Tunnel Boring Machines(TBMs), as the most advanced excavation technology in the current tunnel construction, are widely used in underground engineering. Especially for the deep and long tunnel with TBM excavation, the initial geological exploration cannot fully reflect the situation of the stratum, the effective construction of TBM will been affected to a certain extent. In this paper, a new TBM surrounding rock mass classification is proposed based on the improved energy method. The relationship between the geological conditions and the specific energy (SE) is established considering three part, the geological conditions, the TBM operation specifications and their interaction, including the tunneling parameters and the shape of rock slag. Two important index of specific energy are calculated separately, the total specific energy (TSE) and the rock crushing specific energy (RCSE). It can be found that the RCSE has a good correlation with the stratum. According to the proportion of RCSE account for the TSE, the TBM surrounding rock mass can be divided into four classes, class I to class IV. The lower the class is, the higher the efficiency of TBM excavation is. Also, during TBM excavation process, the value of RCSE and TSE are changing, the front stratum can be predicted by the change of the RCSE, and the TBM tunneling state can be deduced by the new surrounding rock mass classification. For different classes, several flexible measures are suggested to ensure the TBM excavation more efficiency. And a real-time system is established to predict the stratum and evaluate the TBM performance. Furthermore, this TBM surrounding rock mass classification method is applied to the YinHanJiWei water conveyance project.
In recent years, with the acceleration of infrastructure construction and urbanization process, tunnel boring machines (TBMs) are widely used in tunnel excavation. In the process of TBM design, manufacture and construction, the construction efficiency is the key to the success or failure of the project. In practical engineering, the tunneling speed of TBM is greatly affected by geological conditions, and the tunneling rate can vary from 1 to 1500 m per month (Bai et al., 2005). Therefore, it is very important to establish the rock mass classification based on TBM construction to predict the TBM tunneling efficiency (Wang, 1998; He et al., 2002).