Earth pressure balance control for EPB shield

Yang, Huayong; Shi, Hu; Gong, Gwo‐Ching; Hu, Guoliang

doi:10.1007/s11431-009-0245-7

Cited by 30 publications

(4 citation statements)

References 7 publications

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“…The earth pressure of the head chamber can be easily adjusted by increasing or decreasing the speed of the screw conveyor (Yang et al, 2009b). The ability of increasing angular velocity for screw conveyor can significantly affect adjustment interval for controlling earth pressure of the shield machine both for cases of increasing and decreasing earth pressure.…”

Section: Dynamic System Model Derivation Of Earth Pressure Control Ofmentioning

confidence: 99%

Parameter identification and pressure control of dynamic system in shield tunneling using least squares method

Cao

Shangguan

et al. 2010

J Coal Sci Eng China

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An estimation approach using least squares method was presented for identification of model parameters of pressure control in shield tunneling. The state equation of the pressure control system for shield tunneling was analytically derived based on the mass equilibrium principle that the entry mass of the pressure chamber from cutting head was equal to excluding mass from the screw conveyor. The randomly observed noise was numerically simulated and mixed to simulated observation values of system responses. The numerical simulation shows that the state equation of the pressure control system for shield tunneling is reasonable and the proposed estimation approach is effective even if the random observation noise exists. The robustness of the controlling procedure is validated by numerical simulation results.

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Section: Dynamic System Model Derivation Of Earth Pressure Control Ofmentioning

confidence: 99%

Parameter identification and pressure control of dynamic system in shield tunneling using least squares method

Cao

Shangguan

et al. 2010

J Coal Sci Eng China

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“…Considering the vital effect of earth pressure at the excavation face to maintain face stability and control ground deformation, the balance of earth pressure has been investigated by mechanical analysis, numerical analysis, and artificial intelligence (AI) technology. Mechanical analysis is mainly based on mechanical equilibrium to calculate earth pressure distribution [26]- [28]. Using numerical simulations such as finite element methods, numerical analysis has been employed to evaluate the relationship between earth pressure and shield operational parameters such as the screw conveyor speed, the advance rate and rotational speed of the cutter head [29], [30].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Dynamic Earth-Pressure Regulation Model for Shield Tunneling by Integrating GRU Deep Learning Method With GA Optimization

et al. 2020

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This paper proposes an intelligent framework to predict and automatically regulate earth pressure using a deep learning technique during earth pressure balance shield tunneling. A prediction model was proposed by integrating a new cost function (relative mean square error) with a gated recurrent unit (GRU). The moving average smoothing method was also incorporated into the GRU model to reduce the noise of the dataset and improve the accuracy of the proposed model. A real-time dynamic regulation model for adjusting the operational parameters was proposed by integrating the GRU model into a genetic algorithm-based optimizer. By adjusting the operational parameters, the dynamic regulation model regulates the excessive predicted earth pressure within a suggested range. The proposed prediction and regulation models were applied to a metro tunnel construction in Luoyang, China. The results show that the proposed models provide good guidance for automated tunnel construction. INDEX TERMS Automatic regulation, earth pressure, gated recurrent unit, genetic algorithm, shield tunneling.

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“…Shi et al (2008) established an EPB control model by using the adaptive neuro-fuzzy inference system (ANFIS), and it can output the screw conveyor speed. Yang et al (2009) developed the thrust system and screw conveyor system based on electro-hydraulic technology and the thrust speed regulation and the screw conveyor speed adjustment were realized. But the model was established on the assumption that the conditioned soil in the sealed cabin of the shield was plasticized.…”

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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Earth pressure balance control for EPB shield

Cited by 30 publications

References 7 publications

Parameter identification and pressure control of dynamic system in shield tunneling using least squares method

Parameter identification and pressure control of dynamic system in shield tunneling using least squares method

Real-Time Dynamic Earth-Pressure Regulation Model for Shield Tunneling by Integrating GRU Deep Learning Method With GA Optimization

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

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