Method and device for detecting early consolidation pressure of cohesive soil

Abstract

The invention provides a cohesive soil early consolidation pressure detection method and device, and belongs to the technical field of geotechnical engineering detection.The cohesive soil early consolidation pressure detection method comprises the steps that a structured database is established based on engineering area historical drilling data and geotechnical test data; extracting data subsets corresponding to the soil texture types from the database, and respectively constructing mucky soil and conventional cohesive soil early consolidation pressure prediction models; acquiring a standard volume soil sample and density and water content data thereof; drilling position coordinates, orifice elevation, sampling depth and soil sample specific gravity parameters are input; selecting a prediction model according to the soil texture type, inputting related data, and outputting an early consolidation pressure value; and comparing the early consolidation pressure value with the current effective self-weight stress, and judging the consolidation state of the soil body. According to the method, the detection period of the early consolidation pressure of the cohesive soil body is shortened, subjective factors in the manual curve drawing process are eliminated, and the data accuracy and the working efficiency are improved.

Description

Technical Field

[0001] The present invention belongs to the field of rock and soil consolidation detection, and in particular relates to a test method and device for rapidly detecting the early consolidation pressure of clay soil. Background Art

[0002] The Casagrande method, commonly used in engineering practice, determines the initial consolidation pressure. This method requires a large number of closely spaced loading tests to obtain the e-logp curve. The initial consolidation pressure corresponding to the point of minimum curvature radius is then manually plotted and estimated. This method has a long testing cycle, and the results are significantly influenced by subjective factors, making it difficult to meet the timeliness requirements of modern engineering surveys.

[0003] Currently, there is still a lack of rapid detection technology for the early consolidation pressure of clay soils, which makes it difficult to meet the demand for rapid and accurate determination of early consolidation pressure in engineering practice. Summary of the Invention

[0004] In order to solve the problems existing in the above-mentioned background technology, the present application provides a method and device for detecting the early consolidation pressure of clay soil, which meets the demand for rapid and accurate determination of the early consolidation pressure in engineering practice.

[0005] This application provides a method for detecting the pre-consolidation pressure of clay soil, comprising:

[0006] S1: Based on the historical drilling data and geotechnical test data of the project area, a structured database including drilling coordinates, hole elevation, sampling depth, soil physical properties and pre-consolidation pressure is established;

[0007] S2 divides the data in the structured database into a silt soil data subset and a conventional clay soil data subset according to soil type; based on the silt soil data subset, a neural network algorithm is used to construct a silt soil early consolidation pressure prediction model; based on the conventional clay soil data subset, a neighborhood rough set algorithm is used to construct a conventional clay soil early consolidation pressure prediction model;

[0008] S3 obtains standard volume soil samples, soil density data and soil moisture content data;

[0009] S4 inputs the coordinates of the drilling position, the elevation of the hole, the sampling depth and the specific gravity of the soil sample;

[0010] S5 selects the silt soil prediction model or the conventional clay soil prediction model according to the soil type, inputs the standard volume soil sample, soil density data and soil moisture data collected in step S3, the hole position coordinates, hole elevation, sampling depth and soil sample specific gravity parameters entered in step S4 into the selected model, and outputs the preliminary consolidation pressure value of the soil;

[0011] S6 compares the previous consolidation pressure value with the current effective deadweight stress of the soil to generate a soil consolidation state determination result.

[0012] Furthermore, in step S1, the structured database includes pre-set thresholds and conditional variables; the thresholds include the maximum and minimum values of the data; the conditional variables are used to determine the logical correlation between the data; and the structured data of the silty soil or conventional clay soil in the structured database is screened according to the thresholds and the conditional variables.

[0013] Furthermore, in step S3, obtaining the standard volume soil sample, soil density data and soil moisture data includes: preparing the standard volume soil sample using a ring cutter; measuring the mass of the soil sample using an electronic balance to obtain the soil density data; and detecting the soil moisture data using a soil moisture tester.

[0014] Furthermore, in step S5, the silt soil prediction model or the conventional clay soil prediction model is selected according to the soil type, including: identifying the soil type based on the soil density data and soil moisture data collected in step S3, and selecting the silt soil prediction model or the conventional clay soil prediction model.

