A method and system for determining soil cohesion

Abstract

The application relates to the technical field of soil detection, and discloses a soil cohesion force determination method and system. The method comprises the following steps: obtaining an original determination value of soil cohesion force, constructing a statistical matrix, screening effective samples by calculating a correlation score, generating a correction value to check the original determination value; screening effective samples by calculating a correlation score, and performing secondary screening according to the occurrence frequency of historical deviation values and through inter-group correlation analysis to optimize the checking data set. The application quantifies and compensates systematic deviation in the measurement process, overcomes the defect that single measurement is easily affected by external disturbance, improves the accuracy and repeatability of the output value of the corrected cohesion force, and eliminates statistical outliers and accidental deviation data, so that the checking data set has inherent consistency and the checking accuracy is improved.

Description

Technical Field

[0001] This invention belongs to the field of soil testing technology, specifically relating to a method and system for determining soil cohesion. Background Technology

[0002] Soil cohesion, as a core indicator characterizing the cohesive effect between soil particles, determines the structural stability, shear strength, and erosion resistance of soil. Especially in construction engineering, soil cohesion measurement can be used to assess foundation bearing capacity, slope stability, and foundation pit support design. In addition, in modern agricultural production, soil cohesion can be used to assess soil tillage performance, water and fertilizer retention capacity, and soil erosion risk.

[0003] Currently, the measurement of soil cohesion is affected by the temperature and humidity changes in the on-site environment, which directly affect the soil moisture content and cause fluctuations in the measured cohesion value. This results in low accuracy of the measurement results and poses a potential risk to engineering safety assessment. Furthermore, existing measurement methods usually require a laboratory environment, and differences in the sampling, sample preparation, and loading processes can damage the original stress state and structure of the soil, easily introducing errors. At the same time, the measured cohesion value deviates from the true value under the in-situ condition of the soil, affecting the representativeness of the measurement results and causing data distortion.

[0004] In view of this, the present invention provides a method and system for determining soil cohesion. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for measuring soil cohesion, so as to solve the technical problem that the measured cohesion in the prior art fluctuates and deviates, which leads to the overestimation or underestimation of soil cohesion.

[0006] The specific technical solution adopted by this invention is as follows: A method for determining soil cohesion includes the following steps: Based on the set sampling interval, determine the sampling area that includes the reference point and the sampling point; Soil samples were collected at the reference point and the sampling point to prepare the sampling assembly; The sampling assembly was used to obtain raw measurements of soil cohesion. When the original measured value of soil cohesion is obtained, the following steps are performed: Based on multiple pre-stored historical deviation values, a correction value is determined to correct the original measured value; Based on the original measured value and the correction value, the corrected cohesion output value is calculated.

[0007] The process of determining the correction value for correcting the original measurement value based on multiple pre-stored historical deviation values ​​includes: constructing a statistical matrix based on multiple historical deviation values; selecting valid samples with correlation scores greater than a preset score threshold by calculating the correlation scores between each sequence in the statistical matrix; and calculating the correction value based on the valid samples.

[0008] Preferably, the measurement and sampling assembly for obtaining raw measurements of soil cohesion includes: A tensile force is applied to the sampling component until it undergoes adhesive breakage; the instantaneous tensile force value at the point of adhesive breakage is determined as the original measured value.

[0009] Preferably, after filtering out valid samples with relevance scores greater than a preset score threshold, the method further includes: The frequency of each historical deviation value in the effective samples is counted to determine the candidate samples; by performing inter-group correlation analysis on the candidate samples, candidate samples with correlation values ​​lower than the preset correlation threshold are discarded to optimize the effective samples.

[0010] Preferably, the correction value calculated based on valid samples includes: For each valid sample, the average of its historical deviation values ​​is calculated to obtain the average deviation; one of the multiple average deviations is designated as the benchmark deviation, and the remaining average deviations are compared with the benchmark deviation to generate a verification dataset consisting of multiple correction coefficients; the parameter verification range is determined based on the verification dataset; verification parameters are selected within the parameter verification range; and the correction values ​​are calculated based on the verification parameters.

