Multi-source data fusion analysis system for engineering construction foundation bearing capacity

Abstract

The invention relates to the technical field of data processing, in particular to a multi-source data fusion analysis system for engineering construction foundation bearing capacity, which comprises a memory, a processor and a computer program stored in the memory and running on the processor. Obtaining at least two target historical positions similar to the soil state of the target foundation, and constructing a first influence relation curve between the environment temperature and the settlement amount and a second influence relation curve between the environment humidity and the settlement amount in each stage of load test, the temperature influence degree and the humidity influence degree of any test position of the target foundation are obtained, the bearing capacity test value of any test position is corrected, the average value of the bearing capacity correction values of all the test positions of the target foundation serves as the final foundation bearing capacity of the target foundation, and the accuracy of the bearing capacity test result is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a multi-source data fusion analysis system for the bearing capacity of an engineering construction foundation. Background Art

[0002] The bearing capacity of a construction foundation refers to the maximum pressure per unit area that the foundation soil can withstand while meeting certain settlement control conditions. It reflects the foundation's ability to safely support the loads imposed by the superstructure. Assessing the foundation's bearing capacity before construction is crucial to the safety, stability, and service life of the entire project structure. Therefore, the accuracy of the foundation bearing capacity assessment is crucial throughout the entire project implementation process.

[0003] Load testing is a common test method for assessing foundation bearing capacity. The main principle is to apply graded loads to a rigid load plate, record the corresponding settlement, plot a settlement-load curve, and infer the foundation bearing capacity and compression characteristics based on the curve characteristics. However, because soil properties are sensitive to ambient temperature and humidity, the bearing capacity results obtained from load tests are significantly affected by the ambient temperature and humidity during the test, resulting in a possible discrepancy between the foundation bearing capacity at the time of the test and the actual soil bearing capacity.

[0004] Therefore, how to reduce the impact of ambient temperature and humidity during the test and improve the test accuracy of foundation bearing capacity has become an urgent problem to be solved. Summary of the Invention

[0005] In view of this, an embodiment of the present invention provides a multi-source data fusion analysis system for engineering construction foundation bearing capacity to solve the problem of how to reduce the influence of ambient temperature and humidity during testing and improve the testing accuracy of foundation bearing capacity.

[0006] An embodiment of the present invention provides a multi-source data fusion analysis system for the bearing capacity of an engineering construction foundation, comprising a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the following steps are implemented: Obtain foundation bearing capacity test data for a preset number of historical test locations, wherein the foundation bearing capacity test data includes bearing capacity test values, settlement under each load test level, ambient temperature and ambient humidity, particle size distribution curve, and soil plasticity index; Obtain foundation bearing capacity test data for at least one test location of the target foundation, and based on the differences in foundation bearing capacity test data between each test location and each historical test location, obtain at least two target historical locations with soil conditions similar to those of the target foundation from all historical test locations; construct a first influence relationship curve between ambient temperature and settlement and a second influence relationship curve between ambient humidity and settlement under each level of load test based on the foundation bearing capacity test data of all target historical locations; For any test location of the target foundation, based on the foundation bearing capacity test data of the any test location and in combination with the first influence relationship curve and the second influence relationship curve, the temperature influence degree and the humidity influence degree of the any test location are obtained; and using the temperature influence degree and the humidity influence degree of the any test location, the bearing capacity test value of the any test location is corrected to obtain a bearing capacity correction value; The average of the bearing capacity correction values ​​of all test positions of the target foundation is taken as the final foundation bearing capacity of the target foundation.

[0007] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: The present invention obtains the predicted value of the bearing capacity of the foundation through the load test, analyzes the influence surfaces of ambient temperature and ambient humidity on the bearing capacity of different types of soil through historical load tests, constructs a first influence relationship curve between ambient temperature and settlement and a second influence relationship curve between ambient humidity and settlement under each level of load test, and then obtains the temperature influence degree and humidity influence degree of the daily temperature and humidity influence at any test position for characterizing the target foundation according to the first influence relationship curve and the second influence relationship curve, and then corrects the test results to reduce the influence of changes in ambient temperature and humidity on the bearing capacity results during the test, thereby improving the accuracy of the foundation bearing capacity analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0009] Figure 1 This is a method flow chart of a multi-source data fusion analysis method for engineering construction foundation bearing capacity provided by the first embodiment of the present invention; Figure 2 Schematic diagram of a particle size distribution curve provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0010] The embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and intended to be used to explain the present disclosure, but should not be understood as limiting the present disclosure.

