Soil layer strain and settlement data processing method and system based on layered monitoring

Abstract

The invention discloses a stratified monitoring-based soil layer strain and settlement data processing method and system. The method comprises the following steps: acquiring displacement data of a soil layer in real time by utilizing sensor equipment buried at different depths; analyzing the collected data packet, judging whether the sensor crosses a plurality of stratums in combination with the burial depth range of sensor equipment and stratum information, obtaining a corresponding cross-layer depth and an original stratum proportionality coefficient, and calculating to obtain a corresponding actual displacement value in combination with an actual measurement value of the sensor; establishing a space-time correlation database, and storing sensor types, burial depths, geographic coordinates, timestamps, original strain data, original settlement data and displacement measured value data; converting the stored data into a JSON format, organizing a data series according to a three-dimensional geologic model structure, displaying soil layer strain distribution and accumulative settlement distribution in combination with a data visualization technology, and matching soil layer strain values and accumulative settlement values of different depths in sequence; displaying the result data by using the three-dimensional displacement field model; and performing dynamic updating by adopting a periodic updating mode and a trigger updating mode.

Description

Technical Field

[0001] The present invention relates to multiple fields such as civil engineering, geology, environmental monitoring and protection, urban planning and construction, and particularly relates to a method and system for processing soil layer strain and settlement data based on hierarchical monitoring. Background Art

[0002] In the fields of civil engineering, geology, environmental monitoring and protection, urban planning and construction, the distribution of soil layer strain and cumulative settlement are important parameters for evaluating the stability of the foundation, predicting geological disasters, and guiding the excavation and support of underground projects, and are of great importance for preventing geological disasters and ensuring project safety.

[0003] Traditional monitoring methods often rely on on-site observations and experimental data. These data are difficult to obtain and have a long analysis period. Considering the limited amount of data obtained and the large time cost of analysis, it is difficult to establish a mathematical model for simulating the distribution of soil layer strain and cumulative settlement within a fixed time period. Engineering personnel cannot intuitively understand the strain distribution and settlement of the soil layer within a certain period of time in a timely manner, resulting in a lack of scientific basis for preventing geological disasters and control. Summary of the Invention

[0004] In view of the technical defects and drawbacks existing in the prior art, embodiments of the present invention provide a solution to overcome or at least partially solve the above problems, and the specific solutions are as follows:

[0005] As a first aspect of the present invention, a method for processing soil layer strain and settlement data based on hierarchical monitoring is provided, and the method includes:

[0006] Utilize sensor devices buried at different depths to collect displacement data of the soil layer in real time, and the displacement data includes strain and settlement data;

[0007] Analyze the collected data packets, combine the buried depth range of the sensor devices with the formation information, determine whether the sensor crosses multiple formations, obtain the corresponding cross-layer depth and the original formation proportionality coefficient, and calculate the corresponding measured displacement value in combination with the measured values of the sensor;

[0008] Establish a spatio-temporal association database to store sensor type, buried depth, geographical coordinates, time stamps, original strain data, original settlement data, and measured displacement value data, and realize multi-dimensional retrieval through formation classification labels;

[0009] The data to be stored in the spatio-temporal correlation database is used as the data source for simulating the strain and cumulative settlement distribution of the soil layer. The stored data is converted into JSON format, and the data series is organized according to the three-dimensional geological model structure. Combining data visualization technology, heat maps and settlement cumulative curves are rendered through the WebGL engine to display the soil layer strain distribution and cumulative settlement distribution, and the soil layer strain values and cumulative settlement values at different depths are matched in sequence;

[0010] The three-dimensional displacement field model is used to display the result data, supporting time dimension switching. The corresponding warning thresholds are set, and high-risk areas are marked when the warning thresholds are triggered;

[0011] Dynamic updates are carried out using the periodic update mode and the trigger update mode. In the periodic update mode, the data is automatically reloaded at preset time intervals. In the trigger update mode, local data refreshing and model redrawing are started when the strain change rate at a certain layer exceeds the preset threshold.

