Control method, device, system and storage medium of shield machine

Abstract

The application discloses a control method, device and system of a shield tunneling machine and a storage medium, and relates to the technical field of shield tunnel construction and equipment. The control method of the shield tunneling machine comprises the following steps: determining a slag discharging state of the shield tunneling machine according to a slag discharging image of the shield tunneling machine; determining target operation parameters of the shield tunneling machine according to the slag discharging state and tunneling parameters of the shield tunneling machine, wherein the tunneling parameters comprise a current earth chamber pressure of the shield tunneling machine, and the target operation parameters comprise a target opening degree of a rear gate of a screw conveyor, and the target operation parameters are used for controlling the earth chamber pressure of the shield tunneling machine within a target range; and automatically controlling the shield tunneling machine based on the target operation parameters. Through the embodiment of the application, stable control and automation level of the earth chamber pressure in a water-rich stratum are realized, and the construction quality and efficiency of the shield tunneling machine are improved.

Description

Technical Field

[0001] This invention relates to the field of shield tunnel construction technology and equipment, and in particular to a control method, device, system and storage medium for a shield tunneling machine. Background Technology

[0002] Tunnel boring machines (TBMs) are the main equipment for tunnel construction. With the research and development investment of major TBM design and development companies in equipment upgrades and construction efficiency improvements, the TBM construction method is developing towards automation, intelligence, greater depth, larger cross-section, and longer distance.

[0003] When an earth pressure balance tunnel boring machine (TBM) is excavating in stable strata, the speed of muck discharge in the earth chamber can be adjusted by changing the rotational speed of the screw conveyor, and the speed of muck intake in the earth chamber can be adjusted by changing the propulsion speed. By adjusting the muck discharge and intake speeds, the pressure in the earth chamber can be adjusted to stabilize it at a target value. Summary of the Invention

[0004] Analysis revealed that when the equipment was excavating in water-rich strata, the screw conveyor could not form an effective soil plug, and the soil improvement was poor, which could easily lead to gushing. The slag discharge speed could not be adjusted simply by adjusting the speed of the screw conveyor.

[0005] One of the technical problems to be solved by the embodiments of the present invention is: how to improve the stability of tunnel boring machine operation in water-rich strata.

[0006] According to a first aspect of some embodiments of the present invention, a control method for a tunnel boring machine (TBM) is provided, comprising: determining the muck discharge state of the TBM based on muck discharge images of the TBM; determining target operating parameters of the TBM based on the muck discharge state and the tunneling parameters of the TBM, wherein the tunneling parameters include the current soil chamber pressure of the TBM and the target operating parameters include the target opening degree of the rear gate of the screw conveyor, the target operating parameters being used to control the soil chamber pressure of the TBM within a target range; and automatically controlling the TBM based on the target operating parameters.

[0007] In some embodiments, the slag discharge image includes at least one of the images of the slag outlet of the tunnel boring machine and at least a portion of the conveyor belts; the slag discharge status includes at least one of the slag discharge status of the slag outlet and the slag transport status of the conveyor belts and the transport system; and the slag discharge status of the slag outlet includes at least one of the following: smooth slag discharge from the slag outlet, slag blockage at the slag outlet, and slag gushing from the slag outlet; the slag transport status of the conveyor belts and the transport system includes at least one of the following: sluggish slag discharge from the conveyor belts, normal slag discharge from the conveyor belts, and slag and soil discharge from the conveyor belts.

[0008] In some embodiments, determining the muck discharge status of the tunnel boring machine (TBM) based on the muck discharge image includes: processing the muck discharge image using an image processing model; and determining the muck discharge status of the TBM based on the processing result of the image processing model.

[0009] In some embodiments, the target opening of the rear gate of the tunnel boring machine's screw conveyor includes at least one of the opening of the upper rear gate and the opening of the lower rear gate. Based on the target operating parameters, the automatic control of the tunnel boring machine includes: based on at least one of the opening of the upper rear gate and the lower rear gate, automatically controlling at least one of the upper rear gate and the lower rear gate.

[0010] In some embodiments, the target operating parameters further include at least one of the propulsion speed and the rotational speed of the screw conveyor. Based on the target operating parameters, automatic control of the tunnel boring machine includes controlling at least one of the propulsion mechanism and the screw conveyor of the tunnel boring machine based on at least one of the propulsion speed and the rotational speed of the screw conveyor.