[0011] A system for measuring soil cohesion includes the following modules: The raw measurement module is used to obtain the raw measurement values ​​of soil cohesion. The adhesion strength verification module is used to perform the following actions in response to the original measurement values ​​obtained by the original measurement module: determine the correction value based on multiple pre-stored historical deviation values, and calculate the corrected adhesion strength output value based on the original measurement value and the correction value.

[0012] Preferably, obtaining the original measured value of soil cohesion includes: Based on the established sampling interval, determine the sampling area that includes the reference point and the sampling point; collect soil samples at the reference point and the sampling point to prepare a sampling assembly; measure the sampling assembly to obtain the raw measurement values.

[0013] Preferably, the measurement sampling component for obtaining raw measurement values ​​includes: A tensile force is applied to the sampling component until it undergoes adhesive breakage; the instantaneous tensile force value at the point of adhesive breakage is determined as the original measured value.

[0014] Preferably, determining the correction value based on multiple pre-stored historical deviation values ​​includes: A statistical matrix is ​​constructed based on multiple historical deviation values; by calculating the correlation scores between each sequence in the statistical matrix, valid samples with correlation scores greater than a preset score threshold are selected; and correction values ​​are calculated based on the valid samples.

[0015] Preferably, after filtering out valid samples with relevance scores greater than a preset score threshold, the method further includes: The frequency of each historical deviation value in the effective samples is counted to determine the candidate samples; by performing inter-group correlation analysis on the candidate samples, candidate samples with correlation values ​​lower than the preset correlation threshold are discarded to optimize the effective samples.

[0016] Preferably, the step of calculating the correction value based on valid samples includes: For each valid sample, the average of its historical deviation values ​​is calculated to obtain the average deviation; one of the multiple average deviations is designated as the benchmark deviation, and the remaining average deviations are compared with the benchmark deviation to generate a verification dataset consisting of multiple correction coefficients; the parameter verification range is determined based on the verification dataset; verification parameters are selected within the parameter verification range; and the correction values ​​are calculated based on the verification parameters.

[0017] Beneficial effects This invention obtains the original measured value of soil cohesion, constructs a statistical matrix based on pre-stored historical deviation values, and then generates a correction value by calculating the correlation score to screen valid samples and verify the original measured value. This compensates for systematic deviations in the measurement process, overcomes the influence of external disturbances on a single measurement, and improves the accuracy and repeatability of the corrected cohesion output value.

[0018] In the process of calculating the correction value, this invention selects effective samples by calculating the correlation score, and performs secondary screening based on the frequency of occurrence of historical deviation values ​​and through inter-group correlation analysis to optimize the verification dataset. This can eliminate statistical outliers and random deviation data, making the verification dataset internally consistent and improving the verification accuracy.

[0019] In the sampling stage, this invention determines the sampling points by setting the measurement path and sampling interval, and accurately determines the location of the sampling points based on the reference point and preset offset parameters, ensuring the consistency of the spatial layout of sample collection and enhancing the repeatability of the entire soil cohesion determination method. Attached Figure Description

[0020] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a flowchart of the method for optimizing effective samples according to the present invention; Figure 3This is a flowchart of the method for calculating correction values ​​based on valid samples according to the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely for explaining the invention and are not intended to limit the scope of protection of the invention.

[0022] Example 1 Please see Figures 1-3 This embodiment provides a method for determining soil cohesion, including the following steps: Set up a sampling strategy and acquire spatial information to decompose the measurement task into a series of executable sampling points; delineate the area to be measured on an electronic map or field survey map, and plan one or more representative measurement paths within the area to be measured; determine the path length of the measurement path and output the coordinate information of its starting and ending points to form the boundary definition for automated sampling equipment navigation or manual positioning by operators. Based on the predicted homogeneity of the soil in the target area or historical experience, a sampling interval is preset, wherein the preset sampling interval is once every 5 meters; according to the measurement path and sampling interval, multiple measurement points are set up on the path, and the geographic coordinate information of all measurement points is acquired and recorded; a circular or square area with a preset radius of 0.5 meters around each measurement point is determined as the sampling area for performing a single sampling, while the measurement point itself defines the logical sampling interval.