[0012] Furthermore, the sensor devices include the first type of sensors buried at 2m intervals and the second type of sensors buried at 5m intervals. The two types of sensors divide the burial ranges according to the differences in formation categories, and record the geographical coordinates and burial depth parameters.

[0013] Furthermore, the sensor types include distributed optical fiber strain sensors and settlement target media. The distributed optical fiber strain sensors are used to monitor the spatio-temporal evolution characteristics of the soil fracture strain field, and the settlement target media capture displacement changes through visual sensors.

[0014] Furthermore, the formation information includes the top depth and total depth corresponding to each formation. Combining the overlap between the buried depth range of the sensor device and the formation interface, it is dynamically determined whether the sensor spans multiple formations.

[0015] Furthermore, the calculation of the corresponding cross-layer depth and the original formation proportionality coefficient, and combining the measured values of the sensor to calculate the corresponding measured displacement values includes:

[0016] Calculation of the numerator and denominator: Multiply the original formation proportionality coefficient of each soil layer by the cross-layer depth respectively to obtain the numerator. Then add the original formation proportionality coefficients and cross-layer depths of all layers respectively to obtain the denominator. Accumulate the numerator and denominator to obtain the total numerator and total denominator. The formula is as follows:

[0017]

[0018] After multiplying the measured value of the sensor by the cross-layer depth, divide it by the sum of the numerator and denominator. The formula is as follows:

[0019]

[0020] The final total displacement is the sum of the displacements of each layer, and the specific formula is as follows:

[0021]

[0022] where k i is the original formation proportion coefficient of the soil layer of the i-th layer, H i is the cross-layer depth of the soil layer of the i-th layer, s i is the measured value of the sensor of the soil layer of the i-th layer, D i is the measured displacement value of the soil layer of the i-th layer, and D is the sum of the displacements of each layer.

[0023] As the second aspect of the present invention, a soil layer strain and settlement data processing system based on hierarchical monitoring is provided. The system includes a data acquisition module, a data preprocessing module, a data storage module, a strain cumulative distribution simulation module, a displacement dynamic display module, and a dynamic update module;

[0024] The data acquisition module is used to use sensor devices buried at different depths to collect displacement data of the soil layer in real time. The displacement data includes strain and settlement data;

[0025] The data preprocessing module is used to parse the collected data packets, combine the buried depth range of the sensor devices with the formation information, determine whether the sensor spans multiple formations, obtain the corresponding cross-layer depth and the original formation proportion coefficient, and calculate the corresponding measured displacement value in combination with the measured value of the sensor;

[0026] The data storage module is used to establish a spatio-temporal correlation database to store sensor type, buried depth, geographical coordinates, timestamp, original strain data, original settlement data, and measured displacement value data, and realize multi-dimensional retrieval through formation classification labels;

[0027] The strain cumulative distribution simulation is used to use the data stored in the spatio-temporal correlation database as the data source for simulating the soil layer strain and cumulative settlement distribution, convert the stored data into JSON format, organize the data series according to the three-dimensional geological model structure, combine the data visualization technology, and render the heat map and settlement cumulative curve through the WebGL engine to display the soil layer strain distribution and cumulative settlement distribution, and match the soil layer strain values and cumulative settlement values at different depths in turn;

[0028] The displacement dynamic display module is used to display the result data using a three-dimensional displacement field model, support time dimension switching, set the corresponding warning threshold, and mark the high-risk area when the warning threshold is triggered;

[0029] The dynamic update module is used for dynamic update in the periodic update mode and the trigger update mode. In the periodic update mode, data is automatically reloaded at a preset time interval. In the trigger update mode, when the strain change rate at a certain layer exceeds the preset threshold, local data refresh and model redrawing are started.

