Search

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. [ABSTRACT FROM AUTHOR]

Geotechnical and tunneling aspects during the construction of the U5 in Frankfurt am Main The new district Europaviertel in Frankfurt is developed, and will be connected to the public transport system. Therefore, two tunnel tubes of 7.1 m in diameter and approximately 840 m in length will be excavated with an EPB‐TBM. The ARGE U5 Europaviertel, PORR and Stump, were selected by the client, the Stadtbahn Europaviertel Projektbaugesellschaft (SBEV), to build the tunnels. The start for the tunnel drive of the south tube was in August 2019. The project has challenging subsoil conditions. Especially the Frankfurt Clay with chalk and sandstone layers is important but also the western part, directly after the start of each tunnel drive, is challenging due to the heterogeneous subsoil conditions, too. [ABSTRACT FROM AUTHOR]

In order to study multiple problems concerning quickly tunneling in long distance tunnel, we design and develop a shield machine based on drilling, tunneling, protecting and transporting. By study the shield technique method, working sequences, guiding system composition and working principle, direction fixation, forehand detection and new support and protection of coal mining and tunneling in detail, we analyze the difference regarding the usage effectiveness between traditional tunnel tunneling and shield tunneling. Shield tunneling shows the advantage of quickly tunneling, effectiveness and efficiency, safety and cost saving points of view.

Mud and gravel deposition often occurs in circulation systems of pumps. In this paper, a liquid-solid coupling method combining CFD and DEM is proposed to study two-phase flow behavior of water, The flow characteristics of water-clay mud and the motion characteristics of gravel were simulated under different discharge pipe bending radii and geometry shape conditions. Numerical results showed that for a circular cross section pipe with a fixed bending radius, the collision times between the gravel particles and the pipe wall decreased with the increase of the bending radius. [ABSTRACT FROM AUTHOR]

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Zhanjiang Bay Sea-crossing Tunnel is the first phase of an ambitious plan of the Golden Triangle Economic Zone in southwestern China and passes underneath the deepest artificial shipping channel with the highest level in Asia. The tunnel is a world-record extralong and small-diameter corridor constructed using an uninterrupted single-end shield tunneling method in subsea soft ground under ultrahigh hydraulic pressure for water conveyance. This case study first highlights the engineering challenges of constructing the sea-crossing shield tunnel in subsea soft ground under ultrahigh hydraulic pressure. A series of key techniques are then investigated and some innovations are proposed to address the engineering challenges in the following four key aspects of the sea-crossing shield tunneling process: (a) optimal design of segmental linings; (b) adaptive reformation of the shield machine; (c) structural construction of deep vertical shafts; and (d) supporting techniques of long-distance advancing. On the basis of the field monitoring and numerical analyses, it is concluded that the implemented key techniques ensure the successful management and control of the engineering challenges in terms of optimizing the segmental lining, selecting the shield machine and constructing the vertical working shaft during the sea-crossing shield tunneling process with limited geological investigation data available under submarine conditions. [ABSTRACT FROM AUTHOR]

With development of railway transportation, shield tunneling technology has been widely used. As a key component of shield tunneling, the working efficiency and failure form of hob were directly related to the geological conditions and had an important influence on construction schedule and safety. Based on a subway tunneling project, its geology related was analyzed firstly, then the failure types and corresponding causes of the disc cutters were also explained. Finally, a brief discussion was given about the material properties of disc cutters. The results showed that the failure forms were mainly partial grinding, edge curl, fracture of disc cutter ring, cutter ring off, fracture of cutter shaft. [ABSTRACT FROM AUTHOR]