[0011] In some embodiments, determining the target operating parameters of the tunnel boring machine (TBM) based on the slag discharge status and the TBM's tunneling parameters includes: using a machine learning model to process the slag discharge status and the TBM's tunneling parameters to obtain the target operating parameters of the TBM output by the machine learning model, wherein the target operating parameters include the target opening degree of the rear gate.

[0012] In some embodiments, the tunneling parameters of the tunnel boring machine also include at least one of the following: propulsion speed, screw conveyor speed, screw conveyor torque, screw conveyor front pressure, screw conveyor rear pressure, screw conveyor upper rear gate opening, and screw conveyor lower rear gate opening.

[0013] In some embodiments, the control method further includes: when the soil chamber pressure is not within the target range, collecting the tunneling parameters and muck discharge status of the tunnel boring machine as training data; adjusting the operating parameters of the tunnel boring machine until the soil chamber pressure returns to the target range, and using the current operating parameters as the label values ​​of the training data; and using the training data and its label values ​​to train the machine learning model.

[0014] According to a second aspect of some embodiments of the present invention, a control device for a tunnel boring machine (TBM) is provided, comprising: a first determining module configured to determine the muck discharge state of the TBM based on muck discharge images of the TBM; a second determining module configured to determine target operating parameters of the TBM based on the muck discharge state and the tunneling parameters of the TBM, wherein the tunneling parameters include the current soil chamber pressure of the TBM and the target operating parameters include the target opening degree of the rear gate of the screw conveyor, the target operating parameters being used to control the soil chamber pressure of the TBM within a target range; and a control module configured to automatically control the TBM based on the target operating parameters.

[0015] According to a third aspect of some embodiments of the present invention, a control device for a tunnel boring machine is provided, comprising: a memory; and a processor coupled to the memory, the processor being configured to execute any of the aforementioned control methods for a tunnel boring machine based on instructions stored in the memory.

[0016] According to a fourth aspect of some embodiments of the present invention, a control system for a tunnel boring machine is provided, comprising: a control device for a tunnel boring machine as described in any of the foregoing embodiments; and a camera located on the tunnel boring machine for capturing images of slag discharge from the tunnel boring machine's screw conveyor.

[0017] In some embodiments, the camera is directed toward the slag outlet of the screw conveyor and the belt conveyor and transport system belt.

[0018] In some embodiments, the control system further includes: a screw conveyor; and a propulsion system.

[0019] According to a fifth aspect of some embodiments of the present invention, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements any of the aforementioned control methods for a tunnel boring machine.

[0020] Some embodiments of the above-described invention have the following advantages or beneficial effects. Through the embodiments of this disclosure, the current muck discharge status can be automatically obtained through image processing, and the opening of the rear gate of the tunnel boring machine's screw conveyor can be adjusted based on the muck discharge status. This allows for effective regulation of the muck discharge speed even in water-rich strata. Consequently, stable control and automation of soil chamber pressure in water-rich strata are achieved, improving the construction quality and efficiency of the tunnel boring machine.

[0021] Other features and advantages of the invention will become clear from the following detailed description of exemplary embodiments of the invention with reference to the accompanying drawings. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A partial schematic diagram of a tunnel boring machine according to some embodiments of the present disclosure is shown.

[0024] Figure 2 A flowchart illustrating a control method for a tunnel boring machine according to some embodiments of the present invention is shown.

[0025] Figure 3A schematic diagram of the control device for a tunnel boring machine according to some embodiments of the present invention is shown.

[0026] Figure 4 A schematic diagram of the control system of a tunnel boring machine according to some embodiments of the present invention is shown.

[0027] Figure 5 A schematic diagram of the control device for a tunnel boring machine according to other embodiments of the present invention is shown.

[0028] Figure 6 A schematic diagram of the control device for a tunnel boring machine according to some embodiments of the present invention is shown. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0031] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0032] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0033] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0034] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0035] Analysis revealed that in water-rich strata, the screw conveyor struggles to form an effective soil plug, and gushing phenomena are prone to occur when soil improvement is poor, making it impossible to adjust the slag discharge speed solely by regulating the screw conveyor's rotation speed. Therefore, this disclosure proposes an automatic control method for tunnel boring machines (TBMs) in such strata. This method automatically adjusts the slag discharge speed by regulating the opening of the screw conveyor's rear gate, thereby stabilizing the soil chamber pressure. To achieve accurate control, this disclosure utilizes images captured by cameras deployed on the TBM to predict the current slag discharge status, enabling the automatic determination of the TBM's control parameters based on this status.

