Loess collapsibility evaluation method and system based on geophysical prospecting test technology

Abstract

The invention discloses a loess collapsibility evaluation method and system based on a geophysical prospecting test technology, and relates to the field of land exploration, and the method comprises the steps: laying regular detection grids in a to-be-evaluated loess site, and constructing a site geographic coordinate system; collecting Rayleigh wave signals in real time, inverting a transverse wave velocity profile, and collecting apparent resistivity data; a shallow soil sample is drilled, soil property parameters are measured, and a model is constructed according to the mapping relation between the field geophysical prospecting parameters and the soil property parameters; inputting the acquired data into the wave velocity-water content correlation model and the resistivity-dry density correlation model to generate a water content distribution field and a dry density distribution field; and calculating the collapsibility of loess in each detection grid based on a geophysical prospecting response equation of the collapsibility coefficient, outputting a collapsibility coefficient contour cloud picture, and judging the collapsibility grade of each grid and the distribution range of collapsed loess. The method has the advantages that the collapsibility distribution field and the contour cloud picture are generated through accurate non-intrusive data acquisition and model analysis, and a scientific basis is provided for engineering construction.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of land exploration, in particular to a loess collapsibility evaluation method and system based on geophysical testing technology. BACKGROUND

[0002] Loess collapsibility refers to the volume change phenomenon caused by water adsorption under wet or water condition change, which may lead to foundation settlement or damage and affect the safety of engineering structures. With the advancement of urbanization, engineering construction in loess areas is gradually increasing, therefore, loess collapsibility evaluation has become an important content to ensure engineering safety. Geophysical testing technology can effectively obtain physical parameters and collapsibility characteristics of loess layer. Through geophysical testing, collapsibility information of loess can be quickly obtained without damaging the structure of soil layer, helping engineers to judge the stability and adaptability of foundation.

[0003] Current loess collapsibility evaluation methods based on geophysical testing technology on the market rely on manual sampling and local borehole analysis, and the evaluation results are often limited to point data, which cannot fully cover the entire site and has certain spatial error. In addition, the existing methods often ignore the changes in soil characteristics at different depths, and the depth and breadth of evaluation are limited. Moreover, many existing methods require more field investigation and excavation, which may cause damage to the environment and increase engineering cost and construction period, and the existing methods cannot provide the same degree of data integration and visualization as the present method, and the precision and efficiency are relatively low, and may not be applicable in complex site conditions. SUMMARY

[0004] In order to improve the existing method and system, a loess collapsibility evaluation method and system based on geophysical testing technology is provided, which efficiently generates collapsibility distribution field and contour map through precise non-invasive data acquisition and model analysis, providing a scientific basis for engineering construction. Compared with traditional methods, it has low cost, high precision and strong applicability, significantly improving the evaluation efficiency and reliability.

[0005] To achieve the above purposes, the technical scheme adopted by the present application is: The loess collapsibility evaluation method based on geophysical testing technology comprises: A regular detection grid is arranged in the loess site to be evaluated, a site geographic coordinate system is constructed, and site grid position data is mapped into the coordinate system; Rayleigh wave signals are collected in real time along the grid nodes by a surface wave instrument, the shear wave velocity profile of the underground 0~20m depth range is inverted through the dispersion curve, and apparent resistivity data is collected along the same grid by high-density resistivity method; Based on each detection grid, shallow soil samples are drilled to determine soil parameters, including moisture content and dry density, and based on the mapping relationship between the site geophysical parameters and soil parameters, a model is constructed, including a wave velocity-moisture content correlation model and a resistivity-dry density correlation model; The collected shear wave velocity data and apparent resistivity data are input into the wave velocity-moisture content correlation model and the resistivity-dry density correlation model to interpolate the moisture content distribution field and the dry density distribution field; Based on the geophysical response equation of the collapse coefficient, the collapsibility of the loess in each detection grid is calculated, and the collapse coefficient contour map is output by depth layering to determine the collapse grade of each grid and the distribution range of collapsible loess.

