数据驱动的隧道掘进机制造/运维协同决策技术研究

任颖莹; 胡新朋; 夏站辉; 周振建

doi:10.3973/j.issn.2096-4498.2023.03.014

隧道建设 >

2023 , Vol. 43 >Issue 3: 496 - 504

DOI: https://doi.org/10.3973/j.issn.2096-4498.2023.03.014

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数据驱动的隧道掘进机制造/运维协同决策技术研究

任颖莹 ,
胡新朋 ,
夏站辉 ,
周振建

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(1. 中铁隧道局集团有限公司，广东广州 511458； 2. 盾构及掘进技术国家重点实验室，河南郑州 450001； 3. 中铁隧道股份有限公司，河南郑州 450001)

任颖莹（1985—），女，河南南阳人，2013年毕业于郑州大学，控制理论与控制工程专业，硕士，高级工程师，现从事盾构大数据、控制技术方面的研究工作。E-mail： 516760721@qq.com。

网络出版日期: 2023-04-17

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DataDriven Collaborative DecisionMaking Technology for Manufacturing and Operation Maintenance of Tunnel Boring Machine

REN Yingying ,
HU Xinpeng ,
XIA Zhanhui ,
ZHOU Zhenjian

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(1.China Railway Tunnel Group Co.,Ltd.,Guangzhou 511458,Guangdong,China;2.State Key Laboratory of Shield Machine and Boring Technology,Zhengzhou 450001,Henan,China;3.China Railway Tunnel Stock Co.,Ltd.,Zhengzhou 450001,Henan, China)

Online published: 2023-04-17

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摘要

当前隧道掘进机全生命周期中制造和运维存在信息壁垒、数据价值发挥受限，造成决策水平低下、设备效能不足。针对这些问题，分析制造和运维服务现状，提出一种制造和运维跨域数据交互感知和协同决策的新模式。同时，设计制造/运维协同决策体系架构，并详细阐述隧道掘进机跨域融合大数据驱动的协同决策功能和关键技术方法，包括基于隧道掘进机运维数据与经验数据结合的装备选型设计和协同生产，融合设计制造数据和装备运行多阶段数据的维修、维护协同作业方案，跨地域隧道掘进机大数据驱动的运行优化等。通过对协同决策新模式及关键决策技术方法的研究，将隧道掘进机各阶段数据进行融合集成和共享应用，构建出隧道掘进机制造和运维互馈协同决策机制，提升装备制造质量和适应性，保障装备的安全高效运行。

关键词： 隧道掘进机; 数据驱动; 跨域融合; 决策; 制造; 运维; 新模式

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任颖莹 , 胡新朋 , 夏站辉 , 周振建 . 数据驱动的隧道掘进机制造/运维协同决策技术研究[J]. 隧道建设, 2023 , 43(3) : 496 -504 . DOI: 10.3973/j.issn.2096-4498.2023.03.014

Abstract

The manufacturing and operation maintenance of tunnel boring machines in their entire life cycle have certain limitations. These include a low decisionmaking level and inefficient equipment usage caused by information barriers and limited data value utilization. To address these issues, a new mode of crossdomain data interaction and collaborative decisionmaking is proposed by analyzing the current situation of manufacturing and operation maintenance services and a collaborative decisionmaking architectureis designed as well. The collaborative decisionmaking of the tunnel boring machine with crossdomain big datadriven integration is described in detail, including the selection of equipment design and collaborative production based on the combination of tunnel boring machine operation maintenance data and experience data, a cooperative operation scheme of maintenance based on the integration of design and manufacturing data and multistage equipment operation data, and the operation optimization decisionmaking of tunnel boring machines with crossdomain big datadriven. By integrating and sharing data from various stages of tunnel boring machines and establishing a collaborative decisionmaking mechanism for mutual feedback between tunnel boring machine manufacturing and operation maintenance, the quality and adaptability of equipment manufacturing can be improved. This will ensure the safe and efficient operation of equipment.

Key words： tunnel boring machine; datadriven; crossdomain integration; decision making; manufacturing; operation maintenance; new mode

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