[0036] Figure 1 A partial schematic diagram of a tunnel boring machine according to some embodiments of the present disclosure is shown. Figure 1 In the partial structure 1 of the tunnel boring machine shown, the slag discharged from the slag outlet 111 of the screw conveyor 11 falls onto the belt conveyor 13, where it is transported away. Based on this, the present disclosure deploys a camera 12 on the tunnel boring machine, with its shooting angle facing the slag outlet 111, thereby enabling it to capture images reflecting the slag discharge status of the tunnel boring machine. The camera 12 can be connected to the tunnel boring machine's controller via wired or wireless connection to transmit the captured images to the controller for further processing.

[0037] The following is for reference. Figure 2 This invention describes an embodiment of the control method for a tunnel boring machine (TBM).

[0038] Figure 2 A flowchart illustrating a control method for a tunnel boring machine according to some embodiments of the present invention is shown. Figure 2 As shown, the control method of the tunnel boring machine in this embodiment includes steps S202 to S206.

[0039] In step S202, the muck discharge status of the tunnel boring machine (TBM) is determined based on the muck discharge image. The muck discharge image is obtained, for example, through... Figure 1 The data was collected by camera 12.

[0040] The status of the slag discharge image is used to reflect the amount of soil and slag that has been discharged but still remains at the discharge port. It can be represented by continuous values, such as the estimated volume of soil and slag, or by discrete values, such as several levels, categories, or more detailed statuses.

[0041] Considering that the slag discharge process involves a screw conveyor discharging the slag from the outlet and then a belt conveyor transporting it away, the slag discharge status can be considered from two aspects. One is the amount of slag discharged from the outlet, or the current slag discharge capacity; the other is the amount of slag transported away by the belt conveyor, or its carrying capacity. For example, a large amount of slag is discharged from the outlet, but the belt conveyor's carrying capacity is limited. Because the discharged slag is relatively thin, and the belt is inclined (e.g....), the slag discharge may be excessive. Figure 1As shown in the diagram, if too much excavated soil is discharged, the unremoved soil will flow downwards along the conveyor belt (i.e., in the opposite direction to the conveyor belt's movement), causing it to backflow into the tunnel. In this situation, the equipment may even need to be stopped to wait for on-site workers to clear the excavated soil from the tunnel, affecting construction efficiency. To avoid this, it is necessary to consider reducing the discharge speed to match the discharged soil with the conveyor belt's carrying capacity. Therefore, the discharge status can be reflected from two aspects: the discharge status at the discharge outlet and the transport status of the conveyor belt and the transportation system.

[0042] In some embodiments, the muck discharge image includes at least one of the following: an image of the muck outlet of the tunnel boring machine (TBM) and an image of at least a portion of the conveyor belt. The muck discharge status includes at least one of the following: muck outlet discharge status and muck transport status of the conveyor belt and transport system. The muck outlet discharge status includes at least one of the following: smooth muck outlet discharge, muck outlet blockage, and muck outlet gushing muck. The conveyor belt and transport system muck transport status includes at least one of the following: conveyor belt system sluggish discharge, conveyor belt system normal muck discharge, and conveyor belt system muck and soil discharge into the air.

[0043] The slag discharge status can be determined using image processing models such as image classification models and image recognition models. In some embodiments, image processing models are used to process the slag discharge images; the slag discharge status of the tunnel boring machine is determined based on the processing results of the image processing models. Image processing models include, for example, YOLO (a target detection model), GAN (Generative Adversarial Networks), AlexNet (a deep convolutional neural network), and FCN (Fully Convolutional Networks).

[0044] One exemplary method is to input the slag discharge image into an image processing model such as an image classification model, and then have the model directly output the slag discharge status.

[0045] Another exemplary method is to first identify key information in the image using an image processing model such as a target recognition model, such as the location of key objects like soil, slag outlet, and conveyor belt in the image, and then further process (e.g., image classification) or calculate the images of these areas to determine the slag discharge status.

[0046] For example, a target recognition model can be used to identify the slag outlet and the belt of the conveyor belt, and further identify the soil and slag in the adjacent area associated with the slag outlet and the conveyor belt.

