基于大数据和智能感知的车辆数据引擎系统设计

陈希隽

doi:10.13890/j.issn.1000-128X.2023.06.016

您当前的位置：

首页 >

文章列表页 >

基于大数据和智能感知的车辆数据引擎系统设计

智能化技术 | 更新时间：2024-08-02

- 基于大数据和智能感知的车辆数据引擎系统设计
- Design of vehicle data engine system based on big data platform and intelligent perception
- 机车电传动 2023年第6期页码：129-138
- 作者机构：
  
  广州地铁集团有限公司，广东广州 510010
- 作者简介：
  
  陈希隽（1975—），男，高级工程师，主要从事轨道交通车辆运维管理工作；E-mail: chenxijun@gzmtr.com
- 基金信息：
- DOI：10.13890/j.issn.1000-128X.2023.06.016
  中图分类号： U27
- 纸质出版日期：2023-11-10，
  
  收稿日期：2022-08-24，
  
  修回日期：2023-04-08，
- 稿件说明：
扫描看全文
陈希隽. 基于大数据和智能感知的车辆数据引擎系统设计[J]. 机车电传动, 2023(6): 129-138.

CHEN Xijun. Design of vehicle data engine system based on big data platform and intelligent perception[J]. Electric drive for locomotives,2023(6): 129-138.
陈希隽. 基于大数据和智能感知的车辆数据引擎系统设计[J]. 机车电传动, 2023(6): 129-138. DOI： 10.13890/j.issn.1000-128X.2023.06.016.

CHEN Xijun. Design of vehicle data engine system based on big data platform and intelligent perception[J]. Electric drive for locomotives,2023(6): 129-138. DOI： 10.13890/j.issn.1000-128X.2023.06.016.

摘要

为实现城市轨道车辆的精准化运维指导，需要掌握最新的车辆状态数据并对其发展趋势进行预判，对车辆的实时运行数据和历史运维数据进行同时空的数据挖掘分析研究十分必要。最终，用户无须掌握代码编写技能即可自行创建、修改数据分析模型，模型能自动运行输出结果，为车辆状态的判断提供依据。为此，文章基于大数据平台和智能感知技术设计了一套车辆数据引擎系统，将牵引、制动、车门、网络和LCU等系统的运行数据进行清洗整合，实现数据的时空对齐，利用画布开发组件，采用“拖拉拽”的方式构建数据分析策略模型，可替代重复繁杂的人工作业进行多维数据分析决策、作业流程监控、故障隐患甄别并预警、寿命预测等工作，实现数据分析自定义编辑、自动分析、自动预警，指导故障处理、备件采购等功能，从而达到多专业数据融合、数据综合监视、故障联动分析、数据统计分析、自动化处理分析、结果输出和推演预测、一体化决策及可视化展示，为检修运用模式和策略制定提供数据支撑，进一步保证地铁列车行车安全，提升列车可靠性、降低运营成本。

Abstract

To guide the operation and maintenance (O&M) of the urban rail transit vehicles precisely

it is necessary to collect the latest vehicle status data and predict the development trend. Therefore

it is essential to conduct data mining and analysis for the real-time operation data and the historical O&M data of the vehicles in the same time and space

and enable the users to create and modify the data analysis model without the ability to write code. The model can run automatically and output the results to provide a basis for the vehicle status judgment. To this end

a set of vehicle data engine system was designed based on the big data platform and intelligent perception to clean and integrate the operation data of the traction

braking

door

network and LCU systems for the spatial and temporal alignment of data. In addition

data analysis strategy model was developed by means of drag and drop based on the canvas components to carry out multidimensional data analysis

make decisions

monitor the working process

identify hidden troubles and give early warning

and make life predictions

replacing the repetitive and complex manual operation. It can also provide functions such as data analysis custom editing

automatic analysis

automatic warning

troubleshooting guidance

and spare parts procurement

thus achieving multi-discipline data fusion

integrated data supervisory control

fault linkage analysis

data statistical analysis

automated processing analysis

result output

deduction and prediction

integrated decision-making and visual display

providing data support for the development of maintenance modes and strategies

further ensuring the safety of metro trains

improving the train reliability

and reducing the operating costs.

关键词

运维数据组件智能分析自定义编辑数据引擎提质增效城市轨道车辆

Keywords

operation and maintenance datacomponentsintelligent analysiscustom editingdata enginequality and efficiency improvementurban rail transit vehicles

references

新华社. 中共中央国务院印发《交通强国建设纲要》[EB/OL]. (2019-09-19) [2021-05-18]. https://www.gov.cn/gongbao/content/2019/content_5437132.htmhttps://www.gov.cn/gongbao/content/2019/content_5437132.htm.

Xinhua News Agency. The CPC central committee and the state council issued the outline of building a transportation power[EB/OL]. (2019-09-19) [2021-05-18]. http://www.gov.cn/gongbao/content/2019/content_5437132.htmhttp://www.gov.cn/gongbao/content/2019/content_5437132.htm.