Earth pressure balanced (EPB) shield machines are large and complex mechanical systems and have been widely applied to tunnel engineering. Tunnel face stability evaluation is very important for EPB shield machines to avoid ground settlement and guarantee safe construction during the tunneling process. In this paper, we propose a novel earth pressure field modeling approach to evaluate the tunnel face stability of large and complex EPB shield machines. Based on the earth pressures measured by the pressure sensors on the clapboard of the chamber, we construct a triangular mesh model for the earth pressure field in the chamber and estimate the normal vector at each measuring point by using optimization solution and projection Delaunay triangulation, which can reflect the change situation of the earth pressures in real time. Furthermore, we analyze the characteristics of the active and passive earth pressure fields in the limit equilibrium states and give a new evaluation criterion of the tunnel face stability based on Rankine's theory of earth pressure. The method validation and analysis demonstrate that the proposed method is effective for modeling the earth pressure field in the chamber and evaluating the tunnel face stability of EPB shield machines. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central South University is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Earth pressure balance (EPB) shield has been widely used in underground construction. The excavation face stability is crucial to avoid the accidents caused by EPB shield tunneling, so that it is very important to propose an effective control method for the earth pressure balance in sealed cabin. Considering the problem that stable automatic control of the earth pressure in shield's sealed cabin is difficult, an optimal control method of the earth pressure is proposed based on action-dependent heuristic dynamic programming (ADHDP), which can realize online autonomous learning and adaptive control in tunneling process. According to Bellman's principle of optimality, the cost function with respect to the sealed cabin's earth pressure is given. In addition, the action network and critic network of ADHDP controller are constructed. The critic network approximates the cost function and feeds error back into the action network. With the goal of minimizing the cost function, the action network utilizes the critic network's error to optimize screw conveyor speed. The simulation results show that the earth pressure controller based on ADHDP can realize the earth pressure balance control, and the control process is steadier. Moreover, ADHDP controller has good dynamic performance and anti-interference ability. • Action-dependent heuristic dynamic programming (ADHDP) is used to control earth pressure balance in sealed cabin. • Based on Bellman's principle of optimality, ADHDP controller for earth pressure balance is designed. • ADHDP controller can realize earth pressure balance control, and the control process is steadier. • The proposed method has shorter adjusting time and strong anti-interference ability. [ABSTRACT FROM AUTHOR]

• The efficiency enhancement method of abrasive water jet slit-assisted shield cutter cutting reinforced concrete was investigated. • Revealed the efficiency enhancement mechanism of abrasive water jet slit-assisted shield cutters. • The main influencing factors affecting the effectiveness of abrasive water jet slit-assisted shield cutters were discussed. To improve the efficiency and safety of shield machines cutting reinforced concrete (RC) obstacles, using an abrasive waterjet (AWJ)-assisted shield cutter to cut RC is considered a feasible solution. To explore the effect of an AWJ on a shell cutter cutting RC, laboratory experiments and numerical simulation methods were used to compare the breaking performance and damage mechanism of a shell cutter cutting RC with and without a slit. The results showed that the waterjet pre-cutting slit could effectively reduce the cutter force of the shell cutter and promote the cutting of steel bars. The reduction rate of the cutter force by the waterjet slit increased and then decreased with an increase in the penetration degree. When the penetration degree was 1.5 mm, the waterjet cutting slit had the best reduction effect on the cutting force. An optimal critical value was found for the waterjet cutting slit of the steel bar; when the waterjet slit was larger than ½ of the diameter of the steel bar, the steel bar was prone to tensile fracture under the cutting action. The waterjet pre-cutting slit reduced the residual cross-sectional area and stress distribution of the steel bar, which promoted the bending and tensile fracture of the steel bar and thus improved the cutting efficiency. Furthermore, construction recommendations for the AWJ-assisted shield cutting of RC obstacles were identified. The findings presented in this paper can provide useful reference information for the design and construction of AWJ shield machines. [ABSTRACT FROM AUTHOR]