[0047] By determining the proportion of soil and debris in the vicinity of the muck outlet, the amount of muck discharged can be estimated. The vicinity of the muck outlet can be marked by a special structure of the tunnel boring machine, or, if the camera position is fixed relative to the muck outlet, it can be a first designated area in the acquired image. If the amount of muck discharged is greater than a first threshold, the muck discharge status can be considered to include muck gushing from the muck outlet; if the amount of muck discharged is less than a second threshold, the muck discharge status can be considered to include muck blockage at the muck outlet, where the second threshold is less than the first threshold; if the amount of muck discharged is between the first and second thresholds, the muck discharge status can be considered to include smooth muck discharge from the muck outlet.

[0048] By determining the proportion of excavated material in the vicinity of the conveyor belt, the amount of excavated material transported by the conveyor belt and the transport system can be estimated. The vicinity of the conveyor belt can be identified by the special structure of the tunnel boring machine, or, if the camera position is fixed relative to the conveyor belt position, it can be a second designated area in the acquired image. If the amount of excavated material transported is greater than a third threshold, the conveyor belt system can be considered to be experiencing sluggish discharge; if the amount of excavated material transported is less than a fourth threshold, the conveyor belt system can be considered to have emptied the excavated material, where the fourth threshold is less than the third threshold; if the amount of excavated material transported is between the third and fourth thresholds, the discharge status, including the conveyor belt system's discharge, can be considered normal.

[0049] In step S204, the target operating parameters of the tunnel boring machine are determined based on the slag discharge status and the tunneling parameters of the tunnel boring machine. The target operating parameters are used to control the soil chamber pressure of the tunnel boring machine within the target range.

[0050] The tunneling parameters include the current soil chamber pressure of the tunnel boring machine (TBM), and the target operating parameters include the target opening degree of the rear gate of the screw conveyor. That is, the target opening degree of the rear gate of the TBM's screw conveyor must be determined at least based on the muck discharge status and the current soil chamber pressure of the TBM. When the soil has a high water content, if the gate seal is ineffective or cannot be closed in time, a blowout accident may occur, posing a high safety risk. The double-gate design can better improve sealing and effectively avoid blowout accidents. Furthermore, during muck discharge, the muck passing through the gate opening can easily get stuck in the manual outer gate's track, preventing the manual outer gate from closing in an emergency. The double-gate design can prevent this from happening. In addition, the double-gate design can better maintain tunneling safety, ensure the continuous progress of shield tunneling, avoid work stoppages, and reduce manpower input.

[0051] In some embodiments, in addition to the soil chamber pressure, the tunneling parameters of the tunnel boring machine include at least one of the following: propulsion speed, screw conveyor speed, screw conveyor torque, screw conveyor front pressure, screw conveyor rear pressure, screw conveyor upper rear gate opening, and screw conveyor lower rear gate opening. The above parameters are described below by way of example.

[0052] The propulsion speed and the feed rate are positively correlated; for example, the feed rate can be determined based on the product of the propulsion speed and the cutterhead cross-sectional area. Furthermore, the actual feed rate is also affected by the formation conditions.

[0053] The rotational speed of a screw conveyor is positively correlated with the slag discharge rate. For example, in non-water-rich formations, the slag discharge rate can be determined based on the screw conveyor's rotational speed, screw pitch, and cross-sectional area. In water-rich formations, increasing the screw conveyor's rotational speed can also increase the slag discharge rate.

[0054] The torque of a screw conveyor is independent of the slag feeding or discharging speed; it reflects the operating state of the screw conveyor. Due to the friction between the slag and the screw conveyor, the dryness or wetness of the slag can be described, thus indirectly reflecting the state of the slag.

[0055] The pressure at the front of the screw conveyor is unrelated to the slag feeding or discharging speed. It reflects the operating status of the screw conveyor and indirectly reflects the condition of the slag. Both excessively high and low pressures indicate abnormalities in the equipment's excavation.

[0056] The pressure at the rear of the screw conveyor is unrelated to the slag feeding or discharging speed, reflecting the operating status of the screw conveyor and indirectly reflecting the state of the slag. Excessive pressure at the gate is prone to gushing.

[0057] The opening of the upper and lower gates of the screw conveyor is positively correlated with the slag discharge speed.

[0058] Based on the above information, at least one of the following can be known: the current slag feeding status, slag discharge status, and operating status of the tunnel boring machine. Combined with the slag discharge status obtained from the image, the target operating parameters can be determined.

