A TBM belt conveyor machine slag discharge control device and method based on multi-parameter analysis

Abstract

The application relates to the technical field of TBM construction, and discloses a TBM belt conveyor slag discharging control device and method based on multi-parameter analysis. The device aims to solve the technical problems that in the prior art, a single parameter is used to judge the surrounding rock state, so that the misjudgment rate is high, the adjustment hysteresis is strong, and the tunneling parameters and the slag discharging parameters lack collaborative linkage, so that it is difficult to consider the slag discharging efficiency and the equipment operation safety under complex and changeable geological conditions. The application comprises a data processor, a signal input end of the data processor is connected with an edge terminal and a rock slag state analysis component, and a signal output end of the data processor is connected with a feedback and early warning component. The application achieves safe, efficient and controllable operation of the belt conveyor operation state, reduces the accident occurrence rate of the belt conveyor and improves the work efficiency, and has high engineering application value.

Description

Technical Field

[0001] This invention relates to the field of TBM construction technology, and in particular to a TBM belt conveyor slag discharge control device and method based on multi-parameter analysis. Background Technology

[0002] TBM tunneling machines have been gradually introduced into tunnel construction due to their high tunneling efficiency, safety, and excellent adaptability to mountain tunnels. However, they also face a series of problems that need to be solved, especially in tunnel construction under high altitude and deep burial conditions. Due to the limitations of current technology, geological exploration, and surrounding rock monitoring, the muck removal of TBM belt conveyors has always relied on manual control, which is an important factor affecting the tunneling efficiency of TBM tunneling machines.

[0003] Studies have shown that during TBM construction, different types of surrounding rock result in variations in the composition, particle size, and output of the excavated material. In other words, the characteristics of the excavated material correspond to certain quality indicators of the surrounding rock, and the type of surrounding rock can be reflected by the properties of the excavated material. For example, in relatively intact surrounding rock, the rock debris in the excavated material is mostly or entirely flaky with a relatively uniform particle size; when discontinuous surfaces are well-developed and affected by tectonic activity or located in fault fracture zones, the rock debris is mostly or entirely blocky with significant particle size variations.

[0004] Faced with unknown geological conditions, sudden changes in the amount of rock debris significantly impact tunneling efficiency when the surrounding rock conditions change abruptly. Furthermore, if not addressed promptly, this can lead to a series of malfunctions such as conveyor belt failure and motor overload. Research on current technologies reveals that the technique of using rock debris volume to infer the geological conditions ahead is relatively mature; what is lacking is a comprehensive analysis of the surrounding rock condition and tunneling parameters.

[0005] To address the above issues, and in conjunction with existing technologies, this study analyzes the rock and slag conditions of TBMs in different geological formations and tunneling parameters. A multi-parameter analysis-based intelligent control system for TBM belt conveyor slag removal has been developed, which can effectively solve the problems of TBM slag removal efficiency and safety. Summary of the Invention

[0006] In view of the above technical problems, this disclosure provides a TBM belt conveyor slag discharge control device and method based on multi-parameter analysis, which solves the technical problems in the prior art that rely on a single parameter to judge the surrounding rock condition, resulting in a high misjudgment rate and strong adjustment lag, as well as the lack of coordination between tunneling parameters and slag discharge parameters, making it difficult to balance slag discharge efficiency and equipment operation safety under complex and variable geological conditions.

[0007] According to one aspect of this disclosure, a TBM belt conveyor slag discharge control device based on multi-parameter analysis is provided, including a data processor, wherein the signal input terminal of the data processor is connected to an edge terminal and a rock slag state analysis component, and the signal output terminal of the data processor is connected to a feedback and early warning component. The edge terminal is deployed in the TBM main control room and communicates with the TBM's PLC control system. It is used to collect tunneling parameters and belt conveyor parameters related to the amount of slag discharged and to send control commands to the PLC control system. The rock slag condition analysis component is installed above the belt conveyor and is used to collect image information and / or three-dimensional information of the rock slag on the belt conveyor in real time to obtain the particle size and shape characteristics of the rock slag. The data processor is used to receive and store the collected parameters and rock debris characteristic data, determine the current surrounding rock state based on the data, and generate adjustment commands for the belt conveyor speed according to the feedback control principle, which are then sent to the PLC control system of the TBM through the edge terminal. In some embodiments of this disclosure, the feedback and warning component is used to issue an alarm signal when an abnormal operating condition is detected.