• It proposes a geological adaptive operating parameters decision-making method. • It also optimizes parameters of screw machine rotation speed and soil bin pressure. • A D-ResNet network is proposed to predict tunneling speed and cutterhead torque. • Optimization time of our method is much lower than existing optimization methods. • Our decision-making method effectively balance efficiency and energy consumption. The performance of shield machine is sensitive to geological conditions and its operation depends on driver experience. Based on D-ResNet network and improved inertia weight adaptive constrained particle swarm optimization algorithm (IWACPSO), this study proposes an adaptive operating parameters decision-making method for shield machine considering geological environment. First, a novel D-ResNet network is proposed to establish the mapping models between geological type, operating parameters and tunneling speed, cutterhead torque, respectively. Then, we design the evaluation indicators of tunneling performance considering construction efficiency and considering both construction efficiency and energy consumption, respectively, and build the mapping model between operating parameters and performance evaluation indicators. On this basis, the optimization equation with operation parameters as control variables and improving tunneling performance as the goal is established. In order to solve the decision results of optimal operating parameters under various geological types, we present an enhanced inertia weight adaptive constrained particle swarm optimization algorithm. Finally, the proposed D-ResNet and IWACPSO-based decision-making method are verified by the actual construction data of subway project in Singapore. The results show that the R2 values of the proposed D-ResNet network for predicting the tunneling speed and cutterhead torque reach 0.98 and 0.96, respectively, which are much better than AdaBoost, support vector regression, multiple linear regression and deep neural network. The IWACPSO-based decision-making method could accurately solve the optimal solution of operating parameters, and the optimization time is much lower than that of ant colony algorithm, genetic algorithm and exhaustive method. Moreover, operation parameter decision-making method considering construction efficiency increased the tunneling speed by 61.02% on average, and the operation parameter decision-making method considering construction efficiency and energy consumption increased the tunneling speed by 59.55% on average, while the tunneling specific energy decreased by 20.50% on average compared with the former. [ABSTRACT FROM AUTHOR]

In order to reveal the nonlinear dynamics behavior of the three stage planetary transmission system of the shield driven cutter head,a pure torsional coupled nonlinear dynamics model is established for the number of planets,the gap between the teeth and the dynamic loads. The relative displacement between the various parts of the meshing point is derived,the system differential equation is established,the coordinate transformation of differential equations,and the non dimensional treatment is carried out. Then based on the dimensionless differential equations of four orders variable step Runge Kutta method. The transmission mechanism of the phase diagram,Poincare diagram are got,by changing the amplitude of excitation and the meshing stiffness,the influence of parameter variation on the nonlinear characteristics of the system is analyzed. The results show that with the increase of the amplitude of excitation,the system enters the two periodic state of the system by the steady state of the single cycle,and then enters the chaotic motion through the multi period motion. With the increase of the meshing stiffness,the system is in a state of multi periodic motion,and the system is stable in a single period. With increasing the meshing stiffness of ks3,reducing the excitation amplitude,the stability of the system can be improved.

In order to improve the working efficiency and system stability of cutter head rotary system of shield machine, a mathematical model of cutter head rotary hydraulic system is established by simplifying the model of cutter head rotary hydraulic system. The cutter head rotary load is analyzed, and the calculation model of load torque of hydraulic system is determined. A cutter head based on variable universe fuzzy PID is established by using variable universe method for rotary hydraulic system. A simulation study on the control system of linear variable load and random load applied to the cutter head torque is carried out. The results show that when the cutter head torque increases, the proposed control system can adjust the cutter head rotation speed at any time to achieve the balance of the total power of the system and reduce the cutter head speed adjustment. The results provide a theoretical basis for the design and improvement of rotary hydraulic system of cutter head of shield machine. [ABSTRACT FROM AUTHOR]

Earth pressure in sealed chamber is affected by multisystem and multifield coupling during shield tunneling process, so it is difficult to establish a mechanism earth pressure control model. Therefore, a data-driven modeling method of earth pressure in sealed chamber is proposed, which is based on parallel least squares support vector machine optimized by parallel cooperative particle swarm (parallel cooperative particle swarm optimization-partial least squares support vector machine). The vectors are parallel studied according to different hierarchies firstly, then the initial classifiers are updated by using cross-feedback method to retrain the vectors, and finally the vectors are merged to obtain the support vectors. The parameters of least squares support vector machine are optimized by the parallel cooperative particle swarm optimization, so as to predict quickly for large-scale data. Finally, the simulation experiment is carried out based on in-site measured data, and the results show that the method has high computing efficiency and prediction accuracy. The method has directive significance for engineering application. [ABSTRACT FROM AUTHOR]

