Tunnel Boring Machine Cutterhead Research Articles

Finite element analysis and fatigue life prediction of tunnel boring machine cutter head

Finite element analysis and fatigue life prediction of tunnel boring machine cutter head

Real-time forecasting of TBM cutterhead torque and thrust force using aware-context recurrent neural networks

Tunnel Boring Machines (TBMs) are instrumental in the construction of modern tunnels, known for their operational reliability and efficiency. The real-time prediction of cutterhead loads is essential for effective project scheduling, cost management, and risk reduction. This study develops machine learning models for predicting future cutterhead torque and thrust force, simultaneously. The dataset is derived from the Yingsong water diversion project and consists of 12,962 steady-state boring cycles. Because geological conditions and setting values are available in advance, we build a geological parameter-based model and a setting value-based model for regression analysis of cutterhead torque and thrust force. In one-step forecasts, the operational parameter-based model closely captures the trend of the measured results, employing the recurrent neural network (RNN), long short-term memory (LSTM) and gated recurrent unit (GRU). We propose an aware-context recurrent neural network (AC-RNN) model that integrates historical operational parameters and the aware context of setting values, leading to a significant improvement in forecasting accuracy. A sensitivity analysis is carried out to quantify the relative importance of input parameters, revealing that the setting value of revolutions per minute is crucial in forecasting. The results of this study offer valuable practical insights into real-time forecasting, thereby informing engineering applications in this field.

Three-Dimensional ERT Advanced Detection Method with Source-Position Electrode Excitation for Tunnel-Boring Machines

Tunnel-boring machines (TBMs) are widely used in urban underground tunnel construction due to their fast and efficient features. However, shield-tunnel construction faces increasingly complex geological environments and may encounter geological hazards such as faults, fracture zones, water surges, and collapses, which can cause significant property damage and casualties. Existing geophysical methods are subject to many limitations in the shield-tunnel environment, where the detection space is extremely small, and a variety of advanced detection methods are unable to meet the required detection requirements. Therefore, it is crucial to accurately detect the geological conditions in front of the tunnel face in real time during the tunnel boring process of TBM tunnels. In this paper, a 3D-ERT advanced detection method using source-position electrode excitation is proposed. First, a source-position electrode array integrated into the TBM cutterhead is designed for the shield-tunnel construction environment, which provides data security for the inverse imaging of the anomalous bodies. Secondly, a 3D finite element tunnel model containing high- and low-resistance anomalous bodies is established, and the GREIT reconstruction algorithm is utilized to reconstruct 3D images of the anomalous body in front of the tunnel face. Finally, a physical simulation experiment platform is built, and the effectiveness of the method is verified by laboratory physical modeling experiments with two different anomalous bodies. The results show that the position and shape of the anomalous body in front of the tunnel face can be well reconstructed, and the method provides a new idea for the continuous detection of shield construction tunnels with boring.

Experimental and numerical investigations on the force characteristics of cutter in different regions of the TBM cutterhead

The cutters on the cutterhead of a tunnel boring machine (TBM) are usually divided into center cutters, face cutters, and gage cutters, and have significantly different force characteristics. In this study, the authors conduct a series of full-scale cutter rotary cutting tests to compare the differences in the cutter force, the morphology of rock ships, and the efficiency of rock breaking. The results indicate that with increasing cutter spacing, the influence exerted by the cutters on one another in terms of their performance at breaking rocks decreases and their normal force gradually increases, while the rolling force of the cutters is less influenced by the spacing between them. The ratio of the normal force to the rolling force of the gage cutter is less than that of the face cutter, indicating a lower efficiency of breaking rock of the gage cutter. The ratio of rock chips with larger size (>50 mm) and smaller size (<10 mm) gradually decreases while that of rock chips with medium size (about 10–50 mm) gradually increases with increasing installation angle, such that the distribution of the particle size becomes more uniform. Excessive or insufficient penetration rate (PR) will increase the proportion of small rock chips, and a moderate PR will produce rock chips with a larger characteristic size and a more uniform size distribution. Then, a three-dimensional rock-breaking model by all cutters of actual TBM cutterhead is established based on the particle flow method. The results of the simulations indicate that the force on the inner ring of the center cutter is greater than that on the outer ring, and an increase in the installation radius weakens the load difference between the two rings. The normal and rolling forces of face cutters gradually increase, while their side force first increases and then decreases. The side force of the gage cutter significantly increases with the installation angle.

