A multi-stage early warning system and method for slope revetment stability

Abstract

The application discloses a slope type revetment stability multistage early warning system and method, comprising: a distributed stress monitoring array for monitoring stress data of each part in real time; a data acquisition and transmission module in communication connection with the distributed stress monitoring array for acquiring and transmitting stress data; a data processing and risk analysis module in communication connection with the data acquisition and transmission module for receiving stress data; processing stress data and identifying an instability risk mode; a graded early warning response module in communication connection with the data processing and risk analysis module for triggering corresponding early warning levels and response instructions according to the identified instability risk mode; the application can continuously monitor stress states of key parts of a revetment, realize real-time online sensing and quantitative diagnosis of underwater hidden damage, directly associate specific damage modes with different early warning levels and disposal suggestions, and promote a change of revetment operation and maintenance to an active intelligent management mode.

Description

Technical Field

[0001] This invention relates to a multi-level early warning system and method for the stability of sloping revetments based on stress field collaborative monitoring, belonging to the field of water conservancy engineering safety monitoring technology. Background Technology

[0002] Sloping revetments are a common form of river and coastal protection engineering. The underwater sections, including the bottom and toe protection structures, directly bear the dynamic forces of water flow erosion and wave action, making them the weakest points most susceptible to damage. Because they are submerged for extended periods, their damage process is often insidious and gradual. Once instability occurs, it frequently leads to landslides on the surface, causing significant safety accidents and economic losses. Therefore, effective monitoring and early warning of the stability of the underwater sections of revetments are crucial.

[0003] Traditional manual inspections and periodic underwater topographic surveys suffer from inherent drawbacks such as long monitoring cycles, poor real-time performance, and high costs, making it difficult to detect and warn of damage processes in their early stages. To improve real-time monitoring, existing technologies employ fixed-point sensor-based methods, such as deploying inclinometers or displacement gauges. However, these methods typically trigger alarms only after visible deformation or displacement of the structure occurs, resulting in significant delays in warnings and an inability to determine the specific mode, location, and severity of damage. Summary of the Invention

[0004] The technical problem to be solved by the present invention is that the early warning is delayed and the specific mode, location and severity of the damage cannot be determined in the prior art.

[0005] To solve the above-mentioned technical problems, the present invention is implemented using the following technical solution.

[0006] On the one hand, the present invention provides a multi-level early warning system for the stability of sloping revetments, including: a distributed stress monitoring array, a data acquisition and transmission module, a data processing and risk analysis module, and a graded early warning response module;

[0007] The distributed stress monitoring array is installed at key mechanical parts of the revetment to monitor stress data at each part in real time.

[0008] The data acquisition and transmission module is communicatively connected to the distributed stress monitoring array and is used to acquire and transmit the stress data.

[0009] The data processing and risk analysis module is communicatively connected to the data acquisition and transmission module and is used to receive the stress data. The data processing and risk analysis module processes the stress data, extracts the effective earth pressure data reflecting the stress on the soil structure, and identifies instability risk patterns based on the spatiotemporal variation characteristics of the effective earth pressure data.

[0010] The graded early warning response module is communicatively connected to the data processing and risk analysis module, and is used to trigger the corresponding early warning level and response command based on the identified instability risk pattern.

[0011] By using a distributed stress monitoring network, the stress state of key parts of the revetment is continuously monitored, enabling real-time online perception and quantitative diagnosis of underwater hidden damage, making the hidden scouring process observable and quantifiable.

[0012] The key mechanical components include the bottom protection, toe protection, core protection, and water level benchmark of the revetment.

[0013] The distributed stress monitoring array includes a first pressure sensing unit deployed in the bottom protection area, a second pressure sensing unit deployed in the foot protection area, and a third pressure sensing unit deployed in the still water area at or near the top of the bottom protection. The monitoring data of the third pressure sensing unit is used to provide a benchmark for dynamic water pressure compensation calculation.

[0014] The distributed stress monitoring array also includes a multi-axis stress sensing unit deployed inside the core of the embankment for measuring the stress state of the soil in the core.