[0023] Furthermore, dual-point displacement sampling is performed and a sampling assembly is prepared. Dual-point displacement sampling involves setting a reference point and a sampling point with a fixed offset, and after sampling at the two points, they are brought into contact and compacted together under pressure. This creates a physical interface with known geometric features inside the soil sample to simulate natural shear failure within the soil, and this interface is used as an artificial shear surface. In each of the defined sampling areas, the position of the measurement point is set as the reference point, and the reference point is used as the origin (0,0) of the local coordinate system of that area; and the position of the sampling point is calculated and determined according to the preset offset direction and preset offset distance; wherein, the preset offset direction is perpendicular to the tangent direction of the measurement path at that point, and the preset offset distance is 5 cm; The area containing the reference point and the sampling point was identified as the designated area for preparing the sampling component. Two independent soil samples were collected at the reference point and the sampling point, respectively. The two soil samples were then tightly bonded together in a special mold and prepared into a complete sampling component through a standardized pressure compaction process. The bonding surface formed by the two soil samples inside the sampling component is the bonding surface to be tested in this measurement. The standardized pressure compaction molding process involves applying 50 Newtons of pressure for 10 seconds.

[0024] Further, physical measurements are performed and raw measured values ​​are obtained. After obtaining the prepared sampling component, it is installed on a tensile testing device, and the direction of tensile force application is ensured to be perpendicular to the bonding surface to be tested. Then, based on the material properties and bonding characteristics of the sampling components, a standardized tensile loading process is set; tensile force is applied at a preset constant displacement rate. During the tensile loading process, data acquisition is performed at a high frequency to continuously record and generate a complete data curve of the instantaneous tensile force value changing with time or displacement. The constant displacement rate can be 2 mm / min, and the high-frequency continuous recording of data acquisition is performed at a frequency of 100 Hz. When the tensile force increases to a critical point, causing the sampling component to undergo macroscopically visible bond fracture on the bonding surface to be tested; the peak tensile force on the current data curve is acquired and recorded, and the peak tensile force is determined as the original measured value of soil bonding force; the time or displacement reading corresponding to the moment of bond fracture is recorded as the benchmark reference point for subsequent calculations.

[0025] Furthermore, a verification procedure was constructed and a correction value was calculated. The original measured value is easily affected by various non-target factors such as ambient temperature and humidity and the drift of the equipment sensor itself. In order to obtain soil cohesion that reflects the true physical properties of the soil, the data was corrected through a verification procedure based on statistical analysis of historical data. The verification procedure based on historical data statistical analysis includes: obtaining multiple historical deviation values ​​by repeatedly measuring standard soil samples under various preset standardized experimental conditions, specifically under different combinations of temperature, humidity, and the use of different batches of sensors, to quantify the error under each experimental condition; The process of obtaining historical deviation values ​​is as follows: under various experimental conditions, tensile tests are conducted to obtain complete data curves of instantaneous tensile values ​​changing with time or displacement; in each set of complete data curves of instantaneous tensile values ​​changing with time or displacement, two fixed measurement nodes are selected as calculation base points to define the effective data range for calculating stress response rate; specifically, the calculation base points can be selected at two points where the tensile force reaches 20% and 80% of the peak value; The instantaneous average tensile force corresponding to each of the two calculation base points is obtained, and the time difference between the two points is calculated as the fracture time difference; where the instantaneous average tensile force is the arithmetic mean of the tensile force data recorded by the sensor, which is used to smooth high-frequency noise; the fracture time difference reflects the deformation response speed of the soil sample during the stress process; The verification parameters are calculated using a preset calculation formula. The calculation formula is based on the ratio of the difference between two instantaneous average tensile forces to the difference in fracture time, which reflects the stress-strain response characteristics of the material. The calculation formula for the verification parameters is as follows:

[0026] In the formula, This represents the verification parameter, which describes the dynamic stiffness characteristic value of the soil sample under specific environmental conditions. This represents the average tension at the first instant, meaning the instantaneous average tension value at the first measurement node; This represents the second instantaneous average tension, which is the instantaneous average tension value at the second measurement node. This represents the time difference between two measurement points. This represents the stiffness coefficient, which is a preset material linear response weighting factor. This represents the viscosity coefficient, which is a preset material viscosity effect weighting factor. The verification parameters are compiled into verification data, and the difference between each verification parameter and the standard value measured under ideal standard conditions is determined as the historical deviation value. Multiple historical deviation values ​​and their corresponding experimental condition data are organized into a data table, where each row represents an independent experimental record. To assess the similarity of error patterns in different experimental records, the correlation between rows was calculated; any selected row in the data table was used as the baseline sequence, and the remaining rows were used as comparison sequences; by calculating correlation coefficients such as the Pearson correlation coefficient between the baseline sequence and each comparison sequence, a correlation score was obtained to quantify the degree of similarity between the two sequences. The experimental records are sorted in descending order based on the calculated correlation scores, and those with correlation scores greater than a preset score threshold are identified as valid samples. The preset score threshold is 0.85. To further refine the data, effective samples are screened: the frequency of occurrence of each historical deviation value range in the effective samples is statistically analyzed, and effective samples with a frequency greater than a preset frequency threshold are identified as candidate samples, where the preset frequency threshold is that the occurrence frequency accounts for more than 10% of the total number of effective samples; among the candidate samples, two groups of candidate samples are randomly selected for inter-group correlation analysis to obtain the inter-group correlation value in order to assess the redundancy between samples. If the correlation value between groups is lower than the preset correlation threshold, it indicates that the two groups of samples represent different error patterns and are retained simultaneously. The preset correlation threshold is 0.95. If the correlation value between groups is higher than the threshold, it indicates that the two groups of data are redundant. In this case, one of the two groups of candidate samples is discarded according to the preset selection rule. The preset selection rule is to prioritize retaining the candidate samples corresponding to experimental conditions that are closer to the current measurement environment parameters, such as temperature and humidity. After the above screening, for each retained cluster that has become highly correlated, the arithmetic mean of the historical deviation values ​​contained therein is calculated to obtain the average deviation, and the experiment number associated with the effective sample cluster is recorded. From the calculated average deviations, the one that best matches the experimental conditions and environmental parameters such as temperature, humidity and equipment model measured on-site is selected as the baseline deviation; the other average deviations are compared with the baseline deviation one by one to generate a verification dataset consisting of multiple correction coefficients. Calculate the deviation between each correction coefficient in the verification dataset and the preset benchmark difference, which is usually zero, and determine the error range based on the statistical distribution of the deviation, such as the standard deviation. Based on the error range, set a reasonable parameter verification range, and select the optimal verification parameter within this range by interpolation or table lookup. Based on the relationship between the optimal verification parameter and the benchmark deviation, calculate the correction value used to correct this measurement using a preset conversion formula. The formula for calculating the correction value used to correct this measurement is as follows:

[0027] In the formula, This indicates the correction value, which represents the amount of mechanical compensation that needs to be added to the original measured value. The baseline deviation represents the average deviation between the associated experimental conditions and the current field environment. This represents the optimal calibration parameter, which is the correction factor determined within the parameter calibration range that best reflects the characteristics of the current measurement error. This refers to the reference parameter, which means the benchmark value of the verification parameter under the preset standard state. This represents the adjustment factor, which is a dimensionless coefficient used to adjust the correction sensitivity.

[0028] Furthermore, the correction results are output and verification is performed. Based on the calculated correction value and the obtained original measurement value, the corrected bond strength output value that reflects the true bonding characteristics of the soil is calculated by adding the original measurement value and the correction value or adjusting the ratio. An optional verification step can be performed before outputting the final result to ensure the robustness of the verification procedure. The verification step selects any one of the calculated average deviations, applies a preset small numerical offset to the selected item to generate alternative verification parameters, and recalculates the candidate adhesion results based on the alternative verification parameters and the original measured values. The small numerical offset is 5% of the value, either increasing or decreasing it. The average deviation value after superimposing the numerical offset on the alternative verification parameter is used to simulate the compensation mechanism when a positive numerical offset is applied to the average deviation, and a negative numerical offset of equal magnitude and opposite direction is applied to the original measured value. By observing the variation of the candidate cohesion result relative to the corrected cohesion output value, the sensitivity and stability of the verification process can be evaluated. If the variation is lower than the preset amplitude threshold (which can be less than 2%), the verification process is considered robust. The corrected and verified cohesion output value is recorded or displayed as the final soil cohesion result.

