Intelligent monitoring method and system for construction of super-large-section shallow-buried excavation tunnel

Abstract

The invention discloses an intelligent monitoring method and system for construction of an extra-large-section shallow-buried excavation tunnel, and the method comprises the steps: summarizing all important monitoring indexes in the construction process of the extra-large-section shallow-buried excavation tunnel, and installing monitoring equipment at the positions of important monitoring points; predicted values of the important monitoring indexes in ideal states are input into a data analysis system before construction; the field values of the important monitoring indexes monitored by the monitoring equipment are collected to a data analysis system, and the data analysis system judges whether abnormal construction conditions occur or not according to the field values and predicted values of the important monitoring indexes; when an abnormal construction condition occurs, the data analysis system gives an on-site alarm through the early warning system, predicts the type of an abnormal construction method according to abnormal construction data, and gives corresponding construction rectification measures at the same time. According to the method, the safety and the high efficiency in the construction process of the super-large-section shallow-buried excavation tunnel are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel construction, and in particular to an intelligent monitoring method and system for the construction of a shallow-buried dark-excavated tunnel with an extra-large cross-section. Background Art

[0002] During the construction of shallow tunnels, due to insufficient construction technology and construction management, problems such as water-carrying operations, poor monitoring, irregular construction, over-excavation, and water leakage are easily caused. Since the relevant issues cover a large number of construction organizations, and considering the complex on-site conditions and limited management capabilities, multiple problems are often summarized and solutions are discussed through daily briefings. At the same time, when a certain indicator exceeds the limit due to construction problems, the other on-site indicators will also become abnormal, and the exceeding of a certain indicator at the construction site will often have an adverse effect on the other indicators. The occurrence of this situation will cause great trouble to construction management.

[0003] The above shortcomings need to be improved. Summary of the invention

[0004] In order to overcome the above-mentioned deficiencies in the prior art, the present invention provides an intelligent monitoring method and system for the construction of a shallow-buried dark-excavated tunnel with an extra-large cross-section.

[0005] The technical solution of the present invention is as follows:

[0006] In a first aspect, the present invention provides an intelligent monitoring method for construction of a shallow-buried dark-excavated tunnel with a large cross-section, comprising the following steps:

[0007] Step S1, summarizing various important monitoring indicators during the construction of a large-section shallow-buried dark-excavated tunnel, and installing monitoring equipment at important monitoring points;

[0008] Step S2: before construction, the predicted values ​​of various important monitoring indicators under ideal conditions are input into the data analysis system;

[0009] Step S3: The on-site values ​​of various important monitoring indicators monitored by the monitoring equipment are collected into the data analysis system. The data analysis system determines whether there is any abnormal construction situation through the on-site values ​​and predicted values ​​of various important monitoring indicators;

[0010] Step S4: When an abnormal construction situation occurs, the data analysis system issues an on-site alarm through the early warning system, and predicts the type of abnormal construction method based on the abnormal construction data, and gives corresponding construction rectification measures;

[0011] Step S5: After the construction and renovation is completed, repeat the operation of step S4 until the early warning system stops alarming.

[0012] As a preferred solution of the present invention, important monitoring indicators include tunnel clearance convergence, crown settlement, invert arch uplift, overbreak and underbreak, surface settlement, tunnel vibration speed, surface building displacement and rotation angle.

[0013] As a preferred solution of the present invention, in step S2, the design drawings are referred to, and the predicted values ​​of various important monitoring indicators are obtained through existing engineering experience, industry standards and predictive simulation calculations.

[0014] As a preferred solution of the present invention, the existing engineering experience includes a construction monitoring database of the existing engineering.

[0015] As a preferred solution of the present invention, in step S3, the data analysis system establishes a data monitoring abnormality alarm limit. When the on-site value of a certain important monitoring indicator or the on-site value of a certain important monitoring indicator exceeds the corresponding predicted value for a long time, it is judged that an abnormal construction situation has occurred.

[0016] As a preferred solution of the present invention, in step S4, the abnormal construction data includes the displacement and vibration parameters of the underground structure, strata and surrounding buildings exceeding the limit in a single construction cycle, the sudden increase of structural deformation at a certain advance length, and the simultaneous increase of surrounding rock deformation and structural internal force.

[0017] As a preferred solution of the present invention, in step S4, when the data analysis system issues an on-site alarm through the early warning system, the on-site construction is terminated and an abnormal situation is checked.

