Intelligent construction system for controlling tunnel blasting back break

Abstract

The invention relates to an intelligent construction system for controlling over-break and under-break in tunnel blasting, and aims to systematically solve the problems of over-break and under-break and under-break caused by blasting in tunnel construction by fusing an advanced intelligent control technology, a data analysis algorithm and a real-time monitoring means. The system is composed of a blasting parameter setting module, a real-time monitoring module, a data analysis and feedback module and an automatic adjustment module. By means of multi-dimensional real-time monitoring of the blasting process and combination of advanced data analysis methods such as machine learning, blasting parameters are dynamically optimized, accurate control over the blasting effect is achieved, safety and economical efficiency of tunnel construction are guaranteed, and the method is suitable for tunnel engineering under various geological conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel construction, and in particular to a system for controlling over-break and under-break of tunnel blasting based on intelligent construction technology. Background Art

[0002] During tunnel excavation, blasting is a commonly used construction method. However, due to the complexity of geological conditions and the uncertainty of the construction environment, over-excavation or under-excavation often occurs after blasting. This not only affects the construction quality, but may also increase the difficulty of subsequent support construction and even cause safety accidents. The existing technology lacks effective real-time monitoring and intelligent adjustment mechanisms, resulting in poor adaptability of traditional blasting construction to the environment. An intelligent system is urgently needed to accurately control the blasting effect in order to effectively control the over-excavation and under-excavation phenomena. Summary of the invention

[0003] The purpose of the present invention is to improve the deficiencies in existing construction technology methods and to provide an intelligent construction system for controlling over-break or under-break in tunnel blasting, which can alleviate the problem of over-break or under-break after blasting.

[0004] To achieve the above-mentioned purpose, the present invention proposes a mining method tunnel excavation over-excavation and under-excavation control construction method, including a blasting parameter setting module, a real-time monitoring module, a data analysis and feedback module, and an automatic adjustment module.

[0005] S1. Blasting parameter setting module, which is used to set the basic parameters required for blasting operations according to construction geological characteristics, tunnel design requirements and relevant engineering specifications, including but not limited to explosive type, amount, blasting method and its arrangement and combination, and has parameter optimization function.

[0006] S2. Real-time monitoring module, which continuously monitors key physical quantities before, during and after blasting through a series of sensors, including vibration intensity, sound wave amplitude, displacement and acceleration, and transmits monitoring data in real time.

[0007] S3. Data analysis and feedback module, which uses data mining and machine learning algorithms to conduct in-depth analysis of the monitored data to evaluate the blasting effect, identify potential over-break or under-break risks, and generate visual reports for engineers' decision-making reference.

[0008] S4. Automatic adjustment module, which can provide real-time feedback and automatically adjust blasting parameters according to data analysis results to optimize the subsequent blasting operation results and generate detailed adjustment reports.

[0009] Preferably, in step S1, the blasting parameter setting module has a self-learning function, and can continuously optimize parameter settings according to historical blasting data and real-time monitoring results to adapt to construction requirements under different geological conditions.

[0010] Preferably, in step S2, the real-time monitoring module includes a vibration sensor, an acoustic wave sensor and a displacement sensor, and the sensors are connected to the data analysis and feedback module via wireless communication technology to achieve efficient real-time transmission of data.

[0011] Preferably, in step S3, the data analysis and feedback module adopts a prediction model based on deep learning to improve the prediction accuracy of over-break and under-break phenomena by training historical data during the blasting process.

[0012] Preferably, in step S4, the automatic adjustment module has a decision support function, and can intelligently adjust the blasting parameters according to the changes in the current construction environment and the construction progress, and provide real-time feedback to the blasting parameter setting module.

[0013] Preferably, in step S4, the system can realize centralized monitoring and data analysis of multiple tunnel construction projects by integrating cloud computing technology, so as to improve the overall construction management efficiency and safety assurance.

