1434 results about "Tunnel boring machine" patented technology

A method of predicting tunnel boring machine (TBM) jamming based on deep neural network and numerical simulation and a system thereof are provided, belonging to the technical field of tunnel boring. The method including the following steps: constructing a jamming numerical sample library by using s numerical simulation technology; establishing a jamming prediction model based on the jamming numerical sample library by using a Convolutional Neural Network (CNN) and a Transformer; and implementing real-time monitoring and early warning of TBM jamming by using the jamming prediction model. The present application realizes the real-time monitoring and early warning of TBM jamming, reduces or avoids the jamming phenomenon, and improves the safety and efficiency of TBM construction.

The disclosure relates to the technical field of tunnel excavation, in particular to a non-blasting tunnel boring machine and a tunneling method. The tunneling machine comprises a vehicle-mounted device (1), a rotational driving device (2), a translation device (40), a working disc (3), a foundation trench excavation device (4), a drilling and splitting device (5), a hazard removal device (50), a dust suppression device (6) and a material feeding device (7). The rotational driving device (2) is arranged on the vehicle-mounted device (1), the working disc (3) is connected with the rotational driving device (2), the rotational driving device (2) drives the working disc (3) to rotate around a center of the working disc, the foundation trench excavation device (4) is arranged on the working disc (3), the drilling and splitting device (5) comprises a drilling machine (51) and a rock splitter (52) both arranged on the working disc (3), the drilling machine (51) is suitable for drilling a hole in a tunnel face in an annular crack arrest groove, the rock splitter (52) is suitable for splitting the tunnel face, the hazard removal device (50) is arranged on the working disc (3), the dust suppression device (6) is arranged on the vehicle-mounted device (1), and the material feeding device (7) is used for receiving and conveying materials dropped during excavation.

Disclosed is a method for identifying a vibration magnitude of a TBM main beam using a geological feature parameter and a tunneling feature parameter constructed based on tunnel boring machine (TBM) tunneling parameters. The method includes: collecting vibration signals of the main beam and tunneling parameters of a TBM through an in-situ tunneling test and preprocessing such data, researching a correlation law between the tunneling parameters and a vibration feature root mean square (RMS), providing two feature parameters of a field penetration index (FPI) and a cutterhead power index (TNI), establishing a multivariate regression prediction model for vibration of the TBM main beam based on the feature parameters, and verifying and analyzing the model under different surrounding rock conditions. An average relative error of prediction is 12% or within, and a quantitative relation between the vibration features of the main beam and the feature parameters of the TBM is given.

The invention provides a full face tunnel boring machine tunnel surrounding rock strength intelligent prediction model training method and equipment. A model capable of effectively predicting coal mine tunnel TBM tunneling tunnel surrounding rock point load strength can be trained. The method comprises the following steps: acquiring first original data corresponding to a target heading machine; removing data of the target heading machine in a stop section and an empty pushing section in the first original data to obtain second original data; processing an abnormal value in the second original data to obtain target operation data; feature parameters in the target operation data are extracted; performing normalization processing on the feature parameters to obtain a model training data set; a Stacking algorithm model is constructed according to a base learner and a meta learner, the base learner comprises a plurality of regression trees, and the output result of the base learner is used as the input of the meta learner; and training the Stacking algorithm model based on the model training data set so as to obtain the prediction model for the surrounding rock strength of the tunneling roadway of the full-face tunneling machine.

The invention belongs to the field of intelligent manufacturing, and particularly relates to an intelligent scheduling method for collaborative manufacturing of tunnel boring machines, in the method, multi-source heterogeneous data including design data, process data, production data, material data and the like are acquired, and a rich data basis is provided for intelligent scheduling. The data fusion method based on the ontology is adopted, and the problems of semantic heterogeneity and structural heterogeneity of multi-source heterogeneous data are effectively solved. By constructing the tunnel boring machine manufacturing field ontology model, semantic association and sharing of data from different sources are realized, and the availability and understandability of the data are improved. An algorithm combining mixed integer programming and deep reinforcement learning is provided for intelligent scheduling of tunnel boring machine collaborative manufacturing. A robust optimization method is introduced to enhance the robustness of the scheduling scheme, and the influence of uncertain factors such as raw material supply and equipment maintenance in the manufacturing process of the tunnel boring machine is considered.