[0030] Furthermore, the sensor device includes the first type of sensors buried in layers at 2m intervals and the second type of sensors buried in layers at 5m intervals. The two types of sensors divide the burial range according to the differences in formation types, and record the geographical coordinates and burial depth parameters.

[0031] Furthermore, the sensor types include distributed fiber optic strain sensors and settlement target media. The distributed fiber optic strain sensors are used to monitor the spatio-temporal evolution characteristics of the soil fissure strain field, and the settlement target media capture displacement changes through visual sensors.

[0032] Furthermore, the formation information includes the top depth and total depth corresponding to each formation. Combining the overlap between the burial depth range of the sensor device and the formation interface, it is dynamically determined whether the sensor spans multiple formations.

[0033] Furthermore, obtaining the corresponding cross-layer depth and the original formation proportion coefficient, and combining with the measured values of the sensor, the calculated corresponding measured displacement values include:

[0034] Calculation of the numerator and denominator: Multiply the original formation proportion coefficient of each soil layer by the cross-layer depth respectively to obtain the numerator. Then, add the original formation proportion coefficients and cross-layer depths of all layers respectively to obtain the denominator. Take the sum of the numerator and denominator for accumulation to obtain the total sum of the numerator and the total sum of the denominator. The formula is as follows:

[0035]

[0036] After multiplying the measured value of the sensor by the cross-layer depth, divide it by the sum of the numerator and denominator. The formula is as follows:

[0037]

[0038] The final total displacement is the sum of the displacements of each layer. The specific formula is as follows:

[0039]

[0040] where, k i is the original formation proportion coefficient of the i-th soil layer, H i is the cross-layer depth of the i-th soil layer, s i is the measured value of the sensor of the i-th soil layer, D i is the measured displacement value of the i-th soil layer, and D is the sum of the displacements of each layer.

[0041] The present invention has the following beneficial effects:

[0042] 1. Improve data interpretation efficiency: Through intuitive and dynamic data chart visualization, engineering personnel can quickly capture key information on soil layer strain and settlement, improving data interpretation efficiency;

[0043] 2. Achieve real-time monitoring: The system can collect and process data in real time, promptly reflecting the dynamic change process of soil layer strain and settlement, providing engineering personnel with real-time assessment capabilities;

[0044] 3. Display spatial distribution characteristics: Through data visualization, engineering personnel can intuitively see the distribution of soil layer strain and settlement at different locations and depths, providing strong support for engineering design and construction;

[0045] 4. Provide early warning function: The system can provide early warning information based on data analysis results, helping engineering personnel take preventive measures before problems occur in soil layer stability and reducing the risk of geological disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic flow chart of a method for processing soil layer strain and settlement data based on hierarchical monitoring provided by an embodiment of the present invention;

[0047] Figure 2 It is a schematic diagram of dividing the soil layer depth according to different formation categories provided by an embodiment of the present invention;

[0048] Figure 3 It is a schematic diagram of the distribution of proportionality coefficients between different formation numbers provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0049] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0050] As Figure 1 shown, it is a method for processing soil layer strain and settlement data based on hierarchical monitoring provided by an embodiment of the present invention, and the method includes:

[0051] Using sensor devices buried at different depths to collect displacement data of the soil layer in real time, where the displacement data includes strain and settlement data, and the strain and settlement data are used as original strain and settlement data;

[0052] Parse the collected data packets, combine the buried depth range of the sensor device and the formation information, determine whether the sensor spans multiple formations, obtain the corresponding cross-layer depth and the original formation proportion coefficient, and calculate the corresponding measured displacement value in combination with the measured value of the sensor;

[0053] Establish a spatio-temporal correlation database to store sensor type, buried depth, geographic coordinates, timestamp, original strain, settlement data, and measured displacement value data, and realize multi-dimensional retrieval through formation classification labels;