[0015] The data acquisition and transmission module includes:

[0016] Multi-channel data acquisition unit: synchronously acquires the raw analog signals of all sensing units at a set sampling frequency, and converts the raw analog signals into digital signals;

[0017] Wireless transmission terminal: A data processing and risk analysis module that packages the digital signals and transmits them in real time via a mobile network to a remote cloud server or monitoring center.

[0018] The data processing and risk analysis module includes:

[0019] A water pressure compensation calculation unit, which uses the monitoring data of the third pressure sensing unit to process the monitoring data of the first pressure sensing unit and the second pressure sensing unit, and performs dynamic water pressure compensation.

[0020] The stress tensor calculation unit calculates the magnitude of the principal stress and the principal stress direction angle of the core soil based on the measured normal stress in at least three different spatial directions and the corresponding layout direction of the multi-axis stress sensing unit, calculates the deflection angular velocity of the principal stress direction angle between adjacent time steps, and calculates the dynamic stress safety margin index in combination with the Mohr-Coulomb failure criterion.

[0021] A composite stress characterization quantity construction unit is used to construct composite stress characterization quantities, which include at least two of the following: the rate of change of effective stress after wave-permeability coupling correction, the deflection angular velocity of principal stress direction angle, the dynamic stress safety margin index, the effective stress spatial gradient modulus, and the directional parameter of the spatial gradient relative to the free surface of the revetment.

[0022] The potential slip surface inversion unit is used to determine the location of the potential slip surface based on the principal stress direction angle distribution, the spatial distribution of the composite stress characterization quantity, and the low value region of the dynamic stress safety margin index at multiple monitoring points, and to identify the abrupt change zone of the principal stress direction or the high value connecting zone of the composite stress, so as to determine the degree of slip surface development.

[0023] A risk pattern recognition unit, which makes a risk judgment based on the composite stress characterization quantity and the degree of development of potential slip surfaces.

[0024] By using dynamic water pressure compensation technology, the dominant interference of water level fluctuations on monitoring data is eliminated, greatly improving the signal-to-noise ratio and reliability of monitoring signals.

[0025] By integrating the effective stress change, principal stress direction evolution, dynamic stress safety margin, and spatial gradient characteristics of wave-seepage coupling correction, a composite stress characterization quantity is constructed. This quantity can more comprehensively reflect the degree of instability development of sloping revetments under the combined effects of scouring, seepage, and shear deformation than a single pressure threshold, single-point anomaly judgment, or single pore pressure index.

[0026] The graded early warning response module includes an early warning level determination unit, an early warning information output unit, and an engineering response linkage unit.

[0027] The early warning level determination unit automatically executes a response strategy based on the received risk pattern recognition results. When the early warning level is determined to be a primary warning, the early warning information output unit outputs a local anomaly alert. When the early warning level is determined to be a medium warning, the early warning information output unit outputs a slip crack development warning and prompts for on-site inspection. When the early warning level is determined to be a high warning, the early warning information output unit outputs a high-risk alarm, and the engineering response linkage unit simultaneously links the audible and visual alarm device, the remote monitoring platform, or the emergency response module.

[0028] The warning level determination unit uses a dynamic threshold adjustment mechanism to determine the warning trigger threshold. The dynamic threshold adjustment mechanism updates the warning trigger boundary in real time based on the historical sequence of composite stress characterization quantity, and adds a duration criterion.

[0029] Different levels of early warning are triggered based on risk patterns, composite stress characterization levels, and the development status of potential slip surfaces. The sampling frequency can be automatically increased or backup monitoring points can be activated in local abnormal areas, thus balancing the accuracy, real-time performance, and efficiency of monitoring resource utilization in early warning.

[0030] When the growth rate of the composite stress characterization quantity, the effective stress spatial gradient modulus, or the principal stress direction deflection angular velocity in a local area exceeds preset conditions, the data acquisition and transmission module increases the sampling frequency of the corresponding sensing unit to perform encrypted monitoring of the abnormal area.

