A cutterhead energy-saving technique for shield tunneling machines based on load characteristic prediction

In this paper, we propose a shield cutterhead load characteristic forecast method and apply it to optimize the efficiency of the cutterhead driving system. For the forecast method, wavelet transform is used for preprocessing, and grey model GM(1,1) for forecasting. The performance of the wavelet-based GM(1,1) (WGM(1,1)) is illustrated through field data based load characteristic prediction and analysis. A cutterhead mode control strategy (CMCS) is presented based on the WGM(1,1). The CMCS can not only provide operators with some useful operating information but also optimize the stator winding connection. Finally, the CMCS is tested on a cutterhead driving experimental platform. Results show that the optimized stator winding connection can improve the system efficiency through reducing the energy consumption under part-load conditions. Therefore, the energy-saving CMCS is useful and practical.