模型。通过实例分析,发现该模型具有较高的准确率,能够准确预测未来地铁车站的安全状况,具有一定的实用价值。
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引用次数: 3
Detection and Diagnosis of Urban Rail Vehicle Auxiliary Inverter Using Wavelet Packet and RBF Neural Network 基于小波包和RBF神经网络的城市轨道车辆辅助逆变器检测与诊断
Pub Date : 2013-11-12 DOI: 10.4236/JILSA.2013.54023
Guangwu Liu, Jingjing Long, Lingzhi Yang, Z. Su, Dechen Yao, Xiangli Zhong
This study concerns with fault diagnosis of urban rail vehicle auxiliary inverter using wavelet packet and RBF neural network. Four statistical features are selected: standard voltage signal, voltage fluctuation signal, impulsive transient signal and frequency variation signal. In this article, the original signals are decomposed into different frequency subbands by wavelet packet. Next, an automatic feature extraction algorithm is constructed. Finally, those wavelet packet energy eigenvectors are taken as fault samples to train RBF neural network. The result shows that the RBF neural network is effective in the detection and diagnosis of various urban rail vehicle auxiliary inverter faults.
研究了基于小波包和RBF神经网络的城市轨道车辆辅助逆变器故障诊断方法。选取四种统计特征:标准电压信号、电压波动信号、脉冲暂态信号和频率变化信号。本文采用小波包将原始信号分解成不同的频率子带。其次,构造了一种自动特征提取算法。最后,将这些小波包能量特征向量作为故障样本,训练RBF神经网络。结果表明,RBF神经网络对各种城市轨道车辆辅助逆变器故障的检测和诊断是有效的。
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引用次数: 1
Reliability Analysis of Metro Door System Based on FMECA 基于FMECA的地铁门系统可靠性分析
Pub Date : 2013-11-12 DOI: 10.4236/JILSA.2013.54024
Xiaoqing Cheng, Z. Xing, Yong Qin, Y. Zhang, Shaohuang Pang, J. Xia
The metro door system is one of the high failure rate subsystems of metro trains. The Failure Mode, Effects and Criticality Analysis (FMECA) method is applied to analyze the reliability of metro door system in this paper. Firstly, failure components of the door are statistically analyzed, and the major failure components are determined. Secondly, failures are classified according to their impacts on operation, and methods of calculating failure mode criticality and the related coefficients are illustrated. Finally, the FMECA is detailed in the selected 12 failure modes, and the failure modes are discovered that they have the most significant effect on metro door system. The obtained results can be used for optimal design and maintenance of the metro door system.
地铁车门系统是地铁列车故障率较高的子系统之一。本文采用失效模式、影响和临界分析(FMECA)方法对地铁门系统进行可靠性分析。首先对门的失效成分进行统计分析,确定主要失效成分;其次,根据故障对运行的影响程度对故障进行分类,并给出了失效模式临界度及相关系数的计算方法;最后,对选取的12种失效模式进行了详细的FMECA分析,发现这些失效模式对地铁门系统的影响最为显著。所得结果可用于地铁门系统的优化设计和维护。
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引用次数: 16
The Research of Urban Rail Transit Sectional Passenger Flow Prediction Method 城市轨道交通分段客流预测方法研究
Pub Date : 2013-11-12 DOI: 10.4236/JILSA.2013.54026
Qian Li, Yong Qin, Zi-yang Wang, Z. Zhao, Minghui Zhan, Yu Liu, Zhiguo Li
This paper studies the short-term prediction methods of sectional passenger flow, and selects BP neural network combined with the characteristics of sectional passenger flow itself. With a case study, we design three different schemes. We use Matlab to realize the prediction of the sectional passenger flow of the Beijing subway Line 2 and make comparative analysis. The empirical research shows that combining data characteristics of sectional passenger flow with the BP neural network have good prediction accuracy.
