Multi-source information advanced grouting reinforcement intelligent device and effect evaluation method

Abstract

The invention discloses a multi-source information advanced grouting reinforcement intelligent device and an effect evaluation method, the device comprises a sensor module, a data acquisition module and a control unit, the sensor module is used for acquiring multi-source information data in a grouting process; the data acquisition module is used for integrating and synchronizing data acquired by the sensor module to ensure the accuracy and consistency of the data; the control unit is used for monitoring, analyzing and processing data in real time, comprehensively evaluating the data through a machine learning algorithm and a data fusion algorithm, generating a grouting scheme and adjusting grouting parameters in real time so as to ensure the stability and reliability of the reinforcement effect. Through comprehensive monitoring and evaluation of the construction process and the reinforcement effect, unnecessary reinforcement repetition and adjustment are avoided, the construction cost and material waste are reduced, problems can be found in time, corresponding adjustment is made, and the construction efficiency is improved.

Description

Technical Field

[0001] The invention belongs to the field of underground construction engineering, and relates to an intelligent device and method which can integrate multiple information sources, perform advance grouting reinforcement on underground engineering and accurately evaluate the reinforcement effect. Background Art

[0002] In underground construction, such as tunnels and mines, various geological disasters are often encountered due to complex geological conditions, such as groundwater leakage, stratum sliding, rock burst, etc. These disasters not only affect the progress of the project, but also may pose a threat to personnel safety. Therefore, how to effectively prevent and control these geological disasters is an important issue in underground construction projects.

[0003] At present, the commonly used prevention and control methods mainly include advance grouting reinforcement, prestressed anchoring, support structure design, etc. Among them, advance grouting reinforcement is a commonly used method, which injects slurry with certain strength and durability into the formation to improve the physical and mechanical properties of the formation and increase the bearing capacity of the formation, so as to achieve the purpose of preventing and controlling geological disasters. However, there are some problems with the traditional advance grouting reinforcement method, such as the difficulty in accurately evaluating the effect of advance grouting, and the possibility of slurry loss and uneven slurry distribution during the advance grouting process.

[0004] In recent years, with the development of information technology, the application of intelligent devices in various fields has become more and more extensive. However, most of the intelligent devices on the market currently operate based on a single information source, such as pre-grouting reinforcement based only on geological radar data, or pre-grouting reinforcement based only on pressure sensor data. This single information source operation mode often cannot fully and accurately evaluate the stability of underground buildings, nor can it effectively solve the problems of traditional pre-grouting reinforcement methods.

[0005] Therefore, it is necessary to develop an intelligent device and method that can integrate multiple information sources, perform advance grouting reinforcement on underground projects, and accurately evaluate the reinforcement effect. Summary of the invention

[0006] In order to solve the problems existing in the traditional advance grouting reinforcement method and the limitations of the prior art, the present invention provides an advance grouting reinforcement intelligent device with multi-source information and an effect evaluation method.

[0007] The objective of the present invention is achieved through the following technical solutions:

[0008] An intelligent device for advanced grouting reinforcement with multi-source information, comprising a sensor module, a data acquisition module and a control unit, wherein:

[0009] The sensor module is installed on the advance grouting pipeline and is used to collect multi-source information data during the grouting process, including the geological conditions within the grouting range, the sound wave propagation speed of the rock, the displacement change of the tunnel structure, the change of the temperature inside the tunnel after grouting, the change of the humidity inside the tunnel after grouting, and the total pressure on the grouting section during the grouting process;

[0010] The data acquisition module is used to integrate and synchronize the data collected by the sensor module to ensure the accuracy and consistency of the data;

[0011] The control unit is used to monitor, analyze and process data in real time, conduct a comprehensive evaluation of the data through machine learning algorithms and data fusion algorithms, generate a grouting plan and adjust the grouting parameters in real time to ensure the stability and reliability of the reinforcement effect.

