Development and Application of Multi-functional and Intelligent Tunnel Boring Machine
【Abstract】After nearly two centuries of development, the tunnel boring machine (TBM) has become increasingly mature in technical performance, reliability, adaptability and other aspects. However, for large deep-buried tunnels, long tunnels, large-diameter tunnels, micro-diameter tunnels, and tunnels in complex geological conditions etc., the adaptability and intelligentization level of TBMs need to be improved. In order to solve the challenges for tunnel construction in extremely complex geological conditions, and make breakthrough in TBM tunneling in complex geology, technologies such as rock detection and perception, intelligent decision-making and early warning technology for equipment need to be developed in combination with sensing technology, big data, cloud computing, machine deep learning, advanced control technology and other technologies, so as to satisfy the requirements of complex tunnel projects with multimode, multi-functional and intelligent technical performance. The author focuses on the research and application of multimode technologies, the concept of integrated functions and intelligentization, especially the new achievements in geotechnical perception, monitoring and feedback of machine condition. It is suggested that the advanced sensing, analysis and control technology can be used to realize intelligent TBM tunneling as well as to achieve early perception, big data research and judgment, intelligent control and operation, and intelligent tunneling support technology.
【Keywords】 tunnel boring machine; multi-mode; integrated functions; intelligentization; tunneling support technology;
 CHEN Kui, YANG Yandong. Innovation and development trends of shield manufacturing technology in China [J]. Tunnel Construction, 2017, 37 (3): 276.
 LONG Zhiyang, GUO Xiaoxian. Development and application of full face tunnel boring machine [J]. Mine Construction Technology, 2017, 38 (5): 7.
 SU Nan. The development status and the future prospects of artificial intelligence [J]. Management & Technology of SME, 2017 (10): 107.
 ZHANG Na, LI Jianbin, JING Liujie, et al. Study and application of intelligent control system of TBM tunneling parameters [J]. Tunnel Construction, 2018, 38 (10): 1734.
//JSAI 2018: Annual Conference of the Japanese Society for Artificial Intelligence. [S.l.: s.n.], 2018.
 ALLENDE V M, MERELLO J P, COFRE P. Artificial intelligence technique for geomechanical forecasting [C]//Tunnels and Underground Cities: Engineering and Innovation Meet Archaeology, Architecture and Art. London: Taylor & Francis Group, 2019: 1629.