[0006] Preferably, the regular detection grid is laid out in the loess site to be evaluated, and a site geographic coordinate system is constructed, and the site grid position data is mapped into the coordinate system, which specifically includes: Based on the terrain and topography of the loess site, a square grid is selected for layout, the grid size is determined, and a unique identifier is added to each grid; Based on the selected site geographic coordinate system, the local coordinate data of each grid is mapped into the geographic coordinate system.

[0007] Preferably, the Rayleigh wave signals are collected in real time along the grid nodes by the surface wave instrument, the shear wave velocity profile of the underground 0~20m depth range is inverted by the dispersion curve, and the apparent resistivity data is collected along the same grid by the high-density resistivity method, which specifically includes: The surface wave instrument receiver is laid out at each grid node, and the distance between the measurement nodes is determined based on the grid spacing; Rayleigh wave signals are collected along each grid node, data is recorded by receiving the vibration signal of the ground, and a dispersion curve is generated by a dispersion analysis algorithm; The dispersion curve is processed by nonlinear inversion to obtain the shear wave velocity profile data at different depths underground; The electrode array required by the high-density resistivity method is laid out at the same grid nodes, data is collected at each grid node, and the apparent resistivity values at each depth are calculated based on the collected current and voltage signal data.

[0008] Preferably, the shallow soil samples are drilled based on each detection grid, the soil parameters including moisture content and dry density are determined, and based on the mapping relationship between the site geophysical parameters and soil parameters, a model is constructed, including a wave velocity-moisture content correlation model and a resistivity-dry density correlation model, which specifically includes: Based on the laid detection grid, representative positions around the grid nodes are selected for drilling sampling; The collected soil samples are analyzed in the laboratory to obtain soil parameters, including: determining the water content of the soil samples by drying method, and determining the dry density of the soil samples by mass method; Based on the shear wave velocity of different grid nodes and the water content data of the soil samples, the relationship between the wave velocity and the water content is fitted by regression analysis to construct a wave velocity-water content correlation model; Based on the apparent resistivity data of different grid nodes and the dry density of the corresponding soil samples, the relationship between the resistivity and the dry density is fitted by regression analysis to construct a resistivity-dry density correlation model.

[0009] Preferably, the inputting of the collected shear wave velocity data and apparent resistivity data into the wave velocity-water content correlation model and the resistivity-dry density correlation model, and the interpolation to generate the water content distribution field and the dry density distribution field specifically includes: The real-time collected shear wave velocity data are inputted into the wave velocity-water content correlation model to calculate the water content data of each grid node; The apparent resistivity data are inputted into the resistivity-dry density correlation model to calculate the dry density data of each grid node; Based on the obtained water content data and dry density data of each grid node, the water content distribution field and the dry density distribution field of the entire site are obtained by spline interpolation.

[0010] Preferably, the calculation of the collapsibility of loess in each detection grid based on the geophysical response equation of the collapsibility coefficient, and the output of the collapsibility coefficient contour map by depth layering, and the determination of the collapsibility grade and the distribution range of collapsible loess of each grid specifically includes: Based on the ratio of the swelling amount of the soil to the initial volume under saturated water state, the collapsibility coefficient is calculated and obtained; According to the relationship between the physical properties of loess and the collapsibility coefficient, the wave velocity-water content model and the resistivity-dry density model are used for calculation to construct the geophysical response equation; The geophysical data and soil parameters of each grid collected and obtained are inputted into the geophysical response equation to calculate and obtain the collapsibility coefficient in each detection grid; According to the hierarchical division of the depth of the loess area, the collapsibility coefficient of each level is calculated to obtain a continuous collapsibility coefficient distribution field, and a collapsibility coefficient contour map is generated; The collapsibility grade is determined based on the size of the collapsibility coefficient; Based on the collapsibility coefficient and the collapsibility grade of each grid, the spatial distribution of collapsible loess is obtained.