[0015] Furthermore, in step S5, before the standard volume soil sample, soil density data and soil moisture data collected in step S3, the hole position coordinates, hole elevation, sampling depth and soil sample specific gravity parameters entered in step S4 are input into the selected model, the soil porosity ratio is calculated, and the calculation formula of the porosity ratio is:

[0016]

[0017] Among them, e is the porosity ratio of soil, G s is the specific gravity of the soil, ω is the natural moisture content of the soil, ρ is the natural density of the soil, and ω is the density of water; the soil porosity ratio and other parameters are input into the selected model to predict the value of the initial consolidation pressure.

[0018] The present application provides a device for detecting the early consolidation pressure of clay soil, comprising:

[0019] The database module is used to establish a structured database containing borehole coordinates, hole elevation, sampling depth, soil physical properties and pre-consolidation pressure based on historical drilling data and geotechnical test data in the project area;

[0020] a model construction module for dividing the data in the structured database into a silt soil data subset and a conventional clay soil data subset according to soil type; constructing a silt soil pre-consolidation pressure prediction model based on the silt soil data subset using a neural network algorithm; and constructing a clay and silty clay pre-consolidation pressure prediction model based on the conventional clay soil data subset using a neighborhood rough set algorithm;

[0021] Data acquisition module, used to obtain standard volume soil samples, soil density data and soil moisture content data;

[0022] Parameter input module, used to input drilling position coordinates, hole elevation, sampling depth and soil sample specific gravity parameters;

[0023] a detection execution module, configured to select the silty soil prediction model or the conventional clay soil prediction model according to the soil type, input the standard volume soil sample, soil density data, and soil moisture data collected by the data acquisition module, and the borehole position coordinates, hole elevation, sampling depth, and soil sample specific gravity parameters input by the parameter input module into the selected model, and output a preliminary consolidation pressure value of the soil;

[0024] The result analysis module is used to compare the previous consolidation pressure value with the current effective deadweight stress of the soil to generate a soil consolidation state determination result.

[0025] Furthermore, the database module includes: a data screening unit, used to set thresholds and conditional variables for the structured database; the thresholds include the maximum and minimum values of the data; the conditional variables are used to determine the logical correlation between the data; and the structured data of the silt soil or conventional clay soil in the structured database is screened according to the thresholds and the conditional variables.

[0026] Furthermore, the data acquisition module includes: a ring cutter for preparing the standard volume soil sample; an electronic balance for measuring the mass of the soil sample to obtain the soil density data; and a soil moisture tester for detecting the soil moisture content data.

[0027] Furthermore, the detection execution module includes a soil type identification unit, which identifies the soil type based on the soil moisture content data and soil density data collected by the data collection module.

[0028] Furthermore, the detection execution module includes: a parameter calculation unit for calculating the soil porosity before inputting the standard volume soil sample, soil density data and soil moisture content data collected by the data acquisition module, the drilling position coordinates, hole elevation, sampling depth and soil sample specific gravity parameters input by the parameter input module into the selected model;

[0029] The calculation formula of the void ratio is:

[0030]

[0031] Among them, e is the porosity ratio of soil, G s is the specific gravity of the soil, ω is the natural moisture content of the soil, ρ is the natural density of the soil, and ω is the density of water; the soil porosity ratio and other parameters are input into the selected model to predict the value of the initial consolidation pressure.

[0032] Advantages of this application:

[0033] The present application provides a method for detecting the early consolidation pressure of clay soil, comprising: S1 establishing a structured database containing the coordinates of the drilling hole, the elevation of the hole, the sampling depth, the physical properties of the soil, and the early consolidation pressure based on the historical drilling data and geotechnical test data of the project area; S2 dividing the data in the structured database into a silt soil data subset and a conventional clay soil data subset according to the soil type; based on the silt soil data subset, using a neural network algorithm to construct a silt soil early consolidation pressure prediction model; based on the conventional clay soil data subset, using a neighborhood rough set algorithm to construct a conventional clay soil early consolidation pressure prediction model; S3 Obtain standard volume soil samples, soil density data and soil moisture content data; S4 inputs the drilling position coordinates, hole elevation, sampling depth and soil sample specific gravity parameters; S5 selects the silt soil prediction model or the conventional clay soil prediction model according to the soil type, inputs the standard volume soil sample, soil density data and soil moisture content data collected in step S3, and the hole position coordinates, hole elevation, sampling depth and soil sample specific gravity parameters entered in step S4 into the selected model, and outputs the preliminary consolidation pressure value of the soil; S6 compares the preliminary consolidation pressure value with the current effective deadweight stress of the soil to generate a soil consolidation state judgment result.

