Rectangular pipe gallery layered backfill soil monitoring method and monitoring system

Abstract

The invention discloses a rectangular pipe gallery layered backfill soil monitoring method and monitoring system, and belongs to the technical field of municipal infrastructure construction monitoring. Comprising the following steps: delimiting a monitoring section for layered backfilling according to a pipe gallery structure; before backfilling of each layer, a sensor array is arranged along the cross section and the longitudinal section of the pipe gallery according to a gridding rule; collecting reference parameters of the undisturbed soil and the first layer of backfill soil, and performing precision verification; after each layer of backfill is completed, actual measurement parameters of backfill soil of the layer are collected in real time and compared with the collected reference data, and after precision verification is carried out, the actual measurement parameters are uploaded to the central processing unit; on the basis of reference data uploaded in real time, the compaction degree evolution model and the local settlement prediction model are input after preprocessing, layered quality scores are generated and associated with a grade table, and construction suggestions are output. According to the method, double dynamic analysis of the compaction degree evolution model and the local settlement prediction model is combined, and full-process real-time monitoring of the dry density, the settlement amount and the load stress in the layered backfilling process is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of municipal infrastructure construction monitoring, and in particular to a rectangular pipe gallery layered backfill soil monitoring method and monitoring system. Background Art

[0002] In municipal underground projects, especially the construction of integrated urban pipeline corridors, rectangular cross-section structures often require layered backfilling. The quality of the backfill directly impacts structural stability and subsequent settlement control. Currently used methods, such as manual sampling for density testing and settlement observation point measurement, suffer from limited monitoring accuracy, delayed response, and a lack of automation, making them incapable of meeting the demand for real-time assessment of the layered compaction process and localized settlement trends.

[0003] Therefore, there is an urgent need for an integrated, efficient, and visual layered backfill monitoring system to achieve dynamic control of the backfill soil quality throughout the entire process and provide early warnings and construction optimization suggestions when the quality is abnormal. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for monitoring layered backfill of rectangular pipeline corridors, so as to realize dynamic monitoring of backfill operations during the construction of urban integrated pipeline corridors, ensure real-time grasp of compaction quality and settlement risk, thereby improving structural stability, reducing subsequent maintenance costs, and facilitating intelligent construction and scientific decision-making.

[0005] To achieve the above object, the present invention provides the following technical solutions: In a first aspect, the present invention discloses a method for monitoring layered backfill soil in a rectangular pipe gallery, comprising the following steps: S1. Selection of monitoring area: Delineate the monitoring section for layered backfilling based on the tunnel structure; S2. Monitoring point layout: Before backfilling each layer, the sensor array is laid out along the cross section and longitudinal section of the corridor according to the grid rule; S3. Benchmark data collection: Collect the benchmark parameters of the original soil and the first layer of backfill soil, and verify the accuracy; S4, real-time data collection and transmission: After each backfill layer is completed, the measured parameters of the backfill soil layer are collected in real time, compared with the benchmark data collected in step S3, and uploaded to the central processing unit after accuracy verification; S5. Data processing and dynamic evaluation: Based on the data uploaded in real time in step S4, after pre-processing, it is input into the compaction evolution model and the local settlement prediction model for calculation, and a layered quality score is generated and associated with the grade table to output construction recommendations; In S5, the compaction evolution model formula is:

[0006] Where,t is the time in seconds; D i(t) It is i Backfill soil layer at time t Backfill soil compaction degree at 10 ... D measured(t) is the initial density of the undisturbed soil; P j(t) It is j External load above the backfill layer, in Pa; H j It is j The thickness of the backfill soil layer, in cm; K j is the soil consolidation coefficient; α j It is j Incremental density coefficient of backfill soil; δP j It is j Additional stress of backfill soil, unit is Pa; i Indicates the current backfill layer. j For the i All soil layers above the backfill layer; in, K j and α j It is pre-calibrated through indoor geotechnical tests and stored in the central processing unit parameter database. It is automatically matched according to the soil type during construction and supports revisions.

