A method, system, device and storage medium for detecting foundation pit slope collapse

Abstract

The present application relates to a method, system, device and storage medium for detecting collapse of foundation pit slopes. The method includes dividing a target area to obtain a number of detection sub-areas; obtaining geological survey data corresponding to each of the detection sub-areas, inputting the geological survey data into a preset resolution analysis model, and obtaining the data resolution corresponding to each of the detection sub-areas based on the resolution analysis model; calculating the stability coefficient according to the data resolution and the corresponding geological survey data to obtain the stability coefficient; and obtaining the collapse detection result of foundation pit slopes according to the stability coefficient. The present application has the effect of improving the accuracy of the parameter data based on which the stability coefficient of the slope is calculated, thereby improving the accuracy of the detection result.

Description

Technical Field

[0001] The present invention relates to the technical field of foundation pit slope detection, and in particular to a foundation pit slope collapse detection method and system, equipment and storage medium. Background Art

[0002] In construction projects, the stability of foundation pit slopes is one of the key factors to ensure construction safety and smooth progress of the project. However, due to the complex and changeable geological conditions and the many uncertain factors in the construction process, foundation pit slope collapse accidents occur from time to time, posing a serious threat to the life safety of construction workers and the quality of the project. Therefore, it is particularly important to detect foundation pit slope collapse. The traditional foundation pit slope collapse detection method mainly relies on manual measurement and observation. This method has many limitations. First, the manual measurement cycle is long, the data is difficult to be accurate, and real-time monitoring cannot be achieved. It is difficult to detect small changes in the slope in time. Secondly, due to the influence of human factors, the monitoring data may have errors, resulting in inaccurate judgments on the stability of the slope. In recent years, with the advancement of science and technology, some foundation pit slope collapse detection technologies based on new technologies and methods have been widely used. For example, the stability coefficient of the slope is calculated by detecting the force parameters, which requires the data based on it to have high accuracy.

[0003] However, when the performance of on-site monitoring equipment and test elements is unstable, or errors occur during on-site data collection and processing, resulting in distorted monitoring results, the accuracy requirements of actual engineering monitoring cannot be met, leading to erroneous monitoring results. These errors not only fail to guide construction, but may also mislead construction and bring greater risks to the project. Summary of the invention

[0004] In order to improve the accuracy of parameter data used to calculate the stability coefficient of a slope, thereby improving the accuracy of detection results, the present application provides a foundation pit slope collapse detection method, system, device and storage medium.

[0005] In the first aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions:

[0006] Divide the target area to obtain several detection sub-areas;

[0007] Acquire geological survey data corresponding to each of the detection sub-areas, input the geological survey data into a preset resolution analysis model, and obtain data resolution corresponding to each of the detection sub-areas based on the resolution analysis model;

[0008] Calculate the stability coefficient according to the data resolution and the corresponding geological survey data to obtain the stability coefficient;

[0009] According to the stability coefficient, the foundation pit slope collapse detection result is obtained.

[0010] By adopting the above technical solution, in the field of foundation pit slope collapse detection, commonly used detection methods include the Swedish strip method. The more prominent feature of the Swedish strip method is to divide the profile of the target area of ​​the detection into a number of equal or unequal width soil strips, perform a separate force analysis on each soil strip, and then combine the force analysis results of each soil strip to determine the stability coefficient of the target area. Therefore, based on the Swedish strip method, the target area is divided to obtain equal or unequal width soil strips, that is, a number of detection sub-areas. Although each detection sub-area is within the target area, it is still possible that each detection sub-area corresponds to a region in the target area. The position, size, and soil properties (such as density, internal friction angle, and cohesion, etc.) are all different. If we simply assume that the parameters of each detection sub-area in the target area are not much different, and use the same data to perform force analysis on each soil strip, the test results will be inaccurate. Therefore, the geological survey data corresponding to each detection sub-area is obtained. At this time, the geological survey data of each detection sub-area may still be inaccurate. Then, the geological survey data is input into a preset resolution analysis model. The resolution analysis model is used to analyze the reliability of the geological survey data of each detection sub-area. The higher the resolution, the better the accuracy. The corresponding detection sub-area has higher data clarity. The more times the detection research results of the corresponding detection sub-area are verified and verified, and the lower the resolution is, the less verification and verification the detection research results of the current corresponding detection sub-area are, and the accuracy is difficult to determine. Therefore, when using geological survey data to calculate the stability coefficient, the geological survey data with lower resolution can be adjusted based on the data resolution. The adjustment amplitude and direction can be based on other areas with similar geological conditions to the current target area or related to the current target area, or a numerical range can be set for the geological survey data with lower resolution, so that the final stability coefficient is also a numerical range, and then the final detection result is determined according to the numerical range of the final stability coefficient. For example, if the numerical range of the final stability coefficient falls within the same evaluation range, it means that even if the accuracy of the geological survey data is low, the detection result of the target area can still be considered accurate. If the numerical range of the final stability coefficient is not within the same evaluation range, the detection result can be determined according to the proportion of the numerical range of the final stability coefficient in different evaluation ranges, thereby improving the fault tolerance of the detection result and improving the accuracy of the parameter data based on which the stability coefficient of the slope is calculated.