[0012] A method for evaluating the effect of advance grouting reinforcement using the above-mentioned intelligent device comprises the following steps:

[0013] Step S1: Install and start the sensor module to collect multi-source information data of the formation during the grouting process;

[0014] Step S2: Transmitting the data collected by the sensor module to the data acquisition module for integration and synchronization processing;

[0015] Step S3: using machine learning algorithms and data fusion algorithms to comprehensively analyze and evaluate the data to identify the formation state;

[0016] Step S4: Generate a grouting plan based on the analysis results, and adjust the grouting parameters in real time to ensure the reinforcement effect;

[0017] Step S5: Perform grouting reinforcement operation according to the generated grouting scheme and monitor the grouting process in real time;

[0018] Step S6: continuously monitor the formation status and evaluate the reinforcement effect using sensor data;

[0019] Step S7: Propose improvement suggestions based on the evaluation results to configure a more reasonable grouting fluid, improve grouting efficiency, enhance reinforcement effect and reduce costs.

[0020] Compared with the prior art, the present invention has the following advantages:

[0021] 1. By integrating a variety of sensor devices, it is possible to achieve comprehensive monitoring of the ground state during underground construction, including information on geological characteristics, groundwater level, structural displacement, temperature, humidity and other aspects.

[0022] 2. The use of intelligent algorithms to conduct comprehensive analysis and evaluation of multi-source information data can more comprehensively and accurately evaluate the grouting reinforcement effect, including the stability, density and stress conditions of the reinforced structure.

[0023] 3. The control unit monitors the data in real time and adjusts the reinforcement plan and parameters according to the evaluation results, so that the reinforcement effect can be optimized and adjusted in real time, improving the construction efficiency and the stability of the reinforcement effect, thereby improving the safety and reliability of the construction process.

[0024] 4. Through comprehensive monitoring and evaluation of the construction process and reinforcement effects, unnecessary reinforcement duplication and adjustment can be avoided, construction costs and material waste can be reduced, problems can be discovered in a timely manner and corresponding adjustments can be made, thus improving construction efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a schematic diagram of the use of the advanced grouting reinforcement intelligent device in the present invention;

[0026] Figure 2 It is a schematic diagram of the grouting pipe structure of the advanced grouting reinforcement intelligent device in the present invention;

[0027] Figure 3 It is a schematic diagram of the fixed support of the geological radar in the present invention;

[0028] Figure 4 It is a schematic diagram of the data acquisition module functional block in the present invention;

[0029] Figure 5 This is a functional schematic diagram of a control unit in the present invention;

[0030] Figure 6 It is a schematic diagram of the reinforcement effect evaluation process in the present invention;

[0031] Explanation of the marks in the figure: 1: grouting pipe, 101: grouting hole, 102: grouting liquid delivery pipe, 103: transmission cable, 104: sliding protrusion; 201: geological radar, 202: ultrasonic wave velocity tester, 203: displacement monitoring sensor, 204: temperature sensor, 205: humidity sensor, 206: grouting pressure gauge; 3: data acquisition module; 4: control unit; 5: grouting control device; 6: geological radar support, 601: support inner sleeve with groove, 602: bearing, 603: support outer sleeve, 604: fixed support, 605: rotating shaft. DETAILED DESCRIPTION

[0032] The technical solution of the present invention is further described below in conjunction with the accompanying drawings, but is not limited thereto. Any modification or equivalent replacement of the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention should be included in the protection scope of the present invention.

[0033] The present invention provides an intelligent device for pre-grouting reinforcement with multi-source information, such as Figure 1 As shown, the device includes a sensor module 2, a data acquisition module 3 and a control unit 4.