The invention provides an end-to-end model TBM tunneling rock mass state sensing method and system, and relates to the technical field of image processing and deep learning. The method comprises the following steps: collecting TBM tunneling parameters and rock slag picture data in a TBM construction case or collecting TBM tunneling parameters and rock slag picture data of a current TBM construction tunnel under construction, and establishing a data storage warehouse module; training an end-to-end neural network model by using the TBM tunneling parameters and the corresponding rock mass state parameters; a trained end-to-end deep neural network model is deployed on a cloud server and used for receiving real-time TBM tunneling parameters and rock slag picture data images and executing rock mass state classification, and surrounding rock grades of tunneling rock masses are displayed on a visual interface of a TBM upper computer. According to the method, the rock mass state information can be displayed on the visual interface of the TBM upper computer in real time, and the defects that traditional rock mass condition parameters are difficult to obtain, and the means are backward are overcome.

The invention relates to the technical field of data processing, discloses a digital twin adaptive decision platform for TBM tunneling and a control method, and aims to solve the problems of single sensing dimension, mutual separation of physical and data models, disjunction of early warning and control links and low man-machine interaction efficiency in the prior art. According to the scheme, the method mainly comprises the steps that multi-source real-time data is collected through a hardware sensing layer, after the multi-source real-time data is processed through a data management and fusion layer, a digital twin model layer constructs a physical-data fusion model and completes risk assessment, finally risk visualization is achieved through an augmented reality interaction layer, and an intelligent control decision-making layer generates a control instruction and outputs the control instruction to a TBM main control system. According to the integrated intelligent decision-making platform and the control method, multi-source perception deep fusion, physical and data model online coupling, risk assessment and equipment control second-level closed loop can be realized, and visual interaction can be realized through augmented reality.

A tunnel boring device and a tunnel boring machine, which aim to solve the problem of a hinged oil cylinder being likely to be damaged due to a propulsion mode. The tunnel boring device (100) comprises a front shield (110), a middle shield (120), and a tail shield (130). A first propulsion assembly (140), a second propulsion assembly (150) and an auxiliary propulsion member (160) are provided inside the tunnel boring device; the auxiliary propulsion member (160) is located between the front shield (110) and the second propulsion assembly (150); and when the front shield (110) is stuck, the second propulsion assembly (150) moves in a tunneling direction, such that a second end of the second propulsion assembly (150) comes into contact with and abuts against the auxiliary propulsion member (160), thereby pushing the front shield (110) to free the front shield. In the present application, a dual-mechanical force transmission structure is provided, which helps to avoid the risk whereby a hinged oil cylinder is likely to be damaged when ultrahigh thrust is transmitted to the front shield by means of a single mechanical force transmission structure, and which transmits the ultrahigh thrust to the front shield, facilitating escape of the front shield, and then guaranteeing normal boring of a tunnel boring machine.

The invention discloses a large-section TBM multi-stage cutter head for high-pressure water jet joint cutting assisted rock breaking. The large-section TBM multi-stage cutter head comprises a cutter head system, a high-pressure water jet coupling system, a cutter head rotating system, a cutter head propelling system and a cutter head supporting frame. The cutterhead system comprises a central cutterhead, an edge cutterhead and a blind area cutterhead, and the central cutterhead and the edge cutterhead are both circular. The edge cutterheads are arranged on the periphery of the center cutterheads, the blind area cutterheads are arranged in blind areas between the center cutterheads and the edge cutterheads, and each center cutterhead and each edge cutterhead are each provided with a plurality of high-pressure water jet coupling systems. The cutting depth and the cutting range of the water jet are effectively increased, the rock breaking capacity is improved, the TBM hob rock breaking efficiency is improved, and the technical progress of coupling high-pressure water jet TBM equipment manufacturing is promoted.