[0007] A further solution: in S3, the reference parameters include porosity, compression modulus, additional stress, initial stress, and external load; In S4, the measured parameters include: dry density, moisture content, settlement, number of rolling times and external load.

[0008] Further solution: In S5, the local settlement prediction model formula is:

[0009] Where, t is the time in seconds; It's time t The predicted amount of backfill settlement at 1 hour, in cm; is the compression coefficient of the i-th layer of backfill soil; It is i The thickness of the backfill soil layer, in cm; It is i The initial stress above the backfill layer, in Pa; It is iExternal load above the backfill layer, in Pa; K i is the soil consolidation coefficient; is the correction factor to adjust for the effects of external loads; It is i Layers of backfill soil over time t Variable external load, in Pa; K i and It is pre-calibrated through indoor geotechnical tests and stored in the central processing unit parameter database. It is automatically matched according to the soil type during construction and supports revisions.

[0010] Further solution: In S5, the hierarchical quality score is obtained by the following formula:

[0011] Where, t is the time in seconds; is the quality score; It is i The ratio of the target value to the actual value of the backfill soil compaction degree; It is i The layout ratio of the target value and actual value of the backfill soil settlement; is the control coefficient The sum is 1.

[0012] in: D i * (t) Calculated according to the following formula:

[0013] Where, t is the time in seconds; is the target compaction value; It is i Backfill soil layer at time t Backfill soil compaction degree at 10 ... Calculated according to the following formula:

[0014] Where, t is the time in seconds; is the actual measurement of settlement, in cm; It's time t The predicted amount of backfill settlement at 1 hour, in cm; is the error value.

[0015] A further solution includes step S6: The layered quality scoring results and grade table are presented as an evaluation curve, and the evaluation curve, risk level, and construction recommendations are visualized and output.

[0016] Further solution: The data collection frequency in step S4 is to start immediately after each layer of backfill is completed, and dynamic pressure data is collected every 5-10 minutes during the operation of the rolling machine.

[0017] Further options: P j(t) Calculated according to the following formula:

[0018] Where, For the k Wet bulk density of backfill soil, in kN / m 3 ; For the k Thickness of backfill layer; Calculated according to the following formula:

[0019] Where, Q It is i The concentrated load above the backfill layer, in N; R is the diffusion influence radius, in cm; η (Z j ) is the attenuation factor.

[0020] Further options: Calculated according to the following formula:

[0021] Where, It is j Wet bulk density of the soil layer, in kN / m 3 ; It is j Thickness of soil layer, in cm; C i Calculated according to the following formula:

[0022] Where, is the natural porosity, expressed in%; is the compression modulus, in Pa.

[0023] In a second aspect, the present invention discloses a monitoring system used in the above-mentioned rectangular tunnel layered backfill monitoring method, comprising: Data acquisition module, which includes pore pressure gauge, dynamic pressure sensor, sedimentation meter, laser rangefinder, and nuclear density meter; The data processing and modeling module is used to normalize and filter the data collected by the sensor array and build a compaction evolution model and a local settlement prediction model; The central processing unit is used to receive processed data and output control commands and construction adjustment suggestions; The evaluation and decision support module is used to generate tiered quality scores based on the output of the data processing and modeling unit and output construction recommendations based on the associated rating table; The user interface and visualization module is used to visualize the results output by the evaluation and decision support unit.

[0024] Compared with the prior art, the present invention has the following beneficial effects: By integrating multi-source sensors and wireless transmission technology, combined with dual dynamic analysis using a compaction evolution model and a local settlement prediction model, this system achieves real-time monitoring of dry density, settlement, and load stress throughout the layered backfill process. Based on a physically driven scoring mechanism, the system automatically outputs construction optimization recommendations, significantly improving the accuracy of compaction quality assessments and the timeliness of settlement risk warnings, forming a closed-loop "monitoring-assessment-decision-making" control system. This approach effectively addresses the lag and reliance on experience inherent in traditional manual sampling and testing, reducing rework rates and providing intelligent, visual, and scientific construction support for urban integrated pipeline corridor projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic diagram of the workflow of the present invention; Figure 2 This is a cross-sectional view of the sensor arrangement in the present invention; Figure 3 This is a longitudinal cross-sectional view of the sensor arrangement in the present invention; In the figure: 1- pore pressure gauge, 2- dynamic pressure sensor, 3- sedimentation meter, 4- laser rangefinder, 5- nuclear density meter. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0027] In the description of the present invention, it should be noted that the terms "upper", "lower", "left", "right", "inside", "outside", etc. indicate directions or positional relationships based on the directions or positional relationships shown in the accompanying drawings, or are directions or positional relationships in which the inventive product is usually placed when in use. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, they should not be understood as limiting the present invention.