[0008] In some embodiments of this disclosure, the tunneling parameters and conveyor parameters include active parameters and passive parameters; the active parameters include the set value of the propulsion speed, the set value of the cutterhead rotation speed, and the set value of the conveyor speed; the passive parameters include the actual value of the propulsion speed, the actual value of the cutterhead rotation speed, the actual value of the conveyor speed, the forward rotation pressure of the conveyor, the total thrust, and the cutterhead torque.

[0009] In some embodiments of this disclosure, the rock debris condition analysis component includes a laser scanner and an industrial camera, used to acquire the particle size distribution and shape characteristics of the rock debris, and to assist in judging the condition of the surrounding rock based on the correspondence between the shape of the rock debris and the integrity of the rock mass.

[0010] In some embodiments of this disclosure, the control logic executed by the data processor is as follows: using the cutterhead rotation speed, the feed speed, and the belt conveyor speed as input parameters; using the real-time cutterhead rotation speed, the feed speed, the total thrust, and the cutterhead torque as correction variables; using the belt conveyor forward rotation pressure and the rock slag particle size as feedback quantities; and using a feedback control algorithm to adjust the belt conveyor speed in real time so that the belt conveyor rotation speed matches the slag discharge under the current surrounding rock condition.

[0011] A method for controlling slag discharge from a TBM belt conveyor based on multi-parameter analysis includes the following steps: S1 Real-time Data Acquisition and Monitoring: During the tunneling process, tunneling parameters and rock debris status information are acquired in real time; the tunneling parameters include at least the total thrust F, cutterhead torque T, cutterhead radius R, and rock-soil friction coefficient μ. The relationship between total thrust and torque satisfies the following formula: ; S2 Surrounding Rock Condition Judgment: Based on the changing trends of the tunneling parameters and the information on the rock debris condition, the current surrounding rock condition is determined; simultaneously, the speed of the belt conveyor is adjusted according to the current surrounding rock condition; in the muck removal of the belt conveyor, its muck removal efficiency is mainly related to the belt conveyor speed, and the corresponding relationship is as follows: ; In the formula, Q: transport volume; v: belt speed; A: cross-sectional area of ​​rock debris; ρ: density of rock debris; The amount of slag discharged is controlled by adjusting the speed of the belt conveyor; S3 Multi-parameter Coordinated Adjustment: Based on the current surrounding rock condition, the cutterhead speed, feed speed and belt conveyor speed are dynamically adjusted to achieve a balance between slag removal efficiency and equipment safety. S4 Feedback Control and Parameter Optimization: Continuously monitor the tunneling parameters and rock debris status information, and iteratively correct each adjustment parameter in step c based on real-time changes using the feedback control principle.

[0012] In some embodiments of this disclosure, step b, determining the current surrounding rock condition, specifically includes: When the total thrust F decreases, the cutterhead torque T increases suddenly and fluctuates, and the rock debris changes from intact to broken, it is determined that the surrounding rock has changed from intact to broken.

[0013] In some embodiments of this disclosure, the dynamic adjustment in step c specifically includes: In response to the judgment that the surrounding rock condition has changed from intact to fractured, the system issues an instruction to perform the following operations: increase the belt conveyor speed while decreasing the cutter head speed and the feed speed.

[0014] In some embodiments of this disclosure, the determination of the current surrounding rock state in step b further includes: When the total thrust F increases while the cutterhead torque T remains unchanged or decreases, the current surrounding rock condition is determined to be hard.

[0015] In some embodiments of this disclosure, the feedback control principle in step d is specifically as follows: the set parameters include the cutterhead rotation speed setpoint, the propulsion speed setpoint, and the belt conveyor speed setpoint; the correction variables include the real-time cutterhead rotation speed, the real-time propulsion speed, the real-time total thrust, and the real-time cutterhead torque; the feedback signal includes at least the belt conveyor forward rotation pressure and the slag particle size; the system adjusts the correction variables according to the deviation between the feedback signal and the set parameters.

[0016] In some embodiments of this disclosure, a warning step e is also included: When the monitored current situation exceeds the system's preset processing capacity, an early warning mechanism is triggered to remind staff to intervene; the early warning mechanism includes near-end audible and visual alarms and sending early warning information to the remote monitoring system.

