Intelligent anchor rod supporting system

Abstract

The invention discloses an intelligent anchor rod supporting system, and relates to the technical field of safety monitoring. The system mainly comprises a sensing unit, a decision control unit, an execution unit and a communication unit. The sensing unit is used for collecting state parameters of the anchor rod and the surrounding rock; the decision control unit is used for analyzing the sensing data and generating a regulation and control instruction; the execution unit is used for receiving the instruction and automatically adjusting the pre-tightening force of the anchor rod; and the communication unit is connected with each functional unit to form a closed-loop control system. By integrating sensing, decision making and execution functions, real-time monitoring, intelligent analysis and self-adaptive regulation and control of the anchor rod supporting state are achieved, a traditional supporting passive response mode is thoroughly changed, and engineering safety and reliability are greatly improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of safety monitoring, in particular to an intelligent anchor rod supporting system. BACKGROUND

[0002] Anchor rod supporting is a widely used reinforcement technology in geotechnical engineering. The traditional anchor rod supporting system passively bears the load and cannot perceive the changes in its own state and the surrounding rock mass. Its supporting effect is fixed after design and construction and cannot cope with complex and time-varying geological conditions. Supporting failure often occurs suddenly and lacks early warning.

[0003] In recent years, technologies have emerged that install sensors on anchor rods to monitor the stress or deformation of the anchor rods. However, these technologies are mostly limited to monitoring and early warning, and after uploading the data, manual judgment and on-site manual adjustment are still required, which is slow in response speed and cannot form an instant closed loop of perception-decision-execution, has low intelligence, and has not fundamentally solved the problem of active and adaptive supporting.

[0004] Therefore, there is an urgent need in the art for an integrated system that deeply integrates monitoring, decision-making, and execution, can automatically and timely respond to environmental changes, and realizes dynamic optimization of supporting parameters, thereby significantly improving engineering safety and reliability. SUMMARY

[0005] (I) Technical problems solved In view of the shortcomings of the prior art, the present application provides an intelligent anchor rod supporting system, which solves the problem of low reliability of traditional anchor rod supporting.

[0006] (II) Technical solutions To achieve the above purpose, the present application is implemented by the following technical solutions: An intelligent anchor rod supporting system comprises a perception unit, a decision control unit, an execution unit, and a communication unit.

[0007] The perception unit is used to collect state parameters of the anchor rod and the surrounding rock and output perception data. Specifically, the perception unit comprises at least one force sensing module and one displacement sensing module. The force sensing module preferably uses a fiber Bragg grating sensor, which measures strain in a wavelength coding manner, monitors the axial force and shear force of the anchor rod by pasting or embedding in the anchor rod body, and has the advantages of anti-electromagnetic interference and good durability. The displacement sensing module preferably uses a laser ranging sensor or a miniature LVDT displacement sensor, which is installed between the anchor rod pad and the rock wall to monitor the radial displacement change of the surrounding rock surface. The perception unit can also include an inclination sensor and the like to monitor the attitude of the anchor rod.

[0008] The decision control unit is connected with the perception unit through a communication unit, and its core function is to receive and analyze the perception data and generate control instructions based on the analysis results. The unit includes both hardware and software. In terms of hardware, its core is an embedded microprocessor and peripheral circuit. In terms of software, it runs built-in intelligent algorithms.

[0009] The decision control unit has a local control module built-in. The module runs a pre-set threshold judgment algorithm. The algorithm compares the real-time perception data received with the safety threshold pre-stored in the memory.

[0010] If the axial force is less than the minimum threshold, indicating that the pretension is insufficient, the algorithm generates a first control instruction "increase pretension" containing the target pretension value.

[0011] If the displacement is greater than the displacement alarm threshold and the displacement rate continues to increase, the algorithm generates a first control instruction "emergency increase pretension to suppress deformation" for sudden situations.

[0012] At the same time, the decision control unit is equipped with a communication interface module for establishing a connection with a remote cloud platform. The decision control unit packages and uploads the perception data to the cloud platform. The cloud platform aggregates data from multiple anchor rods in the region, conducts big data analysis, and can issue two aspects of content: Second control instruction: for example, based on the analysis of the coordinated stress of the group of anchor rods, instruct the anchor rod at a key position to perform a specific adjustment.

[0013] Strategy model: for example, based on long-term data learning, optimize the new safety threshold or algorithm parameters issued to the local control module, so that the local decision is more accurate.

[0014] The execution unit is connected with the decision control unit through a communication unit, for receiving control instructions and automatically performing adjustment operations on the pretension of the anchor rod. To achieve this function, the execution unit specifically includes an intelligent anchor. The core of the intelligent anchor is a controlled torque output device. It includes a servo motor drive system that receives "increase / decrease" instructions and target torque values from the decision control unit, drives the sleeve to rotate through a reduction mechanism, and accurately tightens or loosens the anchor rod nut, achieving infinite and precise control of the pretension. The execution unit is the last link of the closed-loop control, which converts digital instructions into physical actions.