[0028] In this embodiment, a monitoring system for layered backfill of a rectangular pipeline corridor includes a data acquisition module, a data processing and modeling unit, a central processing unit, an evaluation and decision support unit, and a user interface and visualization unit, wherein: like Figure 2-3 As shown in Figure 1, the data acquisition module receives and reads data collected by the sensor array. The acquisition frequency can be set according to the construction process, generally set to collect data immediately after each backfill layer is completed. The sensor array is deployed in a "layer-controlled + point-controlled" manner, forming a regular monitoring grid along the cross-section and longitudinal section to ensure complete coverage of key locations for data collection. The sensor array specifically includes a pore pressure gauge 1, a dynamic pressure sensor 2, a sedimentation meter 3, a laser rangefinder 4, and a nuclear density meter 5. The pore pressure gauge 1 and dynamic pressure sensor 2 are used to collect soil loads, while the dynamic pressure sensor 2 also records the number of mechanical compactions and the applied pressure energy per unit area. The nuclear density meter 5 is placed in the topmost soil layer to measure the dry density and moisture content of the backfill soil. The wet bulk density (wet bulk density = dry density × (1 + moisture content)) is calculated from the dry density and moisture content. The units of wet bulk density and dry density are both kN / m³. The pore pressure gauge 1 and dynamic pressure sensor 2 are laid in an array on the i-th layer of soil. The settlement meter 3 is vertically inserted from the i+1-th layer of soil, penetrating the i+1-th layer and the i-th layer of soil. The laser rangefinder 4 and the settlement meter 3 are used to record the local settlement changes during the backfill process. The position of the laser rangefinder 4 needs to be set according to the on-site working conditions.

[0029] The data processing and modeling module is used to normalize and filter the data collected by the sensor array. The processed data is input into the modeling module, namely the compaction evolution model and the local settlement prediction model; the compaction evolution model is used to derive the compaction of the i-th layer of backfill at time t. , a time-stress coupling analysis is constructed based on compaction energy, dry density, external load and soil layer thickness; a local settlement prediction model is used to derive the settlement evolution curve of the backfill area based on the consolidation coefficient, compression modulus, layer thickness and external load ; The central processing unit is used to receive processed data and output control commands and construction adjustment suggestions; The evaluation and decision support module includes an evaluation model submodule and a decision support submodule. The evaluation model submodule calculates the quality standard value based on the calculation results of the modeling submodule and historical data, and obtains the evaluation result by comparing it with the quality grade evaluation table set in the system (as shown in Table 1 below); the decision support submodule is used to provide a visual report, presenting the evaluation curve, risk level and construction optimization suggestions for on-site management.

[0030] Table 1 Quality Grade Evaluation Table

[0031] The user interface and visualization module includes a data display submodule and a report generation submodule; the data display submodule is used to display the backfill compaction assessment value through a three-dimensional graphical interface and settlement prediction value and linked with BIM or GIS platform; the report generation submodule is used to output construction logs, early warning records and quality assessment reports, and visualize the results output by the assessment and decision support units.