[0011] In a preferred example, the present application may be further configured as follows: the geological survey data is input into a preset resolution analysis model, and based on the resolution analysis model, the data resolution corresponding to each detection sub-area is obtained, specifically including:

[0012] Inputting the geological survey data into a preset resolution analysis model, and judging the degree of visualization of each detection sub-area, as well as the data clarity, data integrity and data reliability of the geological survey data corresponding to each detection sub-area based on the resolution analysis model;

[0013] The data resolution corresponding to each detection sub-region is obtained by comprehensively considering the visualization degree of each detection sub-region and the data clarity, data completeness and data reliability of the geological survey data corresponding to each detection sub-region.

[0014] By adopting the above technical solution, the geological survey data is input into a preset resolution analysis model, and the resolution analysis model is used to analyze the clarity and reliability of the geological survey data from multiple dimensions. For example, in terms of the clarity of the geological survey data, it can be judged from the degree of visualization of each detection sub-area and the data clarity of the geological survey data of each detection sub-area. The degree of visualization of each detection sub-area represents the completeness of the current geological map of the detection sub-area, that is, the completeness of the geological map of all strata and surface layers in the detection sub-area. If the geological map of all strata and surface layers in the detection sub-area has more annotations and has clear evidence, then the visualization degree of the detection sub-area is high. If the geological map of all strata and surface layers in the detection sub-area has fewer annotations or is only drawn without clear evidence, then the clarity of the geological map of all strata and surface layers in the detection sub-area is judged to be In addition, if the consistency of the geological maps of all strata and surface layers in the detection sub-area from multiple sources is low, it can also be judged that the clarity of the geological maps of all strata and surface layers in the detection sub-area is not high; in addition, in terms of the reliability of geological survey data, the data integrity and data reliability of the geological survey data of each detection sub-area can be used for judgment. The data integrity of geological survey data indicates the integrity of geological survey data in all-round geological detection, investigation and research data, for example, the proportion of geological survey data types in geological survey data types with comprehensive aspects such as meteorology, hydrology, topography, strata and rocks, geological structures, rock and soil types and engineering geological properties, hydrogeological conditions, and human engineering activities; based on this, the data resolution of the detection sub-area is judged by comprehensively considering the clarity and reliability of the geological survey data, so as to facilitate the subsequent targeted adjustment of the geological survey data and improve the accuracy of the detection results.

[0015] In a preferred example, the present application may be further configured as follows: the stability coefficient is calculated according to the data resolution and the corresponding geological survey data to obtain the stability coefficient, specifically including:

[0016] Comprehensively judging whether the comprehensive data resolution of the target area meets a preset resolution threshold by comprehensively judging the data resolution of each detection sub-area; if the judgment is yes, calculating the stability coefficient based on the data resolution and the corresponding geological survey data to obtain the stability coefficient; if the judgment is no, extracting the highest data resolution;

[0017] According to the highest data resolution, adjusting other data resolutions;

[0018] The stability coefficient is calculated according to the highest data resolution, the adjusted other data resolutions and the corresponding geological survey data to obtain the stability coefficient.