[0031] Secondly, the present invention provides a method based on the aforementioned multi-level early warning system for slope revetment stability, comprising:

[0032] The distributed stress monitoring array is used to synchronously collect raw stress data of key underwater and internal parts of the revetment.

[0033] The data processing and risk analysis module uses the monitoring data of the water level benchmark area as a reference, and combines the propagation phase lag and amplitude attenuation characteristics of external wave disturbances in the revetment medium to perform hydrodynamic pressure compensation on the original pressure data of the bottom and toe areas, and obtains the wave-seepage coupling correction effective stress data of each monitoring point.

[0034] The data processing and risk analysis module calculates the magnitude and direction angle of the principal stress based on the multi-directional stress data inside the dike core, and calculates the deflection angular velocity of the principal stress direction angle and the dynamic stress safety margin index.

[0035] The data processing and risk analysis module constructs a composite stress characterization quantity to represent the degree of local instability driving of the revetment based on the change rate, spatial gradient, principal stress direction evolution characteristics, and dynamic stress safety margin index of the effective stress data corrected by wave-permeability coupling.

[0036] The data processing and risk analysis module identifies instability risk modes and inverses the development degree of potential slip surfaces based on the composite stress characterization and the spatial distribution of the principal stress direction field.

[0037] The graded early warning and response module automatically executes the corresponding graded early warning and response strategy based on the identified instability risk pattern.

[0038] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0039] This invention continuously monitors the stress state of key parts of the revetment through a distributed stress monitoring array and network, enabling real-time online perception and quantitative diagnosis of underwater hidden damage. Through a graded early warning response module, specific damage modes are directly associated with different early warning levels and handling recommendations, promoting the transformation of revetment operation and maintenance towards a proactive and intelligent management model. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the overall architecture and data flow of the multi-level early warning system for slope revetment stability shown in Embodiment 1 of the present invention;

[0041] Figure 2 This is a schematic cross-sectional view of the monitoring array layout shown in Embodiment 1 of the present invention;

[0042] Figure 3 This is a schematic diagram of the data processing and analysis module algorithm shown in Embodiment 1 of the present invention;

[0043] Figure 4 This is a schematic diagram of the composite stress characterization quantity construction process shown in Embodiment 1 of the present invention.

[0044] Figure 5 This is a schematic diagram of the multi-level early warning response relationship shown in Embodiment 1 of the present invention.

[0045] The system comprises: 1-Distributed stress monitoring array; 2-Data acquisition and transmission module; 3-Data processing and risk analysis module; 4-Graded early warning response module; 11-Bottom protection area; 12-Toe protection area; 13-Dike core interior; 14-Water level reference area; 15-First pressure sensing unit; 16-Second pressure sensing unit; 17-Third pressure sensing unit; 18-Multi-axis stress sensing unit; 21-Multi-channel data acquisition instrument; 22-Wireless transmission terminal; 31-Water pressure compensation calculation unit; 32-Stress tensor solution unit; 33-Composite stress characterization quantity construction unit; 34-Potential slip surface inversion unit; 35-Risk pattern recognition unit; 41-Early warning level determination unit; 42-Early warning information output unit; 43-Engineering response linkage unit. Detailed Implementation

[0046] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0047] Example 1

[0048] like Figure 1 As shown in the figure, this embodiment introduces a multi-level early warning system for the stability of a slope revetment, including: a distributed stress monitoring array 1, a data acquisition and transmission module 2, a data processing and risk analysis module 3, and a graded early warning response module 4;

[0049] Distributed stress monitoring array 1 is installed at key mechanical parts of the revetment to monitor stress data of each part in real time;

[0050] The data acquisition and transmission module 2 is communicatively connected to the distributed stress monitoring array 1 and is used to acquire and transmit stress data.

[0051] The data processing and risk analysis module 3 is connected to the data acquisition and transmission module 2 to receive stress data; the data processing and risk analysis module 3 processes the stress data, extracts the effective earth pressure data reflecting the stress on the soil structure, and identifies instability risk patterns based on the spatiotemporal variation characteristics of the effective earth pressure data.

