Chamber Pressure Prediction and Parameter Optimization for Earth Pressure Balance Shields Based on SSA-RF and PSO

To address the problems of complex influencing factors of chamber pressure and delayed response in manual regulation during shield construction, this study proposes a chamber pressure prediction and parameter-optimization method integrating SSA-RF and PSO based on field tunneling data from 1082 rings. First, on the basis of conventional tunneling parameters, muck improvement parameters, including the cumulative amount of foam mixture in the current ring, the cumulative amount of cutterhead water spray in the current ring, and the cumulative amount of bentonite in the current ring, are introduced. Nine key input variables are then screened by combining Pearson correlation coefficient analysis and distance correlation coefficient analysis. Subsequently, an SSA-RF chamber pressure prediction model is established. The results show that the model achieves an R2 of 0.9968 and a MAPE of only 0.34% on the test set, outperforming the other models. Furthermore, with the objective of minimizing the deviation between the predicted chamber pressure and the target value, the PSO algorithm is used to optimize the propulsion speed and the rotation speed of the screw conveyor. The results indicate that, based on the predicted chamber pressure values, the PSO algorithm can output optimized adjustment suggestions for propulsion speed and screw conveyor rotation speed, thus realizing model-assisted regulation of chamber pressure. This study can provide a reference for chamber pressure prediction and auxiliary regulation of tunneling parameters during earth pressure balance shield tunneling.