Perspectives in Intelligentization of Tunnel Boring Machine (TBM)

YANG Huayong1 ZHOU Xinghai1 GONG Guofang1

(1.State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou, Zhejiang, China 310027)

【Abstract】The development status of artificial intelligence (AI) technologies, the development trend of intelligent engineering machines and the urgent national needs for the future intelligent TBMs are introduced briefly. It is pointed out that the intelligentization will be the hot spot of the tunnel engineering area and the focuses of future industry competition. The scientific challenges due to the complexity of the working environment, including state recognition and environment perception, correlation law between geological environment and operation parameters, intelligent planning and coordinated control of multi systems, are raised. In addition, the existing research foundation is analyzed and the inadequacy of the theory including environment and state perception, adaptive & dynamic control of construction parameters, multi system coordination control and multi-objective optimization are obtained. At last, some thinking from the aspects of design, manufacture and operation, such as excavation perception, the adaptive dynamic control of excavation parameter condition, the excavation parameter data collection and calculation, intelligent optimization and decision-making of tunneling parameters and the multi-system coordination intelligent control are proposed.

【Keywords】 full-face TBM; artificial intelligence; intelligentization; environment perception; adaptive & dynamic control; multi system coordination control;


【Funds】 National Key R & D Plan “Robot Intelligent Operating System for TBM Construction” (2017YFB1302600, 2017YFB1302602, 2017YFB1302604)

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This Article


CN: 41-1448/U

Vol 38, No. 12, Pages 1919-1926

December 2018


Article Outline


  • 0 Introduction
  • 1 Scientific challenges that intelligent TBM faces
  • 2 Existing bases for researches on intelligentization of TBM
  • 3 Intelligent conception of TBM
  • 4 Conclusions
  • References