[0011] It should be noted that the terms "first," "second," and the like in the specification of the present disclosure and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure.

[0012] In order to illustrate the technical solution of the present invention, specific embodiments are provided below.

[0013] The specific scenario targeted by the present invention is: when conducting a load test to test the bearing capacity of the foundation of an engineering construction project, since the properties of the soil are greatly affected by the temperature and humidity of the environment, the foundation bearing capacity obtained from the test may have large errors and cannot accurately reflect the actual bearing capacity of the foundation during long-term use.

[0014] The embodiment of the present invention provides a multi-source data fusion analysis system for the bearing capacity of an engineering construction foundation, comprising a processor and a memory, wherein the processor executes a computer program stored in the memory to implement a multi-source data fusion analysis method for the bearing capacity of an engineering construction foundation, such as Figure 1 As shown, a multi-source data fusion analysis method for the bearing capacity of engineering construction foundations includes the following steps: Step S101: Acquire foundation bearing capacity test data of a preset number of historical test locations.

[0015] In the prior art, load test is used to obtain the bearing capacity test value. The main process is: (1) Install the settlement measuring device on the flat ground at representative locations such as under the column and under the wall. The selection of representative locations is usually determined by the size of the building. This embodiment stipulates that three locations are selected for load testing, and the distance between the test locations is about 30m. (2) Load loading is carried out in stages, and the load loaded at each stage is the estimated ultimate bearing capacity. (The commonly used load level is 10kPa), each load test is maintained for 40 minutes, and the settlement is recorded every 5 minutes. (3) If the settlement rate of a certain level is greater than 0.1mm / 10min, the loading is stopped. When the settlement rate no longer decreases or the load-settlement curve undergoes a significant mutation, it is considered that the ultimate state of the foundation load has been reached. (4) After reaching the ultimate load, the unloading is carried out in stages, where the unloading process has the same number of stages as the loading process. (5) Based on the load data and settlement data recorded during the test, a load-settlement curve is drawn, where the settlement mutation point in the load-settlement curve is the ultimate load. Calculate the absolute value of the tangent slope difference of the data points before and after each data point in the load-settlement curve on the load-settlement curve. The point with the largest absolute value of the tangent slope difference is the settlement mutation point, and the corresponding load is recorded as the final loading load. (6) The calculation formula for the bearing capacity test value is:

[0016] in, Indicates the bearing capacity test value, represents the final loading pressure, Indicates the area of ​​the pressure plate (the pressure plate can be a 250mm, 300mm, or 600mm diameter steel plate, and the specific size is selected according to test requirements).

[0017] Since the present invention needs to analyze the influence of the temperature and humidity of the environment on the bearing capacity of the soil, the temperature data and humidity data are measured once at the test location using a digital thermometer and hygrometer after the settlement is stabilized before the load test and after each level of load test, that is, after the first record before the start of the load test, the data are recorded every 40 minutes. Then, for any level of load test, the average value of the temperature data and the average value of the humidity data recorded before and at the end of the load test of this level are recorded as the environmental temperature T and environmental humidity W of the load test of this level, respectively, and the increase in the settlement at the end of the load test of this level relative to the beginning is calculated and recorded as the settlement under the load test of this level. .

[0018] Because different types of soil have different properties, before the test analysis, it is necessary to use the sedimentation method to obtain the soil particle size composition at the test location and draw the following Figure 2 The particle size distribution curve shown in the figure and the soil plasticity index obtained using the Attenborough limit test are used to reflect the foundation soil type at the test location based on the particle size distribution curve and soil plasticity index. The drawing of the particle size distribution curve and the acquisition of the soil plasticity index are prior art and will not be further described here.

