Roadbed state sensing and active reinforcement system and method based on dynamic stress monitoring
By combining a distributed sensing module and an intelligent analysis and early warning module, the condition of the subgrade soil is monitored in real time and early warning information is generated. The active reinforcement execution module is used for grouting and drainage, which solves the problems of slow response and lack of reinforcement measures in the existing technology, and realizes efficient subgrade condition perception and active reinforcement.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HENAN POLYTECHNIC UNIV
- Filing Date
- 2026-03-25
- Publication Date
- 2026-06-09
Smart Images
Figure CN122169483A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of roadbed condition sensing and maintenance, and in particular to a roadbed condition sensing and active reinforcement system and method based on dynamic stress monitoring. Background Technology
[0002] As the core load-bearing layer and basic support of the road engineering structure system, the long-term service stability of the roadbed is directly related to driving safety and comfort and the service life of the road throughout its entire life cycle.
[0003] During highway operation, vehicle loads act continuously on the road surface in the form of cyclic dynamic loads, which are transmitted from top to bottom through the structural layers to the subgrade soil. This causes reciprocating shearing between soil particles, inducing cumulative dynamic shear stress. When the amplitude of this dynamic shear stress gradually approaches or even exceeds the ultimate shear strength of the subgrade soil, irreversible damage will occur to the internal granular skeleton structure of the soil, manifested as the continuous accumulation of plastic deformation, a decrease in effective soil stress, and progressive softening of strength. If such damage is left unaddressed for a long period, it will further lead to uneven subgrade settlement, local bulging, or even overall slippage and instability, seriously threatening road operation safety.
[0004] Meanwhile, heavy rainfall, as a typical adverse environmental factor during the service life of roadbeds, significantly exacerbates the damage evolution process and may even induce sudden damage changes. When heavy rainfall occurs, rainwater seeps into the roadbed soil through pavement cracks, shoulder gaps, or surface pores, triggering a multi-faceted chain reaction of damage. Rainwater infiltration causes a sharp increase in the water content of the roadbed soil, leading to a significant decrease in the cohesion between soil particles and a significant increase in pore water pressure. This further reduces the effective stress of the soil—which, combined with the effective stress reduction effect caused by cyclic dynamic loading of vehicles, accelerates the gradual softening of soil strength, causing a rapid decline in the ultimate shear strength of the roadbed soil.
[0005] Therefore, monitoring the condition of the roadbed is crucial to ensuring operational safety. However, existing roadbed monitoring technologies are mostly focused on surface displacement, settlement, or static earth pressure monitoring, and lack the ability to proactively intervene in conjunction with reinforcement measures. Even after problems are discovered, manual intervention is still required, resulting in slow response and low efficiency.
[0006] This method of roadbed condition perception and active reinforcement based on dynamic stress monitoring and intelligent early warning achieves full-area coverage monitoring through distributed sensing modules. Compared with existing single-point monitoring, it has a wider monitoring range and faster data timeliness. The constitutive model based on water content coupling calculates the safety factor with higher early warning accuracy compared with traditional static models. The closed-loop active reinforcement logic shortens the time for roadbed instability handling, and is more efficient than traditional passive repairs, while also saving on reinforcement materials. This method can be adapted to different geological conditions (silty clay / sandy soil roadbeds) and different load types (traffic loads / precipitation loads), solving the problem of the "one-size-fits-all" approach in existing reinforcement schemes.
[0007] Therefore, there is an urgent need in this field for an integrated solution that can directly and in real time perceive the key mechanical states (shear stress and shear strength) inside the subgrade soil, and can carry out intelligent early warning and reinforcement based on this. Summary of the Invention
[0008] The present invention aims to at least partially solve one of the technical problems existing in the related art.
[0009] The purpose of this invention is to provide an integrated solution that can directly and in real time perceive the key mechanical state inside the subgrade soil and perform intelligent early warning and reinforcement based on this.
[0010] To achieve the above objectives, the present invention provides a roadbed condition sensing and active reinforcement system based on dynamic stress monitoring, comprising:
[0011] The distributed sensing module is embedded in the roadbed and is used to collect the mechanical state parameters and environmental parameters of the roadbed soil in real time.
[0012] The intelligent analysis and early warning module is communicatively connected to the distributed sensing module. It is used to receive and analyze the data collected by the distributed sensing module and generate corresponding instructions based on the analysis results. The instructions include sending early warning information, which includes the causes of risk, the characteristics of the soil and rock mass in the unstable area, and the deformation trend.