[0017] Step f: Abnormal event cases during the tunneling process are collected and reported to optimize the system's control logic.

[0018] The beneficial effects of this invention are as follows: This invention, through the collection and processing of rock debris data, understands the real-time status of the surrounding rock ahead. By collecting and analyzing relevant tunneling parameters and belt conveyor parameters related to rock debris, its correlation is derived. The operating status is adjusted in real time through these control parameters to ensure that the belt conveyor is in a safe and efficient operating state. Through early warning, emergency control, and case collection, the safety and controllability of the equipment are guaranteed, and the system is continuously improved. This achieves safe, efficient, and controllable operation of the belt conveyor, reduces the accident rate of the belt conveyor, and improves work efficiency, thus having high engineering application value.

[0019] To achieve accurate identification of the surrounding rock condition, a multi-parameter fusion mechanism for surrounding rock condition identification was established by integrating tunneling parameters, total thrust, cutterhead torque collected from the edge terminal, and rock debris particle size and shape characteristics obtained from the rock debris condition analysis component. Compared with traditional methods that rely solely on a single tunneling parameter, this mechanism can more accurately and promptly identify the transition of the surrounding rock from intact to fractured or from fractured to intact, providing a reliable decision-making basis for subsequent control.

[0020] To ensure a dynamic balance between muck removal efficiency and equipment safety, the system coordinates and adjusts multiple parameters, including cutterhead speed, feed rate, and conveyor speed, based on real-time assessment of the surrounding rock conditions. For example, when rock fracturing leads to a sudden increase in muck output, the system automatically increases the conveyor speed to improve muck removal efficiency while simultaneously reducing the cutterhead speed and feed rate to decrease the amount of muck produced per unit time. This effectively prevents conveyor overload, muck slippage, or blockage, achieving optimal matching between tunneling efficiency and equipment safety.

[0021] Equipped with closed-loop feedback control and adaptive optimization capabilities, the system incorporates closed-loop control logic using conveyor belt rotation pressure and excavated soil particle size as feedback signals. Based on the deviation between real-time feedback signals and set parameters, the system automatically and iteratively corrects control parameters such as conveyor belt speed, ensuring the equipment constantly adapts to dynamically changing surrounding rock geological conditions. This significantly enhances the automation and intelligence level of the TBM tunneling system.

[0022] A comprehensive multi-level early warning and safety assurance system has been established. By setting up feedback and early warning components, this disclosure can simultaneously trigger audible and visual alarms at the local end and send early warning information to the remote monitoring system when the system detects abnormal parameters or exceeds its processing capacity, achieving dual monitoring at both the local and remote ends. This buys valuable time for operators to intervene in a timely manner and take emergency braking measures, effectively preventing major equipment failures and safety accidents.

[0023] Equipped with data accumulation and self-learning capabilities, the system collects, reports, and stores abnormal event cases during tunneling, providing a data foundation for continuous optimization of the system's control logic. As the case library grows, the system's accuracy in identifying abnormal events and its control response speed will be further improved, enabling continuous evolution and self-improvement of the equipment. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the slag discharge control device for a TBM belt conveyor based on multi-parameter analysis. Detailed Implementation

[0025] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention. Example 1

[0026] This example discloses a slag discharge control device and method for a TBM belt conveyor based on multi-parameter analysis. (See also...) Figure 1 It includes a data processor, whose signal input end is connected to the edge terminal and the rock slag condition analysis component, and whose signal output end is connected to the feedback and early warning component. The edge terminal is deployed in the TBM main control room and communicates with the TBM's PLC control system. It is used to collect tunneling parameters and belt conveyor parameters related to the amount of slag discharged and send control commands to the PLC control system. The rock slag condition analysis component is installed above the belt conveyor to collect image and / or three-dimensional information of the rock slag on the belt conveyor in real time, so as to obtain the particle size and shape characteristics of the rock slag. The data processor is used to receive and store the collected parameters and rock debris characteristic data, determine the current surrounding rock condition based on the data, and generate adjustment commands for the belt conveyor speed according to the feedback control principle, which are then sent to the PLC control system of the TBM through the edge terminal. The feedback and early warning component is used to issue an alarm signal when abnormal operating conditions are detected.

[0027] The tunneling parameters and conveyor parameters include active parameters and passive parameters; active parameters include the set values ​​for propulsion speed, cutterhead rotation speed, and conveyor speed; passive parameters include the actual values ​​for propulsion speed, cutterhead rotation speed, and conveyor speed, as well as the forward rotation pressure of the conveyor, total thrust, and cutterhead torque.