The invention discloses a visual detection system and method for a TBM wall back grouting effect, and belongs to the technical field of tunnel detection, and the system comprises an acoustic signal transmitting matrix, an acoustic energy sensing matrix, a tunnel half-section synchronous lifting device, a data processing center, a core scheduling unit, a holographic data processing unit and a holographic intelligent analysis unit, the tunnel half-section synchronous lifting device comprises a tunnel half-section synchronous lifting track, a transmitting base, a sensing base, a transmitting sensing partition plate and a transmitting sensing fixing plate. According to the method, grouting attribute information of a to-be-detected area is obtained through a root-mean-square value, a longitudinal wave energy dissipation value, longitudinal wave sending and receiving time difference and a wave velocity value, a three-dimensional information model of a tunnel section is built through a holographic data processing unit based on the information, and difference data and a difference area are presented through a holographic intelligent analysis unit; therefore, visualization processing of the tunnel grouting information is achieved, and the accuracy of TBM wall back grouting effect detection is improved.

The invention discloses a tunnel boring machine (TBM) tunneling method for a large-diameter inclined shaft under a deep coal mine well, belongs to the technical field of mine construction engineering and tunnel tunneling, and aims to solve the problems of poor axis control precision and deviation correction response lag caused by the fact that an existing method depends on manpower and cannot integrate geology and inclination angle information for self-adaptive thrust distribution. The surrounding rock strength grade is judged according to the torque and the speed by collecting the cutterhead torque, the rotating speed, the total propulsive force and the pitch angle in real time; calculating a gravity component force and an unstable moment by combining the pitch angle, and calculating a required deviation correction moment according to the real-time angle deviation; a pre-stored data table is inquired based on the pitch angle, the surrounding rock grade and the deviation rectifying torque, and the target pressure distribution proportion of the upper and lower partition oil cylinders is dynamically generated; and finally, the total propulsive force set value is decomposed according to the proportion, the pressure of an oil cylinder is adjusted through independent closed-loop control, and self-adaptive accurate control over the pitch attitude is achieved. The method is mainly used for improving the axis control precision and stability of the large-diameter inclined shaft TBM construction of the deep coal mine.

The invention discloses a translation type cutting device for a tunnel cantilever heading machine, which comprises a disc-shaped mounting seat movably arranged on a base, a multi-angle adjusting mechanism is arranged between the base and the disc-shaped mounting seat, the lower end of the base is connected with the heading machine through a vertical driving oil cylinder, the upper end of the disc-shaped mounting seat is connected with one end of a suspension arm, and the other end of the suspension arm is connected with the base. The other end of the suspension arm is provided with a monitor body, one end, far away from the suspension arm, of the monitor body is provided with a cutting mechanism, the suspension arm is provided with a driving motor or a hydraulic motor, an output shaft of the driving motor or the hydraulic motor is coaxially connected with one end of a transmission rod, and the transmission rod is coaxially and rotatably assembled in the monitor body; and the other end of the transmission rod is connected with the cutting mechanism. According to the invention, the cutting working surface can be effectively enlarged, the cutting maneuverability is improved, and the tunneling efficiency of the tunneling machine is improved. The invention is suitable for the technical field of tunneling in tunnel construction.

The invention provides a shield / TBM (Tunnel Boring Machine) starting counter-force device in a subsurface tunnel primary support structure, which comprises a starting frame arranged in a tunnel body along the length direction of the tunnel body; the counter-force rings are arranged on the starting frame in an end-to-end connection mode, and the axes of the counter-force rings are parallel to the axis of the tunnel body; the supporting unit comprises a plurality of groups of positive supporting arms and inclined supporting arms which are arrayed on the circumferential side of the counter-force ring at the tail position, the extension line of each positive supporting arm in the length direction is perpendicular to the axis of the counter-force ring, and the extension line of each inclined supporting arm in the length direction forms an included angle of 45-75 degrees with the axis of the counter-force ring; a bracket seat is arranged at one end, far away from the counter-force ring, of each inclined supporting arm; and the multiple sets of pre-embedded steel plates are evenly distributed on the inner wall of the tunnel body, and the multiple sets of positive supporting arms and the multiple sets of bracket bases are connected with the corresponding pre-embedded steel plates correspondingly. The counterforce ring is connected with the underground excavation primary support, and shield launching can be completed under the condition that no station or underground excavation civil air defense tunnel main body structure exists.