Modeling and economic model predictive control of constrained cutterhead system with disturbance in tunnel boring machines

Tunnel boring machines (TBMs) are usually the first choice for tunneling construction with its advantages on high safety, time saving, and less operators. Cutterhead system is an important component for TBMs since it is used to excavate rocks and soil. It is difficult to guarantee both the boring efficiency and energy saving under the excavating rock disturbances and the constraints on the driving motors in TBMs by manual operation. To deal with this problem, it is necessary to develop advanced control algorithms for the cutterhead system. Thus, we investigate an economic model predictive control (EMPC) structure for cutterhead system in TBMs. A generalized nonlinear dynamic model of TBM cutterhead system is built based on the first principle method. An economic cost is constructed with the boring efficiency and energy cost to evaluate the tunnel construction quality. EMPC algorithms are designed to optimize the constructed economic cost for a cutterhead system to guarantee good economic performance. It is shown that EMPC can improve the economic performance of the cutterhead system.

A study of rotary cutting machine (RCM) performance on Korean granite

PurposeDespite the many advantages this type of equipment offers, there are still some major drawbacks. Linear cutting machine (LCM) cannot accurately simulate the true rock-cutting process as 1. it does not account for the circular path along which tunnel boring machine (TBM) disk cutters cut the tunnel face, 2. it does not accurately model the position of a disk cutter on the cutterhead, 3. it cannot perfectly replicate the rotational speed of a TBM. To enhance the knowledge of these issues and in order to mimic the real rock-cutting process, a new lab testing equipment was developed by Hyundai Engineering and Construction.Design/methodology/approachA new testing machine called rotary cutting machine (RCM) is designed to simulate the excavation process of hard-rock TBMs and includes features such as TBM cutterhead, RPM simulation, constant normal force mode and constant penetration rate mode. Two sets of tests were conducted on Hwandeung granite using different disk cutter sizes to analyze the cutting forces in various excavation modes. The results are analyzed using statistical analysis and dimensional analysis. A new model is generated using dimensional analysis, and its results are compared against the results of actual cases.FindingsThe effectiveness of the new RCM test was demonstrated in its ability to apply various modes of excavation. Initial analysis of chip size revealed that the thickness of the chips is largely dependent on the cutter spacing. Tests with varying RPM showed that an increase in RPM results in an increase in the normal force and rolling force. The cutting coefficient (CC) demonstrated a linear correlation with penetration. The optimal specific energy is achieved at an S/p ratio of around 15. However, a slightly lower S/p ratio can also be used in the design if the cutter specifications permit. A dimensional analysis was utilized to develop a new RCM model based on the results from approximately 1200 tests. The model's applicability was demonstrated through a comparison of TBM penetration data from 26 tunnel projects globally. Results indicated that the predicted penetration rates by the RCM test model were in good agreement with actual rates for the majority of cases. However, further investigation is necessary for softer rock types, which will be conducted in the future using concrete blocks.Originality/valueThe originality of the research lies in the development of Hyundai Engineering and Construction’s advanced full-scale laboratory rotary cutting machine (RCM), which accurately replicates the excavation process of hard-rock tunnel boring machines (TBMs). The study provides valuable insights into cutting forces, chip size, specific energy, RPM and excavation modes, enhancing understanding and decision-making in hard-rock excavation processes. The research also presents a new RCM model validated against TBM penetration data, demonstrating its practical applicability and predictive accuracy.

Investigation on the Rock-Fragmentation Process of Conical-Shaped TBM Cutterhead in Extremely Hard Rock Ground

Conical-shaped cutterhead is one type of tunnel boring machine (TBM) cutterhead which may have advantage of high rock-breaking efficiency in extremely hard rock ground. This study investigated the rock-fragmentation process of disc cutters on the conical-shaped cutterhead via a series of numerical simulations that had been verified by laboratory rock-fragmentation tests. Firstly, the rock-fragmentation numerical model of the six cutters in the 'flat-cone' contiguous part was built based on cutting mode analysis of the conical-shape cutterhead. The rock sample in the numerical model was synthesized using a grain-based discrete element method (GB-DEM) and the reliability of this approach was verified via scaled rock-fragmentation tests conducted on a self-developed linear cutting machine (LCM). Then, a series of numerical simulations were conducted to study the influence of cutterhead cone angle, cutter spacing, and cutter installation angle on the rock-fragmentation performance. The results were as follows: 1) the nature of rock fragmentation in the cone area is the rock fragmentation under side free-face condition; 2) the penetration specific energy can be reduced and thus the rock-fragmentation efficiency can be improved by appropriately increasing the conical angle, reducing the cutter spacing, and increasing the cutter installation angle; 3) for the studied granite, the optimal conical angle is 25°, the cutter spacing is suggested to be no more than 70 mm, and the cutter tilt angle is suggested to be no more than 3°. The results obtained in this paper can be used as guidance for the design of the conical-shaped cutterhead.

