Earth pressure balance control for shield tunneling machine based on adaptive dynamic programming

Liu, Xuanyu; Xu, Shuangxi; Zhang, Kaiju

doi:10.1177/0142331220913742

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…Cheng Yeh [6] established the prediction and control model of Earth pressure balance by using a back propagation neural network, which pioneered the application of neural network in Earth pressure balance control. Xuanyu Liu [7] established a value function for the sealed cabin Earth pressure by using the Bellman principle and established a network structure of a dual heuristic programming controller to obtain the optimal tunneling parameters. Xuanyu Liu [8] proposed a data-driven optimal control method for the Earth pressure balance of shield machine.…”

Section: Introductionmentioning

confidence: 99%

Intelligent real-time prediction of multi-region thrust of EPB shield machine based on SSA-LSTM

et al. 2023

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During the tunneling process of shield machine, the accurate determination of tunneling parameters is the guarantee of safe operation of shield machine. Through the real-time construction data analysis and mining of shield machine, the tunneling parameters at the next moment are obtained in real-time. Based on this, this paper proposes an intelligent real-time prediction method for multi-region thrust of EPB shield machine based on SSA-LSTM (Sparrow Search algorithm-Long and Short-term Memory). By correlation analysis of the construction big data, the data features with a great correlation of shield machine thrust are obtained. And it is used as the input of LSTM prediction model to explore the nonlinear relationship between inputs and output. SSA is used to optimize LSTM prediction model to establish a more accurate nonlinear relationship, and then the multi-region thrust of shield machine at the next moment is accurately obtained. The simulation results show that SSA-LSTM model can accurately predict the thrust of each region of shield machine at the next moment, and the prediction performance is better than other models. The method provides a reference basis for shield machine to implement accurate thrust regulation and provides a guarantee for effective control of earth pressure balance (EPB) in sealed cabin to ensure construction safety, which has engineering application value.

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Section: Introductionmentioning

confidence: 99%

Intelligent real-time prediction of multi-region thrust of EPB shield machine based on SSA-LSTM

et al. 2023

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“…However, the structure and parameters of the LSSVM model were fixed. Liu et al (2020) proposed a data-driven multi-variable optimization based on adaptive dynamic programming (ADP) for EPB control of shield machine. For the above research, the EPB control problem of shield machine has been solved to a certain extent.…”

Section: Introductionmentioning

confidence: 99%

Coordinated optimization control of shield machine based on dynamic fuzzy neural network direct inverse control

Liu

Wang

Wang³

et al. 2020

Transactions of the Institute of Measurement and Control

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During shield machine tunneling, the earth pressure in the sealed cabin must be kept balanced to ensure construction safety. As there is a strong nonlinear coupling relationship among the tunneling parameters, it is difficult to control the balance between the amount of soil entered and the amount discharged in the sealed cabin. So, the control effect of excavation face stability is poor. For this purpose, a coordinated optimization control method of shield machine based on dynamic fuzzy neural network (D-FNN) direct inverse control is proposed. The cutter head torque, advance speed, thrust, screw conveyor speed and earth pressure difference in the sealed cabin are selected as inputs, and the D-FNN control model of the control parameters is established, whose output are screw conveyor speed and advance speed at the next moment. The error reduction rate method is introduced to trim and identify the network structure to optimize the control model. On this basis, an optimal control system for earth pressure balance (EPB) of shield machine is established based on the direct inverse control method. The simulation results show that the method can optimize the control parameters coordinately according to the changes of the construction environment, effectively reduce the earth pressure fluctuations during shield tunneling, and can better control the stability of the excavation surface.

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Data-driven deformation prediction and control for existing tunnels below shield tunneling

Feng,

Wang,

Liu

et al. 2024

Engineering Applications of Artificial Intelligence

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Earth pressure balance control for shield tunneling machine based on adaptive dynamic programming

Cited by 4 publications

References 14 publications

Intelligent real-time prediction of multi-region thrust of EPB shield machine based on SSA-LSTM

Intelligent real-time prediction of multi-region thrust of EPB shield machine based on SSA-LSTM

Coordinated optimization control of shield machine based on dynamic fuzzy neural network direct inverse control

Data-driven deformation prediction and control for existing tunnels below shield tunneling

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