[0011] Further, a loess collapsibility evaluation system based on geophysical testing technology is proposed, which includes: The detection grid and coordinate system module is used for arranging a regular detection grid in a loess site to be evaluated and constructing a site geographic coordinate system, and mapping grid position data to the coordinate system; The data acquisition module is used for collecting Rayleigh wave signals along the grid nodes by a surface wave instrument and collecting apparent resistivity data by a high-density resistivity method, and is used for analyzing underground soil physical parameters; The soil property parameter and model module is used for drilling shallow soil samples and measuring soil property parameters, constructing a wave velocity-moisture content correlation model and a resistivity-dry density correlation model; The distribution field generation module is used for inputting collected shear wave velocity data and apparent resistivity data into the correlation model, and generating a moisture content distribution field and a dry density distribution field by interpolation; The collapsibility calculation module is used for calculating the collapsibility of loess in each detection grid based on a collapsibility geophysical response equation, and outputting a collapsibility contour chart by depth layering and determining a collapsibility grade; The collapsible loess distribution module is used for determining the spatial distribution of collapsible loess based on collapsibility coefficient and collapsibility grade data, and completing collapsibility evaluation; The processor is used for processing the calculation process of each formula and the construction and calculation process of each model.

[0012] Compared with the prior art, the present application has the following advantages: By combining a regular detection grid with a geographic coordinate system, the spatial characteristics of the site can be accurately positioned, and the systematicness and accuracy of data acquisition are ensured. Rayleigh wave signals and apparent resistivity data are collected by a surface wave instrument and a high-density resistivity method, respectively, to realize fine inversion of shear wave velocity and resistivity in the depth range of 0-20 m, and the data coverage is comprehensive and efficient. By combining drilling sampling and laboratory analysis, the wave velocity-moisture content and resistivity-dry density correlation models are established, the soil physical parameters are accurately fitted by regression analysis, and the models have high reliability. The moisture content and dry density distribution fields are generated by using the spline interpolation method, the collapsibility is calculated by combining the collapsibility geophysical response equation, and the depth-layered contour chart is generated to intuitively show the collapsibility grade and distribution range. This method does not need large-scale excavation, reduces environmental damage, has low cost and high efficiency, and is suitable for rapid evaluation of complex terrain sites. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 The method proposed in the present application is shown in the figure; Figure 2 The detection grid and the construction of the site geographic coordinate system are shown in the figure; Figure 3 The acquisition of site geophysical parameters is shown in the figure; Figure 4 The construction model schematic diagram proposed by the present application; Figure 5 The generation of water content distribution field and dry density distribution field schematic diagram proposed by the present application; Figure 6 The determination of collapsibility grade and collapsible loess distribution schematic diagram proposed by the present application. DETAILED DESCRIPTION

[0014] The following description is used to disclose the present application to enable a person skilled in the art to implement the present application. The preferred embodiments in the following description are only as examples, and other obvious modifications can be thought of by a person skilled in the art.

[0015] The loess collapsibility evaluation system based on geophysical test technology comprises: The detection grid and coordinate system module: the detection grid and coordinate system module is used to arrange a regular detection grid in a loess field to be evaluated, and construct a field geographic coordinate system, and map the grid position data to the coordinate system; The data acquisition module: the data acquisition module is used to collect Rayleigh wave signals along the grid nodes by a surface wave instrument, and collect apparent resistivity data by a high-density resistivity method, which is used for underground soil physical parameter analysis; The soil property parameter and model module: the soil property parameter and model module is used to drill shallow soil samples and determine soil property parameters, construct a wave velocity-water content correlation model and a resistivity-dry density correlation model; The distribution field generation module: the distribution field generation module is used to input the collected shear wave velocity data and apparent resistivity data into the correlation model, and generate a water content distribution field and a dry density distribution field by interpolation; The collapsibility calculation module: the collapsibility calculation module is used to calculate the collapsibility of loess in each detection grid based on a collapsibility coefficient geophysical response equation, and output a collapsibility coefficient contour chart by depth layering, and determine the collapsibility grade; The collapsible loess distribution module: the collapsible loess distribution module is used to determine the spatial distribution of collapsible loess based on the collapsibility coefficient and collapsibility grade data, and complete the collapsibility evaluation; The processor: the processor is used to process the calculation process of each formula and the construction calculation process of each model.

