Identifying TBM Tunneling Defects through Recognition of Ground Settlement Patterns

Close monitoring of ground settlement during TBM construction plays an important role in controlling construction quality and risk. But how to identify and allocate the tunneling defects implied in large volumes of monitoring data and develop their relations to specific TBM driving parameters, and in what way to convey this information rapidly to the site at first time during tunneling process remains a big problem to constructors, owners and project managers of tunnels. Ground surface settlement, used directly for evaluation of environmental impacts, can be analyzed in depth and imported into the evaluation of TBM driving parameters. Ground surface settlement patterns are established for explicit interpretation of field measured data. By matching them with corresponding mechanical procedures of TBM driving, the tunneling defects or bias can be found out and then the driving parameters can be optimized. Moreover, in reality, large volumes, discrepancy and discreteness of measured data demand sufficient experienced experts and qualified staff onsite to process the data in time. So a method and a procedure for settlement curve pattern-recognition based on fuzzy mathematics is established for automatic data processing on site, to achieve quick responses to risks indicated by the variation of field measured data.