[0052] The graded early warning response module 4 is connected to the data processing and risk analysis module 3 and is used to trigger the corresponding early warning level and response instructions based on the identified instability risk pattern.

[0053] Key mechanical components include the bottom protection 12, toe protection 13, core protection 16, and water level benchmark point of the revetment.

[0054] The distributed stress monitoring array 1 includes a first pressure sensing unit 15 deployed in the bottom protection area, a second pressure sensing unit 16 deployed in the foot protection area, and a third pressure sensing unit 17 deployed in the still water area at or near the top of the bottom protection. The monitoring data of the third pressure sensing unit 17 is used to provide a benchmark for dynamic water pressure compensation calculation.

[0055] The distributed stress monitoring array 1 also includes a multi-axis stress sensing unit 18 deployed inside the core of the embankment for measuring the stress state of the soil in the core of the embankment.

[0056] Specifically, such as Figure 2 As shown, the distributed stress monitoring array 1 includes a first pressure sensing unit 15, a second pressure sensing unit 16, a third pressure sensing unit 17, and a multi-axis stress sensing unit 18. All sensing units are connected to a data acquisition box on the top of the dike or on the shore via armored signal cables.

[0057] Specifically, the first pressure sensing unit 15 adopts a waterproof vibrating wire or fiber optic grating earth pressure cell, which is arranged in layers along the depth direction of the retaining wall 11 structure to directly monitor the total pressure on the retaining wall 11. The arrangement points should cover the top, middle and toe of the retaining wall 11 to monitor the uniformity of its stress distribution and local abrupt changes.

[0058] Specifically, the second pressure sensing unit 16 also uses a waterproof earth pressure cell, and is arranged in layers along the depth direction of the toe 12 structure. The arrangement points should cover the top, middle and toe of the toe 13 to monitor the uniformity of its stress distribution and local abrupt changes.

[0059] Specifically, the third pressure sensing unit 17, serving as a water pressure reference sensor, is positioned in a relatively stable still water area near the top of the bottom liner 12. This third pressure sensing unit is specifically designed to monitor changes in pure water pressure, providing a dynamic compensation reference for subsequent data processing.

[0060] Specifically, the multiaxial stress sensing unit 18 is composed of at least three earth pressure cells arranged in different spatial directions (such as vertical, downslope, and cross slope) and is embedded in a typical cross-section of the embankment core soil. This unit is used to measure the three-dimensional stress state of the embankment core soil. By solving the problem, the maximum and minimum principal stresses and their direction angles can be obtained, which is key to determining the internal stress state and potential slippage trend of the soil.

[0061] Data acquisition and transmission module 2 includes:

[0062] Multi-channel data acquisition unit 21: synchronously acquires the original analog signals of all sensing units at a set sampling frequency, and converts the original analog signals into digital signals;

[0063] Wireless transmission terminal 22: Data processing and risk analysis module 3 that packages digital signals and transmits them in real time to a remote cloud server or monitoring center via a mobile network.

[0064] Specifically, wireless transmission terminals include 4G / 5G / NB-IoT.

[0065] Data processing and risk analysis module 3 is deployed on the server, and its core functions are implemented by software algorithms, such as... Figure 3 As shown, it includes:

[0066] The water pressure compensation calculation unit 31 uses the monitoring data from the third pressure sensing unit 17 to process the monitoring data from the first pressure sensing unit 15 and the second pressure sensing unit 16, and performs dynamic water pressure compensation.

[0067] Specifically, for the third pressure sensing unit at time t k raw pressure observations First, signal attenuation and phase lag compensation are performed:

[0068]

[0069] in, This is the corrected hydrodynamic pressure. As the reference pressure signal attenuation coefficient propagating to monitoring node i, For time t k The original pressure observations, This represents the time delay corresponding to phase lag.