[0019] Due to the different ranges of different types of data, direct analysis has a significant impact on the accuracy of the results. Therefore, the obtained test data will be normalized. Specifically, the ambient temperature, ambient humidity, and settlement will be normalized. The ambient temperature, ambient humidity, and settlement used below are also normalized data. Therefore, the bearing capacity test values ​​are needed to ultimately obtain accurate bearing capacity results, so no normalization is performed. The bearing capacity test values ​​obtained by the load test at each test location, the settlement under each level of load test, the ambient temperature and ambient humidity, the particle size distribution curve, and the soil plasticity index will constitute the foundation bearing capacity test data for the corresponding test location.

[0020] Due to the large differences in local environments between regions, their reference value is low. Therefore, for the foundation to be analyzed, the foundation bearing capacity test data of 100 historical test locations in the province to which the foundation to be analyzed belongs are obtained as reference data to analyze the impact of environmental temperature and humidity on the soil bearing capacity results.

[0021] Step S102: Obtain foundation bearing capacity test data of at least one test position of the target foundation, and according to the difference in foundation bearing capacity test data between each test position and each historical test position, obtain at least two target historical positions with soil conditions similar to those of the target foundation from all historical test positions; and according to the foundation bearing capacity test data of all target historical positions, respectively construct a first influence relationship curve between ambient temperature and settlement and a second influence relationship curve between ambient humidity and settlement under each level of load test.

[0022] In this embodiment of the present invention, the foundation to be analyzed is used as the target foundation. Considering the significant differences in bearing capacity between different types of soil, it is necessary to first obtain historical data with a soil type similar to the target foundation (i.e., foundation bearing capacity test data from historical test locations) to effectively reflect the relationship between the target foundation's bearing capacity and ambient temperature and humidity. First, according to the method in step S101, foundation bearing capacity test data is obtained for at least one test location of the target foundation. Then, based on the differences in foundation bearing capacity test data between each test location and each historical test location, at least two target historical locations with soil conditions similar to the target foundation are obtained from all historical test locations to determine valid reference data.

[0023] The particle size composition reflects the proportion of particles of different sizes in the soil. According to different particle sizes, it can be divided into types such as sand, silt, and clay. The different proportions of different particle sizes in the soil will make the properties of the soil different. Therefore, soils with similar particle size compositions have more similar bearing capacity performance. The soil plasticity index is mainly used for the classification of fine-grained soils. It reflects the plastic deformation ability of the soil under different water contents and affects the strength and stability of the soil. If the soil plasticity index is too low, it means that the soil is easy to flow when it comes into contact with water and has poor bearing capacity; if the soil plasticity index is too high, it means that the soil deforms to a greater extent under different water contents, resulting in large fluctuations in bearing capacity and poor structural stability. Therefore, the soil plasticity index is also one of the key factors affecting bearing capacity. Therefore, in an embodiment of the present invention, based on the similarity of the particle size distribution curve and the soil plasticity index in the foundation bearing capacity test data between each test location and each historical test location, a target historical location with a soil type similar to that of the target foundation is obtained.

[0024] Taking any historical test position as an example, the similarity between the particle size distribution curve of any historical test position and the particle size distribution curve of the target foundation is first analyzed. Since multiple test positions are set for load testing on the target foundation, the similarity between the particle size distribution curve of any historical test position and the particle size distribution curve of each test position of the target foundation is calculated respectively. Then, any test position of the target foundation is taken as the position to be analyzed. According to the difference in the particle size distribution curve between the position to be analyzed and the any historical test position, the similarity of the soil particle size distribution between the position to be analyzed and the any historical test position is obtained.

[0025] Specifically, a first number of data points are uniformly selected from the particle size distribution curve of the position to be analyzed, and according to the abscissa value of each data point, data points corresponding to the same abscissa value are selected on the particle size distribution curve of any historical test position and recorded as target points; the absolute value of the difference in the ordinate value between each data point with the same abscissa value and the target point is calculated respectively to obtain the cumulative value of the absolute value of the difference, and the reciprocal of the sum of the cumulative value and the constant 1 is used as the soil particle size distribution similarity between the position to be analyzed and any historical test position.