[0016] Referring to Figure 1 The loess collapsibility evaluation method based on geophysical test technology comprises: Step one: arranging a regular detection grid in a loess field to be evaluated, constructing a field geographic coordinate system, and mapping the field grid position data to the coordinate system; Step two: Real-time acquisition of Rayleigh wave signals along the grid nodes by the surface wave instrument, inversion of the S-wave velocity profile in the depth range of 0-20m underground through the dispersion curve, and acquisition of apparent resistivity data along the same grid by high-density resistivity method; Step three: Drilling shallow soil samples based on each detection grid, determining soil parameters including moisture content and dry density, and constructing models including wave velocity-moisture content correlation model and resistivity-dry density correlation model according to the mapping relationship between geophysical parameters and soil parameters; Step four: Inputting the acquired S-wave velocity data and apparent resistivity data into the wave velocity-moisture content correlation model and resistivity-dry density correlation model, and interpolating to generate moisture content distribution field and dry density distribution field; Step five: Calculating the collapsibility of loess in each detection grid based on the geophysical response equation of collapsible coefficient, and outputting the collapsible coefficient contour map by depth layering to determine the collapsibility grade and distribution range of collapsible loess in each grid.

[0017] Referring to Figure 2 As shown in the loess field to be evaluated, regular detection grids are laid out, and a site geographic coordinate system is constructed, which specifically includes: Based on the terrain and topography of the loess site, square grids are selected for layout, the size of the grid is determined, and a unique identifier is added to each grid; Based on the selected site geographic coordinate system, the local coordinate data of each grid is mapped to the geographic coordinate system.

[0018] Referring to Figure 3 As shown, Rayleigh wave signals are collected along the grid nodes by the surface wave instrument, and the S-wave velocity profile in the depth range of 0-20m underground is inverted through the dispersion curve, and the apparent resistivity data is collected along the same grid by high-density resistivity method, which specifically includes: Lay out the surface wave instrument receiver at each grid node, determine the distance between the measurement nodes based on the grid spacing; Collect Rayleigh wave signals along each grid node, record data by receiving the vibration signal of the ground, and generate dispersion curves through dispersion analysis algorithm; The dispersion curve is processed by nonlinear inversion to obtain the S-wave velocity profile data at different depths underground; Lay out the electrode array required by high-density resistivity method at the same grid nodes, collect data at each grid node, and calculate the apparent resistivity value at each depth based on the collected current and voltage signal data.

[0019] Specifically, ground vibration signals are collected at each grid node, mainly Rayleigh wave signals are obtained, Rayleigh wave is a surface wave propagating along the ground, sensors on the ground can record vibration data of Rayleigh wave, signal collection can be performed by using an accelerometer, a speed meter or a displacement sensor, and the recorded signal is usually a time series; dispersion analysis is performed on the collected Rayleigh wave signals to obtain a dispersion curve, the dispersion curve is a relationship between wave speed and frequency, indicating the propagation speed of Rayleigh wave at different frequencies, and the dispersion relationship formula is: ; wherein, is the propagation speed at frequency f, is the angular frequency, is the wave number; According to the dispersion curve f and obtained by experiment, the shear wave speed at different depths underground can be deduced; The dispersion curve is used for nonlinear inversion calculation to obtain the shear wave velocity profile underground; An electrode array required by the resistivity method is arranged at the same grid node, a known current is applied through the electrode array, and a voltage difference is measured, the current and voltage signals between each electrode are recorded, and the apparent resistivity is calculated, and the formula is: ; wherein, is the apparent resistivity, is the distance between electrodes, is the applied current, is the measured voltage difference; By continuously changing the configuration of the electrodes and the applied current, the apparent resistivity values at different depths are obtained, and the resistivity profile at different depths underground is calculated according to the resistivity data.

[0020] Referring to FIG. 1, Figure 4 Based on the shallow soil samples drilled in each detection grid, soil parameters including water content and dry density are determined, and a model is constructed according to the mapping relationship between the geophysical parameters and the soil parameters, including a wave speed-water content correlation model and a resistivity-dry density correlation model, which specifically includes: Based on the detection grid arranged, representative positions around the grid nodes are selected for drilling sampling; The collected soil samples are analyzed in the laboratory to obtain soil parameters, including: the water content of the soil sample is determined by drying method, and the dry density of the soil sample is determined by mass method; Based on the shear wave speed and water content data of the soil samples at different grid nodes, the relationship between wave speed and water content is fitted by regression analysis to construct a wave speed-water content correlation model; Based on the apparent resistivity data of different grid nodes and the dry density of the corresponding soil sample, the relationship between resistivity and dry density is fitted by regression analysis to construct the resistivity-dry density correlation model.