[0034] This application establishes a structured database, divides the data subsets of silty soil and conventional clay, and uses neural network and neighborhood rough set algorithms to construct early consolidation pressure prediction models for silty soil and conventional clay, respectively. This shortens the detection cycle, reduces the influence of human factors, and improves detection accuracy and work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a flow chart of the method for detecting the pre-consolidation pressure of clay soil in this application;

[0036] Figure 2 This is a system architecture diagram of the device for detecting the pre-consolidation pressure of clay soil in this application;

[0037] FIG3 is a schematic structural diagram of a device for detecting the early consolidation pressure of clay soil in this application;

[0038] Figure 4 It is a schematic diagram of the detection process of the engineering site embodiment in this application.

[0039] In the figure, 1. Windows touch computer; 2. Ring knife; 3. Electronic balance; 4. Handheld soil moisture tester; 5. Charging port; 6. Power switch; 7. RS232 serial port; 8. USB port; 9. Moisture tester socket; 10. Portable integrated work box; 101. Database module; 102. Model building module; 103. Data acquisition module; 104. Parameter input module; 105. Detection execution module; 106. Result analysis module. DETAILED DESCRIPTION

[0040] In order to make the objectives, technical solutions and advantages of this application more clear, this application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0041] The present application provides a method and device for detecting the preliminary consolidation pressure of clay soil, which belongs to the field of rock and soil consolidation detection. It mainly solves the problems in the prior art that the traditional Casagrande method for determining the preliminary consolidation pressure has a long test cycle and the results are greatly affected by human subjective factors.

[0042] Figure 1 A flow chart of a method for detecting the pre-consolidation pressure of clayey soil is presented.

[0043] Reference Figure 1 As shown, the present application provides a method for detecting the pre-consolidation pressure of clay soil, comprising:

[0044] S1 establishes a structured database containing borehole coordinates, hole elevation, sampling depth, soil physical properties and prior consolidation pressure based on historical drilling data and geotechnical test data in the project area.

[0045] Specifically, by obtaining the original data of drilling and test data from previous projects in the engineering area, the file types of the original data include .xlsx, .docx, .txt and other formats.

[0046] The database is equipped with an intelligent file parsing function, which automatically identifies the format type of the input file and calls the corresponding parsing method according to the different file types to achieve unified reading and extraction of multi-source heterogeneous data.

[0047] The data descriptions extracted from the database include: borehole location coordinates (X, Y), borehole mouth elevation, soil sample sampling depth, soil sample representative bottom depth, soil sample soil type, soil sample physical properties (such as natural moisture content, natural density, specific gravity, etc.) and prior consolidation pressure and other data information.

[0048] Thresholds and conditional variables are set in the database. The thresholds include the maximum and minimum values of the data, and the conditional variables are used to determine the logical correlation between the data.

[0049] The structured data of the silt soil or conventional clay soil in the structured database is screened according to the threshold value and the conditional variable.

[0050] S2 divides the data in the structured database into a silt soil data subset and a conventional clay soil data subset according to the soil type; based on the silt soil data subset, a neural network algorithm is used to construct a silt soil early consolidation pressure prediction model; based on the conventional clay soil data subset, a neighborhood rough set algorithm is used to construct a conventional clay soil early consolidation pressure prediction model.

[0051] Specifically, the structured database is first divided into a silty soil data subset and a conventional clay soil data subset (including clay and silty clay) according to the soil type field.

[0052] Conventional clay (including clay and silty clay) has relatively stable engineering properties; silty soil is a special type of clay with a loose soil structure and extremely low strength. The two have obvious differences in their formation environment and engineering properties, and different algorithms are used to construct prediction models.

