工业4.0下智能铁路前沿技术问题综述

缪炳荣; 张卫华; 刘建新; 周宁; 梅桂明; 张盈

doi:10.19818/j.cnki.1671-1637.2021.01.005

工业4.0下智能铁路前沿技术问题综述

doi: 10.19818/j.cnki.1671-1637.2021.01.005

西南交通大学牵引动力国家重点实验室，四川成都 610031

基金项目:

国家自然科学基金项目 51775456

牵引动力国家重点实验室自主课题 2019TPL_T03

详细信息

作者简介:
缪炳荣(1970-)，男，江苏泰县人，西南交通大学副研究员，工学博士，从事多学科设计优化与智能制造、车辆动力学及寿命预测、结构健康监测研究

中图分类号: U270.12
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出版历程
- 收稿日期: 2020-09-07
- 刊出日期: 2021-08-27

Review on frontier technical issues of intelligent railways under Industry 4.0

State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, Sichuan, China

Funds:

National Natural Science Foundation of China 51775456

Autonomous Research Project of State Key Laboratory of Traction Power 2019TPL_T03

More Information

Author Bio:
MIAO Bing-rong(1970-), male, associate professor, PhD, brmiao@home.swjtu.edu.cn

Article Text (Baidu Translation)

摘要

摘要: 以铁路基础设施和车辆为主要研究对象，结合智能制造涉及的前沿技术和方法，阐述了合理利用工业4.0的内涵要素进行中国下一代智能铁路数字化建设、改造与升级的重要性和必要性；按照工业4.0的基本概念、技术内涵、系统模型和技术框架的影响效果，对比分析了智能基础设施、智慧列车、智能运维及相关技术的实施过程和存在问题，并在此基础上分析了以智慧列车为核心的智能铁路数字化平台建设关键技术；概括了铁路传统制造向智能制造数字化建设的具体技术要求，整理了利用工业4.0六维模型解决人工智能、大数据、云计算和数字孪生等前沿技术与铁路传统制造业的融合问题，包括数据传输与共享、信息通信与安全技术的潜力挖掘、智能管理、技术应用、信息安全、状态智能感知等各个方面。研究结果表明：中国铁路数字信息技术和智能技术与传统制造过程存在融合不足的问题；智能制造的核心技术储备不足，状态智能感知、数据在线分析、工业控制系统等软硬件技术自主性不强；铁路系统大数据建设的数据传输和标准体系也不够完善；未来智能铁路应该加强工业4.0下铁路传统制造的标准化管理系统与数据信息安全系统的数字化设计、升级与改造；需要深刻思考和分析人工智能和大数据驱动等前沿技术与铁路的融合与实施，通过工业4.0涵盖的各项关键技术的实施和准确评估真正有效推动中国智能铁路先进数字化平台的建设和发展。
- 智能铁路 /
- 智慧列车 /
- 工业4.0 /
- 人工智能 /
- 物联网 /
- 大数据
Abstract: The importance and necessity of the rational use of the connotative elements of Industry 4.0 for the digital construction, transformation, and upgrading of the next generation intelligent railways of China were explained. To this end, railway infrastructures and vehicles were considered as research objects, and frontier technologies and methods pertaining to intelligent manufacturing were combined. Based on the impacts of basic concept, technical connotation, system model, and technical framework of Industry 4.0, the implementation processes and existing problems of intelligent infrastructure, smart train, intelligent operation and maintenance, and related technologies were compared and analyzed. In addition, the key technologies for the digital platform construction of intelligent railways focusing on smart trains were analyzed. The specific technical requirements for the digital construction corresponding to traditional manufacturing to intelligent manufacturing were summarized. Problems pertaining to the integration of frontier technologies, such as artificial intelligence, big data, cloud computing, and digital twins, with the traditional railway manufacturing, were compiled and solved using a six-dimensional model of Industry 4.0. These problems included the data transmission and sharing, exploration of the potential of information communication and security technology, and intelligent management, technology application, information security, and intelligent state awareness. Research result demonstrates that the integration of digital information technology and intelligent technology with the traditional manufacturing process is insufficient. The core know-how of intelligent manufacturing is inadequate. A lack of autonomy of software and hardware technologies, such as intelligent state awareness, online data analysis, and industrial control systems, is observed. The data transmission and standard system for the construction of big data for the railway system is not perfect. The digital design, upgrade, and transformation of the standardized management system and data information security system of railway traditional manufacturing in Industry 4.0 should be strengthened in future intelligent railways. Deep thinking and analysis of the integration and implementation of frontier technologies including artificial intelligence and big data drive in railways are required. Various key technologies covered in Industry 4.0 should be implemented and accurately evaluated to truly and effectively promote the construction and development of an advanced digital platform for intelligent railways of China. 1 tab, 13 figs, 69 refs.
- intelligent railway /
- smart train /
- Industry 4.0 /
- artificial intelligence /
- internet of things /
- big data

HTML全文

图 1 工业4.0的发展历程

Figure 1. Development history of Industry 4.0

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图 2 产业化时代和数字生态时代的特征

Figure 2. Characteristics of production and digital ecosystem eras

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图 3 工业4.0的六维模型

Figure 3. Six-dimensional model of Industry 4.0

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图 4 工业4.0的主要制造国家

Figure 4. Major manufacturing countries of Industry 4.0

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图 5 未来的智能铁路构想

Figure 5. Concept of future intelligent railway

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图 6 智能铁路的主要技术框架

Figure 6. Main technical framework of intelligent railway

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图 7 日本未来铁路的智能维护策略

Figure 7. Intelligent maintenance strategy of future railways of Japan

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图 8 高速列车智能诊断与故障预测系统

Figure 8. High-speed train intelligent diagnosis and fault prediction system

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图 9 SKF公司提出的智慧生态系统

Figure 9. Smart eco-system proposed by SKF Company

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图 10 大数据在智能铁路中的应用

Figure 10. Application of big data in intelligent railways

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图 11 增强现实技术在电机维护中的应用

Figure 11. Application of augment reality technology in motor maintenance

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图 12 智慧列车的数字孪生模型

Figure 12. Digital twin model of smart train

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图 13 智能铁路的数字一体化平台框架

Figure 13. Digital integrated platform framework of intelligent railways

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表 1 增强现实的类型及应用

Table 1. Types and applications of augmented realities

类型	描述	应用场景
投影	利用虚拟图像增强用户看到的内容，允许用户与显示的虚拟图像之间交互作用。	虚拟标牌或海报：在物体表面叠加虚拟信息；协作：允许多个用户查看虚拟图像并与之人机交互。
识别	识别现实世界中的对象、图案或标记，向用户提供可补充的实时虚拟信息。	3D可视化：3D信息相对环境特定对象叠加；虚拟演示：在产品制造完成之前显示产品3D表示；原位：可视化对象、标记或图案，放置在环境中的虚拟对象。
定位	基于位置的增强现实技术，利用三角测量技术的详细输入数据为用户提供相关的方向指示，通过将实时虚拟信息精确覆盖在由设备相机呈现给用户的现实世界的视图上，从而获得信息。	位置层：将虚拟信息叠加到相对于用户位置的真实世界，提供有关对象或新地点的数据；兴趣点：提供虚拟标记，指示用户感兴趣的点，传输诸如方向、距离和高度等信息；原位：可视化相对的坐标、标记信息、放置在环境中的虚拟对象。
轮廓	将人的身体或物体的轮廓与虚拟信息融合在一起，从而使用户可以拾取和操纵现实世界中不存在的物体。	培训和教育：提供有关复杂设备或工作场景的动手经验；理解系统：将增强现实用于复杂对象的内部或分解视图。

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