Solving problem of encountering a huge cavern in a TBM drive for water diversion tunnel project in Northern Thailand

AbstractA huge cavern in a zone of thrusted and sheared clastic sedimentary rocks was encountered during drill and blast (D&amp;B) and tunnel boring machine (TBM) excavation of water transfer tunnel in Thailand. The cavern floor made of thick and loose pile of fallen rock blocks hampered the advance of the TBM through it. Because the size of the cavern was large (50 m × 40 m) and the extent of the thickness of the pile of rock blocks could not be precisely determined, the adopted ramification was to solidify a zone of loose rock fragments around the tunnel alignment. This measure is to allow a safe TBM excavation passing the cavern and ensure the long‐term function of the segmented concrete‐lined tunnel to convey water without problem of loss from subsidence damage. The scheme of the solidification consisted of staged grouting that began with polyurethane (PU) foam grouting to form a bottom barrier of the intended cement grout zone. It was followed large void filling by flowable concrete and then cement injection for the remaining smaller voids. The work that took 8 months to complete started with the excavation of a bypass adit to the front of TBM cutterhead as an access to the cavern and the installation of dewatering and ventilation systems to the cavern so that the grouting work could be made.

Real-time tunneling risk forecasting using vibrations from the working TBM

Tunnel Boring Machines (TBMs) are effective tools for excavating tunnels through various soil and rock strata, especially in complex urban areas. During excavating, hazards overlooked during site investigation, such as abrupt geological changes, buried obstacles like boulders and building foundations, fault zones, and water-bearing regions, significantly increase the risks of cutter damage and tunneling accidents. Geophysical methods have been proposed during tunnel excavation to predict these potential hazards ahead of the cutter face. With the existence of a metallic TBM and subsequently installed concrete tunnel lining, the performance of electromagnetic geophysical methods such as ground-penetrating radar and DC resistivity tomography are greatly hampered, despite their success in the traditional open tunnels. In this study, we present a passive seismic method to forecast the tunneling risks ahead of the TBM cutterhead. This method uses the working TBM as the source and predicts the velocity/density changes in front of the TBM by delineating the reflected seismic energy from the noisy recordings. The key to this technology is seismic interferometry, which transforms the chaotic ambient noise into interpretable seismic profiles. We utilize beamforming and semblance analysis to extract the traveltime information from the passive records. After velocity inversion and calibration, we map the arrival-time of a reflection event to a seismic impedance interface ahead of the cutterface. To test the proposed method, we demonstrate the process on a simulated passive seismic record after laying out its theoretical foundations. We present a field application of our method where geological interfaces are predicted in real time as the excavation progresses. The field data results match well with the muck density and TBM parameters measured after excavation and hence demonstrate the applicability of our method in complex urban environments for tunneling risk reduction.

Influences of tunnelling parameters in tunnel boring machine on stress and displacement characteristics of surrounding rocks

During the operation of a tunnel boring machine (TBM), the stress and displacement of the surrounding rock are closely related to the tunnelling parameters, and the judicious selection of these parameters is crucial for improving TBM’s tunnelling efficiency and equipment utilisation. This study uses finite-element software to develop a three-dimensional mechanical model of a TBM cutterhead and the surrounding rock under the combined action of thrust and torque. It simulates the impact of TBM tunnelling construction on the tunnel’s surrounding rock excavation. Through numerical simulation, the relationship and influence of the TBM tunnelling parameters under various surrounding rock conditions are investigated, as well as the distribution characteristics and laws of the surrounding rock stress and displacement near the tunnel face under different thrust and torque conditions and the mechanical behaviour of the TBM cutterhead regarding the front overall surrounding rock. The results indicated that the influence of thrust change on the surrounding rock is significantly greater than that of torque change, which is minimal and can be ignored. The influence range of thrust and torque under class-A surrounding rock is within 1 m of the tunnel face, and under class-B surrounding rock is within 2 m of the tunnel face. The surrounding rock stress and displacement are closely related to the surrounding rock classification: the higher the quality and integrity of the surrounding rock, the lower the surrounding rock stress and displacement, thereby maximising the surrounding rock’s self-supporting ability.