The invention discloses a tunnel surrounding rock deformation prediction method, system and equipment. The tunnel surrounding rock deformation prediction method comprises the steps that actual multi-source data in the tunneling process of a tunnel boring machine (TBM) are obtained, and the multi-source data at least comprise surrounding rock deformation monitoring data, tunneling data of the tunnel boring machine and vibration signal data; the multi-source data is input into a pre-trained prediction model, a prediction result of the tunnel surrounding rock deformation condition in the TBM tunneling process is obtained, and the prediction model is pre-trained with the pre-obtained multi-source data as a training sample and the tunnel surrounding rock deformation condition as a label. According to the embodiment of the invention, the method can achieve the advanced prediction of the deformation of the surrounding rock through the real-time data in the construction process of the tunnel boring machine, provides a scientific basis for the construction parameter optimization and risk early warning of the tunnel boring machine, reduces the workload of manual monitoring, and improves the construction automation level.

The invention relates to the technical field of tunneling machine intelligent control, in particular to a lithology real-time prediction method in the tunneling process of a tunneling machine, which comprises the following steps: detecting effective data in the tunneling process of the tunneling machine; inputting the effective data into the lithology prediction model, and obtaining an output lithology prediction result; during the period, dividing the valid data into at least one feature block according to the size of the feature block; obtaining a time domain attention matrix, a frequency domain attention matrix, a frequency domain feature and a time domain feature corresponding to the feature block according to the set LSTM network and the mixed attention mechanism; based on the time domain attention matrix, the frequency domain attention matrix, the frequency domain features and the time domain features, obtaining a lithology prediction result; and judging the working state of the next tunneling circulating tunnel boring machine according to the lithological prediction result. The method has the beneficial effects that local features in address data are analyzed more meticulously while real-time lithology prediction is realized in the TBM construction process, so that the sensitivity to lithology change is improved.

The invention provides a surrounding rock grading model training method and a surrounding rock grading method and device, and relates to the technical field of tunneling machine construction. The surrounding rock grading model training method comprises the steps of obtaining multi-modal sample data and corresponding labeling data in a tunneling construction process, wherein the labeling data is a surrounding rock grading result; and training the surrounding rock grading model by using the multi-modal sample data and the annotation data so as to adjust parameters of the surrounding rock grading model.

The present disclosure provides a tunnel boring machine excavation parameter prediction method based on offline reinforcement learning and a device. The method comprises: acquiring historical operating data generated by a tunnel boring machine within a specified time interval under normal operating conditions, and preprocessing the data; constructing a tunnel boring machine excavation parameter prediction model on the basis of an offline reinforcement learning model, and training the tunnel boring machine excavation parameter prediction model by means of historical point data in the preprocessed historical operating data; and inputting point data generated by the tunnel boring machine during real-time operation into the trained tunnel boring machine excavation parameter prediction model, and outputting a predicted value of a tunnel boring machine excavation parameter to guide the excavation of the tunnel boring machine. By means of the present invention, a corresponding excavation parameter can be predicted on the basis of point data generated by a tunnel boring machine during operation, providing guidance for a tunnel boring machine operator.

The invention discloses a tunnel boring machine performance prediction and monitoring system and method based on digital twinning and machine learning. The system comprises a data acquisition module, a data preprocessing module, a model construction module, a performance analysis module and a visual analysis module. The data acquisition module is used for acquiring initial data of a tunnel boring machine on a construction site; the data preprocessing module is used for preprocessing the initial data to obtain preprocessed data; the model construction module constructs a prediction model and a digital twinborn model of the tunnel boring machine based on the preprocessed data; the performance analysis module predicts the tunneling speed and the propelling speed of the tunnel boring machine by using the prediction model to obtain a prediction result, and integrates the prediction result with the digital twinborn model; and the visual analysis module is used for constructing a virtual environment and checking the construction progress and the performance prediction result of the tunnel boring machine in real time in a digital twinborn model in the virtual environment.