[0013] The active reinforcement execution module is embedded in the roadbed and communicates with the intelligent analysis and early warning module to generate and execute a roadbed reinforcement plan based on the early warning information.
[0014] A further preferred embodiment of the present invention is that the distributed sensing module is buried at key monitoring points and typical geological interfaces at different depths of the roadbed.
[0015] Preferably, the roadbed mechanical state includes dynamic shear stress, pore water pressure, and soil strain; the environmental parameters include temperature, humidity, and moisture content.
[0016] Preferably, the intelligent analysis and early warning module includes a data preprocessing unit, a shear strength analysis unit, a stability criterion model, and an early warning decision unit, wherein...
[0017] The data preprocessing unit is used to reduce noise, calibrate, and perform spatiotemporal registration on the collected data to ensure the validity and consistency of the input data.
[0018] The shear strength analysis unit is based on the modified dynamic constitutive model of soil and combines real-time monitoring data to invert the dynamic shear strength parameters of the subgrade soil, and quantifies the degree of soil strength deterioration under dynamic load cycles.
[0019] The stability criterion model introduces an evaluation index based on the roadbed stability safety factor to achieve accurate identification of the roadbed's service status;
[0020] The early warning decision-making unit automatically generates graded early warning information and emergency response suggestions based on the stability evaluation results and the disease risk level classification standards.
[0021] Preferably, the active hardening execution module includes a hardening execution mechanism and a control unit, wherein,
[0022] The reinforcement actuator is a distributed grouting drainage anchor bolt, which is horizontally buried in key parts of the roadbed for roadbed drainage and grouting reinforcement;
[0023] The control unit is used to control the reinforcement actuator to drain or grout the roadbed based on the early warning information.
[0024] Preferably, the distributed grouting drainage anchor includes an anchor body and a tapered protrusion fixedly connected to one end of the anchor body and deeply buried in the roadbed, with the end of the anchor body away from the protrusion protruding from the roadbed.
[0025] The anchor rod body is provided with a hollow grouting channel and several drainage channels. Multiple grouting ports and multiple drainage ports are arranged in a ring around the outer periphery of the anchor rod body. All grouting ports are connected to the grouting channels, and the drainage channels are connected to their corresponding drainage ports. The ends of the grouting and drainage channels away from the protrusions protrude from the anchor rod body and are respectively provided with drainage channel connection ports and grouting channel connection ports for outward drainage and inward grouting, respectively. A filter screen is fixed at each drainage port.
[0026] Another aspect of the present invention provides a method for roadbed condition sensing and active reinforcement based on dynamic stress monitoring, comprising the following steps:
[0027] S1. Real-time acquisition of mechanical state parameters and environmental parameters of the subgrade soil, and preprocessing thereof; the subgrade mechanical state includes dynamic shear stress, pore water pressure and soil strain; the environmental parameters include temperature, humidity and moisture content;
[0028] S2. Based on the preprocessed data, the safety factor of roadbed stability is calculated using the physical and mechanical constitutive relationship of the roadbed soil, and compared with the preset critical threshold.
[0029] S3. When the roadbed stability safety factor is lower than the system's preset critical threshold, an early warning message is issued, including the causes of the risk, the characteristics of the soil and rock mass in the unstable area, and the deformation trend.
[0030] S4. Generate a reinforcement plan based on the warning information, and carry out drainage or grouting reinforcement of the roadbed;
[0031] S5. Repeat steps S1-S4 until the roadbed stability safety factor is restored to a safe state.
[0032] Preferably, step S2 calculates the roadbed stability safety factor based on the preprocessed data and the physical and mechanical constitutive relationship of the roadbed soil, specifically as follows:
[0033] (1) Calculate the real-time shear strength of the roadbed :
[0034]
[0035] Where c(ω) is the cohesion related to water content, σ is the normal stress, φ(ω) is the internal friction angle related to water content, and ω is the water content of the soil;
[0036] The formula relating cohesion and moisture content is:
[0037]
[0038] in, The fitted value of cohesion when the moisture content is 0, where k is the moisture content attenuation coefficient of cohesion;
[0039] The fitting formula for the internal friction angle φ and the moisture content ω:
[0040]
[0041] in, is the internal friction angle corresponding to the optimum moisture content; b is the attenuation coefficient of the tangent of the internal friction angle.
[0042] (2) Calculate the dynamic shear stress of the roadbed :
[0043]
[0044] in, This is the dynamic stress concentration factor. The dynamic contact pressure is given by r, the contact radius by β, the vibration angular frequency by t, and time by t.
[0045] Taking the peak time βt = π / 2, the formula simplifies to: =2 × ×r.
