scholarly journals Earth pressure balance control of shield tunneling machine based on nonlinear least squares support vector machine model predictive control

2018 ◽  
Vol 52 (1-2) ◽  
pp. 3-10 ◽  
Author(s):  
Xuanyu Liu ◽  
Kaiju Zhang
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
Balance Control ◽  
Earth Pressure ◽  
Screw Conveyor ◽  
Support Vector ◽  
Pressure Balance ◽  
Machine Model ◽  
The Earth ◽  
Earth Pressure Balance

Background: Earth pressure balance shield machines are widely used in underground engineering. To prevent ground deformation even disastrous accidents, the earth pressure in soil chamber must be kept balance to that on excavation face during shield tunneling. Therefore, in this paper an advanced control strategy that a least squares support vector machine model-based predictive control scheme for earth pressure balance is developed. Methods: A prediction model is established to predict the earth pressure in chamber during the tunneling process by means of least squares support vector machine technology. On this basis, an optimization function is given which aims at minimizing the difference between the predicted earth pressure and the desired one. To obtain the optimal control actions, an improved ant colony system algorithm is used as rolling optimization for earth pressure balance control in real time. Results: Based on the field data the simulation experiments are performed. The results demonstrate that the method proposed is very effective to control earth pressure balance, and it has good stability. Conclusion: The screw conveyor speed and advance speed are the major factors affecting the earth pressure in chamber. The excavation face could be controlled balance better by adjusting the screw conveyor speed and advance speed.

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

2020 ◽  
Vol 42 (13) ◽  
pp. 2440-2449
Author(s):  
Xuanyu Liu ◽  
Sheng Xu ◽  
Kaiju Zhang
Keyword(s):  
Cost Function ◽  
Balance Control ◽  
Earth Pressure ◽  
Screw Conveyor ◽  
Pressure Balance ◽  
The Earth ◽  
Gradient Descent Algorithm ◽  
Action Network ◽  
Earth Pressure Balance ◽  
Cutter Head

In order to avoid the safety accidents caused by earth pressure imbalance during shield machine tunneling process, the earth pressure between excavation face and that in chamber must be maintained balance, but it is difficult for practical engineering. Therefore, a data-driven multi-variable optimization method based on dual heuristic programming (DHP) is proposed. First, a cost function with respect to the chamber’s earth pressure is given in light of Bellman’s principle. Then, based on back propagation neural networks (BPNN), the action network, model network and critic network are established that compose the DHP controller. The networks’ weights are updated through the gradient descent algorithm. By minimizing the cost function, the action network utilizes the critic network’s error to optimize the control variables, so that the optimal advance speed, cutter head torque, cutter head speed, total thrust and screw conveyor speed are obtained. Finally, the simulation experiments are carried out, and the results indicate that the method can effectively control the earth pressure balance in chamber and has strong anti-interference ability.

scholarly journals Predicting Ink Transfer Rate of 3D Additive Printing Using EGBO Optimized Least Squares Support Vector Machine Model

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Shengpu Li ◽  
Yize Sun
Keyword(s):  
Support Vector Machine ◽  
Prediction Model ◽  
Least Squares ◽  
Transfer Rate ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Support Vector ◽  
Experimental Sample ◽  
Machine Model ◽  
Ink Transfer

Ink transfer rate (ITR) is a reference index to measure the quality of 3D additive printing. In this study, an ink transfer rate prediction model is proposed by applying the least squares support vector machine (LSSVM). In addition, enhanced garden balsam optimization (EGBO) is used for selection and optimization of hyperparameters that are embedded in the LSSVM model. 102 sets of experimental sample data have been collected from the production line to train and test the hybrid prediction model. Experimental results show that the coefficient of determination (R2) for the introduced model is equal to 0.8476, the root-mean-square error (RMSE) is 6.6 × 10 (−3), and the mean absolute percentage error (MAPE) is 1.6502 × 10 (−3) for the ink transfer rate of 3D additive printing.

