The effect of TBM operational parameters on the wear of cutting tools using a tunnel boring machine laboratory simulator

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

The performance of mechanized excavation depends on the soil abrasivity and the resistance of cutting tools against wear. The wear has a negative effect on excavation machine parameters, such as penetration rate, and reduces the machine's efficiency. Worn tools require replacement, which interrupts the project and incurs high maintenance costs. For this reason, many efforts have been made to understand the interaction between soil and cutting tools. Various wear-measuring devices have been designed and built to measure soil abrasivity and cutting tool wear. In this research, to study the mechanism of tunnel excavation in the laboratory, a tunnel boring machine laboratory simulator was designed and built, and the effect of the operating parameters of the excavation machine on the average wear of cutting tools was studied. The features of this machine are its horizontal excavation, the low rotation speed of the cutterhead, continuous contact of the cutters with fresh soil during the test, and continuous injection of materials with a specific injection pressure during the test. Using the granulation of soil prepared from Tabriz metro line 2 in three moisture content of zero, 7, and 13%, the effect of the rotation speed of the cutterhead, rotation time, and penetration rate on the wear of cutting tools was studied. The investigations showed that with the increase in the rotation speed of the cutterhead, the average wear increases. Also, the increasing rotation time has caused more friction between the cutting tools and the cutterhead with the soil, and the wear has increased. The wear decreased with the increase in the penetration rate, despite the increase in the intensity of the conflict between the soil particles and the cutting tools. The results obtained from this research by using a tunnel boring machine laboratory simulator are in good agreement with previous studies.

Language:
English
Published:
Journal of Aalytical and Numerical Methods in Mining Engineering, Volume:12 Issue: 33, Winter 2023
Pages:
55 to 63
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