[0046] (3) Obtain the stability safety factor of the roadbed :
[0047] .
[0048] Beneficial effects: This invention achieves real-time perception of the key mechanical state inside the subgrade soil through the coordinated operation of a distributed sensing module, an intelligent analysis and early warning module, and an active reinforcement execution module, and performs intelligent early warning and reinforcement based on this. Attached Figure Description
[0049] Figure 1 This is an overall framework diagram of a roadbed condition sensing and active reinforcement system based on dynamic stress monitoring provided in Embodiment 1 of the present invention.
[0050] Figure 2 This is a structural diagram of the distributed grouting drainage anchor provided in Embodiment 1 of the present invention.
[0051] Figure 3 This is a schematic cross-sectional view of the distributed grouting drainage anchor provided in Embodiment 1 of the present invention.
[0052] Figure 4 This is a flowchart of a roadbed condition sensing and active reinforcement method based on dynamic stress monitoring provided in Embodiment 2 of the present invention.
[0053] The components include: 1. Distributed sensing module; 2. Active reinforcement execution module; 3. Intelligent analysis and early warning module; 4. Drainage channel connection port; 5. Grouting pump connection joint; 6. Rod body; 7. Conical guide head; 8. Grouting channel; 9. Drainage channel; 10. Grouting port; 11. Drainage port. Detailed Implementation
[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, embodiments of this invention, and should not be construed as limiting the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention. In the description of this invention, it should be understood that the terminology used is for descriptive purposes only and should not be construed as indicating or implying relative importance.
[0055] The following is combined Figures 1-4This invention describes a roadbed condition sensing and active reinforcement system and method based on dynamic stress monitoring.
[0056] Example 1: As Figure 1 As shown, this embodiment provides a roadbed condition perception and active reinforcement system based on dynamic stress monitoring, including: a distributed sensing module 1, an intelligent analysis and early warning module 3, and an active reinforcement execution module 2.
[0057] The distributed sensing module 1 includes a dynamic shear stress sensor array, a pore pressure sensor, a soil strain gauge, and environmental auxiliary sensors. These are buried at key monitoring points at different depths in the roadbed (such as the core area of load transfer and easily deformable parts) and at typical stratum interfaces to ensure close contact between the sensors and the soil, thus guaranteeing data acquisition accuracy. The module is used to collect in real time the dynamic shear stress, pore water pressure, soil strain, and other mechanical state parameters of the roadbed soil, as well as environmental auxiliary parameters such as temperature, humidity, and moisture content.
[0058] The intelligent analysis and early warning module 3, communicating with the distributed sensing module, focuses on dynamic assessment of roadbed stability and early warning of road defects. It comprises four core functional units: a data preprocessing unit, a shear strength analysis unit, a stability criterion model, and an early warning decision unit. The data preprocessing unit is responsible for noise reduction, calibration, and spatiotemporal registration of multi-source monitoring data (stress, strain, moisture content, etc.) collected by the distributed sensing module, ensuring the validity and consistency of the input data. The shear strength analysis unit, based on a modified dynamic constitutive model of the soil, combines real-time monitoring data (such as pore water pressure and strain) to invert the dynamic shear strength parameters of the roadbed soil, quantifying the degree of soil strength degradation under dynamic load cycles. The stability criterion model introduces an evaluation index based on the roadbed stability safety factor to accurately determine the service status of the roadbed. The early warning decision unit, based on the stability evaluation results and according to the disease risk level classification standards, automatically generates graded early warning information and emergency response suggestions. The early warning information includes the causes of risk, the characteristics of the soil and rock in the unstable area, and the deformation trend. On the other hand, it sends parameter configuration and sampling frequency adjustment commands to the sensing module, forming an operation mechanism of "data acquisition - analysis and evaluation - early warning decision - issuing commands".
[0059] The active hardening execution module 2 and the intelligent analysis and early warning module are linked via a wired network, automatically activating upon receiving an early warning signal. This includes:
[0060] Strengthening the implementing agency: such as Figures 2-3As shown, a distributed grouting drainage anchor is designed. During construction, the anchor is horizontally deployed at key locations in the roadbed. One end has a conical protrusion 7 that extends deep into the roadbed, while the other end, away from the conical protrusion 7, protrudes from the roadbed. A grouting channel 8 is formed through the middle of the anchor body 6. Four drainage channels 9 are evenly distributed in a ring around the grouting channel 8. The ends of the grouting channel 8 and drainage channels 9, away from the conical protrusion 7, protrude from the anchor body, serving as drainage channel connection ports 4 and grouting pump connection joints 5, respectively. Multiple grouting ports 10 and multiple drainage ports 11 are formed in a ring around the outer periphery of the grouting channel 8 and drainage channels 9. All grouting ports 10 are connected to the grouting channel 8, and each drainage channel 9 is connected to a corresponding drainage port 11. A filter screen with a mesh size of 0.2 mm is fixed at each drainage port 11.