[0019] By adopting the above technical solution, the data resolution of each detection sub-area in the target area may be exactly the same or different. In the case of being exactly the same, it means that the current geological detection, investigation and research on each detection sub-area in the target area are exactly the same. If the same data resolution is high, it is judged that the geological conditions of each detection sub-area are the same, then the geological survey data may not be adjusted, and the original data may be used to calculate the stability coefficient. If the same data resolution is low, it is judged that the research on the detection sub-area is less. Therefore, the geological survey data can be adjusted with exactly the same adjustment range to ensure the consistency of calculation of the target area. The probability that the data resolution of each detection sub-area in the target area is exactly the same is small. In most areas to be detected, different detection sub-areas have the same data resolution. There will be differences in the data resolution of sub-areas. Therefore, the highest data resolution is extracted because the highest data resolution represents a more in-depth and thorough detection and research on the target area. Even if other detection sub-areas and the detection sub-areas corresponding to the highest data resolution are not the same area, they are all closely spaced in the same target area, and adjacent detection sub-areas are close to each other. Therefore, it can be considered that the data resolution of each detection sub-area in the target area is high, and the reason for the low data resolution of other detection sub-areas may be data loss or data omission under the same geological conditions. In this case, the resolution of other data can be improved based on the highest data resolution, thereby achieving the purpose of improving the accuracy of the parameter data used to calculate the stability coefficient of the slope.

[0020] In a preferred example, the present application may be further configured as follows: adjusting other data resolutions according to the highest data resolution specifically includes:

[0021] Adjusting other data resolutions according to the highest data resolution to obtain a first adjusted data resolution, and calculating a stability coefficient based on the highest data resolution and corresponding geological survey data to obtain a highest stability coefficient;

[0022] According to the highest stability coefficient, judging whether the adjustment of the first adjustment data resolution is accurate, if it is judged to be yes, calculating the stability coefficient based on the first adjustment data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient, if it is judged to be no, obtaining historical geological survey data, and obtaining data sensitivity information corresponding to each type of geological survey data according to the historical geological survey data;

[0023] According to the data sensitivity information, the corresponding first adjusted data resolution is adjusted, and the stability coefficient is calculated according to the adjusted first adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient.

[0024] By adopting the above technical solution, the reason why the highest data resolution is different from other data resolutions may be that data is lost or data is omitted under the same geological conditions. In this case, the resolutions of other data can be directly improved. However, if this is not the case, directly improving the resolutions of other data may cause the corresponding geological survey data to be inaccurate. In general, the probability of data loss or data omission under the same geological conditions is small. Therefore, it is necessary to further analyze the specific conditions of the target area and then adjust the resolutions of other data according to the highest data resolution. Based on this, the stability coefficient is calculated based on the highest data resolution and the corresponding geological survey data to obtain the highest stability coefficient, and based on the highest stability coefficient, it is judged whether the adjustment of the first adjusted data resolution is accurate and reasonable. When it is judged that the first adjusted data resolution is accurate and reasonable, the first adjusted data resolution can be directly used to calculate the stability coefficient. When it is judged that the rationality of the first adjusted data resolution is insufficient, historical geological survey data is obtained to determine the data sensitivity information of each geological survey data. The data sensitivity information refers to the degree to which each geological survey data changes after the geological stability coefficient assessment changes. The higher the data sensitivity information, the lower the stability of the geological survey data, and the lower the reliability of the geological survey data. Therefore, the first adjusted data resolution representing the data reliability is further adjusted through the data sensitivity information, so that the accuracy of the first adjusted data resolution is improved, and then the accuracy of the geological survey data corresponding to the first adjusted data resolution is improved.

[0025] In a preferred example, the present application may be further configured as follows: adjusting the corresponding first adjusted data resolution according to the data sensitivity information, calculating the stability coefficient according to the adjusted first adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient, specifically including:

[0026] According to the data sensitivity information, the corresponding first adjusted data resolution is adjusted to obtain a second adjusted data resolution; the second adjusted data resolution and the highest data resolution are combined to determine whether the comprehensive data resolution of the target area meets a preset resolution threshold; if the determination is yes, a stability coefficient is calculated based on the second adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain a stability coefficient; if the determination is no, a stability coefficient is calculated based on the comprehensive data resolution of the target area and the corresponding geological survey data to obtain a sensitivity stability coefficient;

[0027] According to the sensitivity stability coefficient, a third adjustment data resolution is selected from the second adjustment data resolution, and a stability coefficient is calculated based on the third adjustment data resolution, the highest data resolution and the corresponding geological survey data to obtain a stability coefficient.