[0070] For any underwater monitoring node i, such as the first pressure sensing unit 15 or the second pressure sensing unit 16, its effective earth pressure after hydrodynamic pressure compensation at time t is... for:

[0071]

[0072] in, The effective earth pressure at time t after hydrodynamic pressure compensation. The pressure measured at monitoring node i.

[0073] The stress tensor calculation unit 32 calculates the magnitude of the principal stress and the principal stress direction angle of the core soil based on the measured normal stress in at least three different spatial directions and the corresponding layout direction of the multi-axis stress sensing unit 18, calculates the deflection angular velocity of the principal stress direction angle between adjacent time steps, and calculates the dynamic stress safety margin index in combination with the Mohr-Coulomb failure criterion.

[0074] Composite stress characterization quantity construction unit 33, the composite stress characterization quantity construction unit 33 adopts as follows Figure 4 The method shown constructs a composite stress characterization quantity from characteristic terms. The composite stress characterization quantity includes at least two of the following: the rate of change of effective stress after wave-permeability coupling correction, the deflection angular velocity of principal stress direction angle, the dynamic stress safety margin index, the effective stress spatial gradient modulus, and the directional parameter of the spatial gradient relative to the free surface of the revetment.

[0075] Potential slip surface inversion unit 34 is used to determine the location of potential slip surfaces based on the principal stress direction angle distribution, the spatial distribution of composite stress characterization quantity and the low value region of dynamic stress safety margin index at multiple monitoring points, and to identify the abrupt change zone of principal stress direction or the high value connected zone of composite stress, so as to determine the degree of slip surface development.

[0076] Risk pattern recognition unit 35 judges risk based on composite stress characterization and potential slip surface development.

[0077] Specifically, the data processing and risk analysis module 3 is deployed on the server, and its core functions are implemented by software algorithms, such as... Figure 3 As shown, it mainly includes a water pressure compensation calculation unit 31 and a risk pattern recognition unit 35.

[0078] Specifically, the risk pattern recognition unit 35 performs intelligent diagnosis based on the composite stress characterization and the development degree of potential slip surfaces. The risk pattern recognition unit 35 has a pre-built instability characteristic pattern library, which stores digital criteria for four typical instability modes:

[0079] 1) Criteria for bottom scouring mode: The composite stress characterization calculated by the first pressure sensing unit 15 shows a monotonically increasing trend within the duration T1 and exceeds the preset threshold F1.

[0080] 2) Foot protection flushing mode criterion: The composite stress characterization calculated by the second pressure sensing unit 16 shows a monotonically increasing trend within the duration T2 and exceeds the preset threshold F2.

[0081] 3) Criteria for abnormal seepage pressure pattern within the dike: The composite stress characterization quantity calculated by the multiaxial stress sensing unit 18 shows a monotonically increasing trend within the duration T3 and exceeds the preset threshold F3.

[0082] 4) Criterion for overall slip instability mode: The degree of development of the potential slip surface exceeds the threshold.

[0083] Specifically, the risk pattern recognition unit 35 extracts the spatiotemporal features of the current data in real time and performs rolling comparisons and similarity calculations with the criteria in the instability feature pattern library. When the matching degree between the real-time features and a certain pattern criterion exceeds the preset confidence level, the instability risk pattern is identified.

[0084] The graded early warning response module 4 includes an early warning level determination unit 41, an early warning information output unit 42, and an engineering response linkage unit 43.

[0085] The early warning level determination unit 41 automatically executes the response strategy based on the received risk pattern recognition results. When the early warning level is determined to be a primary warning, the early warning information output unit 42 outputs local anomaly prompt information; when the early warning level is determined to be a medium warning, the early warning information output unit 42 outputs slip crack development early warning information and prompts on-site inspection; when the early warning level is determined to be a high warning, the early warning information output unit 42 outputs high-risk alarm information, and at the same time, the engineering response linkage unit 43 links the audible and visual alarm device, the remote monitoring platform, or the emergency response module.

[0086] The warning level determination unit 41 uses a dynamic threshold adjustment mechanism to determine the warning trigger threshold. The dynamic threshold adjustment mechanism updates the warning trigger boundary in real time based on the historical sequence of composite stress characterization quantity, and adds a duration criterion.