[0032] like Figure 1 As shown, in this embodiment, a method for monitoring layered backfill soil in a rectangular pipe gallery includes the following steps: S1. Selection of monitoring area: Delineate the monitoring section for layered backfilling based on the tunnel structure; S2. Monitoring point layout: Before backfilling each layer, the sensor array is laid out along the cross section and longitudinal section of the corridor according to the grid rule; S3. Benchmark data collection: Collect the benchmark parameters of the original soil and the first layer of backfill soil, and verify the accuracy; S4, real-time data collection and transmission: After each backfill layer is completed, the measured parameters of the backfill soil layer are collected in real time, compared with the benchmark data collected in step S3, and uploaded to the central processing unit after accuracy verification; S5. Data processing and dynamic evaluation: Based on the data uploaded in real time in step S4, after pre-processing, it is input into the compaction evolution model and local settlement prediction model for calculation, and a layered quality score is generated and associated with the grade table to output construction recommendations.

[0033] Further: in S3, the benchmark parameters include porosity, compression modulus, additional stress, initial stress, and external load data; In S4, the measured parameters include: dry density, moisture content, settlement, number of rolling times and external load data.

[0034] Further: In step S5, the compaction degree evolution model formula is:

[0035] Where, tis the time in seconds; It is i The compaction degree of backfill soil at time t; is the initial density of the undisturbed soil; It is j External load above the backfill layer, in Pa; It is j The thickness of the backfill soil layer, in cm; K j is the soil consolidation coefficient, which is 5×10 based on the soil type being silty clay. -8 ; It is j The incremental density coefficient of the backfill soil is 3×10 -7 ; It is j Additional stress of backfill soil, unit is Pa; i is the soil layer currently being calculated, j It is the upper soil layer that affects the current soil layer. i and j The relationship is: j Soil layer range: numbered from the surface downwards ( j= 1 is the top layer), until the target layer i The layer directly above j=1 arrive j=i-1 ).

[0036] For example: When calculating the i= At 3 layers, j It is necessary to traverse the 1st and 2nd layers above it.

[0037] j right i Impact of: Upper soil ( j The load, thickness, and soil parameters of the layer will be transferred to the lower soil ( i layer).

[0038] in, K j and It is pre-calibrated through indoor geotechnical tests (the calibration basis in this embodiment is indoor consolidation tests) and stored in the central processing unit parameter database. It is automatically matched according to the soil layer type during construction and supports revision.

[0039] It should be noted that K i The value range is 1×10 -8 ~1×10 -5 ; The value range is 1×10 -8 ~7×10 -7 In other embodiments, for example, if the soil layer type is a medium sand layer, then K i The value of is 1×10 -6 , The value of is 5×10 -8 .

[0040] Further: In step S5, the local settlement prediction model formula is:

[0041] Where, t is the time in seconds; It's time t The predicted amount of backfill settlement at 1 hour, in cm; is the compression coefficient of the i-th layer of backfill soil, which is 2×10 based on the soil type being silty clay. -5 ; It is i The thickness of the backfill soil layer, in cm; It is i The initial stress above the backfill layer, in Pa; It is i External load above the backfill layer, in Pa; K i is the soil consolidation coefficient, which is 5×10 based on the soil type being silty clay. -8 ; is the correction factor for adjusting the influence of external loads, and its value is 1×10 -7 ; It is i Layers of backfill soil over time t Variable external load, in Pa; K i The value range is 1×10 -8 ~1×10 -5 ; The value range is 1×10 -6 ~1×10 -4 ; The value range is 8×10 -9 ~3×10 -7 In other embodiments, the soil layer type is medium sand, then The value of is 5×10 -6 , The value of is 1×10 -6 , The value of is 3×10 -8 .

[0042] K i and It is pre-calibrated through indoor geotechnical tests and stored in the central processing unit parameter database. It is automatically matched according to the soil type during construction and supports revisions.

[0043] Further: In step S5, the hierarchical quality score is obtained by the following formula:

[0044] Where, t is the time in seconds; is the quality score; It is i The ratio of the target value to the actual value of the backfill soil compaction degree; It is i The layout ratio of the target value and actual value of the backfill soil settlement; is the control coefficient The sum is 1.

[0045] in: Calculated according to the following formula:

[0046] Where, t is the time in seconds; is the target value of compaction; It is i Backfill soil layer at time t Backfill soil compaction degree at 10 ... Calculated according to the following formula:

[0047] Where, t is the time in seconds; is the actual measurement of settlement, in cm; It's time t The predicted amount of backfill settlement at 1 hour, in cm; is the error value, the error value The value is 0.8.