The invention provides a rear support of a heading machine and the heading machine, and belongs to the field of tunneling equipment. The rear support of the heading machine comprises a rear support body, a vertical direction adjusting device and a horizontal direction adjusting device which are connected to the rear support body, and further comprises a limiting structure and a matching structure, one of the limiting structure and the matching structure is installed on the rear support body, and the other one is used for being installed on a main beam or an inner yoke. The limiting structure comprises at least two limiting parts which are arranged front and back, the matching structure comprises a limiting matching part which is located between the two limiting parts which are adjacent front and back, and gaps are reserved between the limiting matching part and the limiting part which is adjacent to the front side and / or the limiting part which is adjacent to the rear side. The heading machine comprises the heading machine rear support. The limiting structure and the matching structure can be matched in a limiting mode after the up-down steering amplitude or the left-right steering amplitude of the heading machine exceeds a design value, so that the rear supporting body deflects adaptively, and damage to the knuckle bearing is avoided.

The invention discloses a heading machine capable of synchronously reducing peripheral pollution, and relates to the technical field of heading machine equipment, the heading machine comprises a heading machine main body and a dust collecting pipe fixedly mounted at the top of the heading machine main body, and further comprises a glove box fixedly mounted on one side of the bottom of the dust collecting pipe, and a collecting assembly is arranged in the middle of the interior of the dust collecting pipe; a spraying assembly is arranged on the side, close to the collecting box, of the interior of the dust collecting pipe. The collecting assembly comprises a motor and a rotating shaft, and fan blades and a main gear are sequentially connected to the outer side of the rotating shaft; the spraying assembly comprises mounting blocks which are symmetrically arranged, sliding rods are fixedly connected to the inner sides of the two mounting blocks, and the problems that when a multi-drill-bit heading machine is used, the drilling position is difficult to be completely sealed, dust still escapes all around, and the surrounding environment is polluted are solved; the condition that dust is not completely cleaned still possibly exists, and the dust falling effect of the device is reduced.

The present invention provides a method for designing an abrasive water jet-disc cutter combined rock-breaking cutter head, a system therefor, a cutter head and a tunnel boring machine (TBM), wherein the key technology of designing the abrasive water jet-disc cutter combined rock-breaking cutter head of the TBM are provided from the aspects of determining a combined rock-breaking combination mode, configuration of cutter operation parameters and optimization of the combined cutter head; the performance of the abrasive water jet-disc cutter combined rock-breaking cutter head manufactured according to the optimized layout parameters is improved; and a new idea is provided for the development and application of a full-section rock tunneling machine in the field of underground engineering.

The invention discloses an open-type TBM over-slowly-inclined soft rock stratum zoning and sectioning collaborative supporting construction method. The method comprises the steps that S1, shield tail immediate supporting is conducted; s2, reinforcing and supporting the rear part of the supporting shoe; and S3, bottom arch anchor support closing regulation and control. According to the open-type TBM equipment structure characteristics and the slowly-inclined soft rock stratum deformation rule, a supporting area is divided into three operation sections including a near-shield-tail instant supporting area, a supporting shoe rear reinforcing supporting area and a bottom arch anchor supporting closed regulation and control area, differential supporting is implemented in a staged mode, space-time progressive construction of pre-stressed anchor cables and anchor rods is combined, and the supporting effect is greatly improved. Matching of supporting rigidity and stratum deformation is ensured through dynamic adjustment of prestress, a dynamic collaborative supporting system of instant supporting, reinforcement and closed-loop regulation and control is formed, and double improvement of supporting efficiency and safety is achieved.

