A new approach for developing EPB-TBM disc cutter wear prediction equations in granite stratum using backpropagation neural network

Ding, Xiaobin; Xie, Yuxuan; Xue, Hao; Chen, Rui

doi:10.1016/j.tust.2022.104654

Cited by 14 publications

(1 citation statement)

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“…A new method was proposed for calculating the CERCHAR index based on the mass loss of the pin tip with respect to the dimensions of the pin-tip plane. This method introduces two new metrics: CAIML and MCAIML [3]. A new method for estimating the wear of a disc cutter based on an energy-conversion mechanism was proposed [4].…”

Section: Introductionmentioning

confidence: 99%

Force and wear prediction model of disc cutter under compression shear failure mode based on dense core–cavity expansion theory (U-713)

Su,

Guan,

Deng

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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Calculating disc cutter wear and predicting wear life are long-standing issues affecting the efficiency and cost of tunnel boring machines (TBMs). During the TBM excavation process, the wear of the disc cutter is a comprehensive outcome of the interaction between the tool and rock. Studying the mechanisms of tool rock breaking and wear can assist in developing a more precise model for predicting cutter wear. Therefore, based on the rock-breaking and wear mechanisms of a cutter, this study developed a model for predicting the cutter wear rate and life. The model is based on the theory of dense core–cavity expansion combined with the motion state of a cutter. First, the TBM excavation process and rock-breaking mechanism of a cutter were analyzed in detail. A cutting force model under the compression shear failure mode based on the dense core–cavity expansion theory was established. Based on the force model, a prediction model for the wear rate and life of the disc cutter was established, considering the working characteristics and wear mechanism. Furthermore, the impact of penetration on the prediction model was investigated. In addition, to demonstrate the practicality of the method, this study conducted a comprehensive examination using engineering examples. The results showed that the average difference in the cutter average wear rate using the developed model was less than 3% compared with the actual engineering result. In addition, the average difference in the wear life rate was less than 5%. Finally, the developed prediction method was compared with other models. The wear rate fitting accuracy was improved by 4.91–10.85% and the wear life fitting accuracy was improved by 5.11–12.19% by the developed method. This improvement confirms the reasonableness and reliability of the method. This method can estimate the wear rate and lifespan of a cutter more accurately and reliably than other methods, providing a practical tool to TBM engineers to make informed decisions and optimize tool replacement programs.

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Section: Introductionmentioning

confidence: 99%