Predicted versus measured soil movements induced by shield tunnelling in the Madrid Metro extension

2005 ◽  
Vol 42 (4) ◽  
pp. 1160-1172 ◽  
Author(s):  
Manuel Melis Maynar ◽  
Luis Medina Rodriguez
Keyword(s):  
Numerical Model ◽  
Numerical Modelling ◽  
Earth Pressure ◽  
Pressure Balance ◽  
Ground Movements ◽  
The Earth ◽  
Shield Tunnelling ◽  
Earth Pressure Balance ◽  
Numerical Modelling And Analysis ◽  
Soil Movements

A detailed study on the available methods of predicting ground movements due to tunnelling works was carried out during the construction of the Madrid Metro extensions in 1995–1999 and 1999–2003. A total of 100 km were built and commissioned during this period. A numerical model was developed to simulate the earth pressure balance (EPB) excavation procedure and to complement some of the deficiencies found in previous analytical or empirical subsidence estimation procedures. Before the beginning of the works, a total of six different methods were used to estimate ground movements generated by the tunnelling works at some monitored sections placed in all five cities linked by the 1999–2003 extension, and the estimations were published in an earlier paper in this journal. Once all tunnelling works were finished and actual measurements carried out, a number of comparisons between predictions and measurements were made and are included in this paper. Conclusions about the applicability and accuracy of the methods are established with the aim of helping researchers and engineers in their future projects.Key words: ground movements, monitoring, numerical modelling and analysis, settlement, tunnels.

scholarly journals A Hybrid Least Square Support Vector Machine Model with Parameters Optimization for Stock Forecasting

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Jian Chai ◽  
Jiangze Du ◽  
Kin Keung Lai ◽  
Yan Pui Lee
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
Support Vector Machine Model ◽  
Optimization Methods ◽  
Parameters Optimization ◽  
Least Square ◽  
Movement Direction ◽  
Support Vector ◽  
Machine Model ◽  
Mode Decomposition

This paper proposes an EMD-LSSVM (empirical mode decomposition least squares support vector machine) model to analyze the CSI 300 index. A WD-LSSVM (wavelet denoising least squares support machine) is also proposed as a benchmark to compare with the performance of EMD-LSSVM. Since parameters selection is vital to the performance of the model, different optimization methods are used, including simplex, GS (grid search), PSO (particle swarm optimization), and GA (genetic algorithm). Experimental results show that the EMD-LSSVM model with GS algorithm outperforms other methods in predicting stock market movement direction.

Prediction and analysis of subsidence induced by shield tunnelling in the Madrid Metro extension

2002 ◽  
Vol 39 (6) ◽  
pp. 1273-1287 ◽  
Author(s):  
Manuel Melis ◽  
Luis Medina ◽  
José M Rodríguez
Keyword(s):  
Earth Pressure ◽  
Tunnel Construction ◽  
Pressure Balance ◽  
Ground Movements ◽  
Construction Methods ◽  
The Earth ◽  
Predictive Methods ◽  
Shield Tunnelling ◽  
Earth Pressure Balance ◽  
Numerical Modelling And Analysis

The development of tunnelling projects under heavily populated cities has been rapidly increasing around the world during the last decades. Since tunnel construction can have disastrous effects on buildings, structures, and utilities near the excavation, construction methods have necessarily to provide maximum safety inside and outside the tunnel. To predict and correct dangerous ground movements due to the tunnelling works, the authors developed a numerical model to simulate the earth pressure balance (EPB) excavation procedure and injection to complement some deficiencies found in previous analytical or empirical subsidence estimating procedures. This model takes into account the full excavation sequence and has been validated by a large amount of monitoring data from the previous Madrid Metro extension. In the present paper, several predictive methods are used to predict the ground movements generated during a new Madrid Metro extension project consisting of 48 km of tunnel (1999–2003). At the end of the works the results will be compared with data from monitored sections placed in all five cities linked by the extension. Conclusions about the applicability and accuracy of the methods will be established with the aim of helping researchers and engineers in their future projects.Key words: ground movements, monitoring, numerical modelling and analysis, settlement, tunnels.

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