The utility model relates to the technical field of heading machine cutter installation, and discloses a fast cutter replacement structure based on a tunnel boring machine, which comprises a cutter head main body, a plurality of installation grooves are arranged on one side of the cutter head main body, a plurality of installation plates are fixedly connected in the installation grooves, one side of each installation plate is provided with a connection groove, and the connection grooves are connected with the installation plates. A cutter is slidably connected into the connecting groove, the cutter is placed into the mounting groove, then a fixing bolt is rotated, the fixing bolt drives a cam to rotate, the cam drives a transmission plate to move, and the transmission plate drives a second transmission inclined block to be inserted into a fixing groove in the surface of the cutter through a first transmission inclined block to fix the cutter. And meanwhile, the transmission plate drives the fixing block to be inserted into the fixing groove in the end of the tool to fix the tool, so that portable installation of the tool is achieved, meanwhile, when disassembly needs to be conducted, the tool can be disassembled and assembled in a portable mode only by rotating the fixing bolt reversely, and the tool replacement efficiency is greatly improved.

The invention relates to a heading machine load self-adaptive control method and system, and the method comprises the steps: a data analysis module is disposed on a heading machine equipment layer, collects the heading data of the heading machine equipment layer in real time, and calculates a load coefficient for self-adaptive adjustment; and the control module is connected with the data analysis module and the heading machine equipment layer, and analyzes the accessed load coefficient into a control signal for adjusting rotation and lifting of a cutting arm in the heading machine equipment layer. The method comprises the following steps: determining a motion trail model of a cutting operation surface of a heading machine equipment layer by acquiring perception data of a manual cutting section, determining a load coefficient generated by the motion trail model according to the state change of the cutting operation surface in the cutting process, and adjusting rotation and lifting of a cutting arm in the heading machine equipment layer based on the load coefficient. The self-adaptive control of the equipment layer of the heading machine is realized, the accuracy and the stability of on-line identification of the heading working face are greatly improved, the equipment failure rate and the safety risk of operation are reduced to the greatest extent, and the method has wide applicability.

The invention discloses a shield tunneling machine intelligent tunneling regulation and control system and method based on muck digital imaging and a knowledge graph, and the system comprises a muck image collection module, an image processing unit, a knowledge graph reasoning module, a parameter reference suggestion generation module, a visual interaction module, and a feedback and iterative optimization module. The method comprises the following steps: acquiring an image of residue soil on a residue discharge belt of a shield tunneling machine in real time, dynamically identifying a stratum type and a change trend in combination with a knowledge graph, generating a reference regulation and control suggestion of tunneling parameters of the shield tunneling machine, and displaying the reference regulation and control suggestion on a screen. According to the method, a shield tunneling machine driver can scientifically and systematically adjust construction operation, the real-time performance and accuracy of stratum recognition are improved, cutter head abrasion and shield attitude offset caused by uneven hardness or boulder strata are reduced, and construction safety and tunneling efficiency are improved; the system carries out iterative optimization on the knowledge graph and the image recognition model according to construction feedback, the adaptability and reliability of the system under different working conditions are enhanced, and the construction economy and the engineering application value are improved.

The invention discloses a TBM tunneling state monitoring method, system and device and a medium, and relates to the technical field of TBM tunnel geological recognition and cutterhead maintaining.A plurality of different types of accelerometers are arranged on a cutterhead of a TBM to obtain vibration data of the TBM; establishing independent response models for the vibration data and TBM heading machine operation data, cutterhead data, geological data and construction data to obtain a nonlinear relationship between the vibration data and each data parameter; meanwhile, a comprehensive response model is established according to the nonlinear relation so as to establish a mutual feedback mechanism between the vibration data and the influence factors, and the specific numerical range of each influence factor is calculated according to the vibration data, so that the tunneling state of the TBM is judged; a plurality of accelerometers designed by the invention are slightly influenced by the metal cutterhead, and meanwhile, the tunneling state of the TBM can be judged according to a mutual feedback mechanism between obtained vibration data and related data.