[0014] Preferably, in step S4, the feedback module of the system has an alarm function, and when the risk of over-excavation or under-excavation exceeds a preset threshold, it can automatically issue an alarm and record relevant data for subsequent analysis and improvement.

[0015] The beneficial effects of the present invention based on its technical solution are:

[0016] 1. By introducing intelligent control technology, precise control of blasting operations is achieved, which effectively reduces over-break and under-break phenomena and improves construction quality;

[0017] 2. Improve the safety of tunnel construction, reduce the probability of construction accidents, and ensure the personal safety of workers;

[0018] 3. Through real-time monitoring and data analysis, construction efficiency is improved, construction period is shortened, and construction costs are saved;

[0019] 4. The system can dynamically adjust blasting parameters according to changes in geological conditions to adapt to different construction requirements, thereby enhancing the flexibility and adaptability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flow chart of a system for controlling over-break and under-break of tunnel blasting based on intelligent construction technology according to the present invention;

[0021] Figure 2This is a system page display diagram in the present invention;

[0022] Figure 3 It is the arrangement diagram of the tunnel monitoring points in the present invention;

[0023] Figure 4 It is a layout diagram of the intelligent analysis network in the present invention;

[0024] 1- blasting parameter setting module; 2- real-time monitoring module; 21- vibration intensity; 22- sound wave amplitude; 23- displacement; 24- acceleration; 3- data analysis and feedback module; 4- automatic adjustment module; 5- computer system; 6- tunnel blasting basic information input module; 7- tunnel face; 8- intelligent analysis network; 81- information input terminal; 82- information output terminal; 9- tunnel early warning device; DETAILED DESCRIPTION

[0025] In order to achieve the purpose of the present invention and to better understand the technical solution and effects, the embodiments of the present invention will be further described in conjunction with the accompanying drawings.

[0026] Please refer to Figure 1 , Figure 1 A flow chart of a system for controlling over-break and under-break of tunnel blasting based on intelligent construction technology according to the present invention;

[0027] In order to achieve the above objectives,

[0028] The invention proposes an intelligent construction system for controlling tunnel blasting over-break and under-break, comprising a blasting parameter setting module, a real-time monitoring module, a data analysis and feedback module, and an automatic adjustment module.

[0029] S1. Blasting parameter setting module, which is used to set the basic parameters required for blasting operations according to construction geological characteristics, tunnel design requirements and relevant engineering specifications, including but not limited to explosive type, charge, blasting method and its arrangement and combination, and has parameter optimization function. Figure 2 , 1 is the blasting parameter setting module, 2 is the real-time monitoring module, 3 is the data analysis and feedback module, 4 is the automatic adjustment module, 5 is the computer system, and 6 is the tunnel blasting basic information input module.

[0030] S2. Real-time monitoring module, which continuously monitors key physical quantities before, during and after blasting through a series of sensors, including vibration intensity, sound wave amplitude, displacement and acceleration, and transmits monitoring data in real time. Figure 3 , 21 is the vibration intensity, 22 is the sound wave amplitude, 23 is the displacement, 24 is the acceleration, and 9 is the tunnel early warning device.

[0031] S3. Data analysis and feedback module, which uses data mining and machine learning algorithms to conduct in-depth analysis of the monitored data to evaluate the blasting effect, identify potential over-break or under-break risks, and generate visual reports for engineers' decision-making reference. Figure 4 , 8 is an intelligent analysis network, 81 is an information input terminal, and 82 is an information output terminal.

[0032] S4. Automatic adjustment module, which can provide real-time feedback and automatically adjust blasting parameters according to data analysis results to optimize the subsequent blasting operation results and generate detailed adjustment reports.

[0033] The blasting parameter setting module has a self-learning function. According to 21 vibration intensity, 22 sound wave amplitude, 23 displacement, and 24 acceleration monitor, it can continuously optimize parameter settings based on historical blasting data and real-time monitoring results to adapt to construction needs under different geological conditions.