[0059] In some embodiments, a machine learning model is used to process the muck discharge status and the tunneling parameters of the tunnel boring machine (TBM) to obtain the target operating parameters of the TBM output by the machine learning model. These target operating parameters include the target opening degree of the rear gate. Depending on the needs, the output target operating parameters may also include the propulsion speed and the screw conveyor speed, thereby comprehensively controlling the muck feeding and discharging speeds of the TBM.

[0060] Machine learning models, such as neural network models, can be selected as needed. In some embodiments, the machine learning model can be trained in advance using training data. For example, when the soil chamber pressure is outside the target range, the tunneling parameters and muck discharge status of the tunnel boring machine are collected as training data. Then, the operating parameters of the tunnel boring machine are adjusted. When the soil chamber pressure returns to the target range, the current operating parameters are used as the labeled values ​​of the training data. In this way, a set of training data and its labeled values ​​can be determined. Then, the machine learning model can be trained using the training data and its labeled values. The resulting machine learning model can more accurately predict the target operating parameters.

[0061] In step S206, the tunnel boring machine (TBM) is automatically controlled based on the target operating parameters to ensure that the soil chamber pressure of the TBM remains within the target range. Automatic control allows for adjustment of the TBM's muck discharge speed to regulate the soil chamber pressure.

[0062] For example, the target opening degree of the rear gate of the tunnel boring machine's auger conveyor includes at least one of the opening degree of the upper rear gate and the lower rear gate. Therefore, based on at least one of the opening degrees of the upper and lower rear gates, automatic control is performed on at least one of the upper and lower rear gates. By adjusting the opening degree of the rear gate, the muck discharge rate can be effectively regulated even in water-rich strata.

[0063] In some embodiments, the target operating parameters further include at least one of the propulsion speed and the screw conveyor speed. In this case, at least one of the tunnel boring machine's propulsion mechanism and the screw conveyor can be controlled based on at least one of the propulsion speed and the screw conveyor speed. For example, when the rear gates of the screw conveyor are all opened to the maximum and there is still a large amount of soil residue being discharged, the pressure in the soil chamber can be stabilized by reducing the propulsion speed. As for the screw conveyor speed, although it cannot completely control the muck discharge speed in water-rich strata, it can still play an auxiliary regulatory role.

[0064] The above steps can be repeated until the propulsion stops. After propulsion stops, the screw conveyor gate can be closed.

[0065] Through the above embodiments, the current muck discharge status can be automatically obtained through image processing, and the opening of the rear gate of the tunnel boring machine's screw conveyor can be adjusted based on the muck discharge status. This allows for effective regulation of the muck discharge speed even in water-rich strata. Consequently, stable control and automation of soil chamber pressure in water-rich strata are achieved, improving the construction quality and efficiency of the tunnel boring machine.

[0066] The following is for reference. Figures 3 to 6This invention describes embodiments of the control device and control system for the tunnel boring machine.

[0067] Figure 3 A schematic diagram of the control device for a tunnel boring machine according to some embodiments of the present invention is shown. For example... Figure 3 As shown, the control device 30 of the tunnel boring machine in this embodiment includes: a first determining module 310, configured to determine the muck discharge status of the tunnel boring machine based on the muck discharge image of the tunnel boring machine; a second determining module 320, configured to determine the target operating parameters of the tunnel boring machine based on the muck discharge status and the tunneling parameters of the tunnel boring machine, wherein the tunneling parameters include the current soil chamber pressure of the tunnel boring machine and the target operating parameters include the target opening degree of the rear gate of the screw conveyor, and the target operating parameters are used to control the soil chamber pressure of the tunnel boring machine within the target range; and a control module 330, configured to automatically control the tunnel boring machine based on the target operating parameters.

[0068] In some embodiments, the slag discharge image includes at least one of the images of the slag outlet of the tunnel boring machine and at least a portion of the conveyor belts; the slag discharge status includes at least one of the slag discharge status of the slag outlet and the slag transport status of the conveyor belts and the transport system; and the slag discharge status of the slag outlet includes at least one of the following: smooth slag discharge from the slag outlet, slag blockage at the slag outlet, and slag gushing from the slag outlet; the slag transport status of the conveyor belts and the transport system includes at least one of the following: sluggish slag discharge from the conveyor belts, normal slag discharge from the conveyor belts, and slag and soil discharge from the conveyor belts.