[0048] Further: also including step S6: The layered quality scoring results and grade table are presented as an evaluation curve, and the evaluation curve, risk level, and construction recommendations are visualized and output.

[0049] Furthermore: the data collection frequency in step S4 is to start immediately after each layer of backfill is completed, and dynamic pressure data is collected every 5-10 minutes during the operation of the rolling machine.

[0050] Further: P j(t) Calculated according to the following formula:

[0051] Where, For the k Wet bulk density of backfill soil, in kN / m 3 ; For the k Thickness of backfill layer; Calculated according to the following formula:

[0052] Where, Q is the concentrated load, in N; R is the diffusion influence radius, in cm; The attenuation factor is based on the distance: for every meter away, the attenuation factor decreases by 0.2-0.3; the minimum attenuation factor: when the attenuation factor value is less than 0.1, it is set to 0.1 (to avoid infinitesimal values); Further: Calculated according to the following formula:

[0053] Where, It is j Wet bulk density of the soil layer, in kN / m 3 ; yes j Layer thickness, in cm; Calculated according to the following formula:

[0054] Where, is the natural porosity, expressed in%; is the compression modulus, in Pa.

[0055] The following experiment was conducted using the monitoring system and monitoring method of the present invention: the experimental site was a rectangular tunnel foundation pit with a cross-section of approximately 3.0 m × 2.5 m. Medium sand and silty clay were used as backfill materials. The first to third layers of backfill soil were medium sand, silty clay, and medium sand, respectively. The moisture content was controlled at 8%–12%. The thickness of each soil layer was approximately 30 cm, and each layer was rolled 6–8 times. The monitoring point was arranged at the center of the wheel track. A nuclear densitometer was used to measure the dry density and moisture content. A dynamic pressure sensor recorded the contact pressure, a pore water pressure gauge monitored the excess pore pressure, and a settlement meter / laser rangefinder tracked the accumulated settlement. The dynamic pressure sensor also synchronously obtained the number of rolling passes. All sensors were recorded in a 30-second interval. In order to automatically collect and upload data at sampling intervals, the system calculates the layer compaction degree (D1, D2, D3), layer settlement (S1, S2, S3) and comprehensive score (the comprehensive score is the average of the layer scores) in real time according to the set formula, thereby realizing dynamic monitoring and evaluation of the layered backfill compaction quality. The experimental results are shown in Tables 1 and 2 below.

[0056] Table 1

[0057] Table 2

[0058] Although this specification is described according to implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

[0059] Therefore, the above description is only a preferred embodiment of the present application and is not intended to limit the scope of implementation of the present application; that is, all equivalent modifications made according to the scope of the claims of the present application are within the scope of protection of the claims of the present application.

Claims

1. A method for monitoring layered backfill soil in a rectangular pipeline gallery, characterized in that: The following steps are involved: S1. Delineate the monitoring section for layered backfilling based on the tunnel structure; S2. Before backfilling each layer, the sensor array is laid out along the cross section and longitudinal section of the corridor according to the grid rule; S3. Collect the baseline parameters of the original soil and the first layer of backfill soil, and verify their accuracy; S4. After each backfill layer is completed, the measured parameters of the backfill soil layer are collected in real time, compared with the benchmark data collected in step S3, and uploaded to the central processing unit after accuracy verification; S5. Based on the data uploaded in real time in step S4, after pre-processing, the data is input into the compaction evolution model and the local settlement prediction model to generate a layered quality score and output construction recommendations by associating it with the grade table; In S5, the compaction degree evolution model formula is: Where, t is the time in seconds; D i(t) It is i Backfill soil layer at time t Backfill soil compaction degree at the time of D measured(t) is the initial density of the undisturbed soil; P j(t) It is j External load above the backfill layer, in Pa; H j It is j The thickness of the backfill soil layer, in cm; K j is the soil consolidation coefficient; α j It is j Incremental density coefficient of backfill soil; δP j It is j The additional stress of the backfill soil layer, in Pa; i Indicates the current backfill layer. j For the i All soil layers above the first layer of backfill; in, K j and α j It is pre-calibrated through indoor geotechnical tests and stored in the central processing unit parameter database. It is automatically matched according to the soil type during construction and supports revisions.