Owing to the complex fault information features in the operation of complex large-scale electromechanical systems, the existing semi-artificial state detection method is unable to obtain fast, accurate, or reliable diagnosis results, which causes significant loss to engineering construction projects. To solve this problem, a fault diagnosis method for a shield machine system based on an extension neural network is proposed. Using a matter-element model to describe the fault characteristic information, the upper and lower bounds of the classical domain of the characteristic index are used as the double weights of the neural network. Then, a fault diagnosis is made using the extension distance as the measuring tool, the algorithm structure and flow are constructed, the steps of the algorithm are given, and the effectiveness of the method is verified using tunnel boring machine as an example. The simulation results show that this method simplifies the network structure, improves the convergence speed, and obtains consistent diagnostic results. This research can provide a new method and idea for solving the problems of time, and manpower consumption, as well as the cost, of a fault diagnosis of a semi-automatic shield machine system. [ABSTRACT FROM AUTHOR]

• The proposed method constructs physical models for various hydraulic components and investigates the fault mechanisms of shield machine hydraulic systems to provide theoretical basis for fault injection. • relying solely on the physical models themselves does not guarantee perfect match with the actual physical systems. To eliminate the uncertainties arising from the actual operating conditions of hydraulic systems, a physical model correction method based on cosine similarity is proposed to adjust the sensitive parameters of the physical models and ensure their validity. • Fault injection is then performed based on statistically collected high-frequency fault records. • A new validation method is introduced, using simulated data as the training set and measured data as the test set, to demonstrate the effectiveness of the proposed method. The hydraulic system of shield machine is critical component, and any faults in this system can have severe consequences on construction progress and even pose risks to the safety of construction personnel. However, the high manufacturing and construction costs of shield machines, as well as the use of highly reliable hydraulic components, make it challenging to obtain a large number of fault samples that accurately reflect the actual operating conditions of the hydraulic system. This limitation is one of the major obstacles to the practical application of intelligent fault diagnosis in shield machines. Furthermore, due to the large scale and complex structure of the hydraulic system in shield machines, few scholars have studied the bottleneck that restricts the fault diagnosis of the hydraulic system of the shield machine. To address these challenges, this paper proposes physical model-driven approach for fault diagnosis in shield machine hydraulic systems, aiming to overcome the lack of fault feature information during the fault diagnosis process. Firstly, physical models for various hydraulic components of the shield machine hydraulic system are established, and the relationship between the physical models and fault characteristics is investigated to provide a theoretical basis for fault injection. Then, a physical model correction method based on cosine similarity is proposed. Using recorded high-frequency fault data from shield machine hydraulic systems, fault injection is performed to obtain simulated data that effectively reflects the actual fault states and normal states of the hydraulic system. Finally, using the simulated data as training samples and measured data as test samples, various artificial intelligence diagnosis models, such as Support Vector Machines (SVM), Extreme Learning Machines (ELM), and Convolutional Neural Networks (CNN), are employed for diagnostic classification. The classification results demonstrate the feasibility and effectiveness of the physical model-driven approach for fault diagnosis in shield machine hydraulic systems. Furthermore, this approach exhibits strong universality and scalability, providing a solution for fault diagnosis scenarios with limited or even no fault samples. [ABSTRACT FROM AUTHOR]

In order to reduce the construction risk caused by human operation error and improve the geological adaptive ability of the shield machine, an autonomous intelligent control method is proposed for shield machine within the framework of interaction–judgment–decision based on Deep Deterministic Policy Gradient (DDPG) deep reinforcement learning in this study. Due to the strong nonlinear relationship between the shield machine's tunneling parameters, this research builds a deep reinforcement learning environment using mechanism model of sealed cabin pressure. DDPG agent model of the shield machine is established to replace the shield machine to interact and train with the geological environment. By minimizing the difference between the target pressure setting value and the sealed cabin pressure value, the dynamic balance between the sealed cabin pressure and the pressure on the excavation surface is realized, and the best strategy is obtained. Through real-time interaction with the geological environment, the method in this paper can dynamically adjust the tunneling parameters, accurately control the sealed cabin pressure, and has a strong geological adaptive ability. By realizing the intelligent decision-making of the tunneling parameters, it greatly improves the independent decision-making ability of the shield machine system, reduces the inaccuracy of human operation, and provides an effective guarantee for the efficient and safe operation of the shield machine. This study applies deep reinforcement learning technology to the control field of earth pressure balance shield machine, promotes AI technology, and provides a new idea for the development of AI construction technology in engineering field. [ABSTRACT FROM AUTHOR]