董岳. 基于 “智慧地铁” 的城市轨道交通智能运维模式创新研究[J]. 城市轨道交通研究, 2022, 25(3): 240-241.

DONG Yue. Innovative research on intelligent operation and maintenance mode of urban rail transit based on "smart metro" [J]. Urban mass transit, 2022, 25(3): 240-241.

刘家栋, 毛如香, 马喜成, 等. 事件记录仪在城轨车辆中的应用[J]. 电力机车与城轨车辆, 2013, 36(4): 81-82.

LIU Jiadong, MAO Ruxiang, MA Xicheng, et al. Application of event recorder in urban rail vehicles[J]. Electric locomotives & mass transit vehicles, 2013, 36(4): 81-82.

刘丙林, 朱佳, 李翔宇. 城市轨道交通车辆智能运维系统探索与研究[J]. 现代城市轨道交通, 2019(6): 16-21.

LIU Binglin, ZHU Jia, LI Xiangyu. Exploration and research on intelligent operation and maintenance system of urban rail transit vehicles[J]. Modern urban transit, 2019(6): 16-21.

刘鹏辉. 城市轨道交通车辆智能运维应用研究[J]. 智能城市, 2021, 7(24): 133-134.

LIU Penghui. Research on intelligent operation and maintenance application of urban rail transit vehicles[J]. Intelligent city, 2021, 7(24): 133-134.

王杰, 高会永, 王子龙, 等. CRH5型动车组车载数据智能分析研究[J]. 黑龙江科学, 2022, 13(12): 50-52.

WANG Jie, GAO Huiyong, WANG Zilong, et al. Research on intelligent analysis of on-board data of CRH5 EMU[J]. Heilongjiang science, 2022, 13(12): 50-52.

陈思. 郑州地铁5号线牵引指令丢失故障分析[J]. 科学技术创新, 2020(29): 92-93.

CHEN Si. Analysis of traction command loss fault on Zhengzhou metro line 5[J]. Scientific and technological innovation, 2020(29): 92-93.

娄亭. 轨道交通车站机电设备智能运维系统研究与实践[J]. 交通世界, 2022(18): 57-60.

LOU Ting. Research and practice of intelligent operation and maintenance system for electromechanical equipment of rail transit station[J]. Transpo world, 2022(18): 57-60.

侯文军, 吴彩秀. 地铁车辆智慧运维平台研究[J]. 电力机车与城轨车辆, 2019, 42(6): 1-3.

HOU Wenjun, WU Caixiu. Research on metro vehicle intelligent operation and maintenance platform[J]. Electric locomotives & mass transit vehicles, 2019, 42(6): 1-3.

张毅, 崔晓燕. 基于云计算平台的物联网数据挖掘研究[J]. 软件, 2014, 35(1): 108-111.

ZHANG Yi, CUI Xiaoyan. The data mining of IOT based on cloud computing[J]. Software, 2014, 35(1): 108-111.

赵志伟. 智能化规则引擎技术研究[J]. 软件, 2018, 39(8): 65-69.

ZHAO Zhiwei. The research on intelligent rule engine technology[J]. Software, 2018, 39(8): 65-69.

产院东, 郭乔进, 梁中岩, 等. 规则引擎发展综述[J]. 信息化研究, 2021, 47(2): 1-6.

CHAN Yuandong, GUO Qiaojin, LIANG Zhongyan, et al. A survey of rule engine[J]. Informatization research, 2021, 47(2): 1-6.

王少丽. 基于AngularJS的前端开发框架的设计与应用[D]. 大连: 大连海事大学, 2018.

WANG Shaoli. Design and application of front-end development framework based on AngularJS[D]. Dalian: Dalian Maritime University, 2018.

何中秋. 面向大数据应用的分布式服务组合引擎设计与实现[D]. 北京: 北方工业大学, 2021.

HE Zhongqiu. Design and implementation of distributed service composition engine for big data applications[D]. Beijing: North University of Technology, 2021.

西安西隆电气有限责任公司. D-U200系列瞬动中间继电器使用维护说明书[EB/OL]. [2022-05-18]. https://max.book118.com/html/2015/0808/22859129.shtmhttps://max.book118.com/html/2015/0808/22859129.shtm.

Xi'an Xilong Electric Co., Ltd. D-U200 series instantaneous intermediate relay operation and maintenance manual[EB/OL]. [2022-05-18]. https://max.book118.com/html/2015/0808/22859129.shtmhttps://max.book118.com/html/2015/0808/22859129.shtm.

浏览量

下载量

CSCD

CNKI被引量

文章被引用时，请邮件提醒。

提交

工具集

关联资源

城市轨道交通车辆安全控制系统架构分析及综述

一种界面新颖的LKJ质量智能分析系统