2. The rectangular pipeline gallery layered backfill soil monitoring method according to claim 1 is characterized in that: In S3, the benchmark parameters include porosity, compression modulus, additional stress, initial stress, and external load; In S4, the measured parameters include: dry density, moisture content, settlement, number of rolling times and external load.

3. The rectangular pipeline gallery layered backfill soil monitoring method according to claim 1 is characterized in that: In S5, the local settlement prediction model formula is: Where, t is the time in seconds; It's time t The predicted amount of backfill settlement at 1 hour, in cm; It is i Compression coefficient of backfill soil; It is i The thickness of the backfill soil layer, in cm; It is i The initial stress above the backfill layer, in Pa; It is i External load above the backfill layer, in Pa; K i is the soil consolidation coefficient; is the correction factor to adjust for the effects of external loads; It is i Layers of backfill soil over time t Variable external load, in Pa; K i and It is pre-calibrated through indoor geotechnical tests and stored in the central processing unit parameter database. It is automatically matched according to the soil type during construction and supports revisions.

4. The rectangular pipeline gallery layered backfill soil monitoring method according to claim 1 is characterized in that: In S5, the hierarchical quality score is obtained by the following formula: Where, t is the time in seconds; is the quality score; It is i The ratio of the target value to the actual value of the backfill soil compaction degree; It is i The layout ratio of the target value and actual value of the backfill soil settlement; is the control coefficient The sum is 1. in: D i * (t) Calculated according to the following formula: Where, t is the time in seconds; is the target compaction value; It is i Backfill soil layer at time t Backfill soil compaction degree at the time of Calculated according to the following formula: Where, t is the time in seconds; is the actual measurement of settlement, in cm; It's time t The predicted amount of backfill settlement at 1 hour, in cm; is the error value.

5. The rectangular pipeline gallery layered backfill soil monitoring method according to claim 1 is characterized in that: The step S6 is also included: The layered quality scoring results and grade table are presented as an evaluation curve, and the evaluation curve, risk level, and construction recommendations are visualized and output.

6. The rectangular pipeline gallery layered backfill soil monitoring method according to claim 1 is characterized in that: The data collection frequency in step S4 is to start immediately after each layer of backfill is completed, and dynamic pressure data is collected every 5-10 minutes during the operation of the rolling machine.

7. The rectangular pipeline gallery layered backfill soil monitoring method according to claim 3 is characterized in that: P j(t) Calculated according to the following formula: Where, For the k Wet bulk density of backfill soil, in kN / m 3 ; For the k The thickness of the backfill layer, in cm; δP j Calculated according to the following formula: Where, Q It is i The concentrated load above the backfill layer, in N; R is the diffusion influence radius, in cm; η(Z j ) is the attenuation factor.

8. The rectangular pipeline gallery layered backfill soil monitoring method according to claim 4 is characterized in that: Calculated according to the following formula: Where, It is j Wet bulk density of the soil layer, in kN / m 3 ; It is j Thickness of soil layer, in cm; C i Calculated according to the following formula: Where, is the natural porosity, expressed in%; is the compression modulus, in Pa.

9. The monitoring system used in the rectangular pipeline gallery layered backfill monitoring method according to any one of claims 1 to 8, characterized in that: include: Data acquisition module, which includes pore pressure gauge, dynamic pressure sensor, sedimentation meter, laser rangefinder, and nuclear density meter; The data processing and modeling module is used to normalize and filter the data collected by the sensor array and build a compaction evolution model and a local settlement prediction model; The central processing unit is used to receive processed data and output control commands and construction adjustment suggestions; The evaluation and decision support module is used to generate hierarchical quality scores based on the output of the data processing and modeling unit and output construction recommendations in association with the grade table; The user interface and visualization module is used to visualize the results output by the evaluation and decision support unit.

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