[0028] The rock debris condition analysis component includes a laser scanner and an industrial camera, which are used to acquire the particle size distribution and shape characteristics of rock debris, and to assist in judging the condition of the surrounding rock based on the correspondence between the shape of rock debris and the integrity of the rock mass.

[0029] The control logic executed by the data processor is as follows: the cutterhead rotation speed, the feed speed, and the belt conveyor speed are used as input parameters; the real-time cutterhead rotation speed, feed speed, total thrust, and cutterhead torque are used as correction variables; the belt conveyor forward rotation pressure and rock slag particle size are used as feedback quantities; and the feedback control algorithm is used to adjust the belt conveyor speed in real time so that the belt conveyor rotation speed matches the slag discharge rate under the current surrounding rock conditions.

[0030] A method for controlling slag discharge from a TBM belt conveyor based on multi-parameter analysis includes the following steps: S1 Real-time Data Acquisition and Monitoring: During the tunneling process, tunneling parameters and rock debris status information are acquired in real time; tunneling parameters include at least total thrust F, cutterhead torque T, cutterhead radius R, and soil-rock friction coefficient μ; The relationship between total thrust and torque satisfies the following formula:

[0031] S2 Surrounding Rock Condition Judgment: Based on the changing trends of tunneling parameters and combined with rock and slag condition information, the current surrounding rock condition is determined; simultaneously, the speed of the belt conveyor is adjusted according to the current surrounding rock condition; in belt conveyor slag removal, its slag removal efficiency is mainly related to the belt conveyor speed, and the corresponding relationship is as follows:

[0032] In the formula, Q: transport volume; v: belt speed; A: cross-sectional area of ​​rock debris; ρ: density of rock debris; The amount of slag discharged is controlled by adjusting the speed of the belt conveyor; S3 Multi-parameter Coordinated Adjustment: Based on the current surrounding rock condition, the cutterhead speed, feed speed and belt conveyor speed are dynamically adjusted to achieve a balance between slag removal efficiency and equipment safety. S4 Feedback Control and Parameter Optimization: Continuously monitor tunneling parameters and rock debris status information, and iteratively correct each adjustment parameter in step c based on real-time changes using the feedback control principle.

[0033] Step b, determining the current surrounding rock condition, specifically includes: When the total thrust F decreases, the cutterhead torque T increases suddenly and fluctuates, and the rock debris changes from intact to broken, it is determined that the surrounding rock has changed from intact to broken.

[0034] The dynamic adjustment in step c specifically includes: In response to the judgment that the surrounding rock condition has changed from intact to fractured, the system issues an instruction to perform the following operations: increase the belt conveyor speed while decreasing the cutter head speed and feed rate.

[0035] Step b, determining the current surrounding rock condition, also includes: When the total thrust F increases while the cutterhead torque T remains unchanged or decreases, the current surrounding rock condition is determined to be hard.

[0036] The feedback control principle in step d is as follows: the set parameters include the cutterhead rotation speed setpoint, the propulsion speed setpoint, and the belt conveyor speed setpoint; the correction variables include the real-time cutterhead rotation speed, the real-time propulsion speed, the real-time total thrust, and the real-time cutterhead torque; the feedback signals include at least the belt conveyor forward rotation pressure and the slag particle size; the system adjusts the correction variables according to the deviation between the feedback signals and the set parameters.

[0037] It also includes warning step e: When the monitored current situation exceeds the system's preset processing capacity, an early warning mechanism is triggered to remind staff to intervene. The early warning mechanism includes near-end audible and visual alarms and sending early warning information to the remote monitoring system.

[0038] Step f: Abnormal event cases during the tunneling process are collected and reported to optimize the system's control logic.

[0039] The purpose of this invention is to provide an intelligent control system for slag discharge of a TBM belt conveyor based on multi-parameter analysis through integrated analysis of multiple parameters.

[0040] The present invention achieves the above objectives through the following technical solutions: A smart control system for slag discharge from a TBM belt conveyor based on multi-parameter analysis includes: Edge terminals for TBM tunneling data acquisition and interaction: Deployed in the TBM main control room, they communicate with the TBM's PLC control system, collect relevant TBM tunneling data for data analysis, and serve as a carrier for subsequent parameter control. The main data they collect are tunneling parameters related to the amount of slag removed, belt conveyor parameters, and corresponding control parameters.