The invention discloses a rock slag multi-dimensional intelligent identification and real-time early warning method for tunnel boring machine construction. The method comprises the steps that continuous rock slag images are acquired and preprocessed; inputting the preprocessed rock slag image into the trained multi-task network, and outputting a multi-task result; wherein the task network adopts a unified encoder and multi-head decoder architecture, the multi-head decoder comprises a segmentation head, a detection head, a regression head and an anomaly scoring head, the segmentation head outputs a pixel mask, the detection head outputs a rock slag frame and category, the regression head outputs a particle size distribution parameter, and the anomaly scoring head outputs a frame level anomaly score; synchronously carrying out sliding window statistics based on output results of the regression head and the abnormal score head; and performing multi-level early warning judgment based on a sliding window statistical result. According to the method, multiple functions of rock slag instance segmentation, target detection, particle size distribution regression, flow estimation, anomaly scoring and the like can be realized, and multi-stage early warning and parameter suggestion are realized through time sequence statistics.

The utility model relates to the technical field of coal mine heading machines, and discloses a dust removal device for a heading machine, a dust removal spray seat is arranged at the upper part of a dust suction port, a dust removal spray head is arranged at the lower part of the dust removal spray seat, and an exhaust fan blade and a centrifugal net cylinder respectively rotate on the inner sides of an exhaust cylinder seat and a separation cylinder seat under the driving of a driving motor; the dust removal spraying base is arranged at the dust collection opening in the front of the dust removal box base, the exhaust fan blades are arranged in the dust removal box base, external dust is sucked into the dust collection opening through the exhaust fan blades, and the dust is adsorbed and settled through water mist sprayed out of the dust removal spraying base, so that the dust generated when the heading machine works can be effectively removed; a centrifugal separation structure is adopted, dust adsorbed by water mist is separated from water liquid through rotary centrifugation of the centrifugal net barrel after flowing into the centrifugal net barrel, water liquid separation and recovery can be achieved, water liquid outflow waste is avoided, meanwhile, water liquid can be effectively recycled, and the water-liquid separation and recovery efficiency is improved. Field operation is facilitated, and a large amount of water can be saved.

The utility model relates to the technical field of tunnel construction and underground space engineering construction, in particular to a TBM (Tunnel Boring Machine) hob performance test detection device based on linear rock breaking, which comprises a base, a frame is arranged on the base, and a rock breaking mechanism, a rock box mechanism, a rock breaking hob component and a rock box body are arranged in the frame. A load sensor is fixed between the tool support and the hydraulic oil cylinder, and a three-way force sensor is fixed between the tool support and the tool apron; a confining pressure sensor is arranged on the rock box body, a weighing device is arranged at the bottom end in the frame, and a photoelectric temperature integrated sensor is arranged on the weighing device. By monitoring various performance parameters such as hob load, temperature and abrasion in real time, analyzing hob diameter and weight changes, analyzing rock breaking effects of different hobs and researching a hob rock breaking mechanism, quantitative evaluation of performance differences of different hobs is achieved, reference is provided for manufacturers to manufacture and optimize hob performance, and the hob rock breaking performance evaluation device is suitable for large-scale popularization and application. And key guidance is provided for selection of tunnel project hobs and selection of construction parameters.

The invention belongs to the field of tunnel boring machine internal equipment, and discloses a multi-degree-of-freedom large-magnification-ratio visual carrying motion protection platform suitable for a long and narrow space in a TBM (Tunnel Boring Machine), which comprises a guide rail, a loading platform, a horizontal telescopic mechanism, a rotating mechanism, a vertical telescopic mechanism, a visual protection system and a front-back swinging mechanism. According to the multi-degree-of-freedom large-magnification-ratio vision carrying motion protection platform, the flexibility and coverage range of TBM internal vision monitoring are improved, and the requirements of different monitoring positions can be met; through multi-degree-of-freedom motion and a large magnification ratio, comprehensive monitoring of a complex environment in the TBM is realized; the visual protection system effectively protects visual equipment, and durability and stability of the equipment are improved; the structure design is compact, deployment and operation in a long and narrow space in the TBM are suitable, and the space utilization rate is increased; and through automatic and intelligent design, the requirement of manual operation is reduced, the operation risk is reduced, and the working efficiency is improved.