[0034] like Figure 2 As shown, the sensor module 2 is installed on the grouting pipe 1, including a geological radar 201, an ultrasonic wave velocity tester 202, a displacement monitoring sensor 203, a temperature sensor 204, a humidity sensor 205, and a grouting pressure gauge 206, which are used to collect multi-source information data during the grouting process, including the geological conditions within the grouting range, the sound wave propagation velocity of the rock, the displacement change of the tunnel structure, the change of the temperature inside the tunnel after grouting, the change of the humidity inside the tunnel after grouting, and the total pressure on the grouting section during the grouting process. Among them:

[0035] The geological radar 201 is used to detect the geological conditions within the grouting range, including the formation of the strata, rock cracks, groundwater conditions, etc., so as to evaluate the effect of grouting reinforcement;

[0036] The ultrasonic wave velocity tester 202 is used to measure the sound wave propagation velocity of the rock, so as to determine the texture and density of the rock and help evaluate the effect of grouting reinforcement;

[0037] The displacement monitoring sensor 203 is used to monitor the displacement change of the tunnel structure to evaluate the impact of grouting reinforcement on the structural stability;

[0038] The temperature sensor 204 is used to monitor the change of the temperature inside the tunnel after grouting, and helps to evaluate the grouting solidification condition;

[0039] The humidity sensor 205 is used to monitor the change of humidity inside the tunnel after grouting, and to evaluate the grouting curing and its impact on the structure;

[0040] The grouting pressure gauge 206 is used to monitor the total pressure of the grouting section during the grouting process to evaluate the grouting effect.

[0041] like Figure 3 As shown, the geological radar 201 is fixed on the grouting pipe 1 through the geological radar support 6. The geological radar support 6 includes a support inner sleeve 601 with a groove, a bearing 602, a support outer sleeve 603, a fixed support 604 and a rotating shaft 605. The support inner sleeve 601 with a groove cooperates with the sliding protrusion 104 at the tail of the grouting pipe 1 to enable the geological radar 201 to slide along the pipe body at the tail of the grouting pipe 1. A bearing 602 is arranged between the support inner sleeve 601 with a groove and the support outer sleeve 603. The outer sleeve 603 and the fixed support 604 thereon can rotate 360 ​​degrees through the bearing 602, and the geological radar 201 can adjust the angle through the rotating shaft 605 on the fixed support 604.

[0042] like Figure 4 As shown, the data acquisition module 3 is used to integrate and synchronize the data collected by the sensor acquisition module 2 to ensure the accuracy and consistency of the data.

[0043] like Figure 5 As shown, the control unit 4 is used to monitor, analyze and process data in real time, conduct a comprehensive evaluation of the data through machine learning algorithms and data fusion algorithms, generate a grouting plan and adjust the grouting parameters (grouting pressure, grouting rate, grouting material ratio) in real time to ensure the stability and reliability of the reinforcement effect.

[0044] A method for evaluating the effect of advance grouting reinforcement using the above intelligent device, such as Figure 6 As shown, the method comprises the following steps:

[0045] Step S1: Install and start the sensor module 2 to collect multi-source information data of the formation during the grouting process. The specific steps are as follows:

[0046] Step S11: Using bolts or adhesive to install the sensor module 2 on the grouting pipe 1;

[0047] Step S12: Start the sensor module 2 and begin to collect multi-source information data of the stratum, including geological structure, material density, water level, temperature, humidity and other information, specifically including the geological conditions within the grouting range, the sound wave propagation speed of the rock, the displacement change of the tunnel structure, the change of the temperature inside the tunnel after grouting, the change of the humidity inside the tunnel after grouting and the total pressure on the grouting section during the grouting process.

[0048] Step S2: The data collected by the sensor module 2 is transmitted to the data acquisition module 3 for integration and synchronization processing. The specific steps are as follows:

[0049] Step S21: Transmitting various sensor data collected by the sensor module 2 to the data acquisition module 3 via the transmission cable 103;

[0050] Step S22: The data acquisition module 3 integrates and synchronizes the data collected by the sensor module 2 to ensure the accuracy and consistency of the data.

[0051] Step S3: Comprehensively analyze and evaluate the data using intelligent algorithms to identify the formation status. The specific steps are as follows:

[0052] Step S31: the control unit 4 receives data transmitted by the data acquisition module 3;

[0053] Step S32: using machine learning algorithms and fusion algorithms to comprehensively analyze and evaluate the data transmitted in step S31;

[0054] Step S33: Analyze the state of the stratum, including possible cracks, loose strata, water level changes, ground stress changes, grouting fluid hardening, etc.