[0069] In some embodiments, the first determining module 310 is further configured to process the slag discharge image using an image processing model; and determine the slag discharge status of the tunnel boring machine based on the processing result of the image processing model.

[0070] In some embodiments, the target opening of the rear gate of the tunnel boring machine's screw conveyor includes at least one of the opening of the upper rear gate and the opening of the lower rear gate. The control module 330 is further configured to automatically control at least one of the upper rear gate and the lower rear gate based on at least one of the opening of the upper rear gate and the lower rear gate.

[0071] In some embodiments, the target operating parameters further include at least one of the propulsion speed and the screw conveyor speed, and the control module 330 is further configured to control at least one of the propulsion mechanism and the screw conveyor of the tunnel boring machine based on at least one of the propulsion speed and the screw conveyor speed.

[0072] In some embodiments, the second determining module 320 is further configured to use a machine learning model to process the slag discharge status and the tunneling parameters of the tunnel boring machine to obtain the target operating parameters of the tunnel boring machine output by the machine learning model, wherein the target operating parameters include the target opening degree of the rear gate.

[0073] In some embodiments, the tunneling parameters of the tunnel boring machine also include at least one of the following: propulsion speed, screw conveyor speed, screw conveyor torque, screw conveyor front pressure, screw conveyor rear pressure, screw conveyor upper rear gate opening, and screw conveyor lower rear gate opening.

[0074] In some embodiments, the control device further includes a training module 340, configured to: collect tunneling parameters and muck discharge status of the tunnel boring machine as training data when the soil chamber pressure is not within the target range; adjust the operating parameters of the tunnel boring machine until the soil chamber pressure returns to the target range, and use the current operating parameters as the label values ​​of the training data; and train the machine learning model using the training data and its label values.

[0075] Figure 4 A schematic diagram of the control system of a tunnel boring machine according to some embodiments of the present invention is shown. For example... Figure 4 As shown, the control system 4 of this embodiment includes: a control device 41 for the tunnel boring machine, the specific implementation of which can be referred to the control device 30; and a camera 42 located on the tunnel boring machine for capturing images of the slag discharge from the tunnel boring machine's screw conveyor.

[0076] The control device 41 of the tunnel boring machine can be implemented as a programmable logic controller (PLC) system.

[0077] In some embodiments, the camera 42 is directed toward the slag outlet of the screw conveyor and the belt conveyor and transport system belt.

[0078] In some embodiments, the control system 4 further includes: a screw conveyor 43; and a propulsion system 44.

[0079] Figure 5 A schematic diagram of the control device for a tunnel boring machine according to other embodiments of the present invention is shown. For example... Figure 5 As shown, the control device 50 of the tunnel boring machine in this embodiment includes: a memory 510 and a processor 520 coupled to the memory 510. The processor 520 is configured to execute the control method of the tunnel boring machine in any of the foregoing embodiments based on the instructions stored in the memory 510.

[0080] The memory 510 may include, for example, system memory, fixed non-volatile storage media, etc. The system memory may store, for example, the operating system, application programs, boot loader, and other programs.

[0081] Figure 6A schematic diagram of the control device for a tunnel boring machine according to some embodiments of the present invention is shown. For example... Figure 6 As shown, the control device 60 for the tunnel boring machine in this embodiment includes a memory 610 and a processor 620, and may also include an input / output interface 630, a network interface 640, a storage interface 650, etc. These interfaces, as well as the memory 610 and the processor 620, can be connected, for example, via a bus 660. The input / output interface 630 provides a connection interface for input / output devices such as a display, mouse, keyboard, and touchscreen. The network interface 640 provides a connection interface for various networked devices. The storage interface 650 provides a connection interface for external storage devices such as SD cards and USB flash drives.

[0082] Embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, characterized in that the program, when executed by a processor, implements any of the aforementioned control methods for a tunnel boring machine.