[0026] In one embodiment, the first number is set to 20. The higher the similarity assessment accuracy, the larger the first number should be. This is not limited here and can be set according to the implementation scenario. The calculation formula for the soil particle size distribution similarity between the location to be analyzed and any of the historical test locations is:

[0027] in, represents the similarity of soil particle size distribution between the Ath test position of the target foundation and the uth historical test position, Represents the ordinate value of the i-th data point on the particle size distribution curve of the A-th test position of the target foundation, represents the ordinate value of the i-th target point on the particle size distribution curve of the u-th test position, || represents the absolute value symbol, 1 represents a constant, It represents the number of data points selected on the particle size distribution curve of the Ath test position of the target foundation, that is, the number of target points selected on the particle size distribution curve of the uth test position.

[0028] It should be noted that The smaller the value of , the more consistent the amplitude of the particle size distribution curve at point i between the Ath test position and the uth historical test position, corresponding to The smaller the value of , the more similar the particle size distribution curves between the Ath test location and the uth historical test location are, and the greater the similarity of the corresponding soil particle size distribution; To ensure that the fraction is meaningful, and .

[0029] Furthermore, based on the similarity of the particle size distribution curves, combined with the difference in soil plasticity index between the position to be analyzed and any of the historical test positions, the similarity of the foundation soil between the position to be analyzed and any of the historical test positions is analyzed. Specifically, the absolute value of the difference in soil plasticity index between the position to be analyzed and any of the historical test positions is obtained, and based on the absolute value and the similarity of the soil particle size distribution, the foundation soil similarity index between the position to be analyzed and any of the historical test positions is obtained.

[0030] The calculation formula for the foundation soil similarity index between the location to be analyzed and any historical test location is:

[0031] in, represents the foundation soil similarity index between the Ath test position of the target foundation and the uth historical test position, represents the normalization function, represents the similarity of soil particle size distribution between the Ath test position of the target foundation and the uth historical test position, represents the soil plasticity index of the Ath test position of the target foundation, represents the soil plasticity index at the u-th historical test location, || represents the absolute value sign, and 1 represents a constant.

[0032] It should be noted that The smaller the value, the closer the soil plasticity index between the Ath test location and the uth historical test location is, the more similar the corresponding foundation soil is, and the larger the foundation soil similarity index between the corresponding location to be analyzed and any historical test location is; Used to ensure that fractions make sense.

[0033] According to the above-mentioned method for obtaining the foundation soil similarity index between the Ath test location and the uth historical test location of the target foundation, the foundation soil similarity index between each test location of the target foundation and any of the historical test locations is respectively obtained to obtain the average foundation soil similarity index. The larger the average foundation soil similarity index, the more similar the soil properties of any historical test location are to the target foundation, and the more effective reference data can be used. Therefore, if the average foundation soil similarity index is greater than or equal to the preset foundation soil similarity index threshold, it is considered that the soil conditions at any historical test location are highly similar to the soil of the target foundation, that is, they can reflect the influence of temperature and humidity on the bearing capacity test results of the target foundation, and then any of the historical test locations is used as the target historical location. Similarly, each historical test location is traversed to obtain at least two target historical locations in the historical test locations.

[0034] After screening and obtaining multiple target historical locations with soil properties similar to those of the target foundation, the relationship between the environmental temperature and humidity and the bearing capacity test results can be analyzed based on the foundation bearing capacity test data of each target historical location. Ambient temperature mainly affects the bearing capacity of the soil indirectly by affecting the structure and freezing state of the soil. For example, under high temperatures, the soil shrinks and cracks, and the structure is destroyed, resulting in a decrease in bearing capacity; while sustained low temperatures can cause the soil to freeze, temporarily strengthening the structure; ambient humidity mainly affects the water content of the soil, which in turn affects the bearing capacity of the soil. For example, in a high humidity environment, soil evaporation is weakened and the water absorption capacity is enhanced, resulting in an increase in soil water content and a decrease in strength, thereby resulting in a decrease in bearing capacity. In a low humidity environment, the bearing capacity will initially increase, but in the long term, the soil will dry out and crack, and the structure will be damaged. Therefore, according to the embodiment of the present invention, based on the ambient humidity, ambient temperature, and settlement of each target historical location under each load test level, a first influence relationship curve between ambient temperature and settlement and a second influence relationship curve between ambient humidity and settlement are constructed for each load test level.