[0018] As a preferred solution of the present invention, in step S4, the data analysis system analyzes the data change rules based on the over-limit values ​​and over-limit durations of the abnormal construction data, infers the types of abnormal construction methods that may cause construction problems and feeds back to the site, while providing corresponding construction rectification measures and precautions.

[0019] As a preferred solution of the present invention, in step S4, when the data analysis system performs data change law analysis, it includes analyzing the over-limit value and over-limit duration of the abnormal construction data, and the correlation between the abnormal construction data and other important monitoring indicators.

[0020] In a second aspect, the present invention provides an intelligent monitoring system for shallow-buried dark-excavated tunnels with extra-large cross-sections, which is applied to the intelligent monitoring method for construction of shallow-buried dark-excavated tunnels with extra-large cross-sections described in any of the above-mentioned schemes, including monitoring equipment, a data analysis system and an early warning system.

[0021] The present invention according to the above scheme has the following beneficial effects:

[0022] The present invention conducts all-round and comprehensive monitoring of the tunnel construction site, screens abnormal construction data and gives the types of possible problems according to the data of abnormal indicators or indicator groups in the monitoring data, and automatically analyzes and gives corrective measures for the problems in the construction process, thereby improving the safety and efficiency of the construction process of ultra-large-section shallow buried dark-excavated tunnels. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flow chart of the intelligent monitoring method for the construction of a shallow-buried dark-excavated tunnel with a very large cross-section in the present invention;

[0024] Figure 2 It is a structural schematic diagram of the present invention for monitoring important monitoring indicators in shallow buried dark excavation tunnel construction;

[0025] Figure 3 A schematic structural diagram of an intelligent monitoring system for a shallow-buried dark-excavated tunnel with a very large cross-section in the present invention. DETAILED DESCRIPTION

[0026] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0027] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0028] Please refer to Figure 1 This embodiment provides an intelligent monitoring method for large-section shallow-buried dark-excavated tunnel construction, comprising the following steps:

[0029] Step S1, summarize the important monitoring indicators during the construction of the extra-large cross-section shallow buried dark excavation tunnel, and install monitoring equipment 1 at important monitoring points to obtain the on-site values ​​of various important monitoring indicators in real time, provide basic data support for subsequent monitoring and analysis, and ensure that any abnormalities in the construction process can be discovered in time.

[0030] Specifically, important monitoring indicators include the amount of clearance convergence in the tunnel, arch settlement, invert arch uplift, over-excavation and under-excavation, surface settlement, tunnel vibration speed, surface building displacement and rotation angle, etc. These indicators can comprehensively reflect the safety and stability of tunnel construction.

[0031] Step S2, referring to design drawings and other schemes, obtain the predicted values ​​of various important monitoring indicators through existing engineering experience (such as the construction monitoring database of existing projects), industry standards and predictive simulation calculations, and input the predicted values ​​of various important monitoring indicators under ideal conditions into the data analysis system 2 before construction.

[0032] Among them, the predicted values ​​of various important monitoring indicators are used as important data reference values ​​in the construction monitoring process, reflecting the reasonable range that each monitoring indicator should reach under ideal construction conditions, so as to provide the data analysis system 2 with the occurrence of abnormal construction conditions. By comparing the data monitoring results of the monitoring equipment 1 with the common ranges of various indicators in the existing engineering measured data, the dynamic change relationship between different indicators, and whether the range exceeds the limit or the correlation between parameters is abnormal under a stable state, a comprehensive judgment of the monitoring data of multiple indicators can be achieved, and the normal and abnormal construction conditions can be predicted by referring to the size of the over-limit values ​​of each indicator.

[0033] Step S3: The on-site values ​​of various important monitoring indicators monitored by the monitoring equipment 1 are collected into the data analysis system 2. The data analysis system 2 determines whether any abnormal construction situation occurs based on the on-site values ​​and predicted values ​​of various important monitoring indicators.