[0053] Based on the silt soil data subset, a neural network algorithm was used to construct a silt soil early consolidation pressure prediction model.

[0054] Based on the conventional clay soil data subset, a neighborhood rough set algorithm was used to construct a conventional clay soil early consolidation pressure prediction model.

[0055] S3 obtains standard volume soil samples, soil density data and soil moisture content data;

[0056] Specifically, when collecting soil sample data on site, a standard volume soil sample is prepared using the ring cutter 2 .

[0057] Electronic balance 3 weighs the prepared sample to obtain the natural mass of the soil. Combined with the volume of ring cutter 2, the natural density and natural gravity of the soil are calculated. Electronic balance 3 is connected to Windows touch-screen computer 1 via RS232 serial port 7, and the measurement results are automatically transmitted to the computer.

[0058] The handheld soil moisture meter's probe is inserted into a soil sample to quickly measure the soil's natural moisture content. The test results are automatically transmitted to a Windows touchscreen computer via a dedicated interface.

[0059] S4 inputs the coordinates of the drilling position, hole elevation, sampling depth and soil sample specific gravity parameters.

[0060] Specifically, the following parameters are manually input through the input interface of the Windows touch computer 1: drilling position coordinates (X, Y), drilling hole elevation, sample representative bottom depth, soil sample specific gravity and other data.

[0061] The soil specific gravity can be based on empirical values according to the soil type (for example, the specific gravity of clay is 2.74, the specific gravity of silty clay is 2.72, the specific gravity of silty clay is 2.74, and the specific gravity of silty silty clay is 2.72), or it can be entered as the actual value measured by the pycnometer method.

[0062] S5 selects the silty soil prediction model or the conventional clay soil prediction model according to the soil type, inputs the standard volume soil sample, soil density data and soil moisture data collected in step S3, the hole position coordinates, hole mouth elevation, sampling depth and soil sample specific gravity parameters entered in step S4 into the selected model, and outputs the preliminary consolidation pressure of the soil.

[0063] Specifically, the detection is performed by first identifying the soil type (clay, silty clay, silty soil) based on the soil density data and soil moisture data collected in step S3.

[0064] Based on the soil type, the system automatically selects the corresponding pre-consolidation pressure detection model: silt soil uses the silt soil pre-consolidation pressure prediction model, and clay and silty clay use the conventional clay soil pre-consolidation pressure prediction model.

[0065] Before inputting the standard volume soil sample, soil density data and soil moisture data collected in step S3, the hole position coordinates, hole mouth elevation, sampling depth and soil sample specific gravity parameters entered in step S4 into the selected model, the soil porosity is calculated using the following formula:

[0066]

[0067] Among them, e is the soil porosity ratio, G s is the specific gravity of the soil, ω is the natural moisture content of the soil, ρ is the natural density of the soil, and ω is the density of water.

[0068] The calculated porosity ratio is input into the selected model together with other collected and entered parameters (including drilling location coordinates, hole elevation, sampling depth, natural moisture content, natural density and specific gravity, etc.). Through model calculation, the preliminary consolidation pressure value of the soil is output.

[0069] S6 compares the previous consolidation pressure value with the current effective deadweight stress of the soil to generate a soil consolidation state determination result.

[0070] Specifically, the ratio of the previous consolidation pressure value to the current effective self-weight stress, namely the overconsolidation ratio (OCR), is calculated:

[0071] OCR=Preliminary consolidation pressure / Current effective deadweight stress

[0072] According to the value of the overconsolidation ratio, the soil consolidation state (normally consolidated soil, overconsolidated soil or underconsolidated soil) and stress history are determined.

[0073] The results of consolidation state determination can be directly applied to foundation treatment design, foundation design and foundation settlement calculation of engineering projects, providing important parameter support for the project.

[0074] Figure 2 The system architecture diagram of a device for detecting the pre-consolidation pressure of clay soil is shown.

[0075] FIG3 shows a schematic structural diagram of a device for detecting the pre-consolidation pressure of clay soil.

[0076] Reference Figure 2 As shown in FIG3 , the present application also provides a device for detecting the pre-consolidation pressure of clay soil, comprising: a database module 101 , a model building module 102 , a data acquisition module 103 , a parameter input module 104 , a detection execution module 105 , and a result analysis module 106 .