[0035] Taking the first influence relationship curve between ambient temperature and settlement as an example, its specific construction method is as follows: Because the load test lasts for a long time, the temperature data during the load test will also change to a certain extent. In some places, the temperature difference may vary greatly. In order to avoid the influence of the combined effect of different load changes and temperature changes on the analysis of the relationship between temperature and bearing capacity, the load test is divided according to the level. Since the classification of each level of load test is the same, the analysis is carried out by taking any level of load test as an example. Then, for any level of load test, the ambient temperature and settlement of all target historical positions under any level of load test are obtained; because settlement may also be affected by humidity, there may be multiple settlements corresponding to the same ambient temperature. In order to obtain a more accurate influence relationship between temperature and settlement, it is necessary to analyze the ambient humidity of the target historical position under any level of load test as much as possible. For target historical positions with higher ambient humidity similarity than other target historical positions, the corresponding ambient temperature and settlement should account for a larger proportion when constructing the first influence relationship curve between ambient temperature and settlement. Therefore, the ambient humidity of each target historical position under any level of load test is formed into an ambient humidity set, and the humidity similarity between each ambient humidity in the ambient humidity set and the remaining ambient humidity is calculated.

[0036] For any ambient humidity in the ambient humidity set, the absolute value of the difference between the any ambient humidity and each ambient humidity in the ambient humidity set is calculated respectively, recorded as the humidity difference, the accumulated value of all humidity differences is normalized to obtain a normalized value, and the difference between the constant 1 and the normalized value is recorded as the humidity similarity between the any ambient humidity and the other remaining ambient humidities.

[0037] The calculation formula for the humidity similarity between any ambient humidity and the remaining ambient humidity is:

[0038] in, It represents the humidity similarity between the vth ambient humidity in the ambient humidity set and the rest of the ambient humidity. 1 represents a constant. represents the normalization function, N represents the number of ambient humidity in the ambient humidity set, represents the vth ambient humidity in the ambient humidity set, represents the i-th ambient humidity in the ambient humidity set, and || represents the absolute value sign.

[0039] It should be noted that The smaller the value of , the smaller the humidity difference between the vth ambient humidity in the ambient humidity set and the other remaining ambient humidity is, and the higher the humidity similarity corresponding to the vth ambient humidity is.

[0040] Similarly, the humidity similarity of each ambient humidity in the ambient humidity set is obtained, and used as the weight of the ambient humidity corresponding to each target historical position under any level load test. Then, according to the humidity similarity of each ambient humidity in the ambient humidity set, all settlements corresponding to the ambient temperature of all target historical positions under any level load test are weighted and summed to obtain the settlement value of each ambient temperature.

[0041] Specifically: the ambient temperature of each target historical position under any level of load test is formed into an ambient temperature set; for any ambient temperature in the ambient temperature set, at least one target historical position corresponding to the any ambient temperature is obtained and recorded as the target position; among the humidity similarities of each ambient humidity in the ambient humidity set, the humidity similarity corresponding to each target position is obtained to form a humidity similarity set; the proportion of each humidity similarity in the humidity similarity set in the humidity similarity set is calculated and recorded as the temperature influence weight of the corresponding target position; The settlement amount of each target position under the said any one level load test is obtained, and based on the temperature influence weight of each target position, the settlement amounts of all target positions under the said any one level load test are weighted summed to obtain the settlement value of the said any ambient temperature.

[0042] The calculation formula for the settlement value at any ambient temperature is:

[0043] in, Indicates ambient temperature The settlement value, Indicates ambient temperature The number of corresponding target locations, Indicates ambient temperature The humidity similarity of the ambient humidity at the corresponding j-th target location, Indicates ambient temperature The sum of the humidity similarities of the ambient humidity at each target location, Indicates ambient temperature The corresponding settlement amount of the j-th target position.