[0028] By adopting the above technical solution, the first adjusted data resolution after the data sensitivity information is adjusted is used as the second adjusted data resolution. After obtaining the second adjusted data resolution, it is judged whether the comprehensive data resolution of the target area based on the second adjusted data resolution can meet the preset resolution threshold. If it is judged to be yes, it means that the accuracy of the geological survey data corresponding to the second adjusted data resolution at this time is guaranteed after adjustment. Therefore, the stability coefficient can be calculated by the second adjusted data resolution, the highest data resolution and the corresponding geological survey data. If it is judged to be no, it means that the accuracy of the geological survey data corresponding to the second adjusted data resolution at this time after adjustment still cannot meet the requirements of actual engineering monitoring. Therefore, the stability coefficient is first calculated based on the second adjusted data resolution, the highest data resolution and the corresponding geological survey data at this time. The accuracy of the sensitivity stability coefficient obtained at this time is not high enough. Therefore, all possible data resolution situations are inferred by using the sensitivity stability coefficient, and then the second adjusted data resolution is adjusted by the one with the smallest difference from the original data resolution situation in each possible data resolution situation, thereby further adjusting the geological survey data corresponding to the second adjusted data resolution with insufficient accuracy.

[0029] In the second aspect, the above invention objective of the present application is achieved through the following technical solutions:

[0030] A foundation pit slope collapse detection system, the foundation pit slope collapse detection system comprising:

[0031] A region division module is used to divide the target region into several detection sub-regions;

[0032] A resolution analysis module, used to obtain geological survey data corresponding to each of the detection sub-areas, input the geological survey data into a preset resolution analysis model, and obtain the data resolution corresponding to each of the detection sub-areas based on the resolution analysis model;

[0033] A stability coefficient calculation module, used to calculate the stability coefficient according to the data resolution and the corresponding geological survey data to obtain the stability coefficient;

[0034] The detection result analysis module is used to obtain the foundation pit slope collapse detection result according to the stability coefficient.

[0035] Optionally, the resolution analysis module includes:

[0036] A model analysis submodule, used for inputting the geological survey data into a preset resolution analysis model, and judging the degree of visualization of each detection sub-area, as well as the data clarity, data integrity and data reliability of the geological survey data corresponding to each detection sub-area based on the resolution analysis model;

[0037] The comprehensive analysis submodule is used to comprehensively analyze the visualization degree of each detection sub-area, as well as the data clarity, data integrity and data reliability of the geological survey data corresponding to each detection sub-area, to obtain the data resolution corresponding to each detection sub-area.

[0038] Optionally, the stability coefficient calculation module includes:

[0039] The highest extraction submodule is used to comprehensively judge whether the comprehensive data resolution of the target area meets the preset resolution threshold by comprehensively judging the data resolution corresponding to each of the detection subregions. If it is judged to be yes, the stability coefficient is calculated based on the data resolution and the corresponding geological survey data to obtain the stability coefficient. If it is judged to be no, the highest data resolution is extracted; the highest adjustment submodule is used to adjust other data resolutions according to the highest data resolution;

[0040] The highest calculation submodule is used to calculate the stability coefficient according to the highest data resolution, the adjusted other data resolutions and the corresponding geological survey data to obtain the stability coefficient.

[0041] In the third aspect, the above invention objective of the present application is achieved through the following technical solutions:

[0042] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned foundation pit slope collapse detection method when executing the computer program.

[0043] In a fourth aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions:

[0044] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned foundation pit slope collapse detection method.