Mechanical characteristics of a tunnel boring machine cutterhead during rock breaking: Physical model tests and transient dynamic analysis

During tunnel excavation using a tunnel boring machine (TBM), the interaction between the cutter and the rock causes the cutterhead to generate abrupt vibrations, which could lead to engineering problems, such as bearing seal failure and even cutterhead cracking. In this study, large-scale physical model tests with various cutter spacings were performed to study the vibration and load characteristics of the cutterhead during the rock-breaking process. Through a TBM modal comprehensive test bench, the real-time acceleration of the cutterhead was obtained using a monitoring system. The test results showed that the complete time-domain curves were stepped and periodic. When the cutterhead was stuck or rock peeled off during the excavation, the monitoring curves showed abrupt vibrations, which were mainly concentrated at 0–3 Hz and were typical low-frequency vibrations. Taking measured data as the driving parameter, the real-time mechanical characteristics of the cutterhead were determined through transient dynamic analysis. Numerical simulation results showed that the vibration trend during excavation was the superposition of random vibrations generated by rock breaking and tunneling without rock cutting. During the tunneling process, the wear of the edge cutters should be highlighted in actual construction. The related methods and results can provide an essential reference for the selection of cutterheads.

An innovative design of mega shaft boring machine (SBM) cutterhead based on TRIZ and AD theory

Cutterhead is the key component of the mega shaft boring machine (SBM), whose complex structure and huge size lead to high manufacturing difficulty and cost, and its reliability is difficult to guarantee under huge loads. It is difficult to design the cutterhead only referring to the existing small horizontal tunnel boring machine cutterhead. In order to brainstorm innovative ideas, the paper incorporates the TRIZ into AD to address the following issues. Firstly, engineering conflicts in designing process are eliminated by TRIZ tools to generating innovative ideas. Then, the decomposition of functional requirements and design parameters are employed based on independence axiom of AD, transferring the abstract ideas into concrete design solutions. Moreover, fuzzy comprehensive evaluation is adopted to choose a better design scheme from alternatives of critical component. Finally, the feasibility and practicality of the proposed approach has been demonstrated through case study of designing a novel mega SBM cutterhead. The cutterhead structure is significantly improved with embedded movable cutter boxes, which can excavate step by step to reduce the driving torque, and the manufacturing and transportation cost has been greatly reduced. The method can help designer to innovative design the key components of large-scale underground tunneling equipment.

Design Method of Anti-Damage and Anti-Crack for Main Parameters of Tunnel Boring Machine Cutter Head

Design Method of Anti-Damage and Anti-Crack for Main Parameters of Tunnel Boring Machine Cutter Head

Combined effects of microwave irradiation and water cooling on the deformation and failure behaviours of CSTBD granite

The low cutting rate and high cutting tool wear rate in hard rock tunnel excavation by a tunnel boring machine (TBM) are critical problems. By integrating microwave technology with water cooling into the TBM cutterhead, microwave-assisted mechanical rock breaking provides a promising solution. To reveal the deformation and failure behaviours of hard rocks after microwave heating and water cooling, this work experimentally conducted a series of tests on cracked straight-through Brazilian disc (CSTBD) granite specimens, where the crack angle was set to 0, 30, 60, and 90° and the microwave heating duration was set to 0.5, 1, 3, 5, and 7 min. During the experiment, digital image correlation (DIC) technology was employed to measure the deformation and failure process. The results show that microwave heating and water-based cooling facilitate the failure of CSTBD granite. The mode-Ⅰ fracture toughness linearly decreases with heating duration for pure tensile failure (crack angle: θ=0°), while it linearly increases with heating duration at other crack angles (30°, 60°, and 90°). The mode-Ⅱ fracture toughness linearly decreases with heating duration in the crack angle range of 0° to 90°. The mode-Ⅰ fracture toughness linearly decreases with the crack angle. The mode-Ⅱ fracture toughness increases with a crack angle of <24° and decreases in the crack angle range of 24° to 90°. The failure patterns are divided into five categories by different crack angles: pure tensile failure (θ = 0°), tensile-shear mixed failure (0° <θ < 24°), shear failure (θ = 24°), compressive-shear mixed failure (24° <θ < 90°), and compressive failure (θ = 90°). The reasons for the main and second cracks during the failure process are revealed. The experimental results have significant implications for microwave-assisted mechanical rock breaking.