[0034] Specifically, the data analysis system 2 is equipped with an abnormal alarm limit for data monitoring. When the on-site value of a certain important monitoring indicator or the on-site value of a certain important monitoring indicator exceeds the corresponding predicted value for a long time, it is judged that an abnormal construction situation has occurred. In addition, in view of the fact that the construction site environment may be unstable, resulting in the transient amplitude of the important monitoring indicator exceeding the limit, a certain safety margin will be reserved in the analysis of the peak over-limit point when the transient of the physical quantity is monitored in real time. At the same time, according to the real-time change law of each physical quantity, it will be evaluated whether the physical quantity has recovered to below the limit within the control period, which will be used as the basis for judging the abnormal construction situation. The above-mentioned construction abnormality judgment method fully considers the mechanical properties between the stratum and the structure in the underground project, combines the comprehensive judgment ideas of long-term monitoring and stable parameters, and incorporates the unstable deformation of the stratum that may occur during the excavation and support process, as well as the fluctuation of the construction parameters within a reasonable range during the mechanical balance stage after support. It can more accurately identify construction abnormalities and effectively avoid the occurrence of false alarms.

[0035] Step S4: When an abnormal construction situation occurs, the data analysis system 2 immediately issues an on-site alarm through the early warning system 3, and predicts the type of abnormal construction method based on the abnormal construction data (such as the displacement and vibration of the underground structure, stratum and surrounding buildings in a single construction cycle, the sudden increase of structural deformation at a certain footage, and the simultaneous increase of surrounding rock deformation and structural internal force, etc.), and gives corresponding construction rectification measures. The purpose of this step is to respond quickly after the abnormal construction is discovered, and to eliminate safety hazards by taking targeted rectification measures to ensure the smooth progress of the construction process.

[0036] Specifically, when the data analysis system 2 issues an on-site alarm through the early warning system 3, in order to ensure personnel safety and construction quality, on-site construction will be terminated immediately, and then the construction team will quickly organize personnel to investigate the abnormal situation. The investigation work includes a detailed inspection of the specific monitoring indicators indicated by the alarm to confirm the specific manifestation, degree and possible cause of the abnormality. The investigation work also involves a comprehensive assessment of multiple aspects such as the tunnel structure, ground stability, construction equipment and surrounding environment to fully understand the scope of the impact of the abnormal situation.

[0037] Step S5: After the construction modification is completed, the operation of step S4 is repeated, that is, the monitoring data is collected, analyzed and abnormal judgment is performed again until the early warning system 3 stops alarming. If the early warning system 3 stops alarming, it means that the construction abnormality has been effectively eliminated and the construction can continue. If the early warning system 3 still alarms, it is necessary to further analyze the cause and take more in-depth rectification measures. The purpose of this step is to ensure that the construction abnormality is completely resolved and to prevent the hidden danger from recurring, thereby ensuring the overall quality and safety of the tunnel construction.

[0038] In one embodiment, in step S4, the data analysis system 2 analyzes the data change patterns based on the over-limit values ​​and over-limit durations of the abnormal construction data, infers the types of abnormal construction methods that may cause construction problems and feeds back to the site, while also providing corresponding construction rectification measures and precautions.

[0039] Specifically, in the analysis of data change patterns, the data analysis system 2 first focuses on the over-limit values ​​and over-limit duration of various important monitoring indicators. The over-limit value refers to the deviation between the actual measured value (on-site value) and the preset safety threshold (predicted value), while the over-limit duration refers to the length of time these abnormal indicators exceed the preset safety threshold. The size of the over-limit value directly reflects the severity of the construction abnormality and has important reference value for judging the type of problems that may arise; at the same time, the data analysis system 2 will also analyze the correlation between abnormal construction data and other important monitoring indicators. This correlation analysis helps to reveal the systematic problems or causal relationships that may exist behind the abnormal construction data.

[0040] By combining these analyses, the data analysis system 2 can more accurately infer the types of abnormal construction methods that may cause construction problems.

[0041] Once the possible abnormal construction method is determined, the data analysis system 2 will immediately feed back this information to the construction site so that the construction team can quickly locate the problem and take targeted corrective measures. At the same time, according to the specific situation of the problem, corresponding construction corrective measures and precautions will be given to ensure the effectiveness and safety of the rectification work.

[0042] In one embodiment, the monitoring device 3 adopts a high-precision integrated monitoring device. The high-precision integrated monitoring device adopts advanced sensing technology and signal processing algorithms to ensure the accuracy and stability of the monitoring data, providing a reliable basis for abnormal detection, early warning and decision-making during the construction process.

[0043] Figure 2 Taking the shallow buried dark excavation tunnel construction as an example, an important monitoring indicator monitoring scheme of the present invention is listed. Figure 2 The important monitoring indicators of medium-shallow buried tunnels include the clearance convergence in the tunnel, the displacement of the arch crown, the uplift of the invert arch, the over-break and under-break, the surface settlement, the vibration velocity and the displacement of the surface buildings. The corresponding predicted values, on-site values ​​and rectification measures are shown in Table 1.