[0015] The communication unit is a neural network connecting each functional unit in the system. It adopts wired or wireless communication mode to form a data interaction bus inside the system, ensuring low-delay and high-reliability data transmission among the three links of perception, decision-making and execution. At the same time, the communication unit also supports remote data connection with the external cloud platform through the communication interface module of the decision control unit.

[0016] The perception unit, decision control unit and execution unit are interconnected through the communication unit to form a closed-loop control system. The working process of the system is a continuous running "collection-analysis-decision-execution-feedback" cycle until the system reaches and stabilizes at the expected optimal state.

[0017] (Three) beneficial effects The application provides an intelligent anchor rod support system. The following beneficial effects are achieved: I. The complete automatic process from state perception, data analysis to instruction execution is realized, which eliminates the dependence on manual intervention and greatly improves the working efficiency and management level of the support system. The system has a multi-level decision-making mechanism, which can realize millisecond-level rapid response through the local control module and macroscopic optimization analysis through the cloud platform, realizing the coordination and unity of the local and the global.

[0018] II. The system continuously improves the support effect and system performance through continuous learning and optimization. Through comprehensive analysis of multi-parameter data, the system can detect potential safety hazards in advance, realize early warning and active protection, and greatly improve the engineering safety. And using modular design, the system can flexibly configure the number of perception units and execution units according to the engineering needs, supporting large-scale networking applications. DETAILED DESCRIPTION

[0019] Fig. 1 It is the overall architecture diagram of the system of the application; Fig. 2 It is the closed-loop control working process diagram of the system of the application. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the application.

[0021] Embodiment 1: In the tunnel engineering construction, the implementation mode of the system is as follows: Please refer to Figs. 1-2 The application provides a technical solution: An intelligent anchor rod support system includes a perception unit, a decision control unit, an execution unit, and a communication unit. The perception unit is used to collect state parameters of the anchor rod and surrounding rock and output perception data. The perception unit includes multiple functional modules: a force sensing module uses a stress sensing device to monitor the force state of the anchor rod; a displacement sensing module measures the displacement change of the surrounding rock surface through a deformation detection device; and an environmental sensing module collects surrounding rock temperature and humidity parameters through a geological monitoring device. These modules collectively form a multi-parameter perception network to provide comprehensive state monitoring data for the system.

[0022] The decision control unit is connected to the perception unit through the communication unit and includes a local control module and a communication interface module. The local control module has multiple layers of judgment logic: the first layer performs data validity verification, the second layer performs threshold comparison analysis, and the third layer generates control strategies. The communication interface module supports multiple network protocols to enable bidirectional data exchange with a remote cloud platform. The decision control unit uses a weight distribution algorithm to fuse and analyze multiple sensing parameters and generate accurate control instructions based on a pre-set support stability model.

[0023] The execution unit uses an intelligent drive device to adjust the anchor rod pre-tightening force through a torque adjustment mechanism after receiving instructions from the decision control unit. The execution unit includes an action feedback mechanism that returns the execution status to the decision control unit in real time, forming an execution verification closed loop.

[0024] The communication unit uses a multi-mode transmission scheme, with high-speed data exchange within the system through an industrial bus protocol and remote data transmission supported by a wireless communication module for external connection. The communication unit has data priority processing capability to ensure the real-time and reliability of control instructions.

[0025] The perception unit is arranged as follows: intelligent anchor rods are installed at key positions on the tunnel vault and sidewall, with a stress sensing device and a displacement detection device built into each anchor rod. The stress sensing device uses a fiber Bragg grating sensor and is distributed along the anchor rod axis to monitor stress states at different depths. The displacement detection device uses a miniature laser range finder and is installed on the contact surface between the anchor rod tray and the rock wall to monitor the deformation of the surrounding rock in real time.

[0026] The decision control unit needs to be deployed, with a local control station set up in the tunnel and an embedded industrial controller installed as the local control module. The controller has multiple levels of judgment algorithms: the first level filters and verifies the effectiveness of the sensing data; the second level compares real-time data with pre-set thresholds; and the third level generates control instructions based on the comparison results. A 4G / 5G communication module is also provided to establish a connection with the cloud management platform.

[0027] The execution unit adopts an intelligent tightening device driven by a servo motor, which is installed at the outer end of the anchor rod. The device is built-in with a torque sensor and an angle encoder, which can accurately control the application process and final value of the pre-tightening force.