Success and challenges in predicting TBM penetration rate using recurrent neural networks

Tunnel Boring Machines (TBMs) have been increasingly used in tunnelling projects. Forecasting future TBM performance would be desirable for project time management and cost control. We aim to use recurrent neural networks to predict the near future TBM penetration rate from historical data. Our datasets are composed of Changsha and Zhengzhou metro lines, with totally different geological conditions. In the experiments, the one-step forecast of TBM penetration rate by the traditional recurrent neural network (RNN) or long short-term memory (LSTM) is relatively accurate, irrespective of the different geological conditions used in training and evaluation. Predicting the next Nth step penetration rate proves to be more challenging and depends on the time to the future or the distance ahead of the TBM cutterhead. There are generally time lags between measured and predicted results. The recursive RNN is then developed to address the lag problems, but to no avail. Alternative methods for predicting future penetration rates are studied, including the penetration rate at the Nth step in the future and the average penetration rate of the next N steps, with the latter being trained by long-input or short-input methods. The average N-step forecast using short inputs provides the best results, and its performance over other alternatives becomes more distinct as the number N increases. We also discuss the possibility of the forecast problem as a quasi-random walk, which means that forecasting penetration rate cannot easily be achieved using low-frequency data with RNNs, and that the accuracy depends on the correlation between the last and predicted steps in the data.

Adaptive sliding mode control for tunnel boring machine cutterhead telescopic system with uncertainties

PurposeThis paper aims to present an adaptive sliding mode control (ASMC) for tunnel boring machine cutterhead telescopic system with uncertainties to achieve a high-precision trajectory in complex strata. This method could be applied to solve the problems caused by linear and nonlinear model uncertainties.Design/methodology/approachFirst, an integral-type sliding surface is defined to reduce the static tracking error. Second, a projection type adaptation law is designed to approximate the linear and nonlinear redefined parameters of the electrohydraulic system. Third, a nonlinear robust term with a continuous approximation function is presented for handling load force uncertainty and reducing sliding mode chattering. Moreover, Lyapunov theory is applied to guarantee the stability of the closed-loop system. Finally, the effectiveness of the proposed controller is proved by comparative experiments on a scaled test rig.FindingsThe linear and nonlinear model uncertainties lead to large variations in the dynamics of the mechanism and the tracking error. To achieve precise position tracking, an adaptation law was integrated into the sliding mode control which compensated for model uncertainties. Besides, the inherent sliding mode chattering was reduced by a continuous approximation function, while load force uncertainty was solved by a nonlinear robust feedback. Therefore, a novel ASMC for tunnel boring machine cutterhead telescopic system with uncertainties can improve its tracking precision and reduce the sliding mode chattering.Originality/valueTo the best of the authors’ knowledge, the ASMC is proposed for the first time to control the tunnel boring machine cutterhead telescopic system with uncertainties. The presented control is effective not only in control accuracy but also in parameter uncertainty.

A real-time prediction method for tunnel boring machine cutter-head torque using bidirectional long short-term memory networks optimized by multi-algorithm