[0021] Specifically, the water content is analyzed by the drying method, and the drying method specifically includes placing a certain mass of soil sample into an oven, drying at 105 DEG C + 5 DEG C for 24 hours, and measuring the dry weight after cooling; the dry density is analyzed by the mass method, and the mass method specifically includes calculating the dry density of the soil sample according to the dry weight of the soil sample and the volume of the soil sample; Based on the shear wave velocity obtained by surface wave detection and the water content of the soil sample obtained by laboratory analysis, data is collected at different grid nodes; The relationship between the shear wave velocity and the water content is fitted by regression analysis, and the formula is: ; wherein, the natural water content of the loess, the shear wave velocity, a is the logarithmic coefficient, b is the power function coefficient, and c is the power index; The apparent resistivity data obtained by the resistivity method and the dry density obtained by laboratory analysis are collected at different grid nodes; The relationship between the apparent resistivity and the dry density is fitted by using the regression method, and the formula is: ; wherein, the dry density of the loess, the apparent resistivity, the scale factor, the resistivity index, the background density offset.

[0022] Referring to Figure 5 The collected shear wave velocity data and apparent resistivity data are input into the wave velocity-water content correlation model and the resistivity-dry density correlation model, and the interpolation is performed to generate the water content distribution field and the dry density distribution field, and the interpolation specifically includes: The real-time collected shear wave velocity data are input into the wave velocity-water content correlation model to calculate the water content data of each grid node; The apparent resistivity data are input into the resistivity-dry density correlation model to calculate the dry density data of each grid node; Based on the obtained water content data and dry density data of each grid node, the water content distribution field and the dry density distribution field of the entire site are obtained by spline interpolation.

[0023] Specifically, for the shear wave velocity of each grid node, the corresponding water content is calculated by substituting the wave velocity-water content correlation model; for the apparent resistivity of each grid node, the corresponding dry density is calculated by substituting the resistivity-dry density correlation model; Based on the water content data and dry density data of the grid nodes, a continuous water content distribution field and a dry density distribution field are generated by spline interpolation, usually cubic spline interpolation, in the two-dimensional plane of the entire site; The coefficients of cubic spline interpolation are determined by the following conditions, including: node value condition: the interpolation function passes through the data of all grid nodes; continuity condition: the first and second derivatives of the function at the nodes are continuous; boundary condition: natural boundary condition or fixed boundary condition is usually used; Through interpolation, the water content distribution field and the dry density distribution field of the entire site are obtained, which represent the water content and dry density values of any point in the site.

[0024] Referring to Figure 6 As shown, the collapsibility of loess in each detection grid is calculated based on the geophysical response equation of the collapsibility coefficient, and the collapsibility coefficient contour map is output by depth layering, and the collapsibility grade of each grid and the distribution range of collapsible loess are determined, which specifically includes: Based on the ratio of the swelling amount of the soil to the initial volume under saturated water state, the collapsibility coefficient is calculated and obtained; According to the relationship between the physical properties of loess and the collapsibility coefficient, the wave velocity-water content model and the resistivity-dry density model are used for calculation and construction to build the geophysical response equation; The geophysical data and soil parameters of each grid collected are input into the geophysical response equation to calculate and obtain the collapsibility coefficient in each detection grid; According to the hierarchical division of the depth of the loess site area, the collapsibility coefficient of each level is calculated to obtain a continuous collapsibility coefficient distribution field and generate a collapsibility coefficient contour map; The collapsibility grade is determined based on the size of the collapsibility coefficient; Based on the collapsibility coefficient and the collapsibility grade of each grid, the spatial distribution of collapsible loess is obtained.