[0029] Example 2 This embodiment provides a soil bonding strength measurement system, including the following modules: The raw measurement module is used to obtain the raw measurement value of soil cohesion and determine the sampling interval based on external input or internal preset sampling strategy. Based on the sampling interval, a sampling area is defined that includes a reference point and at least one sampling point; wherein, the reference point can serve as a benchmark for measurement, while the sampling point is used to collect representative soil samples. Then, the operator is controlled or guided to collect soil at the reference point and the sampling point, and to prepare the sampling assembly for subsequent measurement according to the standard procedure. The sampling assembly can be in the form of a standard-sized soil sample cylinder or other shapes suitable for tensile testing. The sampling component is measured to obtain the original measured value. Specifically, a tensile force is continuously applied to the sampling component through an integrated or externally connected tensile testing device until it breaks due to insufficient cohesion. The tensile force is monitored in real time by a built-in sensor, and the instantaneous tensile force value at the moment of detection of bond breakage is captured and determined as the original measured value of this measurement.

[0030] The adhesion strength verification module is used to perform data analysis and calculation after receiving the original measurement value to determine the correction value used to correct the original measurement value, and finally calculate the corrected adhesion strength output value. Upon receiving the original measured value, multiple historical deviation values ​​are retrieved from a pre-stored database or storage unit; these historical deviation values ​​are records of the deviation between the original measured value and the standard value when measurements were previously performed under similar conditions. A statistical matrix is ​​constructed based on multiple historical deviation values. In the statistical matrix, different rows or columns can represent measurement data sequences from different batches, times, or locations. The consistency and correlation between historical data are assessed by calculating the correlation scores between each sequence in the statistical matrix. The calculated relevance scores are compared with a preset score threshold, and sequences with relevance scores greater than the threshold are selected as valid samples; thus eliminating statistical outliers and ensuring the reliability of the data basis used for verification. After selecting valid samples, optimization steps can be performed to further improve data quality. The optimization steps include: statistically analyzing the frequency of each historical deviation value in the effective samples to identify the values ​​with higher frequencies as candidate samples; performing inter-group correlation analysis on the candidate samples to calculate their inter-group correlation values, and discarding those candidate samples whose inter-group correlation values ​​are lower than a preset correlation threshold, thereby obtaining an optimized effective sample set. The correction value is calculated based on the effective sample or the optimized effective sample, including: for each effective sample, which is usually a data sequence, the arithmetic mean of all the historical deviation values ​​contained therein is calculated to obtain the average deviation; after obtaining multiple average deviations, one of them is designated as the benchmark deviation, specifically the arithmetic mean of the first, last or all average deviations can be designated as the benchmark deviation; and the remaining average deviations are compared one by one with the benchmark deviation, and the comparison results such as difference or ratio are used to generate a verification dataset consisting of multiple correction coefficients. Based on the distribution characteristics of the verification dataset, such as the maximum value, minimum value, and central tendency, a reasonable parameter verification range is determined. Within this parameter verification range, the optimal verification parameter is selected according to the preset rules. The preset rules can take the median, arithmetic mean, or weighted average as the optimal verification parameter. Based on the selected calibration parameters, the final correction value is calculated. After obtaining the correction value, the final calculation is performed: based on the received original measurement value and the correction value just calculated, the corrected cohesion output value is calculated through preset arithmetic relationships such as addition, subtraction or more complex functional relationships, and this value is output or stored as the final high-precision soil cohesion result.

[0031] By combining single physical measurements with long-term historical data statistical analysis, systematic biases and random errors that may exist in the measurement process can be corrected, thereby improving the accuracy, reliability, and repeatability of soil cohesion results.