[0045] In summary, the present application includes at least one of the following beneficial technical effects:

[0046] 1. Obtain the geological survey data corresponding to each detection sub-area. At this time, the geological survey data of each detection sub-area may still be inaccurate. Then input the geological survey data into a preset resolution analysis model. The resolution analysis model is used to analyze the reliability of the geological survey data of each detection sub-area. The higher the resolution, the higher the data clarity of the corresponding detection sub-area, and the more times the detection and research results of the corresponding detection sub-area have been verified and verified. The lower the resolution, the lack of verification and verification of the detection and research results of the corresponding detection sub-area, and the accuracy is difficult to determine. Therefore, when using geological survey data to calculate the stability coefficient, the geological survey data with lower resolution can be adjusted based on the data resolution. The amplitude and direction of adjustment can be based on other areas with geological conditions similar to or related to the current target area, or a numerical range can be set for geological survey data with lower resolution, so that the final stability coefficient is also a numerical range, and then the final test result is determined according to the numerical range of the final stability coefficient. For example, if the numerical range of the final stability coefficient falls within the same evaluation range, it means that even if the accuracy of the geological survey data is low, the test result of the target area can still be considered accurate. If the numerical range of the final stability coefficient is not within the same evaluation range, the test result can be determined according to the proportion of the numerical range of the final stability coefficient in different evaluation ranges, thereby improving the fault tolerance of the test result. , improve the accuracy of parameter data based on which the stability coefficient of the slope is calculated; 2. Input the geological survey data into a preset resolution analysis model, which is used to analyze the clarity and reliability of the geological survey data from multiple dimensions. For example, in terms of the clarity of the geological survey data, it can be judged from the degree of visualization of each detection sub-area and the data clarity of the geological survey data of each detection sub-area. The degree of visualization of each detection sub-area indicates the completeness of the current geological map of the detection sub-area, that is, the completeness of the geological map of all strata and surface layers in the detection sub-area. If the geological maps of all strata and surface layers in the detection sub-area are more marked and have clear evidence, then the detection sub-area The visualization degree is high, and if the geological map of all strata and surfaces in the detection sub-area is less marked or only drawn without clear evidence, it is judged that the clarity of the geological map of all strata and surfaces in the detection sub-area is not high. In addition, if the consistency of the geological maps of all strata and surfaces in the detection sub-area from multiple sources is low, it can also be judged that the clarity of the geological map of all strata and surfaces in the detection sub-area is not high; in addition, in terms of the reliability of geological survey data, the data integrity and data reliability of the geological survey data of each detection sub-area can be judged. The data integrity of geological survey data indicates the integrity of geological survey data in all-round geological detection, investigation and research data;Based on this, the data resolution of the detection sub-area is determined by comprehensively considering the clarity and reliability of the geological survey data, which facilitates the subsequent targeted adjustment of the geological survey data and improves the accuracy of the detection results;

[0047] 3. The data resolution of each detection sub-area in the target area may be exactly the same or different. In the case of being exactly the same, it means that the current geological detection, investigation and research of each detection sub-area in the target area are exactly the same. If the same data resolution is high, it is judged that the geological conditions of each detection sub-area are the same, then the geological survey data can be left unchanged and the original data can be used to calculate the stability coefficient. If the same data resolution is low, it is judged that the research on the detection sub-area is less. Therefore, the geological survey data can be adjusted with exactly the same adjustment range to ensure the consistency of calculation of the target area. The probability that the data resolution of each detection sub-area in the target area is exactly the same is small. In most areas to be detected, the data resolution of different detection sub-areas is the same. There will be differences in data resolution, so the highest data resolution is extracted, because the highest data resolution represents a more in-depth and thorough detection and research on the target area, and even if the other detection sub-areas and the detection sub-areas corresponding to the highest data resolution are not the same area, they are all closely spaced in the same target area, and adjacent detection sub-areas are close to each other. Therefore, it can be considered that the data resolution of each detection sub-area in the target area is high, and the reason for the low data resolution of other detection sub-areas may be data loss or data omission under the same geological conditions. In this case, the resolution of other data can be improved based on the highest data resolution, thereby achieving the purpose of improving the accuracy of the parameter data used to calculate the stability coefficient of the slope. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flow chart of a method for detecting foundation pit slope collapse in an embodiment of the present application;

[0049] Figure 2 is a flowchart for implementing S20 of the foundation pit slope collapse detection method in the embodiment of the present application;

[0050] Figure 3 is a flowchart for implementing S30 of the foundation pit slope collapse detection method in the embodiment of the present application;