[0041] The TBM PLC control module, as the control system of the TBM itself, determines the operating status of various TBM devices and connects to the edge terminal, providing a port for data acquisition and control.

[0042] The edge terminal primarily collects tunneling parameters, conveyor belt parameters, and corresponding control parameters related to the slag discharge volume. Table 1 below shows the main parameters involved:

[0043] Among them, the active parameters are used as control parameters, and their values ​​determine the given state of the corresponding device. The passive parameters are used as display parameters, which indicate the current operating state of the corresponding device. It is important to emphasize here that another function of the edge terminal is to connect with the TBM PLC control module and send commands to the aforementioned active parameters to enable the system to control various parts of the TBM.

[0044] It should be emphasized that those skilled in the art should understand that, under normal operating conditions, the operating power of the conveyor belt and the amount of slag discharged from the TBM are related to the current surrounding rock conditions, as well as the propulsion speed and the cutterhead rotation speed.

[0045] TBM belt conveyor slag discharge information acquisition and analysis device for rock slag condition analysis: This device utilizes relatively mature existing technologies, combining laser scanners with industrial cameras to acquire rock slag information. Details will not be repeated here, but those skilled in the art can refer to existing technologies for specific understanding. This device can clearly obtain the condition of rock slag for subsequent correlation analysis.

[0046] It should be emphasized again that those skilled in the art can judge the surrounding rock condition by the shape and particle size of the rock fragments. The specific comparison is shown in Table 2:

[0047] Data processors used for data analysis, processing, and storage: They mainly serve as carriers for extracting, cleaning, analyzing, and issuing control commands for historical data. No specific performance requirements are placed on them; servers with high data processing and storage capabilities on the market can meet their actual needs.

[0048] Data collected through edge terminals and conveyor belt muck information acquisition devices is stored on a server. It is categorized according to the particle size of the conveyor belt muck, and the variation patterns of various parameters under different muck conditions are analyzed. Feedback control is primarily used for data control here. The cutterhead rotation speed, feed speed, and conveyor speed are used as input parameters; the cutterhead rotation speed, feed speed, total thrust, and cutterhead torque are used as correction variables; the conveyor rotation speed is used as the output variable; and the conveyor forward pressure and conveyor muck particle size are used as feedback control quantities. The conveyor speed is adjusted in real time to identify their corresponding relationships and determine the appropriate tunneling parameters and conveyor speed for different surrounding rock conditions. Reasonable adjustment of the conveyor speed ensures safe and efficient operation.

[0049] Feedback and early warning devices for early warning, emergency control, and case collection: Their main function is to promptly alert relevant personnel to take emergency measures when the current situation exceeds the system's processing capacity. This is achieved primarily through two methods: audible and visual alarms and information sent via a remote monitoring system. These methods address real-time monitoring and early warning of system operation from both near and far ends, ensuring the system remains in a safe and controllable state at all times. Simultaneously, they collect and report abnormal event cases, continuously improving the system itself.

[0050] The core of this invention is an intelligent control system for slag discharge of a TBM belt conveyor based on multi-parameter analysis. By analyzing data related to the slag discharge volume, it achieves flexible control of the belt conveyor, enabling efficient, safe, and stable operation of the conveyor.

[0051] Please refer to Figure 1 , Figure 1 This is a schematic diagram of the structure of an intelligent control system for slag discharge of a TBM belt conveyor based on multi-parameter analysis, which clearly shows the composition of the system.

[0052] This invention provides an intelligent slag discharge system for TBM belt conveyors based on multi-parameter analysis, comprising an edge acquisition device, a belt conveyor slag discharge information acquisition device, a system operation carrier server, and a feedback device. Its main feature is a belt conveyor slag discharge control system based on feedback control principle deployed on the server.