[0034] The real-time monitoring module includes a vibration sensor, an acoustic wave sensor and a displacement sensor, and the sensors are connected to the data analysis and feedback module through wireless communication technology to achieve efficient real-time transmission of data.

[0035] The data analysis and feedback module adopts a prediction model based on deep learning, and improves the prediction accuracy of over-break and under-break phenomena by training historical data during the blasting process.

[0036] The automatic adjustment module has a decision support function, and can intelligently adjust the blasting parameters according to the changes in the current construction environment and the construction progress, and provide real-time feedback to the blasting parameter setting module.

[0037] The system integrates cloud computing technology to achieve centralized monitoring and data analysis of multiple tunnel construction projects, thereby improving overall construction management efficiency and safety.

[0038] The feedback module of the system has an alarm function. When the risk of over-excavation or under-excavation exceeds a preset threshold, the 9 tunnel early warning device can automatically sound an alarm and record relevant data for subsequent analysis and improvement.

Claims

1. The present invention proposes an intelligent construction system for controlling over-break and under-break of tunnel blasting, comprising a blasting parameter setting module, a real-time monitoring module, a data analysis and feedback module, and an automatic adjustment module. S1. Blasting parameter setting module, which is used to set the basic parameters required for blasting operations according to construction geological characteristics, tunnel design requirements and relevant engineering specifications, including but not limited to explosive type, amount, blasting method and its arrangement and combination, and has parameter optimization function. S2. Real-time monitoring module, which continuously monitors key physical quantities before, during and after blasting through a series of sensors, including vibration intensity, sound wave amplitude, displacement and acceleration, and transmits monitoring data in real time. S3. Data analysis and feedback module, which uses data mining and machine learning algorithms to conduct in-depth analysis of the monitored data to evaluate the blasting effect, identify potential over-break or under-break risks, and generate visual reports for engineers' decision-making reference. S4. Automatic adjustment module, which can provide real-time feedback and automatically adjust blasting parameters according to data analysis results to optimize the subsequent blasting operation results and generate detailed adjustment reports.

2. The intelligent construction system for controlling overbreak and underbreak of tunnel blasting according to claim 1, characterized in that: In step S1, the blasting parameter setting module has a self-learning function and can continuously optimize parameter settings according to historical blasting data and real-time monitoring results to adapt to construction requirements under different geological conditions.

3. The intelligent construction system for controlling overbreak and underbreak of tunnel blasting according to claim 1, characterized in that: In step S2, the real-time monitoring module includes a vibration sensor, an acoustic wave sensor and a displacement sensor, and the sensors are connected to the data analysis and feedback module through wireless communication technology to achieve efficient real-time transmission of data.

4. The intelligent construction system for controlling overbreak and underbreak of tunnel blasting according to claim 1, characterized in that: In step S3, the data analysis and feedback module adopts a prediction model based on deep learning to improve the prediction accuracy of over-break and under-break phenomena by training historical data during the blasting process.

5. The intelligent construction system for controlling overbreak and underbreak of tunnel blasting according to claim 1, characterized in that: In step S4, the automatic adjustment module has a decision support function, and can intelligently adjust the blasting parameters according to the changes in the current construction environment and the construction progress, and provide real-time feedback to the blasting parameter setting module.

6. The intelligent construction system for controlling overbreak and underbreak of tunnel blasting according to claim 1, characterized in that: In step S4, the system can realize centralized monitoring and data analysis of multiple tunnel construction projects by integrating cloud computing technology to improve overall construction management efficiency and safety assurance.

7. The intelligent construction system for controlling tunnel blasting over-break and under-break according to claim 1, characterized in that: In step S4, the feedback module of the system has an alarm function. When the risk of over-excavation or under-excavation exceeds a preset threshold, it can automatically issue an alarm and record relevant data for subsequent analysis and improvement.

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