[0077] The database module 101 is used to establish a structured database including borehole coordinates, hole elevation, sampling depth, soil physical properties and pre-consolidation pressure based on historical drilling data and geotechnical test data in the project area.

[0078] Specifically, the database module 101 is set in the Windows touch computer 1. The database module 101 includes a data screening unit for setting thresholds and conditional variables for a structured database to screen data in the database.

[0079] Thresholds include the maximum and minimum values of the data; conditional variables are used to determine the logical correlation between data.

[0080] The structured data of the silt soil or conventional clay soil in the structured database is screened according to the threshold value and the conditional variable.

[0081] The structured database can be stored locally on a computer or in a cloud server, supporting multi-terminal access and data synchronization.

[0082] The model construction module 102 is configured to divide the data in the structured database into a silt soil data subset and a conventional clay soil data subset according to soil type; based on the silt soil data subset, a neural network algorithm is used to construct a silt soil early consolidation pressure prediction model; based on the conventional clay soil data subset, a neighborhood rough set algorithm is used to construct a clay and silty clay early consolidation pressure prediction model;

[0083] Specifically, the structured database is first divided into a silty soil data subset and a conventional clay soil data subset (including clay and silty clay) according to the soil type field.

[0084] The model building module 102 is set in the Windows touch computer 1, and uses different intelligent algorithms to build early consolidation pressure prediction models for clay soils with different properties.

[0085] Based on the silt soil data subset, the model building module 102 applies a neural network algorithm to build a prediction model.

[0086] Based on the conventional clay soil data subset, the model building module 102 uses a neighborhood rough set algorithm to build a prediction model.

[0087] The data acquisition module 103 is used to obtain standard volume soil samples, soil density data and soil moisture content data;

[0088] Specifically, the data acquisition module 103 includes a ring knife 2, an electronic balance 3 and a handheld soil moisture tester.

[0089] Ring knife 2 is used to prepare standard volume soil samples; the dimensions of ring knife 2 include: bottom area 30cm 2 , height 2cm, volume 60cm 3 .

[0090] The electronic balance 3 weighs the prepared sample to obtain the natural mass of the soil, and the natural density and natural weight of the soil are calculated in combination with the volume of the ring cutter 2; the electronic balance 3 is connected to the Windows touch computer 1 through the RS232 serial port 7, and the measurement results are automatically transmitted to the computer.

[0091] The probe of the handheld soil moisture tester is inserted into the soil sample to quickly detect the natural moisture content of the soil; the handheld soil moisture tester 4 is connected to the Windows touch computer 1 through the moisture tester socket 9 to realize automatic data collection.

[0092] The parameter input module 104 is used to input the coordinates of the drilling position, the elevation of the hole, the sampling depth and the specific gravity of the soil sample.

[0093] Specifically, the parameter input module 104 is set in the Windows touch computer 1, providing a user interface for technicians to manually input parameters such as drilling position coordinates (X, Y), drilling hole elevation, sample representative bottom depth and soil sample specific gravity.

[0094] The detection execution module 105 is used to select the silt soil prediction model or the conventional clay soil prediction model according to the soil type, input the standard volume soil sample, soil density data and soil moisture content data collected by the data acquisition module 103, and the drilling position coordinates, hole elevation, sampling depth and soil sample specific gravity parameters input by the parameter input module 104 into the selected model, and output the preliminary consolidation pressure value of the soil;

[0095] Specifically, the detection execution module 105 is set in the Windows touch computer 1, including a soil type identification unit, a model selection unit and a parameter calculation unit:

[0096] The soil type identification unit identifies the soil type (clay, silty clay, silty soil) based on the soil moisture content data and soil density data collected by the data collection module 103 .

[0097] The model selection unit automatically selects an applicable pre-consolidation pressure prediction model according to the soil type.

