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Journal of Zhejiang University SCIENCE A 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/jzus.A2400068


Impact of disc-cutter partial wear on tunneling parameters and a high-accuracy method for discrimination of partial wear


Author(s):  Xinghai ZHOU, Yakun ZHANG, Guofang GONG, Huayong YANG

Affiliation(s):  State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310058, China

Corresponding email(s):   yakunzhang@zju.edu.cn

Key Words:  Tunnel boring machine (TBM), Disc cutter, Partial wear, Tunneling parameters, Multi-domain features, Ensemble learning


Xinghai ZHOU, Yakun ZHANG, Guofang GONG, Huayong YANG. Impact of disc-cutter partial wear on tunneling parameters and a high-accuracy method for discrimination of partial wear[J]. Journal of Zhejiang University Science A, 1998, -1(-1): .

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author="Xinghai ZHOU, Yakun ZHANG, Guofang GONG, Huayong YANG",
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doi="10.1631/jzus.A2400068"
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%T Impact of disc-cutter partial wear on tunneling parameters and a high-accuracy method for discrimination of partial wear
%A Xinghai ZHOU
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%A Guofang GONG
%A Huayong YANG
%J Journal of Zhejiang University SCIENCE A
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%D 1998
%I Zhejiang University Press & Springer
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T1 - Impact of disc-cutter partial wear on tunneling parameters and a high-accuracy method for discrimination of partial wear
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A1 - Yakun ZHANG
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A1 - Huayong YANG
J0 - Journal of Zhejiang University Science A
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DOI - 10.1631/jzus.A2400068


Abstract: 
In tunnel construction with tunnel boring machines (TBMs), accurate knowledge of disc-cutter failure states is crucial to ensuring efficient operation and preventing delays and cost overruns. This study investigates the influence of disc-cutter partial wear on tunneling parameters and proposes a novel method for discriminating partial-wear ratio based on a stacking ensemble model. The time-domain features, including the mean and standard deviation, of torque and thrust are analyzed through a series of scaled-down experimental tests on partial wear. Torque and thrust values increase when a disc cutter becomes trapped and partially worn. The impact of the partial-wear ratio on tunneling parameters appears to be more significant than partial-wear depth. A total of 40 features are selected from the time domain, frequency domain, and time-frequency domain to describe the torque and thrust. The relationships between these features and the partial-wear ratio are analyzed using Pearson coefficients and Copula Entropy. The results reveal that, except for the form factor in the time-domain features, the remaining features exhibit certain linear or non-linear correlations with the partial-wear ratio. Lastly, the proposed model successfully achieves discrimination of the partial-wear ratio and outperforms other commonly used models in terms of overall classification accuracy and differentiation capability in different categories. This research provides effective support for monitoring and health management of disc-cutter failure states.

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