[0083] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0084] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0085] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0086] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0087] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for controlling a tunnel boring machine, comprising: Based on the muck discharge images of the tunnel boring machine (TBM), the muck discharge status of the TBM is determined. The muck discharge images include images of the muck outlet of the TBM and images of at least part of the conveyor belt. The muck discharge status includes the muck discharge status of the muck outlet and the muck transport status of the conveyor belt and the transport system. Based on the slag discharge status and the tunneling parameters of the tunnel boring machine (TBM), the target operating parameters of the TBM are determined, including: using a machine learning model to process the slag discharge status and the tunneling parameters of the TBM to obtain the target operating parameters of the TBM output by the machine learning model, wherein the target operating parameters include the target opening degree of the rear gate, the tunneling parameters include the current soil chamber pressure of the TBM, and the target operating parameters are used to control the soil chamber pressure of the TBM within a target range; The tunnel boring machine is automatically controlled based on the target operating parameters.

2. The control method according to claim 1, wherein: The slag discharge state of the slag outlet includes at least one of the following: smooth slag discharge, blocked slag discharge, and gushing slag discharge. The slag transport status of the belt conveyor and transport system includes at least one of the following: belt conveyor system sluggish discharge, belt conveyor system normal slag discharge, and belt conveyor system slag and soil discharge into the air.

3. The control method according to claim 1, wherein, Determining the muck discharge status of the tunnel boring machine (TBM) based on its muck discharge images includes: The slag discharge image is processed using an image processing model; Based on the processing results of the image processing model, the slag discharge status of the tunnel boring machine is determined.

4. The control method according to claim 1, wherein, The target opening degree of the rear gate of the tunnel boring machine's screw conveyor includes at least one of the opening degree of the upper rear gate and the opening degree of the lower rear gate. The automatic control of the tunnel boring machine based on the target operating parameters includes: Based on at least one of the opening degree of the upper rear gate and the lower rear gate of the screw conveyor, at least one of the upper rear gate and the lower rear gate of the screw conveyor is automatically controlled.

5. The control method according to claim 4, wherein, The target operating parameters also include at least one of propulsion speed and screw conveyor speed, and the automatic control of the tunnel boring machine based on the target operating parameters includes: Based on at least one of the propulsion speed and the rotational speed of the screw conveyor, the propulsion mechanism of the tunnel boring machine and at least one of the screw conveyor are controlled.

6. The control method according to claim 1, wherein, The tunneling parameters of the tunnel boring machine also include at least one of the following: propulsion speed, screw conveyor speed, screw conveyor torque, screw conveyor front pressure, screw conveyor rear pressure, screw conveyor upper rear gate opening, and screw conveyor lower rear gate opening.

7. The control method according to claim 5 further includes: When the soil chamber pressure is outside the target range, the tunneling parameters and muck discharge status of the tunnel boring machine are collected as training data. Adjust the operating parameters of the tunnel boring machine until the soil chamber pressure returns to the target range, and use the current operating parameters as the label values ​​of the training data; The machine learning model is trained using the training data and its labeled values.

8. A control device for a tunnel boring machine, comprising: The first determining module is configured to determine the muck discharge status of the tunnel boring machine (TBM) based on the muck discharge images of the TBM, wherein the muck discharge images include images of the muck outlet of the TBM and at least a portion of the conveyor belt, and the muck discharge status includes the muck discharge status of the muck outlet and the muck transport status of the conveyor belt and the transport system. The second determining module is configured to determine the target operating parameters of the tunnel boring machine (TBM) based on the slag discharge status and the tunneling parameters of the TBM, including: processing the slag discharge status and the tunneling parameters of the TBM using a machine learning model to obtain the target operating parameters of the TBM output by the machine learning model, wherein the target operating parameters include the target opening degree of the rear gate, the tunneling parameters include the current soil chamber pressure of the TBM, and the target operating parameters are used to control the soil chamber pressure of the TBM within a target range; The control module is configured to automatically control the tunnel boring machine based on the target operating parameters.

9. A control device for a tunnel boring machine, comprising: Memory; as well as A processor coupled to the memory, the processor being configured to execute the control method for the tunnel boring machine as described in any one of claims 1 to 7 based on instructions stored in the memory.

10. A control system for a tunnel boring machine, comprising: The control device for the tunnel boring machine according to claim 8 or 9; A camera, located on the tunnel boring machine, is used to capture images of the slag discharge from the tunnel boring machine's screw conveyor.

11. The control system according to claim 10, wherein, The camera is pointed towards the slag outlet of the screw conveyor and the belt conveyor and transport system belt.

12. The control system according to claim 10, further comprising: Screw conveyor; and Propulsion system.

13. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the control method for a tunnel boring machine according to any one of claims 1 to 7.

Images