[0098] The parameter calculation unit is used to calculate the soil porosity before inputting the standard volume soil sample, soil density data and soil moisture data collected by the data acquisition module 103, the drilling position coordinates, hole elevation, sampling depth and soil sample specific gravity parameters input by the parameter input module 104 into the selected model; the calculation formula of the porosity is:

[0099]

[0100] Among them, e is the soil porosity ratio, G s is the specific gravity of the soil, ω is the natural moisture content of the soil, ρ is the natural density of the soil, and ω is the density of water; the soil porosity ratio and other parameters are input into the selected model to predict the value of the initial consolidation pressure.

[0101] The result analysis module 106 is used to compare the previous consolidation pressure value with the current effective deadweight stress of the soil to generate a soil consolidation state determination result.

[0102] Specifically, the result analysis module 106 is provided in the Windows touch computer 1 and is used to compare the previous consolidation pressure value with the current effective deadweight stress of the soil to calculate the overconsolidation ratio (OCR):

[0103] OCR=Preliminary consolidation pressure / Current effective deadweight stress

[0104] According to the value of the overconsolidation ratio, the soil consolidation state (normally consolidated soil, overconsolidated soil or underconsolidated soil) and stress history are determined.

[0105] Furthermore, the device for detecting the early consolidation pressure of clay soil also includes a portable integrated work box 10, which is made of lightweight and high-strength material and provides a working space and a fixed platform for a Windows touch computer 1, a ring knife 2, an electronic balance 3, a handheld soil moisture tester 4, etc.

[0106] Furthermore, the device for detecting the early consolidation pressure of clay soil also includes a power module including a rechargeable battery, a power switch 6 and a charging port 5. The rechargeable battery provides power support for the detection device and controls the on / off state of the detection device through the power switch 6; the charging port 5 is connected to an external power supply to provide charging services for the battery.

[0107] Furthermore, the device for detecting the pre-consolidation pressure of clay soil also includes an expansion interface module. The expansion interface unit includes a USB port 8 and an RS232 serial port 7, which facilitates device expansion and data input and output.

[0108] Figure 4 A schematic diagram of the detection process of an engineering site embodiment is shown.

[0109] This example fully demonstrates the technical advantages of this application: by establishing a structured database and constructing prediction models based on different soil data subsets, it significantly shortens the initial consolidation pressure testing cycle, improves work efficiency, and meets the timeliness requirements of engineering survey projects. It also avoids the subjective factors involved in manually drawing the e-log p compression curve and determining the minimum curvature radius, improving the accuracy and consistency of the test results.

[0110] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The scope of protection of the present application is not limited thereto. Although the present application has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed in the present application, or perform equivalent replacements for some of the technical features thereof. These modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the scope of protection of the claims.

Claims

1. A method for detecting the early consolidation pressure of clay soil, characterized in that: include: S1: Based on the historical drilling data and geotechnical test data of the project area, a structured database including drilling coordinates, hole elevation, sampling depth, soil physical properties and pre-consolidation pressure is established; S2 divides the data in the structured database into a silt soil data subset and a conventional clay soil data subset according to the soil type; Based on the said silty soil data subset, a neural network algorithm is used to construct a silty soil early consolidation pressure prediction model; based on the said conventional clay soil data subset, a neighborhood rough set algorithm is used to construct a conventional clay soil early consolidation pressure prediction model; S3 obtains standard volume soil samples, soil density data and soil moisture content data; S4 inputs the coordinates of the drilling position, the elevation of the hole, the sampling depth and the specific gravity of the soil sample; S5 selects the silt soil prediction model or the conventional clay soil prediction model according to the soil type, inputs the standard volume soil sample, soil density data and soil moisture data collected in step S3, the hole position coordinates, hole elevation, sampling depth and soil sample specific gravity parameters entered in step S4 into the selected model, and outputs the preliminary consolidation pressure value of the soil; S6 compares the previous consolidation pressure value with the current effective deadweight stress of the soil to generate a soil consolidation state determination result.

2. The method for detecting the early consolidation pressure of clay soil according to claim 1, characterized in that: In the step S1, the structured database includes: preset thresholds and conditional variables; The threshold value includes the maximum value and the minimum value of the data; The conditional variables are used to determine the logical correlation between data; The structured data of the silt soil or conventional clay soil in the structured database is screened according to the threshold value and the conditional variable.