• A novel approach for adjusting the shield's attitude and position during tunneling was proposed. • A hybrid deep learning prediction framework including comprehensive feature evaluation method, EEMD, CA-CNN and GRU-TA is established. • The test is carried out with the field data collected from the railway in Shanghai, China. • The proposed model is significantly superior to other models in prediction accuracy and prediction efficiency. • The contributions of CA and TA in the model are revealed. In constructing long-distance shield tunnels, it is a difficult challenge to maintain the tunneling trajectory consistent with the design tunnel axis. The accurate prediction of the attitude and position during tunneling can reap the advantage of optimizing the tunneling operation parameters in advance leading to the best tunneling trajectory. This study investigates a framework based on a hybrid deep learning model for attitude and position prediction of the shield machine. This prediction framework contains comprehensive feature evaluation method, ensemble empirical mode decomposition (EEMD), convolutional neural network (CNN), and gate recurrent unit (GRU). The introduction of channel attention and temporal attention in CNN and GRU further strengthens the spatial and temporal feature extraction ability of the model. The performance of the prediction framework is verified through a case study with data collected from the Shanghai urban railway tunnel section. Results reveal that the proposed model with dual attention significantly outperforms other models in prediction accuracy and speed. The bias of feature data can be alleviated by introducing channel attention, and using temporal attention can capture long-distance temporal feature data. The model can support shield construction safety by adjusting the operation parameters, and an application example is used to demonstrate the feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

Copyright of Guangdong Architecture Civil Engineering is the property of Guangdong Architecture Civil Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The dynamics equation of the four gears parallel drive system of shield machine cutter is established.The 3D model of the four gears parallel drive system is established by using the UG software.The dynamic process of the four gears parallel drive system is simulated by using the ADAMS software.Then the influence of meshing damping,meshing stiffness,backlash and distribution of driving gear on the load sharing are also analyzed.The research shows that the larger the difference between meshing stiffness and meshing damping is,the more uneven the load sharing is,when the driving load changes,backlash has a larger effect on the load balance,the different distributions of driving gear have rather a great impact on the stability of driven system.The results can provide theoretical basis for the design and manufacture of the four gears parallel drive system.

Abstract: For tunnelling in loose rock, where active and continuous support of the face is required, the application areas of mix/hydro and EPB shield machines are increasingly overlapping to such a degree that the use of both types of machine is possible both in the fine‐grain range and in coarse‐grained loose rock. Since the prevailing soil conditions are rarely homogeneous, but rather characterised by alternating sequence, the planning process is of decisive importance. However, it is not possible to select machines solely based on soil conditions or geotechnical parameters. The supplementary assessment areas include the machine‐ and process‐engineering, system‐immanent special features, e.g. management of bricks/blocks, transfer of supporting pressure and maintenance, interaction of TVM building ground regarding wear and sticking, utilization of the overburden as well as evaluation of the spoil quality. This article describes the main aspects of the decision‐making process for suitable machine and tunnelling technology and summarizes the advantages and disadvantages. [ABSTRACT FROM AUTHOR]

Based on the airshaft of Wang Fu Zhuang station to Da Yang Zhuang station of Jinan rail transit line R1, the separate starting scheme of three different types of air well length was evaluated. The advantages and disadvantages of each scheme were also analyzed. From the construction efficiency and economic benefits of the two aspects of comprehensive comparison, 83 m separate launching scheme was determined to have the best comprehensive benefit. The research results can be used as references for similar engineering projects. [ABSTRACT FROM AUTHOR]