[0061] In other embodiments, the number of drainage channels is set according to the actual situation.
[0062] Control unit: Based on the warning signal, controls the working mode and intensity of the reinforcement actuator. For example, when the warning signal is triggered under heavy load, grouting reinforcement is initiated; while when the warning signal is triggered under heavy rainfall, comprehensive grouting and drainage measures are initiated.
[0063] When the subgrade soil experiences shear strain concentration due to load and requires increased strength, a precast grout, such as cement grout or cement mortar, is injected into the soil through the grouting channel 8 via the grouting pump connector 5 connected to the anchor head of an external grouting pump. The grout is evenly diffused into the pores of the soil through the grouting port 10. After the grout solidifies, the subgrade soil is reinforced, improving its shear strength and stability. When heavy rainfall or other factors cause an increase in pore water pressure and a decrease in effective stress in the soil, water in the subgrade soil is discharged to the external drainage system through the drainage port 11 into the drainage channel 9. This reduces the pore water pressure in the soil, restores the effective stress, and ensures soil stability.
[0064] Example 2: Figure 4 As shown in the figure, this embodiment provides a method for roadbed condition sensing and active reinforcement based on dynamic stress monitoring, including the following steps:
[0065] S1. Real-time acquisition of mechanical state parameters (dynamic shear stress, pore water pressure, and soil strain) and environmental parameters (temperature, humidity, and moisture content) of the subgrade soil, and preprocessing them; the preprocessing specifically involves: noise reduction, calibration, and spatiotemporal registration of the multi-source monitoring data such as stress, strain, and moisture content acquired by the distributed sensing module to ensure the validity and consistency of the input data.
[0066] S2. Based on the preprocessed data, the safety factor of roadbed stability is calculated using the physical and mechanical constitutive relationship of the roadbed soil, and compared with the preset critical threshold.
[0067] (1) Calculate the real-time shear strength of the roadbed :
[0068]
[0069] Where c(ω) is the cohesion related to water content, σ is the normal stress, φ(ω) is the internal friction angle related to water content, and ω is the water content of the soil;
[0070] The formula relating cohesion and moisture content is:
[0071]
[0072] in, The fitted value of cohesion when the moisture content is 0, where k is the moisture content attenuation coefficient of cohesion;
[0073] The fitting formula for the internal friction angle φ and the moisture content ω:
[0074]
[0075] in, is the internal friction angle corresponding to the optimum moisture content; b is the attenuation coefficient of the tangent of the internal friction angle.
[0076] (2) Calculate the dynamic shear stress of the roadbed :
[0077]
[0078] in, This is the dynamic stress concentration factor. The dynamic contact pressure is given by r, the contact radius by β, the vibration angular frequency by t, and time by t.
[0079] Taking the peak time βt = π / 2, the formula simplifies to: =2 × ×r.
[0080] (3) Obtain the stability safety factor of the roadbed :
[0081] .
[0082] S3. When the roadbed stability safety factor is lower than the system's preset critical threshold, an early warning message is issued, including the causes of the risk, the characteristics of the soil and rock mass in the unstable area, and the deformation trend.
[0083] S4. Generate a reinforcement plan based on the warning information, and carry out drainage or grouting reinforcement of the roadbed;
[0084] S5. Repeat steps S1-S4 until the roadbed stability safety factor is restored to a safe state.
[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A roadbed condition sensing and active reinforcement system based on dynamic stress monitoring, characterized in that, include: The distributed sensing module is embedded in the roadbed and is used to collect the mechanical state parameters and environmental parameters of the roadbed soil in real time. The intelligent analysis and early warning module is communicatively connected to the distributed sensing module. It is used to receive and analyze the data collected by the distributed sensing module and generate corresponding instructions based on the analysis results. The instructions include sending early warning information, which includes the causes of risk, the characteristics of the soil and rock mass in the unstable area, and the deformation trend. The active reinforcement execution module is embedded in the roadbed and communicates with the intelligent analysis and early warning module to generate and execute roadbed reinforcement schemes based on early warning information.
2. The roadbed condition sensing and active reinforcement system based on dynamic stress monitoring according to claim 1, characterized in that, The distributed sensing modules are buried at key monitoring points and typical geological interfaces at different depths of the roadbed.