[0055] Step S4: Generate a grouting plan based on the analysis results, and adjust the grouting parameters in real time to ensure the reinforcement effect. The specific steps are as follows:

[0056] Step S41: According to the analysis result of step S3, the control unit 4 generates a reinforcement plan for the stratum, including the type and proportion of grouting materials, grouting position and depth, grouting pressure, and grouting rate;

[0057] Step S42: The control unit 4 generates a response strategy to adjust the grouting parameters in real time, including the type and proportion of grouting materials, grouting position and depth, grouting pressure, and grouting rate, to ensure the reinforcement effect.

[0058] Step S5: Perform grouting reinforcement operation according to the generated grouting scheme and monitor the grouting process in real time. The specific steps are as follows:

[0059] Step S51: performing grouting reinforcement operation according to the new reinforcement scheme generated in step S4;

[0060] Step S52: Use the temperature sensor 204, the humidity sensor 205, and the grouting pressure gauge 206 to monitor the grouting process in real time to ensure the accuracy and completeness of the grouting.

[0061] Step S6: Continuously monitor the formation status and use sensor data to evaluate the reinforcement effect. The specific steps are as follows:

[0062] Step S61: After the grouting operation is completed, continuously monitor the state of the formation;

[0063] Step S62: using the evaluation algorithm in the control unit 4, including data processing and finite element analysis algorithm based on the physical model, the reinforcement effect is dynamically evaluated according to the data collected during the whole grouting process.

[0064] Step S7: Propose improvement suggestions based on the evaluation results to configure a more reasonable grouting fluid, improve grouting efficiency, enhance reinforcement effect, and reduce costs. The specific steps are as follows:

[0065] Step S71: Recording the geological conditions of the grouting site and the configuration of the grouting liquid;

[0066] Step S72: Providing more reasonable grouting parameter suggestions according to different geological conditions.

Claims

1. An intelligent device for advanced grouting reinforcement with multi-source information, characterized in that The device comprises a sensor module, a data acquisition module and a control unit, wherein: The sensor module is installed on the advance grouting pipeline and is used to collect multi-source information data during the grouting process, including the geological conditions within the grouting range, the sound wave propagation speed of the rock, the displacement change of the tunnel structure, the change of the temperature inside the tunnel after grouting, the change of the humidity inside the tunnel after grouting, and the total pressure on the grouting section during the grouting process; The data acquisition module is used to integrate and synchronize the data collected by the sensor module to ensure the accuracy and consistency of the data; The control unit is used to monitor, analyze and process data in real time, conduct a comprehensive evaluation of the data through machine learning algorithms and data fusion algorithms, generate a grouting plan and adjust the grouting parameters in real time to ensure the stability and reliability of the reinforcement effect.

2. The multi-source information advanced grouting reinforcement intelligent device according to claim 1 is characterized in that The sensor module includes a geological radar, an ultrasonic wave velocity tester, a displacement monitoring sensor, a temperature sensor, a humidity sensor, and a grouting pressure gauge, wherein: The geological radar is used to detect the geological conditions within the grouting range, including the formation of the strata, rock cracks, and groundwater conditions, so as to evaluate the effect of grouting reinforcement; The ultrasonic wave velocity tester is used to measure the sound wave propagation velocity of the rock, so as to judge the texture and density of the rock and help evaluate the effect of grouting reinforcement; The displacement monitoring sensor is used to monitor the displacement change of the tunnel structure to evaluate the impact of grouting reinforcement on the structural stability; The temperature sensor is used to monitor the change of the temperature inside the tunnel after grouting, and helps to evaluate the grouting solidification condition; The humidity sensor is used to monitor the change of humidity inside the tunnel after grouting, and to evaluate the grouting curing and its impact on the structure; The grouting pressure gauge is used to monitor the total pressure of the grouting section during the grouting process to evaluate the grouting effect; The geological radar is fixed on the grouting pipe through a geological radar support. The geological radar support includes a support inner sleeve with a groove, a bearing, a support outer sleeve, a fixed support and a rotating shaft. The support inner sleeve with a groove cooperates with the sliding protrusion at the tail of the grouting pipe to realize the sliding of the geological radar along the pipe body at the tail of the grouting pipe. A bearing is arranged between the support inner sleeve with a groove and the support outer sleeve. The outer sleeve and the fixed support thereon rotate 360 ​​degrees through the bearing, and the geological radar adjusts its angle through the rotating shaft on the fixed support.