[0053] In this system, the conveyor belt slag discharge information acquisition device is mainly used to collect rock slag information and determine the rock slag particle size, providing basic information for surrounding rock analysis. This technology utilizes existing mature technologies and can identify the rock slag particle size through laser scanning technology and image segmentation principles, and use this as a basis to analyze the surrounding rock conditions ahead. Meanwhile, based on the tunneling parameters, the condition information of the surrounding rock was verified from the side. During tunneling, the relationship between total thrust and torque is as follows:

[0054] (T: Torque; F: Thrust; R: Cutterhead radius; μ: Coefficient of friction between rock and soil) Changes in torque and total thrust reflect changes in the surrounding rock. A decrease in total thrust and a sudden increase in torque indicate that the surrounding rock is relatively fragmented. An increase in total thrust and a constant or decreasing torque indicate that the surrounding rock is relatively hard.

[0055] Based on the above principles, in the actual tunneling process, by analyzing the current state of the rock debris and the tunneling parameters, the current state of the surrounding rock can be determined, and the speed of the belt conveyor can be adjusted according to the current state of the surrounding rock.

[0056] It should be noted that the slag discharge efficiency of a belt conveyor is mainly related to the belt conveyor speed, and the corresponding relationship is as follows:

[0057] (Q: Transport volume; v: Belt speed; A: Cross-sectional area of ​​rock debris; ρ: Density of rock debris) The slag discharge efficiency of a belt conveyor is positively correlated with the belt conveyor speed. In actual control, the slag discharge amount can be controlled by adjusting the belt conveyor speed. The following example illustrates the system's operation by showing the surrounding rock condition changing from intact to broken during tunneling: When the surrounding rock condition changes from intact to broken, the first reaction should be a decrease in total thrust and an increase in cutterhead torque, exhibiting fluctuations, as seen in the data collected by the edge terminal. At this time, the rock debris identification device can observe that the rock debris condition has changed from intact to broken. Based on these factors, the system will determine that the surrounding rock condition has changed from intact to broken. To ensure a dynamic balance between slag removal efficiency and equipment safety, the system will send commands through the edge terminal to increase the cutterhead rotation speed, advance speed, and belt conveyor rotation speed, thereby increasing the belt conveyor speed while decreasing the cutterhead rotation speed and advance speed to ensure slag removal efficiency and prevent blockage. Meanwhile, the system will continuously monitor the state of the rock debris and the changes in parameters such as total thrust and cutterhead torque, and continuously adjust the parameters according to the real-time situation. In this process, the principle of feedback control is mainly adopted: The parameters to be set are: cutter head rotation speed (RPM), feed speed (mm / min), and belt conveyor speed (m / s). The corrected variables are: real-time cutterhead rotational speed, feed rate, total thrust (kN), and cutterhead torque (kN·m). The feedback signals are: conveyor belt forward rotation pressure (MPa) and slag particle size (mm). Meanwhile, a feedback and early warning device has been added. Its main function is to promptly remind relevant personnel to take emergency braking when the current situation exceeds the system's processing capacity. It mainly uses two methods: sound and light alarm devices and information sent by the remote monitoring system to provide prompts. This solves the problem of real-time monitoring and early warning of the system's operating status at both the near and far ends, ensuring that the system is always in a safe and controllable state. At the same time, it collects and reports abnormal event cases to continuously improve the system itself.

[0058] Although some preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0059] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this application and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A slag discharge control device for a TBM belt conveyor based on multi-parameter analysis, characterized in that: It includes a data processor, the signal input terminal of which is connected to an edge terminal and a rock slag condition analysis component, and the signal output terminal of which is connected to a feedback and early warning component; The edge terminal is deployed in the TBM main control room and communicates with the TBM's PLC control system. It is used to collect tunneling parameters and belt conveyor parameters related to the amount of slag discharged and to send control commands to the PLC control system. The rock slag condition analysis component is installed above the belt conveyor and is used to collect image information and / or three-dimensional information of the rock slag on the belt conveyor in real time to obtain the particle size and shape characteristics of the rock slag. The data processor is used to receive and store the collected parameters and rock debris characteristic data, determine the current surrounding rock state based on the data, and generate adjustment commands for the belt conveyor speed according to the feedback control principle, which are then sent to the PLC control system of the TBM through the edge terminal. The feedback and early warning component is used to issue an alarm signal when an abnormal operating condition is detected.

2. The TBM belt conveyor slag discharge control device based on multi-parameter analysis as described in claim 1, characterized in that: The tunneling parameters and conveyor parameters include active parameters and passive parameters; the active parameters include the set values ​​for propulsion speed, cutterhead rotation speed, and conveyor speed; the passive parameters include the actual values ​​for propulsion speed, cutterhead rotation speed, and conveyor speed, the forward rotation pressure of the conveyor, the total thrust, and the cutterhead torque.