[0044] Similarly, the settlement value for each ambient temperature under any level of load test can be obtained. Then, with ambient temperature as the horizontal axis and settlement value as the vertical axis, a first influence relationship curve between ambient temperature and settlement under any level of load test can be constructed using the least squares method. The least squares method is a prior art and will not be further described here.

[0045] According to the above-mentioned method for obtaining humidity similarity, based on the ambient temperature of each target historical position under the any level load test, the temperature similarity of each ambient temperature under the any level load test is obtained, and then according to the method for obtaining the settlement value of any ambient temperature, the settlement value corresponding to each ambient humidity under the any level load test is obtained. Finally, with the ambient humidity as the horizontal axis and the settlement value as the vertical axis, the least squares method is used to construct the second influence relationship curve between the ambient humidity and the settlement under the any level load test.

[0046] At this point, the first influence relationship curve between ambient temperature and settlement under any level of load test and the second influence relationship curve between ambient humidity and settlement can be obtained. Similarly, the first influence relationship curve between ambient temperature and settlement under each level of load test and the second influence relationship curve between ambient humidity and settlement can be obtained respectively.

[0047] Step S103, for any test position of the target foundation, based on the foundation bearing capacity test data of any test position, and in combination with the first influence relationship curve and the second influence relationship curve, obtain the temperature influence degree and humidity influence degree of any test position; use the temperature influence degree and humidity influence degree of any test position to correct the bearing capacity test value of any test position to obtain a bearing capacity correction value.

[0048] Since the slope of the first influence relationship curve between ambient temperature and settlement under each level of load test can characterize the degree of influence of temperature on settlement, and the slope of the second influence relationship curve between ambient humidity and settlement under each level of load test can characterize the degree of influence of humidity on settlement, that is, the degree of influence on soil bearing capacity, therefore, according to the corresponding degree of influence in the first influence relationship curve and the second influence relationship curve of each test position of the target foundation under each level of load test, the temperature influence degree and humidity influence degree of each test position of the target foundation are obtained respectively.

[0049] Taking the degree of temperature influence as an example, the data points corresponding to the ambient temperature and settlement under each level of load test at any test position in the first influence relationship curve are obtained respectively, recorded as the first points to be analyzed, and the tangent slope value of each first point to be analyzed in the first influence relationship curve is obtained, and the average of all tangent slope values ​​is calculated as the degree of temperature influence at any test position.

[0050] The calculation formula for the temperature influence degree of any test position is:

[0051] in, It indicates the temperature influence degree of the Ath test position of the target foundation, m indicates the level of the load test, It represents the tangent slope value of the first point to be analyzed in the first influence relationship curve of the Ath test position under the rth level load test.

[0052] Similarly, obtain the data points corresponding to the ambient humidity and settlement under each level of load test at any test position in the second influence relationship curve, record them as the second points to be analyzed, obtain the tangent slope value of each second point to be analyzed in the second influence relationship curve, and calculate the average of all tangent slope values ​​as the humidity influence degree of any test position .

[0053] Furthermore, the bearing capacity test value of any test position is corrected using the temperature influence degree and humidity influence degree of any test position to obtain a bearing capacity correction value, including: The sum of the constant 1, the temperature influence degree and the humidity influence degree of any test position is used as a correction coefficient, and the bearing capacity correction value is obtained according to the product of the bearing capacity test value of any test position and the correction coefficient.

[0054] The calculation formula for the bearing capacity correction value is:

[0055] in, Indicates the bearing capacity correction value of the target foundation at the Ath test position, that is, the corrected bearing capacity test value. Indicates the bearing capacity test value of the target foundation at the Ath test position, 1 represents a constant, Indicates the degree of temperature influence at the Ath test position of the target foundation, Indicates the degree of humidity influence at the Ath test position of the target foundation.

[0056] Similarly, the degree of temperature influence and the degree of humidity influence of each test position of the target foundation can be obtained, and then the temperature influence and the degree of humidity influence of each test position can be used to adaptively correct the bearing capacity test value of each test position, thereby obtaining the bearing capacity correction value of each test position of the target foundation.