[0054] Use the data stored in the spatio-temporal correlation database as the data source for simulating soil layer strain and cumulative settlement distribution. Convert the stored data into JSON format, organize the data series according to the three-dimensional geological model structure, and combine data visualization technology to render the heat map and settlement cumulative curve through the WebGL engine, display the soil layer strain distribution and cumulative settlement distribution, and match the soil layer strain values and cumulative settlement values at different depths in turn to obtain the values of two physical quantities (strain and cumulative settlement) at the same depth;

[0055] Use the three-dimensional displacement field model to display the result data (the result data includes soil layer strain distribution, cumulative settlement distribution data, and matching result data), support time dimension switching, set the corresponding warning threshold, and calibrate the high-risk area when the warning threshold is triggered;

[0056] Adopt the periodic update mode and the trigger update mode for dynamic update. The periodic update mode automatically reloads the data at a preset time interval, and the trigger update mode starts local data refreshing and model redrawing when the strain change rate of a certain layer exceeds the preset threshold.

[0057] Among them, the sensor device includes: the first type of sensor buried in layers at 2m intervals and the second type of sensor buried in layers at 5m intervals. The buried depth range of the first type of sensor is 0-2m, 2-4m, 4-6m,... in turn, and the buried depth range of the second type of sensor is 0-5m, 5-10m, 10-15m,... in turn, and so on. The two types of sensors divide the buried range according to the formation category difference, and record the geographic coordinates and buried depth parameters.

[0058] Among them, the sensor type includes distributed optical fiber strain sensors and settlement target media. The distributed optical fiber strain sensors are used to monitor the spatio-temporal evolution characteristics of the soil mass fracture strain field, and the settlement target media capture displacement changes through visual sensors.

[0059] The present invention mainly focuses on the changes in the soil layer strain distribution and cumulative settlement distribution in the fields of civil engineering, geology, environmental monitoring and protection, urban planning and construction, etc. Based on the different formation numbers and different formation depths corresponding to different formation categories, different acquisition devices are distinguished according to the fixed points of 2m and 5m. By calculating the range of the top depth and bottom depth of the fixed point, it is judged whether the acquisition sensor device at this fixed point straddles different formations. Then, according to the calculated results, the original proportional coefficients of different formation numbers are obtained. Finally, the displacement amounts of different formations are calculated, and combined with data visualization technology, the physical quantities of soil layer strain and cumulative settlement distribution are dynamically simulated in real time, so as to achieve real-time monitoring and early warning of soil layer strain and cumulative settlement.

[0060] Based on the soil layer strain and cumulative data collected in real time by sensors buried at different formation depths, by calculating the buried depth range, and then querying different formation information and the original formation proportional coefficients, the device is accurately positioned whether it straddles layers. Then, the settlement displacement amounts of different layers are calculated, and the experimental data and simulation results are compared to continuously optimize the algorithm. Combined with data visualization technology, the intuitive changes in the soil layer strain distribution and cumulative settlement distribution within a period of time are simulated, forming a set of scientific, rigorous, reasonable and mature simulation analysis methods and systems.

[0061] The present invention also divides the soil layer depth according to different formation categories, as Figure 2 shown, where ID: the unique identifier of the sample or data, ZKBH: represents the device number, YSDCH: represents the formation number, DCLB: represents the formation category, used to describe the specific characteristics of the rock and soil layer; ZTOP: represents the top depth of the rock and soil of this layer; ZDEEP: represents the bottom depth of the rock and soil of this layer; CH: represents the layer thickness;

[0062] Based on the above formation information, it can be judged whether the device straddles different formations, including which formations, etc., based on the depth range of the fixed-point burial of the acquisition device. Based on these basic information, by consulting the original formation proportional information, the proportional coefficient distribution situation between different formation numbers is obtained, as Figure 3 shown, BL represents the proportional coefficient between formations, and the value of this field is given in proportion form, used to further refine the proportional distribution between formations, ZKTYPE: represents the device type collected at fixed points of 2m / 5m.

