Neuro-Fuzzy method to predict the penetration rate of Tunnel Boring Machines (TBM)

Drilling TBMs are those machines which function with applying the driving force and rotating the cutter head by cutter discs, dig the tunnel as a uniform and with different circular shape. The analysis of TBM performance is the basis of estimating the expenditures and timetable of each tunnel project. One of the methods to prediction of the performance of these machines is the estimation of their penetration rate. Different researchers, all over the world, have studied the effect of the properties of intact rock and rock mass on the performance of TBM for the penetration rates of these machines. In this paper we used an Adaptive Neuro Fuzzy Interference System (ANFIS) in which the inputs are the uniaxial compression strength, the point load strength index, the penetration force of each disc and the number of cutter head revolution per minute; and its output is the penetration rate of the machine.

کلیدواژه ها:

Fuzzy Neural Networks ، Penetration Rate ، Golab ، TBM