Excessive wear of cutting tools has been reported in some earth pressure balance tunneling project in gravel and the intermediately weathered mudstone. In order to reasonably organize the changing work, the wear of the cutting tools should be predicted. Based on the operational data collected from 20 units of Chengdu Metro, the torque energy of cutterhead was chosen as the input parameter of cutter wear model. A relationship between the number of cutter changes and the torque energy was fitted. The volume of foaming liquid was then added to develop a multiple regression model, which can further improve the prediction precision of tools wear. The result shows that the number of cutter replaced increases with the increase of torque energy or the decrease of volume of foaming liquid. The relationship between the number of cutter replaced and the two input parameters is statistically significant. The number of cutter replaced for the gravel and the intermediately weathered mudstone both agree with the multiple regression model. For different soil types, different fitting parameters are observed. The multiple regression model gives more reasonable predictions than the model based on excavated length and the JTS model.
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