[0057] Step S104: taking the average of the bearing capacity correction values ​​of all test positions of the target foundation as the final foundation bearing capacity of the target foundation.

[0058] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A multi-source data fusion analysis system for the bearing capacity of engineering construction foundations, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: Obtain foundation bearing capacity test data for a preset number of historical test locations, wherein the foundation bearing capacity test data includes bearing capacity test values, settlement under each load test level, ambient temperature and ambient humidity, particle size distribution curve, and soil plasticity index; Obtain foundation bearing capacity test data for at least one test location of the target foundation, and based on the differences in foundation bearing capacity test data between each test location and each historical test location, obtain at least two target historical locations with soil conditions similar to those of the target foundation from all historical test locations; construct a first influence relationship curve between ambient temperature and settlement and a second influence relationship curve between ambient humidity and settlement under each level of load test based on the foundation bearing capacity test data of all target historical locations; For any test location of the target foundation, based on the foundation bearing capacity test data of the any test location and in combination with the first influence relationship curve and the second influence relationship curve, the temperature influence degree and the humidity influence degree of the any test location are obtained; and using the temperature influence degree and the humidity influence degree of the any test location, the bearing capacity test value of the any test location is corrected to obtain a bearing capacity correction value; The average of the bearing capacity correction values ​​of all test positions of the target foundation is taken as the final foundation bearing capacity of the target foundation.

2. The multi-source data fusion analysis system for engineering construction foundation bearing capacity according to claim 1 is characterized in that: The step of obtaining at least two target historical locations having soil conditions similar to those of the target foundation from all historical test locations based on the difference in foundation bearing capacity test data between each test location and each historical test location includes: For any historical test location, any test location of the target foundation is taken as the location to be analyzed, and based on the difference in particle size distribution curves between the location to be analyzed and the any historical test location, the soil particle size distribution similarity between the location to be analyzed and the any historical test location is obtained; Obtaining an absolute value of a difference in soil plasticity index between the position to be analyzed and any of the historical test positions, and obtaining a foundation soil similarity index between the position to be analyzed and any of the historical test positions based on the absolute value and the similarity of the soil particle size distribution; Obtain the foundation soil similarity index between each test position of the target foundation and any of the historical test positions, and obtain the average value of the foundation soil similarity index. If the average value of the foundation soil similarity index is greater than or equal to a preset foundation soil similarity index threshold, then use any of the historical test positions as the target historical position.

3. The multi-source data fusion analysis system for engineering construction foundation bearing capacity according to claim 2 is characterized in that: The obtaining the soil particle size distribution similarity between the position to be analyzed and any of the historical test positions based on the difference in particle size distribution curves between the position to be analyzed and any of the historical test positions includes: uniformly selecting a first number of data points on the particle size distribution curve of the position to be analyzed, and selecting, based on the abscissa value of each data point, data points corresponding to the same abscissa value on the particle size distribution curve of any historical test position, and recording them as target points; The absolute value of the difference in the ordinate value between each data point and the target point under the same abscissa value is calculated respectively to obtain the cumulative value of the absolute value of the difference, and the reciprocal of the sum of the cumulative value and the constant 1 is used as the similarity of the soil particle size distribution between the position to be analyzed and any of the historical test positions.

4. The multi-source data fusion analysis system for engineering construction foundation bearing capacity according to claim 2 is characterized in that: The obtaining of a foundation soil similarity index between the position to be analyzed and any of the historical test positions based on the absolute value and the soil particle size distribution similarity includes: The reciprocal of the sum of the absolute value and the constant 1 is calculated and recorded as the soil plasticity similarity between the position to be analyzed and any of the historical test positions; the sum of the soil particle size distribution similarity and the soil plasticity similarity is normalized to obtain a foundation soil similarity index between the position to be analyzed and any of the historical test positions.