[0063] For example, the devices with 2m fixed points can be divided into 0-2, 2-4, 6-8, 18-20m in sequence according to the depth. According to the depth description information of different formation numbers in the original formation information table, it can be judged whether the device straddles formations. For example, the device at 2-4m straddles two formations of 1-1 and 1-2. The devices with 5m fixed points can be judged in the same way. It is necessary to accurately judge which formation the device belongs to, which will affect the calculation of the subsequent result data.

[0064] In some embodiments, obtaining the corresponding cross-layer depth and the original formation proportion coefficient, and combining with the measured values of the sensor to calculate the corresponding measured displacement values includes:

[0065] Calculation of the numerator and denominator: Multiply the original formation proportion coefficient of each soil layer by the cross-layer depth respectively to obtain the numerator, then add the original formation proportion coefficients and cross-layer depths of all layers respectively to obtain the denominator, and accumulate the numerator and denominator to obtain the total numerator and total denominator. The formula is as follows:

[0066]

[0067] After multiplying the measured value of the sensor by the cross-layer depth, divide it by the sum of the numerator and denominator. The formula is as follows:

[0068]

[0069] The final total displacement is the sum of the displacements of each layer. The specific formula is as follows:

[0070]

[0071] where k i is the original formation proportion coefficient of the i-th soil layer, H i is the cross-layer depth of the i-th soil layer, s i is the measured value of the sensor of the i-th soil layer, that is, the displacement data collected by the sensor device, D i is the measured displacement value of the i-th soil layer, and D is the sum of the displacements of each layer.

[0072] It should be noted that for the measured displacement value, when the displacement data is strain data, the corresponding measured displacement value is the displacement value corresponding to the strain. When the displacement data is settlement data, the corresponding measured displacement value is the displacement value corresponding to the settlement. Based on the measured displacement value corresponding to the strain data, the corresponding soil layer strain distribution can be obtained. Based on the measured displacement value corresponding to the settlement, the corresponding cumulative settlement distribution can be obtained.

[0073] The present invention draws on the core idea of the layer-wise summation method. By calculating the compression amounts of each soil layer layer by layer and then accumulating them, the compression contributions of different layers are comprehensively considered. Among them, the original formation proportion coefficient reflects the amplification effect of soil compressibility on displacement, the cross-layer depth directly affects the weight of the compression amount of each layer, and the measured value of the sensor needs to be multiplied by the cross-layer depth to reflect the actual influence of the strain of soil layers at different depths on displacement, which conforms to the processing logic of layer-wise monitoring data.

[0074] An embodiment of the present invention also provides a soil layer strain and settlement data processing system based on hierarchical monitoring, which is characterized in that the system includes a data acquisition module, a data preprocessing module, a data storage module, a strain cumulative distribution simulation module, a displacement dynamic display module, and a dynamic update module;

[0075] The data acquisition module is used to collect the displacement data of the soil layer in real time by using sensor devices buried at different depths, and the displacement data includes strain and settlement data;

[0076] The data preprocessing module is used to parse the collected data packets, combine the buried depth range of the sensor devices and the formation information, determine whether the sensor crosses multiple formations, obtain the corresponding cross-layer depth and the original formation proportion coefficient, and calculate the corresponding measured displacement value in combination with the measured values of the sensors;

[0077] The data storage module is used to establish a spatio-temporal association database, store the sensor type, buried depth, geographical coordinates, timestamp, original strain data, original settlement data, and measured displacement value data, and realize multi-dimensional retrieval through formation classification labels;

[0078] The strain cumulative distribution simulation is used to use the data stored in the spatio-temporal association database as the data source for simulating the soil layer strain and cumulative settlement distribution, convert the stored data into JSON format, organize the data series according to the three-dimensional geological model structure, combine the data visualization technology, and render the heat map and settlement cumulative curve through the WebGL engine to display the soil layer strain distribution and cumulative settlement distribution, and match the soil layer strain values and cumulative settlement values at different depths in turn;

[0079] The displacement dynamic display module is used to display the result data by using the three-dimensional displacement field model, support the time dimension switching, set the corresponding warning threshold, and mark the high-risk area when the warning threshold is triggered;

[0080] The dynamic update module is used to perform dynamic updates in a periodic update mode and a trigger update mode. The periodic update mode automatically reloads the data at a preset time interval, and the trigger update mode starts local data refreshing and model redrawing when the strain change rate of a certain layer exceeds the preset threshold.