3. The TBM belt conveyor slag discharge control device based on multi-parameter analysis as described in claim 1, characterized in that: The rock debris condition analysis component includes a laser scanner and an industrial camera, used to acquire the particle size distribution and shape characteristics of the rock debris, and to assist in judging the condition of the surrounding rock based on the correspondence between the shape of the rock debris and the integrity of the rock mass.

4. The TBM belt conveyor slag discharge control device based on multi-parameter analysis as described in claim 1, characterized in that: The control logic executed by the data processor is as follows: the cutterhead rotation speed, the feed speed, and the belt conveyor speed are used as input parameters; the real-time cutterhead rotation speed, the feed speed, the total thrust, and the cutterhead torque are used as correction variables; and the belt conveyor forward rotation pressure and the rock slag particle size are used as feedback quantities. A feedback control algorithm is used to adjust the belt conveyor speed in real time so that the belt conveyor speed matches the slag discharge rate under the current surrounding rock conditions.

5. A method for controlling slag discharge from a TBM belt conveyor based on multi-parameter analysis, characterized in that, Includes the following steps: S1 Real-time Data Acquisition and Monitoring: During the tunneling process, tunneling parameters and rock debris status information are acquired in real time; the tunneling parameters include at least the total thrust F, cutterhead torque T, cutterhead radius R, and rock-soil friction coefficient μ. The relationship between total thrust and torque satisfies the following formula: ; S2 Surrounding Rock Condition Judgment: Based on the changing trends of the tunneling parameters and the information on the rock debris condition, the current surrounding rock condition is determined; simultaneously, the speed of the belt conveyor is adjusted according to the current surrounding rock condition; in the muck removal of the belt conveyor, its muck removal efficiency is mainly related to the belt conveyor speed, and the corresponding relationship is as follows: ; In the formula, Q represents the transportation volume; v: belt speed; A: cross-sectional area of ​​rock debris; ρ: density of rock debris; The amount of slag discharged is controlled by adjusting the speed of the belt conveyor; S3 Multi-parameter Coordinated Adjustment: Based on the current surrounding rock condition, the cutterhead speed, feed speed and belt conveyor speed are dynamically adjusted to achieve a balance between slag removal efficiency and equipment safety. S4 Feedback Control and Parameter Optimization: Continuously monitor the tunneling parameters and rock debris status information, and iteratively correct each adjustment parameter in step c based on real-time changes using the feedback control principle.

6. The TBM belt conveyor slag discharge control method based on multi-parameter analysis as described in claim 5, characterized in that: The determination of the current surrounding rock state in step b specifically includes: when the total thrust F decreases, the cutterhead torque T increases suddenly and fluctuates, and the rock debris state changes from intact to broken, the surrounding rock state is determined to change from intact to broken; the determination of the current surrounding rock state in step b also includes: when the total thrust F increases, the cutterhead torque T remains unchanged or decreases, the current surrounding rock state is determined to be hard.

7. The TBM belt conveyor slag discharge control method based on multi-parameter analysis as described in claim 5, characterized in that: The dynamic adjustment described in step c specifically includes: in response to the judgment that the surrounding rock condition changes from intact to broken, the system issues an instruction to perform the following operations: increase the belt conveyor speed while decreasing the cutter head speed and the feed speed.

8. The TBM belt conveyor slag discharge control method based on multi-parameter analysis as described in claim 5, characterized in that: The feedback control principle described in step d is as follows: the set parameters include the cutterhead rotation speed setpoint, the propulsion speed setpoint, and the belt conveyor speed setpoint; the correction variables include the real-time cutterhead rotation speed, the real-time propulsion speed, the real-time total thrust, and the real-time cutterhead torque; the feedback signals include at least the belt conveyor forward rotation pressure and the slag particle size; the system adjusts the correction variables according to the deviation between the feedback signals and the set parameters.

9. The TBM belt conveyor slag discharge control method based on multi-parameter analysis as described in claim 5, characterized in that: It also includes an early warning step e: when the monitored current situation exceeds the system's preset processing capacity, an early warning mechanism is triggered to remind staff to intervene; the early warning mechanism includes near-end audible and visual alarms and sending early warning information to the remote monitoring system; Step f: Collect and report abnormal event cases during the tunneling process to optimize the system's control logic.

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