[0025] Specifically, the collapsibility coefficient refers to the ratio of the swelling amount of the soil to the initial volume of the soil under saturated water state. According to the relationship between the physical properties of loess and the collapsibility coefficient, the collapsibility coefficient is calculated through the existing wave velocity-water content correlation model and resistivity-dry density correlation model, and is represented by the geophysical response equation, which is: ; Wherein, is the collapsibility coefficient, is the difference between the saturated state and the natural state shear wave velocity, is a natural state shear wave velocity, is a difference between the saturated state and the natural state resistivity, is a natural state apparent resistivity, is a wave velocity attenuation contribution weight, is a resistivity change contribution weight, is a resistivity nonlinear response index; The geophysical data and soil property parameters of each grid collected are input into the geophysical response equation, and based on these data, the collapse coefficient of each grid node is obtained; According to the depth of the loess field region, hierarchical division is performed, the collapse coefficient of each layer can be obtained by calculating the geophysical data at different depths, the collapse coefficient distribution field of the entire region is obtained by calculating the collapse coefficients at different depths, based on the calculated collapse coefficient distribution field, the contour map of the collapse coefficient is generated, according to the size of the collapse coefficient, the collapsibility is graded, usually by setting a threshold to divide the collapse coefficient into several grades, based on the collapse coefficient and the collapsibility grade of each grid, the spatial distribution of the collapsible loess is obtained.

[0026] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the above describes the specific embodiments of the present specification. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

[0027] Each embodiment in the specification is described in a progressive manner, and the same and similar parts between each embodiment can be referred to each other, and each embodiment mainly describes the difference from other embodiments.

[0028] The above only describes the preferred embodiments of the present application, and does not limit the present application, any modification, equivalent replacement, improvement, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A loess collapsibility evaluation method based on geophysical testing technology is characterized by: include: A regular detection grid is laid out on the loess site to be evaluated, a site geographic coordinate system is constructed, and the site grid position data is mapped to the coordinate system; Rayleigh wave signals were collected in real time along the grid nodes using a surface wave meter. The shear wave velocity profile at a depth of 0-20 m was inverted using dispersion curves. Apparent resistivity data were collected along the same grid using the high-density resistivity method. Based on the shallow soil samples drilled in each detection grid, soil parameters, including water content and dry density, were measured. Based on the mapping relationship between the site geophysical parameters and soil parameters, models were constructed, including the wave velocity-water content correlation model and the resistivity-dry density correlation model. The acquired shear wave velocity data and apparent resistivity data are input into the wave velocity-water content correlation model and the resistivity-dry density correlation model to interpolate and generate the water content distribution field and dry density distribution field; The collapsibility of loess in each detection grid is calculated based on the geophysical response equation of the collapsibility coefficient, and the collapsibility coefficient contour map is output according to the depth layer to determine the collapsibility grade of each grid and the distribution range of the collapsible loess.

2. The loess collapsibility evaluation method based on geophysical testing technology according to claim 1 is characterized in that: The process of laying out a regular detection grid on the loess site to be evaluated, constructing a site geographic coordinate system, and mapping the site grid position data to the coordinate system specifically includes: Based on the topography and landform of the loess site, square grids are selected for layout, the grid size is determined, and a unique identifier is added to each grid; Based on the selected site geographic coordinate system, the local coordinate data of each grid is mapped to the geographic coordinate system.

3. The loess collapsibility evaluation method based on geophysical testing technology according to claim 1 is characterized in that: The real-time acquisition of Rayleigh wave signals along the grid nodes by the surface wave meter, the inversion of the shear wave velocity profile in the underground depth range of 0-20m by the dispersion curve, and the acquisition of apparent resistivity data along the same grid by the high-density resistivity method specifically include: Surface wave receivers are arranged at each grid node, and the distance between measurement nodes is determined based on the spacing of the grid setting; Rayleigh wave signals are collected along each grid node, data is recorded by receiving ground vibration signals, and dispersion curves are generated through dispersion analysis algorithms; The dispersion curve is processed through nonlinear inversion to obtain the shear wave velocity profile data at different depths underground; The electrode array required for the high-density resistivity method is arranged at the same grid nodes, data is collected at each grid node, and the apparent resistivity value at each depth is calculated based on the collected current and voltage signal data.

