Fault diagnosis of TBM hob eccentric wear based on wavelet time-frequency analysis and Inception-BiGRU model

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Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (15) : 232-240.

FAN Xiangxiang1,2, XIANG Zaiyu1,2, SUN Ruixue1,2, ZHANG Min1, MO Jiliang1,2

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Abstract

Cutters of shield boring machine (TBM) generally work in a complex geological environment with heavy load and impact, which can easily result in failure due to the partial wear of the cutter. Therefore, it is of particular importance to monitor the wear situation of the cutter to diagnose the cutter partial wear fault and guide the operations of the equipment based on data-driven techniques. In this study, aiming at the cutter partial wear problem, a novel diagnostic model based on wavelet time-frequency analysis and Inception-BiGRU is proposed, which can improve the fault diagnosis efficiency compared with existing models. The disc cutter is selected to perform linear rock breaking experiments on a multi-functional scaled rock-breaking test machine, during the process the vibration signals are collected. After that continuous wavelet transform (CWT) is used to obtain the wavelet time-frequency diagram that reflects the time-frequency domain characteristics of the vibration signals, and then the multi-scale spatial information is adaptively extracted using the convolutional kernels of different sizes of the Inception model. Furthermore, bidirectional gated recurrent units (BiGRU) are added to enable the model to learn the rich time-dependent relationships in the time-frequency diagram more accurately, and the hyperparameters of the model are determined by Bayesian optimization algorithm. The four diagnostic experiments of different cutter wear degree indicate that the proposed model can effectively extract the partial wear characteristics from the time-frequency diagram and diagnose the partial wear state of the cutting tools, which can realize end-to-end fault diagnosis of the TBM cutter's partial wear. The proposed model shows an average diagnostic accuracy up to 98.5%, whose diagnostic accuracy and stability are both indicated to outperform other algorithms, which proves the superiority of the proposed method.

Key words

Shield boring machine (TBM) / cutter / fault diagnosis of partial wear / wavelet time-frequency diagram / Inception model / Bidirectional gated recurrent units (BiGRU)

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FAN Xiangxiang1,2, XIANG Zaiyu1,2, SUN Ruixue1,2, ZHANG Min1, MO Jiliang1,2. Fault diagnosis of TBM hob eccentric wear based on wavelet time-frequency analysis and Inception-BiGRU model[J]. Journal of Vibration and Shock, 2023, 42(15): 232-240

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