• An analytical approach was developed to investigate the effects of slurry clogging. • The workface deformation caused by the reverse circulation of slurry was analyzed. • The ultimate volume deviation ratio of slurry was proposed to alarm the collapse. • The validity of the analytical approach was verified by the field measurements. The pressurized slurry is the essential part of the slurry pressure balanced shield (SPBS) for stabilizing the working face and transporting the excavated soil. If clogging occurs in case of adverse ground conditions or equipment failure, a series of consequences will happen, such as sudden changes in slurry pressure, massive ground loss, and deformation or even collapse at tunnel workface. The present study reviewed and summarized the clogging mechanism of the slurry shield under different ground conditions. Then, based on the law of conservation of mass and Bernoulli's Equation, an analytical approach was developed to investigate the effects of clogging on the slurry velocity and pressure along with the deformation of tunnel workface. Furthermore, a case study and field measurements were conducted to validate the analytical method. The significant findings drawn from the study can be summarized as follows: (1) The clogging of a slurry shield imposes severe effects on the slurry pressure balancing mechanism of shield tunneling. It can occur in both cohesive and non-cohesive ground with different formation mechanisms. (2) During the initial clogging, the slurry pressure above the spring line increases, and that below the spring line decreases. With the clogging deteriorating, the slurry velocity drops considerably at the top of the deposit area and escalates near the discharging port. The presence and increase of deposit lead to a sharp rise of slurry pressure in the slurry chamber, especially in the clogging region. (3) The reverse circulation of the slurry system (RCSS) is useful to clear the clogging. Still, the slurry deposits at the bottom will obstruct the slurry reverse flow, resulting in inward deformation of the tunnel face and a drastic increase in overcutting volume. (4) The ultimate volume deviation ratio of the slurry was proposed as a useful index to alarm the potential risk of collapse induced by the RCSS. (5) The timely adoption of RCSS is strongly suggested when any abnormal changes in the slurry pressure or the ultimate volume deviation ratio are observed for the first time. [ABSTRACT FROM AUTHOR]

The maximum ground surface settlement prediction is a complex problem as the settlement depends on plenty of intrinsic and extrinsic factors. To obtain the approximate range of the settlement, a hybrid prediction dataset including the geological and construction parameters is built using spatial and temporal series according to the sampling methods. The settlement prediction task is transformed into a multi-modal and multi-variate series prediction task. Hence, a spatial-temporal fusion network (STF-Network) is proposed. The spatial-temporal fusion mechanism is firstly designed to establish the spatial-temporal fusion map, which makes spatial and temporal series interact earlier. Then, the 3D residual unit structure is designed to capture the features of temporal series and spatial-temporal fusion map, and two fully-connected layers are established to capture the spatial structural information. Finally, the final output is merged by the three components. The experimental results for STF-Network demonstrate the superiority over state-of-the-art methods. • Establishing a hybrid prediction dataset using spatial and temporal series • Designing a spatial-temporal fusion network (STF-Network) for settlement prediction • Employing STFM make spatial and temporal series interact earlier • Designing 3D-ResUnit structure based on the periodicity of the temporal series data [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel geological information prediction method for shield machine. • Important basis for this model to extract important features. • Correlation of geological information of adjacent working face. • Indicators of EMSACNN are significantly better than those of existing models. Due to the closed working environment of shield machines, the construction personnel cannot observe the construction geological environment, which seriously restricts the safety and efficiency of the tunneling process. In this study, we present an enhanced multi-head self-attention convolution neural network (EMSACNN) with two-stage feature extraction for geological condition prediction of shield machine. Firstly, we select 30 important parameters according to statistical analysis method and the working principle of the shield machine. Then, we delete the non-working sample data, and combine 10 consecutive data as the input of the model. Thereafter, to deeply mine and extract essential and relevant features, we build a novel model combined with the particularity of the geological type recognition task, in which an enhanced multi-head self-attention block is utilized as the first feature extractor to fully extract the correlation of geological information of adjacent working face of tunnel, and two-dimensional CNN (2dCNN) is utilized as the second feature extractor. The performance and superiority of proposed EMSACNN are verified by the actual data collected by the shield machine used in the construction of a double-track tunnel in Guangzhou, China. The results show that EMSACNN achieves at least 96% accuracy on the test sets of the two tunnels, and all the evaluation indicators of EMSACNN are much better than those of classical AI model and the model that use only the second-stage feature extractor. Therefore, the proposed EMSACNN achieves high accuracy and strong generalization for geological information prediction of shield machine, which is of great guiding significance to engineering practice. [ABSTRACT FROM AUTHOR]