[0044] Table 1 Important monitoring indicators of shallow buried tunnel construction process and their corresponding predicted values, on-site values ​​and rectification measures

[0045]

[0046]

[0047] Table 1 above can represent the interface in the alarm state of the actual monitoring process of the present invention. Here, a case where a tunnel structure and surrounding rock displacement are too large in a project is taken as an example. The main design ideas include:

[0048] (1) It was confirmed that the tunnel structure displacement, surface settlement and other indicators had exceeded the limit, and this exceeded the limit and continued to occur for more than the time limit, proving that the above abnormal conditions were not false abnormalities and needed to be reported and rectified;

[0049] (2) Automatically propose possible causes and give concentrated or weak causes through data analysis, while excluding unreasonable causes. Analysis shows that the causes of displacement exceeding the limit may include over-excavation, untimely closure, and encountering soft strata. According to the monitoring results, the tunnel has no over-excavation or under-excavation, and the high vibration speed indicates that there is no obvious soft stratum. Finally, the cause is pointed out to the untimely closure of the lining, and corrective measures are automatically given;

[0050] (3) Based on the analysis results, on-site rectification is carried out. After the rectification, construction monitoring is continued, and the analysis results and rectification effects of the problem are entered into the big data analysis system to further improve the accuracy of the algorithm and thus improve the safety of construction process management.

[0051] In Table 1 above, if the field value of the invert uplift exceeds the corresponding predicted value for a long time, the corresponding corrective measures are:

[0052] (1) It is necessary to check the over-excavation and under-excavation and surrounding rock support settings. If there are no problems, it is recommended to reinforce the base stratum with grouting, anchor bolts, etc.;

[0053] (2) Strengthen the rigidity of the inverted arch steel at the bottom of the tunnel.

[0054] If the on-site value of over-excavation exceeds the corresponding predicted value for a long time, the corresponding corrective measures are:

[0055] (1) Control blasting parameters and achieve smooth blasting;

[0056] (2) Strictly calibrate laser measurement;

[0057] (3) When over-excavation occurs, the over-excavation part needs to be filled to the original design contour line by shotcrete.

[0058] If the on-site value of under-excavation exceeds the corresponding predicted value for a long time, the corresponding corrective measures are:

[0059] (1) Accurately control the amount of blasting explosives;

[0060] (2) Manual removal of the under-excavated parts.

[0061] If the on-site value of the surface building displacement exceeds the corresponding predicted value for a long time, the corresponding corrective measures are:

[0062] (1) Strengthen the foundation of the building, such as increasing the width and depth of the foundation or using pile foundations, to improve its bearing capacity;

[0063] (2) For water-rich strata, the precipitation depth can be controlled, thereby improving the bearing capacity of the strata.

[0064] The intelligent monitoring method for the construction of shallow-buried tunnels with extra-large cross-sections provided in this embodiment conducts comprehensive and all-round monitoring of the site. According to the data of abnormal indicators or indicator groups in the monitoring data, the abnormal construction data is screened and the types of possible problems are given. At the same time, corrective measures are automatically analyzed for problems in the construction process, thereby improving the safety and efficiency of the underground structure construction process.

[0065] In one embodiment, the present invention provides an intelligent monitoring system for a shallow-buried dark tunnel with a very large cross-section, which is applied to the intelligent monitoring method for the construction of a shallow-buried dark tunnel with a very large cross-section as described in any of the above-mentioned schemes, including a monitoring device 1, a data analysis system 2 and an early warning system 3.

[0066] The intelligent monitoring system for shallow-buried and dark-excavated tunnels with extra-large cross-sections provided in this embodiment can execute the above-mentioned method embodiments, and its implementation principles and technical effects are similar, which will not be repeated here.

[0067] In addition, the intelligent monitoring system for shallow-buried tunnels with extra-large cross-sections of the present invention has strong intelligence and automation performance, and can realize non-manual, fully automatic monitoring and early warning; the monitoring method takes into account tunnel construction diseases and construction problems under multi-length coupling conditions, and the data analysis also takes into account data anomalies under multi-length action conditions, and makes suggestions for various rectification measures; the analysis of abnormal construction mainly refers to the big data monitoring results of existing construction sites and the preliminary results of numerical simulation; at the same time, the system itself can be used as a big data acquisition device, and big data can be collected while realizing abnormal monitoring of construction data, enriching the construction database and providing important reference data for future monitoring of similar projects; early warning notifications of multiple problems can be realized, and the construction management of different teams on site has the functions of timely notification and reasonable solution suggestions.