5. The multi-source data fusion analysis system for engineering construction foundation bearing capacity according to claim 1 is characterized in that: The first influence relationship curve between ambient temperature and settlement and the second influence relationship curve between ambient humidity and settlement under each level of load test are constructed based on the foundation bearing capacity test data of all target historical locations, including: For any level of load test, the ambient humidity of each target historical position under the any level of load test is formed into an ambient humidity set, and the humidity similarity between each ambient humidity in the ambient humidity set and the other remaining ambient humidity is calculated; based on the humidity similarity of each ambient humidity in the ambient humidity set, all settlements corresponding to the ambient temperature of all target historical positions under the any level of load test are weighted summed to obtain the settlement value for each ambient temperature; with the ambient temperature as the horizontal axis and the settlement value as the vertical axis, the least squares method is used to construct a first influence relationship curve between the ambient temperature and the settlement under the any level of load test; Obtain the temperature similarity of each ambient temperature under any level load test, obtain the settlement value corresponding to each ambient humidity under any level load test, take the ambient humidity as the horizontal axis and the settlement value as the vertical axis, and use the least squares method to construct a second influence relationship curve between the ambient humidity and the settlement under any level load test.

6. The multi-source data fusion analysis system for engineering construction foundation bearing capacity according to claim 5 is characterized in that: Calculating the humidity similarity between each ambient humidity in the ambient humidity set and the remaining ambient humidity includes: For any ambient humidity in the ambient humidity set, the absolute value of the difference between the any ambient humidity and each ambient humidity in the ambient humidity set is calculated respectively, recorded as the humidity difference, the accumulated value of all humidity differences is normalized to obtain a normalized value, and the difference between the constant 1 and the normalized value is recorded as the humidity similarity between the any ambient humidity and the other remaining ambient humidities.

7. The multi-source data fusion analysis system for engineering construction foundation bearing capacity according to claim 5 is characterized in that: According to the humidity similarity of each ambient humidity in the ambient humidity set, weighted summation is performed on all settlements corresponding to the ambient temperatures of all target historical positions under any level of load test to obtain the settlement value of each ambient temperature, including: The ambient temperature of each target historical position under any one level of load test is formed into an ambient temperature set. For any ambient temperature in the ambient temperature set, at least one target historical position corresponding to the any ambient temperature is obtained and recorded as the target position. From the humidity similarity of each ambient humidity in the ambient humidity set, the humidity similarity corresponding to each target position is obtained to form a humidity similarity set. The proportion of each humidity similarity in the humidity similarity set in the humidity similarity set is calculated and recorded as the temperature influence weight of the corresponding target position. The settlement amount of each target position under the said any one level load test is obtained, and based on the temperature influence weight of each target position, the settlement amounts of all target positions under the said any one level load test are weighted summed to obtain the settlement value of the said any ambient temperature.

8. The multi-source data fusion analysis system for engineering construction foundation bearing capacity according to claim 1 is characterized in that: The obtaining of the temperature influence degree and the humidity influence degree of any test location based on the foundation bearing capacity test data of any test location and in combination with the first influence relationship curve and the second influence relationship curve includes: Obtain the data points corresponding to the ambient temperature and settlement under each level of load test at any test position in the first influence relationship curve respectively, record them as the first points to be analyzed, obtain the tangent slope value of each first point to be analyzed in the first influence relationship curve, and calculate the average of all tangent slope values ​​as the temperature influence degree of any test position.

9. The multi-source data fusion analysis system for engineering construction foundation bearing capacity according to claim 8, characterized in that: The obtaining of the temperature influence degree and the humidity influence degree of any test location based on the foundation bearing capacity test data of any test location and in combination with the first influence relationship curve and the second influence relationship curve includes: Obtain the data points corresponding to the ambient humidity and settlement under each level of load test at any test position in the second influence relationship curve respectively, record them as second points to be analyzed, obtain the tangent slope value of each second point to be analyzed in the second influence relationship curve, and calculate the average of all tangent slope values ​​as the humidity influence degree of any test position.

10. The multi-source data fusion analysis system for engineering construction foundation bearing capacity according to claim 1, characterized in that: The method of correcting the bearing capacity test value of any test position by using the temperature influence degree and humidity influence degree of any test position to obtain the bearing capacity correction value includes: The sum of the constant 1, the temperature influence degree and the humidity influence degree of any test position is used as a correction coefficient, and the bearing capacity correction value is obtained according to the product of the bearing capacity test value of any test position and the correction coefficient.

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