[0087] Specifically, when the identification result is a bottom scour mode, a primary warning is triggered, and a response instruction to replenish bottom scour material is generated; when the identification result is a toe scour mode or an abnormal seepage pressure mode within the dike, a medium warning is triggered, and a response instruction to reinforce the structure or repair the drainage system is generated; when the identification result is an overall slippage and instability mode, a high-level warning is triggered, and a response instruction to activate an audible and visual alarm, issue evacuation information, and prompt immediate emergency repairs is generated.

[0088] Specifically, the tiered early warning response module 4 receives the risk pattern recognition results and automatically executes, such as... Figure 5 The response strategy shown is as follows:

[0089] 1) When the identification result is a bottom erosion pattern, a primary warning is triggered. The response instruction sends a prompt message to the management personnel through the monitoring platform interface, SMS, etc., such as: "Primary warning: Erosion signs have been detected in the bottom erosion of section X. It is recommended to add bottom erosion blocks in the near future."

[0090] 2) When the identification result is a toe scour pattern or an abnormal seepage pressure pattern within the dike, a medium-level warning is triggered. The system automatically increases the monitoring frequency and sends the instruction: "Medium-level warning: Local instability risk in the toe structure of section X / abnormal seepage within the dike. It is recommended to arrange structural reinforcement inspection and drainage system maintenance."

[0091] 3) When the identification result indicates an overall slippage instability mode, an advanced early warning is immediately triggered. The module simultaneously executes multiple instructions: activates audible and visual alarms at the monitoring center and control site; disseminates personnel evacuation information through broadcasts, application software, and other channels; sends the highest-level alarm to the emergency command department, with the message: "Advanced Warning: There is an overall slippage risk in section X. Please organize emergency rescue and repair immediately!"

[0092] When the growth rate of the composite stress characterization quantity, the effective stress spatial gradient modulus, or the principal stress direction deflection angular velocity in a local area exceeds the preset conditions, the data acquisition and transmission module 2 increases the sampling frequency of the corresponding sensing unit to implement encrypted monitoring of the abnormal area.

[0093] Example 2

[0094] Based on the same inventive concept as Embodiment 1, this embodiment introduces a method for a multi-level early warning system for the stability of a sloped revetment, including:

[0095] The distributed stress monitoring array 1 is used to synchronously collect raw stress data of key parts of the revetment underwater and inside.

[0096] The data processing and risk analysis module 3 uses the monitoring data of the water level benchmark area as a reference, and combines the propagation phase lag and amplitude attenuation characteristics of external wave disturbances in the revetment medium to perform hydrodynamic pressure compensation on the original pressure data of the bottom and toe areas, and obtains the wave-seepage coupling correction effective stress data of each monitoring point.

[0097] The data processing and risk analysis module 3 calculates the magnitude of the principal stress and the principal stress direction angle based on the multi-directional stress data inside the dike core, and calculates the deflection angular velocity of the principal stress direction angle and the dynamic stress safety margin index.

[0098] The data processing and risk analysis module 3 constructs a composite stress characterization quantity to represent the degree of local instability driving of the revetment based on the change rate, spatial gradient, principal stress direction evolution characteristics and dynamic stress safety margin index of the effective stress data corrected by wave-permeability coupling.

[0099] The data processing and risk analysis module 3 identifies instability risk modes and inverses the development degree of potential slip surfaces based on the composite stress characterization quantity and the spatial distribution of the principal stress direction field.

[0100] The graded early warning and response module 4 automatically executes the corresponding graded early warning and response strategy based on the identified instability risk pattern.

[0101] Specifically, the steps are as follows:

[0102] Simultaneous acquisition of raw stress data. Through the deployed distributed stress monitoring array 1, raw stress data of key parts of the bottom protection, toe protection, and core of the dike, as well as the reference point in the still water area, are collected synchronously using a unified clock reference.