[0028] The communication unit uses industrial Ethernet to connect each unit inside the network, ensuring the real-time nature of data transmission. Wireless communication is used with the cloud to achieve remote monitoring and data management. The perception unit continuously collects anchor rod stress data and surrounding rock displacement data at a sampling frequency of 10 Hz, and the data is transmitted to the decision control unit through the communication unit; The local control module analyzes and processes the data, first verifies the data validity, and eliminates outliers; then compares the stress data with the preset safety threshold range; finally generates the corresponding control instructions according to the deviation degree; if it is found that the stress value of a certain anchor rod is lower than the lower limit of the threshold, an additional pre-tightening force instruction is generated immediately and sent to the execution unit through the communication unit; after receiving the instruction, the execution unit drives the servo motor to rotate the nut, increasing the pre-tightening force to the target value; The perception unit monitors the adjusted state parameters in real time and feeds back the data to the decision control unit, which verifies the adjustment effect. If the expected target is not reached, a new control instruction is generated to continue fine-tuning until the parameters are stable within the ideal range. At the same time, all running data are uploaded to the cloud platform through the communication interface module. The cloud platform comprehensively analyzes the data of multiple anchor rods in the region, evaluates the overall support effect, and issues optimization instructions or updates the judgment parameters of the local control module as necessary.

[0029] Example 2: In slope reinforcement engineering, the implementation of the system is similar to Example 1, but the following special configurations are made according to the characteristics of slope engineering: The perception unit adds an inclination sensor and a rainfall monitoring device to strengthen the monitoring of environmental factors that have a significant impact on slope stability. The decision control unit adds a slope stability analysis model that can combine geological conditions and environmental factors for comprehensive analysis. The execution unit adopts a waterproof and corrosion-resistant design to meet the working requirements of outdoor harsh environments. The communication unit uses a solar-powered wireless transmission scheme to solve the problem of power supply in the slope area.

[0030] It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting; it is not intended to exclude myriad other embodiments of the present application that other inventors can develop based on the same general inventive concepts embodied by the described embodiments. That is, although the present application is described in terms of particular embodiments and implementations, it is to be understood that the terminology used is for the purpose of descriptive clarity and that it should be taken in a descriptive sense and not a limiting sense.

[0031] While the embodiments of the application have been shown and described herein, it is to be understood that the application is not limited to these embodiments. Rather, many modifications, changes, substitutions, and alterations can be made to the embodiments of the application without departing from the spirit and scope of the application as defined by the appended claims and their equivalents.

Claims

1. An intelligent anchor bolt support system, characterized in that, include: The sensing unit is used to collect state parameters of the anchor bolt and surrounding rock and output sensing data. The decision control unit is communicatively connected to the sensing unit and is used to receive and analyze the sensing data, and generate control commands based on the analysis results. The execution unit is communicatively connected to the decision control unit and is used to receive the control command and automatically perform the adjustment operation on the anchor bolt preload. The sensing unit, decision control unit, and execution unit are interconnected through a communication unit to form a closed-loop control system.

2. The intelligent anchor bolt support system according to claim 1, characterized in that, The decision control unit includes: The local control module is used to process the sensed data in real time based on a preset threshold judgment algorithm and generate a first control command. The communication interface module is used to establish a connection with a remote cloud platform and receive a second control command or strategy model issued by the cloud platform.

3. The intelligent anchor bolt support system according to claim 2, characterized in that, The first control command generated by the local control module is used to achieve millisecond-level fast response control; the second control command received by the communication interface module is used to achieve optimized control based on multi-anchor collaboration and macro trend analysis.

4. The intelligent anchor bolt support system according to claim 1, characterized in that, The sensing unit includes a force sensing module for monitoring the force on the anchor bolt and a displacement sensing module for monitoring the deformation of the surrounding rock. The decision control unit is used to comprehensively analyze the coupling change trend of force and displacement and generate corresponding control commands.

5. The intelligent anchor bolt support system according to claim 1, characterized in that, The communication unit adopts wired or wireless communication to form a data interaction bus between the sensing unit, decision control unit and execution unit, and supports remote data connection with external cloud platform.

6. The intelligent anchor bolt support system according to claim 1, characterized in that, The decision control unit continuously receives the adjusted data fed back by the sensing unit, compares the adjusted data with the expected target value, and iteratively generates new control instructions based on the comparison difference until the state parameter reaches and is maintained within the target range.

7. A smart anchor bolt support method based on the system of claim 1, characterized in that, The method includes: Step 1: Continuously collect the state parameters of the anchor bolt support system through the sensing unit; Step 2: Analyze the state parameters using the algorithm model built into the decision control unit to generate decision results; Step 3: Based on the decision results, generate specific control instructions; Step 4: The control command is executed by the execution unit to automatically adjust the anchor bolt support parameters; Step 5: Collect the adjusted data through the sensing unit and feed it back to the decision control unit to form a closed-loop control flow.

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