4. The loess collapsibility evaluation method based on geophysical testing technology according to claim 1 is characterized in that: The shallow soil samples are drilled based on each detection grid to measure soil parameters, including water content and dry density. Based on the mapping relationship between the site geophysical parameters and the soil parameters, a model is constructed, including a wave velocity-water content correlation model and a resistivity-dry density correlation model. Specifically, the following are included: Based on the laid-out detection grid, representative locations around the grid nodes are selected for drilling sampling; Conduct laboratory analysis on the collected soil samples to obtain soil parameters, including: measuring the moisture content of the soil samples by drying method and measuring the dry density of the soil samples by mass method; Based on the shear wave velocity at different grid nodes and the water content data of soil samples, the relationship between wave velocity and water content is fitted through regression analysis to construct a wave velocity-water content correlation model. Based on the apparent resistivity data of different grid nodes and the dry density of the corresponding soil samples, the relationship between resistivity and dry density was fitted through regression analysis, and a resistivity-dry density correlation model was constructed.

5. The loess collapsibility evaluation method based on geophysical testing technology according to claim 1 is characterized in that: The step of inputting the acquired shear wave velocity data and apparent resistivity data into the velocity-water content correlation model and the resistivity-dry density correlation model to interpolate and generate the water content distribution field and the dry density distribution field specifically includes: Input the real-time collected shear wave velocity data into the wave velocity-water content correlation model to calculate the water content data of each grid node; Input the apparent resistivity data into the resistivity-dry density correlation model to calculate the dry density data of each grid node; Based on the obtained moisture content data and dry density data of each grid node, the spline interpolation method is used to perform interpolation processing to obtain the moisture content distribution field and dry density distribution field of the entire site.

6. The loess collapsibility evaluation method based on geophysical testing technology according to claim 1 is characterized in that: The geophysical response equation based on the collapsibility coefficient is used to calculate the collapsibility of loess in each detection grid, and a collapsibility coefficient contour map is output according to depth. The collapsibility grade of each grid and the distribution range of the collapsible loess are determined specifically as follows: The collapsibility coefficient is calculated based on the ratio of the volume expansion of the soil due to water changes to the initial volume when the soil is saturated with water. According to the relationship between the physical properties of loess and the collapsibility coefficient, the wave velocity-water content model and the resistivity-dry density model are used to calculate and construct the geophysical response equation. Input the collected geophysical data and soil parameters of each grid into the geophysical response equation to calculate the collapsibility coefficient of each detection grid; Divide the loess site into layers according to its depth, calculate the collapsibility coefficient of each layer, obtain a continuous distribution field of the collapsibility coefficient, and generate a contour map of the collapsibility coefficient; Determine the level of collapsibility based on the size of the collapsibility coefficient; Based on the collapsible coefficient and collapsible grade of each grid, the spatial distribution of collapsible loess is obtained.

7. A loess collapsibility evaluation system based on geophysical testing technology, used to implement the loess collapsibility evaluation method based on geophysical testing technology according to any one of claims 1 to 6, characterized in that: include: Detection grid and coordinate system module: The detection grid and coordinate system module lays out a regular detection grid on the loess site to be evaluated, constructs the site geographic coordinate system, and maps the grid position data into the coordinate system; Data acquisition module: The data acquisition module collects Rayleigh wave signals along the grid nodes through a surface wave meter and collects apparent resistivity data through a high-density resistivity method for underground soil physical parameter analysis; Soil parameter and model module: The soil parameter and model module constructs a wave velocity-water content correlation model and a resistivity-dry density correlation model by drilling shallow soil samples and measuring soil parameters; Distribution field generation module: The distribution field generation module inputs the collected shear wave velocity data and apparent resistivity data into the correlation model, and generates the water content distribution field and dry density distribution field through interpolation; Collapsibility calculation module: The collapsibility calculation module calculates the collapsibility of loess in each detection grid based on the geophysical response equation of the collapsibility coefficient, and outputs a contour line cloud map of the collapsibility coefficient by depth layer to determine the collapsibility grade; Collapsible loess distribution module: The collapsible loess distribution module determines the spatial distribution of collapsible loess based on the collapsible coefficient and collapsible grade data, and completes the collapsible assessment; Processor: The processor is used to process the calculation process of each formula and the construction calculation process of each model.

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