[0103] The water pressure compensation calculation unit 31 uses the monitoring data of the water level reference area as a reference, and combines the propagation phase lag and amplitude attenuation characteristics of external wave disturbance in the revetment medium to perform dynamic water pressure compensation on the original pressure data of the bottom protection area and the toe protection area, so as to obtain the effective earth pressure data of each monitoring point.

[0104] The stress tensor calculation unit 32 calculates the magnitude of the principal stress and the direction angle of the principal stress based on the multi-directional stress data inside the dike core, and calculates the deflection angular velocity of the principal stress direction angle and the dynamic stress safety margin index.

[0105] The composite stress characterization unit 33 constructs a composite stress characterization quantity to characterize the degree of local instability driving the revetment based on the change rate, spatial gradient, principal stress direction evolution characteristics and dynamic stress safety margin index of the effective earth pressure data.

[0106] The potential slip surface inversion unit 34 identifies the instability risk mode and inverts the development degree of the potential slip surface based on the composite stress characterization quantity and the spatial distribution of the principal stress direction field.

[0107] The risk pattern recognition unit 35 intelligently matches and analyzes the calculated results with the criteria pre-stored in the instability feature pattern library to identify the specific instability risk pattern currently faced by the bank protection.

[0108] The graded early warning response module 4 automatically maps the identified specific risk patterns to the corresponding early warning levels and triggers all preset response instructions for that level, completing a closed loop from risk perception to control execution.

Claims

1. A multi-level early warning system for the stability of a sloping revetment, characterized in that, include: Distributed stress monitoring array (1), data acquisition and transmission module (2), data processing and risk analysis module (3) and graded early warning response module (4); The distributed stress monitoring array (1) is located at key mechanical parts of the revetment and is used to monitor stress data of each part in real time. The data acquisition and transmission module (2) is communicatively connected to the distributed stress monitoring array (1) and is used to acquire and transmit the stress data; The data processing and risk analysis module (3) is communicatively connected to the data acquisition and transmission module (2) and is used to receive the stress data. The data processing and risk analysis module (3) processes the stress data, extracts the effective earth pressure data reflecting the stress on the soil structure, and identifies the instability risk mode based on the spatiotemporal variation characteristics of the effective earth pressure data. The graded early warning response module (4) is communicatively connected to the data processing and risk analysis module (3) and is used to trigger the corresponding early warning level and response instructions based on the identified instability risk pattern.

2. The multi-level early warning system for slope revetment stability according to claim 1, characterized in that, The key mechanical components include the bottom (12), toe (13), core (16), and water level reference point of the revetment.

3. The multi-level early warning system for slope revetment stability according to claim 1, characterized in that, The distributed stress monitoring array (1) includes a first pressure sensing unit (15) deployed in the bottom protection area, a second pressure sensing unit (16) deployed in the foot protection area, and a third pressure sensing unit (17) deployed in the top or nearby still water area of ​​the bottom protection. The monitoring data of the third pressure sensing unit (17) is used to provide a benchmark for dynamic water pressure compensation calculation.

4. The multi-level early warning system for slope revetment stability according to claim 1, characterized in that, The distributed stress monitoring array (1) also includes a multi-axis stress sensing unit (18) deployed inside the core of the embankment for measuring the stress state of the soil in the core of the embankment.

5. The multi-level early warning system for slope revetment stability according to claim 1, characterized in that, The data acquisition and transmission module (2) includes: Multi-channel data acquisition instrument 21: synchronously acquires the raw analog signals of all sensing units at a set sampling frequency, and converts the raw analog signals into digital signals; Wireless transmission terminal 22: Packs the digital signal and transmits it in real time to the data processing and risk analysis module (3) via the mobile network.