3. The method for detecting the early consolidation pressure of clay soil according to claim 1, characterized in that: In step S3, obtaining the standard volume soil sample, soil density data, and soil moisture content data includes: The standard volume soil sample is prepared by using a ring cutter; Using an electronic balance to measure the mass of the soil sample to obtain the soil density data; A soil moisture tester is used to detect the soil moisture content data.

4. The method for detecting the early consolidation pressure of clay soil according to claim 1, characterized in that: In step S5, the silt soil prediction model or the conventional clay soil prediction model is selected according to the soil type, including: Based on the soil density data and soil moisture data collected in step S3, the soil type is identified, and the silt soil prediction model or the conventional clay soil prediction model is selected.

5. The method for detecting the early consolidation pressure of clay soil according to claim 1, characterized in that: In step S5, before inputting the standard volume soil sample, soil density data and soil moisture data collected in step S3, the hole position coordinates, hole mouth elevation, sampling depth and soil sample specific gravity parameters entered in step S4 into the selected model, the following steps are included: Calculate the soil porosity ratio. The calculation formula of the porosity ratio is: Among them, e is the porosity ratio of soil, G s is the specific gravity of the soil, ω is the natural moisture content of the soil, ρ is the natural density of the soil, and ω is the density of water; The soil porosity ratio and other parameters are input into the selected model to predict the value of the preliminary consolidation pressure.

6. A device for detecting the early consolidation pressure of clay soil, characterized in that: include: The database module is used to establish a structured database containing borehole coordinates, hole elevation, sampling depth, soil physical properties and pre-consolidation pressure based on historical drilling data and geotechnical test data in the project area; A model building module, configured to divide the data in the structured database into a silt soil data subset and a conventional clay soil data subset according to soil type; Based on the silty soil data subset, a neural network algorithm is used to construct a silty soil early consolidation pressure prediction model; based on the conventional clay soil data subset, a neighborhood rough set algorithm is used to construct a clay and silty clay early consolidation pressure prediction model; Data acquisition module, used to obtain standard volume soil samples, soil density data and soil moisture content data; Parameter input module, used to input drilling position coordinates, hole elevation, sampling depth and soil sample specific gravity parameters; a detection execution module, configured to select the silty soil prediction model or the conventional clay soil prediction model according to the soil type, input the standard volume soil sample, soil density data, and soil moisture data collected by the data acquisition module, and the borehole position coordinates, hole elevation, sampling depth, and soil sample specific gravity parameters input by the parameter input module into the selected model, and output a preliminary consolidation pressure value of the soil; The result analysis module is used to compare the previous consolidation pressure value with the current effective deadweight stress of the soil to generate a soil consolidation state determination result.

7. The device for detecting the early consolidation pressure of clay soil according to claim 6, characterized in that: The database module includes: a data screening unit for setting thresholds and conditional variables for the structured database; The threshold value includes the maximum value and the minimum value of the data; The conditional variables are used to determine the logical correlation between data; The structured data of the silt soil or conventional clay soil in the structured database is screened according to the threshold value and the conditional variable.

8. The device for detecting the early consolidation pressure of clay soil according to claim 6, characterized in that: The data acquisition module includes: A ring cutter, used for preparing the standard volume soil sample; An electronic balance, used to measure the mass of the soil sample to obtain the soil density data; The soil moisture tester is used to detect the soil moisture content data.

9. The device for detecting the early consolidation pressure of clay soil according to claim 6, characterized in that: The detection execution module includes a soil type identification unit, which identifies the soil type based on the soil moisture content data and soil density data collected by the data collection module.

10. The device for detecting the early consolidation pressure of clay soil according to claim 6, characterized in that: The detection execution module includes: a parameter calculation unit, which is used to calculate the soil porosity before inputting the standard volume soil sample, soil density data and soil moisture data collected by the data acquisition module, the drilling position coordinates, hole elevation, sampling depth and soil sample specific gravity parameters input by the parameter input module into the selected model; the calculation formula of the porosity is: Among them, e is the porosity ratio of soil, G s is the specific gravity of the soil, ω is the natural moisture content of the soil, ρ is the natural density of the soil, and ω is the density of water; The soil porosity ratio and other parameters are input into the selected model to predict the value of the preliminary consolidation pressure.

Images