3. The roadbed condition sensing and active reinforcement system based on dynamic stress monitoring according to claim 1, characterized in that, The subgrade mechanical state includes dynamic shear stress, pore water pressure, and soil strain; the environmental parameters include temperature, humidity, and moisture content.
4. The roadbed condition sensing and active reinforcement system based on dynamic stress monitoring according to claim 1, characterized in that, The intelligent analysis and early warning module includes a data preprocessing unit, a shear strength analysis unit, a stability criterion model, and an early warning decision unit. The data preprocessing unit is used to reduce noise, calibrate, and perform spatiotemporal registration on the collected data to ensure the validity and consistency of the input data. The shear strength analysis unit is based on the modified dynamic constitutive model of soil and combines real-time monitoring data to invert the dynamic shear strength parameters of the subgrade soil, and quantifies the degree of soil strength deterioration under dynamic load cycles. The stability criterion model introduces an evaluation index based on the roadbed stability safety factor to achieve accurate identification of the roadbed's service status; The early warning decision-making unit automatically generates graded early warning information and emergency response suggestions based on the stability evaluation results and the disease risk level classification standards.
5. The roadbed condition sensing and active reinforcement system based on dynamic stress monitoring according to claim 1, characterized in that, The active hardening execution module includes a hardening execution mechanism and a control unit, wherein... The reinforcement actuator is a distributed grouting drainage anchor bolt, which is horizontally buried in key parts of the roadbed for roadbed drainage and grouting reinforcement; The control unit is used to control the reinforcement actuator to drain or grout the roadbed based on the early warning information.
6. The roadbed condition sensing and active reinforcement system based on dynamic stress monitoring according to claim 5, characterized in that, The distributed grouting drainage anchor includes an anchor body and a tapered protrusion that is fixedly connected to one end of the anchor body and deeply buried in the roadbed. The end of the anchor body away from the protrusion protrudes from the roadbed. The anchor rod body is provided with a hollow grouting channel and several drainage channels. Multiple grouting ports and multiple drainage ports are arranged in a ring around the outer periphery of the anchor rod body. All grouting ports are connected to the grouting channels, and the drainage channels are connected to their corresponding drainage ports. The ends of the grouting and drainage channels away from the protrusions protrude from the anchor rod body and are respectively provided with drainage channel connection ports and grouting channel connection ports for outward drainage and inward grouting, respectively. A filter screen is fixed at each drainage port.
7. A method for roadbed condition sensing and active reinforcement based on dynamic stress monitoring, using the system described in any one of claims 1-6, characterized in that, Includes the following steps: S1. Real-time acquisition of mechanical state parameters and environmental parameters of the subgrade soil, and preprocessing thereof; the subgrade mechanical state includes dynamic shear stress, pore water pressure and soil strain; the environmental parameters include temperature, humidity and moisture content; S2. Based on the preprocessed data, the safety factor of roadbed stability is calculated using the physical and mechanical constitutive relationship of the roadbed soil, and compared with the preset critical threshold. S3. When the roadbed stability safety factor is lower than the system's preset critical threshold, an early warning message is issued, including the causes of the risk, the characteristics of the soil and rock mass in the unstable area, and the deformation trend. S4. Generate a reinforcement plan based on the warning information, and carry out drainage or grouting reinforcement of the roadbed; S5. Repeat steps S1-S4 until the roadbed stability safety factor is restored to a safe state.
8. The method for roadbed condition sensing and active reinforcement based on dynamic stress monitoring according to claim 7, characterized in that, Step S2, based on the preprocessed data, calculates the roadbed stability safety factor using the physical and mechanical constitutive relationship of the roadbed soil. Specifically: (1) Calculate the real-time shear strength of the roadbed : Where c(ω) is the cohesion related to water content, σ is the normal stress, φ(ω) is the internal friction angle related to water content, and ω is the water content of the soil; The formula relating cohesion and moisture content is: in, The fitted value of cohesion when the moisture content is 0, where k is the moisture content attenuation coefficient of cohesion; The fitting formula for the internal friction angle φ and the moisture content ω: in, is the internal friction angle corresponding to the optimum moisture content; b is the attenuation coefficient of the tangent of the internal friction angle. (2) Calculate the dynamic shear stress of the roadbed : in, This is the dynamic stress concentration factor. The dynamic contact pressure is given by r, the contact radius by β, the vibration angular frequency by t, and time by t. Taking the peak time βt = π / 2, the formula simplifies to: =2 × ×r. (3) Obtain the stability safety factor of the roadbed. : 。