Based on data from the Jilin Water Diversion Tunnels from the Songhua River (China), an improved and real-time prediction method optimized by multi-algorithm for tunnel boring machine (TBM) cutter-head torque is presented. Firstly, a function excluding invalid and abnormal data is established to distinguish TBM operating state, and a feature selection method based on the SelectKBest algorithm is proposed. Accordingly, ten features that are most closely related to the cutter-head torque are selected as input variables, which, in descending order of influence, include the sum of motor torque, cutter-head power, sum of motor power, sum of motor current, advance rate, cutter-head pressure, total thrust force, penetration rate, cutter-head rotational velocity, and field penetration index. Secondly, a real-time cutter-head torque prediction model's structure is developed, based on the bidirectional long short-term memory (BLSTM) network integrating the dropout algorithm to prevent overfitting. Then, an algorithm to optimize hyperparameters of model based on Bayesian and cross-validation is proposed. Early stopping and checkpoint algorithms are integrated to optimize the training process. Finally, a BLSTM-based real-time cutter-head torque prediction model is developed, which fully utilizes the previous time-series tunneling information. The mean absolute percentage error ( MAPE ) of the model in the verification section is 7.3%, implying that the presented model is suitable for real-time cutter-head torque prediction. Furthermore, an incremental learning method based on the above base model is introduced to improve the adaptability of the model during the TBM tunneling. Comparison of the prediction performance between the base and incremental learning models in the same tunneling section shows that: (1) the MAPE of the predicted results of the BLSTM-based real-time cutter-head torque prediction model remains below 10%, and both the coefficient of determination ( R 2 ) and correlation coefficient ( r ) between measured and predicted values exceed 0.95; and (2) the incremental learning method is suitable for real-time cutter-head torque prediction and can effectively improve the prediction accuracy and generalization capacity of the model during the excavation process. • A torque prediction model based on BLSTM and multi-algorithm fusion is developed. • The Dropout algorithm is integrated to prevent overfitting. • Bayesian and Cross-Validation based hyperparameter optimization method is presented. • EarlyStopping and ModelCheckPoint are integrated to optimize the training process. • An incremental learning method is proposed to improve the model's adaptability.

Construction geological logging of the Thames Tideway Tunnel beneath central London: unearthing the ground truth

Large-scale underground structures excavated during the construction of the Thames Tideway Tunnel have facilitated observations of the in situ geology and revealed sedimentary characteristics that were not fully evident in disturbed samples from ground investigation boreholes or laboratory tests. These have led to significant improvements in the understanding of groundmass behaviour of several strata within the London Basin geological sequence that are not easily studied by intrusive ground investigations, especially those involving sand channels and the ‘Pebble Bed’ within the Lambeth Group deposits. Further validation of the ground model and geology projected over the scheme during the preconstruction design has been gained from logging the geology within deep shafts, open-face connection tunnels and the main 8.8 m-outer-diameter tunnel from behind the tunnel-boring machine cutterhead. It is recommended that an archive of field logs, as obtained during construction, be established to augment archives of borehole logs. Thematic collection: This article is part of the Geology of London and its implications for ground engineering collection available at: https://www.lyellcollection.org/cc/london-basin

Vibration characteristics of hard rock cutterhead under spatial distribution load

During the actual operation of the full-face tunnel boring machine (TBM), the vibration of the mainframe system is very strong, leading to the failure of key parts. Therefore, the vibration characteristics of TBM Cutter head under the maximum thrust condition are analyzed by ANSYS finite element software, and the effects of Cutter head panel thickness, Cutter head baseplate thickness, and support plate thickness on Cutter head vibration are analyzed. Subsequently, the optimal solution of the system is obtained by analyzing the data with orthogonal tests. It provides a reference for vibration reduction and parameter matching of Cutter head.

Coupling dynamic characteristics of tunnel boring machine cutterhead system with multi-source uncertainties

During tunnel boring machine (TBM) tunneling, the violent vibration of the cutterhead system is the major cause of structural failure and engineering accidents. There are many uncertain coupled factors of the cutterhead system, which can lead to inaccurate vibration analysis and difficulty predicting the dynamic response. In this study, coupling dynamic characteristics under multi-source uncertainties of the TBM cutterhead system were analyzed. First, a geological uncertain coupling model and disc cutter uncertain coupling model were established. Then, the load interval boundaries with multi-source uncertainties under different working conditions were obtained and the load interval boundary was combined with the cutterhead dynamic model to establish a dynamic model with multi-source uncertainties. Finally, a dynamic characteristic analysis was carried out using a real-world engineering example to validate the model. The results show that when multi-source uncertainties are considered: (1) The maximum increase in the radial load amplitude and corresponding load interval median are about 137% and 73%, respectively. The maximum increase in the overturning moment amplitude and the load interval median are roughly 92% and 93%, respectively. (2) Under typical working conditions, the maximum increase in the stability vibration response boundary is about 92% for the radial displacement response, with a maximum increase in overturning angle displacement of 70%. (3) The optimum mass fraction of the cutterhead center block is around 46.5%, resulting in the smallest vibration amplitude. The results provide a theoretical reference for the design of cutterhead structures for vibration reduction.