6. The multi-level early warning system for slope revetment stability according to claim 1, characterized in that, The data processing and risk analysis module (3) includes: Water pressure compensation calculation unit (31) uses the monitoring data of the third pressure sensing unit (17) to process the monitoring data of the first pressure sensing unit (15) and the second pressure sensing unit (16) and perform dynamic water pressure compensation. The stress tensor calculation unit (32) calculates the principal stress magnitude and principal stress direction angle of the core soil based on the measured normal stress in at least three different spatial directions and the corresponding layout direction of the multi-axis stress sensing unit (18), calculates the deflection angular velocity of the principal stress direction angle between adjacent time steps, and calculates the dynamic stress safety margin index in combination with the Mohr-Coulomb failure criterion. A composite stress characterization construction unit (33) constructs composite stress characterizations, which include at least two of the following: the rate of change of effective stress corrected by wave-permeation coupling, the deflection angular velocity of principal stress direction angle, the dynamic stress safety margin index, the effective stress spatial gradient modulus, and the directional parameter of spatial gradient relative to the free surface of the revetment. Potential slip surface inversion unit (34) is used to determine the location of potential slip surfaces based on the principal stress direction angle distribution, the spatial distribution of composite stress characterization quantity and the low value region of dynamic stress safety margin index of multiple monitoring points, and to identify the abrupt change zone of principal stress direction or the high value connection zone of composite stress, so as to determine the degree of slip surface development. Risk pattern recognition unit (35) performs risk judgment based on the composite stress characterization quantity and the degree of development of potential slip surface.

7. The multi-level early warning system for slope revetment stability according to claim 1, characterized in that, The graded early warning response module (4) includes an early warning level determination unit (41), an early warning information output unit (42), and an engineering response linkage unit (43).

8. The multi-level early warning system for slope revetment stability according to claim 7, characterized in that, The warning level determination unit (41) automatically executes the response strategy based on the received risk pattern recognition result. When the warning level is determined to be a primary warning, the warning information output unit (42) outputs local anomaly prompt information. When the warning is determined to be a medium-level warning, the warning information output unit (42) outputs the slip crack development warning information and prompts the on-site inspection; when the warning is determined to be a high-level warning, the warning information output unit (42) outputs the high-risk alarm information, and at the same time the engineering response linkage unit (43) links the sound and light alarm device, the remote monitoring platform or the emergency response module. The warning level determination unit (41) uses a dynamic threshold adjustment mechanism to determine the warning trigger threshold. The dynamic threshold adjustment mechanism updates the warning trigger boundary in real time based on the historical sequence of composite stress characterization quantity and adds a duration criterion.

9. The multi-level early warning system for slope revetment stability according to claim 1, characterized in that, When the growth rate of the composite stress characterization quantity, the effective stress spatial gradient modulus, or the principal stress direction deflection angular velocity in a local area exceeds the preset conditions, the data acquisition and transmission module (2) increases the sampling frequency of the corresponding sensing unit to perform encrypted monitoring of the abnormal area.

10. A method for a multi-level early warning system for the stability of a slope-type revetment as described in any one of claims 1-9, characterized in that, include: The distributed stress monitoring array (1) is used to synchronously collect raw stress data of key parts of the revetment underwater and inside. The data processing and risk analysis module (3) uses the monitoring data of the water level benchmark area as a reference, and combines the propagation phase lag and amplitude attenuation characteristics of external wave disturbance in the revetment medium to perform hydrodynamic pressure compensation on the original pressure data of the bottom protection area and the toe protection area, and obtains the wave-seepage coupling correction effective stress data of each monitoring point. The data processing and risk analysis module (3) calculates the magnitude of the principal stress and the direction angle of the principal stress based on the multi-directional stress data inside the dike core, and calculates the deflection angular velocity of the principal stress direction angle and the dynamic stress safety margin index. The data processing and risk analysis module (3) constructs a composite stress characterization quantity to represent the degree of local instability driving of the revetment based on the change rate, spatial gradient, principal stress direction evolution characteristics and dynamic stress safety margin index of the effective stress data corrected by wave-permeability coupling. The data processing and risk analysis module (3) identifies instability risk modes and inverses the development degree of potential slip surfaces based on the spatial distribution of the composite stress characterization quantity and the principal stress direction field. The graded early warning response module (4) automatically executes the corresponding graded early warning response strategy based on the identified instability risk pattern.

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