부산대학교 도서관

Cutter life is an important economical index for tunnel boring machines (TBM) excavation, and its prediction is widely concerned. This paper introduces a method for predicting cutter life on the basis of statistics and regression. Traditional researches only evaluate the average mileage or time interval of each cutter change. Differently, the proposed method can accurately predict the mileage position of each cutter relatively, on the premise of knowing the installment radius of each cutter and the rock properties along the tunnel. In this procedure, the influence of the rock classification and rock properties of each cutter passing area on their passing distance is obtained by linear regression. For proposing and verifying the prediction method, totally 1,200 records of cutter changing caused by normal cutter wear are collected from the 4th Section of Water Supply Project from Songhua River. Among them, randomly selected 920 samples are used to determine the regression coefficients involved in the method. The method is verified by the rest 280 samples, and a reliable predicted result is obtained (MAPE = 27%, and R2 = 0.69).