[0032] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for determining soil cohesion, characterized in that, Includes the following steps: Based on the set sampling interval, determine the sampling area that includes the reference point and the sampling point; Soil samples were collected at the reference point and the sampling point to prepare the sampling assembly; The sampling assembly was used to obtain raw measurements of soil cohesion. When the original measured value of soil cohesion is obtained, the following steps are performed: Based on multiple pre-stored historical deviation values, determine the correction value used to correct the original measured value; Based on the original measured value and the correction value, the corrected adhesive force output value is calculated; The process of determining the correction value for correcting the original measurement value based on multiple pre-stored historical deviation values ​​includes: constructing a statistical matrix based on multiple historical deviation values; selecting valid samples with correlation scores greater than a preset score threshold by calculating the correlation scores between each sequence in the statistical matrix; and calculating the correction value based on the valid samples.

2. The method for determining soil cohesion according to claim 1, characterized in that, The measurement and sampling assembly, used to obtain raw measurements of soil cohesion, includes: A tensile force is applied to the sampling component until it undergoes adhesive breakage; the instantaneous tensile force value at the point of adhesive breakage is determined as the original measured value.

3. The method for determining soil cohesion according to claim 1, characterized in that, After selecting valid samples with relevance scores greater than a preset score threshold, the process further includes: The frequency of each historical deviation value in the effective samples is counted to determine the candidate samples; by performing inter-group correlation analysis on the candidate samples, candidate samples with correlation values ​​lower than the preset correlation threshold are discarded to optimize the effective samples.

4. The method for determining soil cohesion according to claim 1, characterized in that, The correction value calculated based on valid samples includes: For each valid sample, the average of its historical deviation values ​​is calculated to obtain the average deviation; one of the multiple average deviations is designated as the benchmark deviation, and the remaining average deviations are compared with the benchmark deviation to generate a verification dataset consisting of multiple correction coefficients; the parameter verification range is determined based on the verification dataset; verification parameters are selected within the parameter verification range; and the correction values ​​are calculated based on the verification parameters.

5. A system for measuring soil cohesion, characterized in that, Includes the following modules: The raw measurement module is used to obtain the raw measurement values ​​of soil cohesion. The adhesion strength verification module is used to perform the following actions in response to the original measurement values ​​obtained by the original measurement module: determine the correction value based on multiple pre-stored historical deviation values, and calculate the corrected adhesion strength output value based on the original measurement value and the correction value.

6. The soil cohesion determination system according to claim 5, characterized in that, The acquisition of the original measured values ​​of soil cohesion includes: Based on the established sampling interval, determine the sampling area that includes the reference point and the sampling point; collect soil samples at the reference point and the sampling point to prepare a sampling assembly; measure the sampling assembly to obtain the raw measurement values.

7. The soil cohesion determination system according to claim 6, characterized in that, The measurement sampling component, for obtaining raw measurement values, includes: A tensile force is applied to the sampling component until it undergoes adhesive breakage; the instantaneous tensile force value at the point of adhesive breakage is determined as the original measured value.

8. The soil cohesion determination system according to claim 5, characterized in that, The step of determining the correction value based on multiple pre-stored historical deviation values ​​includes: A statistical matrix is ​​constructed based on multiple historical deviation values; by calculating the correlation scores between each sequence in the statistical matrix, valid samples with correlation scores greater than a preset score threshold are selected; and correction values ​​are calculated based on the valid samples.

9. The soil cohesion determination system according to claim 8, characterized in that, After selecting valid samples with relevance scores greater than a preset score threshold, the process further includes: The frequency of each historical deviation value in the effective samples is counted to determine the candidate samples; by performing inter-group correlation analysis on the candidate samples, candidate samples with correlation values ​​lower than the preset correlation threshold are discarded to optimize the effective samples.

10. A soil cohesion determination system according to claim 8, characterized in that, The correction value calculated based on valid samples includes: For each valid sample, the average of its historical deviation values ​​is calculated to obtain the average deviation; one of the multiple average deviations is designated as the benchmark deviation, and the remaining average deviations are compared with the benchmark deviation to generate a verification dataset consisting of multiple correction coefficients; the parameter verification range is determined based on the verification dataset; verification parameters are selected within the parameter verification range; and the correction values ​​are calculated based on the verification parameters.

Images