本文对分段客流的短期预测方法进行了研究,选择了结合分段客流本身特点的BP神经网络。通过案例研究,我们设计了三种不同的方案。利用Matlab实现了对北京地铁2号线分段客流的预测,并进行了对比分析。实证研究表明,将分段客流数据特征与BP神经网络相结合,具有较好的预测精度。
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引用次数: 11
Importance Analysis of Urban Rail Transit Network Station Based on Passenger 基于乘客的城市轨道交通网络站点重要性分析
Pub Date : 2013-11-12 DOI: 10.4236/JILSA.2013.54027
J. Jin, Man Li, Yan-hui Wang, Lingxi Zhu, Li Ping, Boxuan Wang, Ping Li
Current urban rail transit has become a major mode of transportation, and passenger is an important factor of urban rail transport, so this article is based on passenger and the degree of the road network structure, calculating the point intensity of stations of urban rail transit, and then reaching a station importance by integrating many point intensities in a survey cycle time, and getting the station importance of urban rail transit network through concrete examples.
当前城市轨道交通已成为城市轨道交通的主要交通方式,而乘客是城市轨道交通的重要因素,因此本文以乘客和路网结构的程度为基础,计算城市轨道交通站点的点强度,然后在一个调查周期时间内将多个点强度综合得出一个站点重要性,通过具体实例得到城市轨道交通网络的站点重要性。
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引用次数: 0
Fault Isolation of Light Rail Vehicle Suspension System Based on D-S Evidence Theory and Improvement Application Case 基于D-S证据理论的轻轨车辆悬架系统故障隔离及改进应用案例
Pub Date : 2013-11-12 DOI: 10.4236/JILSA.2013.54029
Xiukun Wei, Kun Guo, L. Jia, Guangwu Liu, Minzheng Yuan
This paper presents an innovative approach for the fault isolation of Light Rail Vehicle (LRV) suspension system based on the Dempster-Shafer (D-S) evidence theory and its improvement application case. The considered LRV has three rolling stocks and each one equips three sensors for monitoring the suspension system. A Kalman filter is applied to generate the residuals for fault diagnosis. For the purpose of fault isolation, a fault feature database is built in advance. The Eros and the norm distance between the fault feature of the new occurred fault and the one in the feature database are applied to measure the similarity of the feature which is the basis for the basic belief assignment to the fault, respectively. After the basic belief assignments are obtained, they are fused by using the D-S evidence theory. The fusion of the basic belief assignments increases the isolation accuracy significantly. The efficiency of the proposed method is demonstrated by two case studies.
提出了一种基于Dempster-Shafer (D-S)证据理论的轻轨车辆悬架系统故障隔离创新方法及其改进应用实例。考虑的LRV有三个机车车辆,每个机车车辆配备三个传感器用于监测悬挂系统。利用卡尔曼滤波产生残差进行故障诊断。为了实现故障隔离,预先建立了故障特征库。应用Eros和新发生故障的故障特征与特征库中的故障特征之间的范数距离来度量特征的相似度,这是对故障进行基本信念赋值的基础。在得到基本信念赋值后,利用D-S证据理论对其进行融合。基本信念赋值的融合显著提高了分离精度。通过两个实例验证了该方法的有效性。
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引用次数: 5
Preliminary Study on Selling Tickets in Reason for Last Trains on Beijing Rail Transit Network 北京轨道交通末班车合理售票初探
Pub Date : 2013-11-12 DOI: 10.4236/JILSA.2013.54030
Yang Wang, Jie Xu, L. Jia, Jianyuan Guo, Ping Liang, Bochen Wang, Jinxin Xie
With the increase of Beijing urban rail transport network, the structure of the road network is becoming more complex, and passengers have more travel options. Together with the complex paths and different timetables, taking the last train is becoming much more difficult and unsuccessful. To avoid losses, we propose feasible suggestions to the last train with reasonable selling tickets system.
随着北京城市轨道交通网络的增加,路网结构日趋复杂,旅客出行选择也越来越多。再加上复杂的路线和不同的时刻表,乘坐末班车变得更加困难和不成功。为避免损失,提出了末班车合理售票制度的可行性建议。
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引用次数: 0
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