[0068] In addition, although the operations of the method of the present invention are described in a specific order in the drawings, this does not require or imply that the operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0069] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all these improvements and changes should fall within the scope of protection of the appended claims of the present invention.

[0070] The above is an exemplary description of the present invention in conjunction with the accompanying drawings. It is obvious that the implementation of the present invention is not limited to the above-mentioned method. As long as various improvements are made by adopting the method concept and technical solution of the present invention, or the concept and technical solution of the present invention are directly applied to other occasions without improvement, they are all within the protection scope of the present invention.

Claims

1. An intelligent monitoring method for large-section shallow-buried tunnel construction, characterized in that: include: Step S1, summarizing various important monitoring indicators during the construction of a large-section shallow-buried dark-excavated tunnel, and installing monitoring equipment at important monitoring points; Step S2: before construction, the predicted values ​​of various important monitoring indicators under ideal conditions are input into the data analysis system; Step S3: The on-site values ​​of various important monitoring indicators monitored by the monitoring equipment are collected into the data analysis system. The data analysis system determines whether there is any abnormal construction situation through the on-site values ​​and predicted values ​​of various important monitoring indicators; Step S4: When an abnormal construction situation occurs, the data analysis system issues an on-site alarm through the early warning system, and predicts the type of abnormal construction method based on the abnormal construction data, and gives corresponding construction rectification measures; Step S5: After the construction and renovation is completed, repeat the operation of step S4 until the early warning system stops alarming.

2. The method for intelligent monitoring of large-section shallow-buried tunnel construction according to claim 1 is characterized in that: Important monitoring indicators include the amount of clearance convergence in the tunnel, arch settlement, invert arch uplift, over-excavation and under-excavation, surface settlement, tunnel vibration velocity, surface building displacement and rotation angle.

3. The intelligent monitoring method for construction of a shallow-buried tunnel with a large cross-section according to claim 1 is characterized in that: In step S2, the design drawings are referred to, and the predicted values ​​of various important monitoring indicators are obtained through existing engineering experience, industry standards and predictive simulation calculations.

4. The method for intelligent monitoring of large-section shallow-buried tunnel construction according to claim 3 is characterized in that: Existing project experience includes the construction monitoring database of existing projects.

5. The method for intelligent monitoring of large-section shallow-buried tunnel construction according to claim 1 is characterized in that: In step S3, the data analysis system sets up data monitoring abnormal alarm limits. When the on-site value of a certain important monitoring indicator or the on-site value of a certain important monitoring indicator exceeds the corresponding predicted value for a long time, it is determined that an abnormal construction situation has occurred.

6. The intelligent monitoring method for construction of a shallow-buried tunnel with a large cross-section according to claim 1 is characterized in that: In step S4, the abnormal construction data include displacement and vibration parameter exceeding the limit of the underground structure, stratum and surrounding buildings in a single construction cycle, sudden increase of structural deformation at a certain footage, and simultaneous increase of surrounding rock deformation and structural internal force.

7. The method for intelligent monitoring of large-section shallow-buried tunnel construction according to claim 1 is characterized in that: In step S4, when the data analysis system issues an on-site alarm through the early warning system, the on-site construction is terminated and an abnormal situation is checked.

8. The method for intelligent monitoring of large-section shallow-buried tunnel construction according to claim 1 is characterized in that: In step S4, the data analysis system analyzes the data change pattern based on the over-limit values ​​and over-limit duration of the abnormal construction data, infers the types of abnormal construction methods that may cause construction problems and feeds back to the site, while also providing corresponding construction rectification measures and precautions.

9. The method for intelligent monitoring of large-section shallow-buried tunnel construction according to claim 8 is characterized in that: In step S4, the data analysis system performs data change pattern analysis, including analyzing the over-limit value and over-limit duration of the abnormal construction data, and the correlation between the abnormal construction data and other important monitoring indicators.

10. An intelligent monitoring system for a large-section shallow-buried dark-excavated tunnel, applied to the intelligent monitoring method for construction of a large-section shallow-buried dark-excavated tunnel as claimed in any one of claims 1 to 9, characterized in that: Including monitoring equipment, data analysis system and early warning system.

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