[0081] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A soil layer strain and settlement data processing method based on layered monitoring, characterized in that: The method comprises: Using sensor devices buried at different depths to collect displacement data of soil layers in real time, the displacement data includes strain and settlement data; Parse the collected data packets, combine the buried depth range of the sensor equipment and the formation information, determine whether the sensor spans multiple formations, obtain the corresponding cross-layer depth and original formation scale coefficient, and combine the sensor measured value to calculate the corresponding displacement measured value; Establish a spatiotemporal correlation database to store sensor type, burial depth, geographic coordinates, timestamp, original strain data, original settlement data, and displacement measured value data, and realize multi-dimensional retrieval through stratum classification labels; The data stored in the spatiotemporal correlation database is used as the data source for simulating soil layer strain and cumulative settlement distribution. The stored data is converted into JSON format, and the data series is organized according to the three-dimensional geological model structure. Combined with data visualization technology, the heat map and settlement accumulation curve are rendered through the WebGL engine to display the soil layer strain distribution and cumulative settlement distribution, and the soil layer strain values ​​and cumulative settlement values ​​at different depths are matched in turn. Use the three-dimensional displacement field model to display the results data, support time dimension switching, set the corresponding warning threshold, and mark the high-risk area when the warning threshold is triggered; The dynamic update is performed using the periodic update mode and the triggered update mode. The periodic update mode automatically reloads data at preset time intervals, and the triggered update mode starts local data refresh and model redrawing when the strain change rate of a certain layer exceeds a preset threshold.

2. The soil layer strain and settlement data processing method based on layered monitoring according to claim 1 is characterized in that: The sensor equipment includes a first type of sensors buried in layers at intervals of 2m and a second type of sensors buried in layers at intervals of 5m. The two types of sensors are divided into buried ranges according to differences in stratum categories and record geographic coordinates and buried depth parameters.

3. The soil layer strain and settlement data processing method based on layered monitoring according to claim 1 is characterized in that: The sensor types include distributed optical fiber strain sensors and settlement target media. The distributed optical fiber strain sensors are used to monitor the spatiotemporal evolution characteristics of soil crack strain fields, and the settlement target media capture displacement changes through visual sensors.

4. The soil layer strain and settlement data processing method based on layered monitoring according to claim 1 is characterized in that: The stratum information includes the top depth and total depth corresponding to each stratum. Combined with the overlap between the buried depth range of the sensor equipment and the stratum interface, it is dynamically determined whether the sensor spans multiple strata.

5. The method for processing soil layer strain and settlement data based on layered monitoring according to claim 1 is characterized in that: The obtaining of the corresponding cross-layer depth and the original formation scale coefficient, and combining the sensor measured value to calculate the corresponding displacement measured value includes: Calculation of numerator and denominator: Multiply the original stratigraphic proportion coefficient of each soil layer by the cross-layer depth to obtain the numerator, then add the original stratigraphic proportion coefficient of all layers and the cross-layer depth to obtain the denominator, add the numerator and denominator to obtain the sum of the numerator and the sum of the denominator. The formula is as follows: After multiplying the sensor measured value by the cross-layer depth, divide it by the sum of the numerator and denominator. The formula is as follows: The final total displacement is the sum of the displacements of each layer. The specific formula is as follows: Among them, k i is the original stratum proportion coefficient of the i-th soil layer, H i is the inter-layer depth of the i-th soil layer, s i is the sensor measured value of the i-th layer of soil, that is, the displacement data collected by the sensor equipment, D i is the measured displacement value of the i-th soil layer, and D is the sum of the displacements of each layer.