3. A method for evaluating the effect of advance grouting reinforcement using the device according to any one of claims 1 to 2, characterized in that The method comprises the following steps: Step S1: Install and start the sensor module to collect multi-source information data of the formation during the grouting process; Step S2: Transmitting the data collected by the sensor module to the data acquisition module for integration and synchronization processing; Step S3: using machine learning algorithms and data fusion algorithms to comprehensively analyze and evaluate the data to identify the formation state; Step S4: Generate a grouting plan based on the analysis results, and adjust the grouting parameters in real time to ensure the reinforcement effect; Step S5: Perform grouting reinforcement operation according to the generated grouting scheme and monitor the grouting process in real time; Step S6: continuously monitor the formation status and evaluate the reinforcement effect using sensor data; Step S7: Propose improvement suggestions based on the evaluation results to configure a more reasonable grouting fluid, improve grouting efficiency, enhance reinforcement effect and reduce costs.

4. The method for evaluating the effect of advance grouting reinforcement according to claim 3 is characterized in that The specific steps of step S1 are as follows: Step S11: installing the sensor module on the grouting pipe using bolts or adhesive; Step S12: Start the sensor module and start collecting multi-source information data of the formation.

5. The method for evaluating the effect of advance grouting reinforcement according to claim 3 is characterized in that The specific steps of step S2 are as follows: Step S21: transmitting various sensor data collected by the sensor module to the data acquisition module via a transmission cable; Step S22: The data acquisition module integrates and synchronizes the data collected by the sensor module to ensure the accuracy and consistency of the data.

6. The method for evaluating the effect of advance grouting reinforcement according to claim 3, characterized in that The specific steps of step S3 are as follows: Step S31: The control unit receives data from the data acquisition module; Step S32: using machine learning algorithms and fusion algorithms to comprehensively analyze and evaluate the data transmitted in step S31; Step S33: Analyze the state of the stratum, including possible cracks, loose strata, water level changes, ground stress changes, and grouting fluid hardening conditions.

7. The method for evaluating the effect of advance grouting reinforcement according to claim 3 is characterized in that The specific steps of step S4 are as follows: Step S41: According to the analysis result of step S3, the control unit generates a reinforcement plan for the stratum, including the type and proportion of grouting materials, grouting position and depth, grouting pressure, and grouting rate; Step S42: The control unit generates a response strategy to adjust the grouting parameters in real time, including the type and proportion of grouting materials, grouting position and depth, grouting pressure, and grouting rate to ensure the reinforcement effect.

8. The method for evaluating the effect of advance grouting reinforcement according to claim 3 is characterized in that The specific steps of step S5 are as follows: Step S51: performing grouting reinforcement operation according to the new reinforcement scheme generated in step S4; Step S52: Use temperature sensors, humidity sensors, and grouting pressure gauges to monitor the grouting process in real time to ensure the accuracy and completeness of the grouting.

9. The method for evaluating the effect of advance grouting reinforcement according to claim 3, characterized in that The specific steps of step S6 are as follows: Step S61: After the grouting operation is completed, continuously monitor the state of the formation; Step S62: using the evaluation algorithm in the control unit, including data processing and finite element analysis algorithm based on the physical model, the reinforcement effect is dynamically evaluated according to the data collected during the entire grouting process.

10. The method for evaluating the effect of advance grouting reinforcement according to claim 3, characterized in that The specific steps of step S7 are as follows: Step S71: Recording the geological conditions of the grouting site and the configuration of the grouting liquid; Step S72: Providing more reasonable grouting parameter suggestions according to different geological conditions.

Images