6. A soil layer strain and settlement data processing system based on layered monitoring, characterized in that: The system includes a data acquisition module, a data preprocessing module, a data storage module, a strain cumulative distribution simulation module, a displacement dynamic display module and a dynamic update module; The data acquisition module is used to collect displacement data of soil layers in real time using sensor devices buried at different depths, wherein the displacement data includes strain and settlement data; The data preprocessing module is used to parse the collected data packets, combine the buried depth range of the sensor equipment and the formation information, determine whether the sensor spans multiple formations, obtain the corresponding cross-layer depth and the original formation scale coefficient, and combine the sensor measured value to calculate the corresponding displacement measured value; The data storage module is used to establish a spatiotemporal correlation database to store sensor type, burial depth, geographic coordinates, timestamp, original strain data, original settlement data, and displacement measured value data, and realize multi-dimensional retrieval through stratum classification labels; The cumulative strain distribution simulation is used to use the data stored in the spatiotemporal correlation database as the data source for simulating soil layer strain and cumulative settlement distribution. The stored data is converted into JSON format, and the data series are organized according to the three-dimensional geological model structure. Combined with data visualization technology, the heat map and settlement accumulation curve are rendered through the WebGL engine to display the soil layer strain distribution and cumulative settlement distribution, and the soil layer strain values ​​and cumulative settlement values ​​at different depths are matched in turn. The displacement dynamic display module is used to display the results data using the three-dimensional displacement field model, supports time dimension switching, sets the corresponding warning threshold, and calibrates the high-risk area when the warning threshold is triggered; The dynamic update module is used to perform dynamic updates using periodic update mode and triggered update mode. The periodic update mode automatically reloads data at preset time intervals, and the triggered update mode starts local data refresh and model redrawing when the strain change rate of a certain layer exceeds a preset threshold.

7. The soil layer strain and settlement data processing system based on layered monitoring according to claim 6 is characterized in that: The sensor equipment includes a first type of sensors buried in layers at intervals of 2m and a second type of sensors buried in layers at intervals of 5m. The two types of sensors are divided into buried ranges according to differences in stratum categories and record geographic coordinates and buried depth parameters.

8. The soil layer strain and settlement data processing system based on layered monitoring according to claim 6 is characterized in that: The sensor types include distributed optical fiber strain sensors and settlement target media. The distributed optical fiber strain sensors are used to monitor the spatiotemporal evolution characteristics of soil crack strain fields, and the settlement target media capture displacement changes through visual sensors.

9. The soil layer strain and settlement data processing system based on layered monitoring according to claim 6 is characterized in that: The stratum information includes the top depth and total depth corresponding to each stratum. Combined with the overlap between the buried depth range of the sensor equipment and the stratum interface, it is dynamically determined whether the sensor spans multiple strata.

10. The soil layer strain and settlement data processing system based on layered monitoring according to claim 6, characterized in that: The obtaining of the corresponding cross-layer depth and the original formation scale coefficient, and combining the sensor measured value to calculate the corresponding displacement measured value includes: Calculation of numerator and denominator: Multiply the original stratigraphic proportion coefficient of each soil layer by the cross-layer depth to obtain the numerator, then add the original stratigraphic proportion coefficient of all layers and the cross-layer depth to obtain the denominator, add the numerator and denominator to obtain the sum of the numerator and the sum of the denominator. The formula is as follows: After multiplying the sensor measured value by the cross-layer depth, divide it by the sum of the numerator and denominator. The formula is as follows: The final total displacement is the sum of the displacements of each layer. The specific formula is as follows: Among them, k i is the original stratum proportion coefficient of the i-th soil layer, H i is the inter-layer depth of the i-th soil layer, s i is the sensor measured value of the i-th soil layer, D i is the measured displacement value of the i-th soil layer, and D is the sum of the displacements of each layer.

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