[0051] Figure 4 is a flowchart for implementing S32 of the foundation pit slope collapse detection method in the embodiment of the present application;

[0052] Figure 5 is a flowchart for implementing S323 of the foundation pit slope collapse detection method in the embodiment of the present application;

[0053] Figure 6This is a principle block diagram of a foundation pit slope collapse detection system in an embodiment of the present application;

[0054] Figure 7 It is a diagram of the internal structure of a computer device in an embodiment of the present application. DETAILED DESCRIPTION

[0055] The following is combined with Figure 1-7 This application is described in further detail.

[0056] In one embodiment, if Figure 1 As shown, the present application discloses a method for detecting foundation pit slope collapse, which specifically includes the following steps:

[0057] S10: Divide the target area to obtain a number of detection sub-areas.

[0058] In this embodiment, the Swedish strip method is used to predict and evaluate the stability of the foundation pit slope collapse / landslide that may be caused during the foundation pit excavation process. The basic principle of the Swedish strip method is to divide the sliding body into a number of strips of equal width, and calculate the stability coefficient of each strip through parameters such as the deadweight, cohesion, and internal friction angle of each strip. The stability coefficient of the sliding body is then obtained by combining the stability coefficient of each strip.

[0059] Specifically, based on the Swedish strip method, the cross section of the target area to be detected is divided into a number of strips of equal or unequal widths to obtain a number of detection sub-areas, and each strip is a detection sub-area.

[0060] It should be noted that in this embodiment, the foundation pit slope collapse stability analysis is performed under the most unfavorable working condition, i.e., the atmospheric heavy rainfall condition, and the most dangerous sliding surface is automatically searched. The automatic search method that can be selected includes taking different center positions and different radii to calculate the stability coefficient, and taking the sliding surface corresponding to the minimum stability coefficient as the most dangerous sliding surface. The target area is the most dangerous sliding surface, and the detection sub-area is the strip divided based on the most dangerous sliding surface. In this embodiment, since the accuracy of the geological survey data is uncertain, the most dangerous sliding surface is first determined by using the original data, and then the accuracy of the geological survey data is analyzed on the basis of the most dangerous sliding surface, so as to calculate on the most dangerous sliding surface according to the analysis results to obtain a more accurate minimum stability coefficient.

[0061] S20: Acquire geological survey data corresponding to each detection sub-region, input the geological survey data into a preset resolution analysis model, and obtain the data resolution corresponding to each detection sub-region based on the resolution analysis model.

[0062] Specifically, after determining the target area and the detection sub-area, the geological survey data corresponding to each detection sub-area is obtained. The geological survey data corresponding to each detection sub-area includes parameter data for calculating the stability coefficient, and information on the source and acquisition method of each parameter data, including parameters such as deadweight, cohesion and internal friction angle. Usually, the target area to be detected is not large, and thus the scope of each detection sub-area divided based on the Swedish strip method is not large. The geological conditions in each detection sub-area are roughly the same, but the amount of calculation when calculating the stability coefficient is large, and the parameter data used for calculating the stability coefficient needs to be used multiple times. Therefore, the error in the parameter data may cause a large deviation in the final calculation result. Therefore, it is necessary to further analyze the accuracy of the geological survey data of each detection sub-area, so as to improve the accuracy of the detection result.

[0063] Based on this, the geological survey data of each detection sub-area is input into a preset resolution analysis model, and the resolution analysis model is used to judge the reliability and clarity of each type of data in the geological survey data of each detection sub-area. Therefore, based on the resolution analysis model, the data resolution corresponding to each detection sub-area is obtained. The data resolution refers to the data reliability and clarity of the detection sub-area. The higher the resolution, the higher the data clarity and reliability of the corresponding detection sub-area, that is, the more times the detection research results of the detection sub-area have been verified and the more complete the data, and the lower the resolution, the lack of verification and verification of the detection research results of the corresponding detection sub-area and the low data completeness, and the accuracy is difficult to determine. For example, geological survey data include soil layer structure information of each detection sub-area, density, saturated density and bonding strength of each soil layer, and these parameters are obtained through field testing, laboratory measurement and calculation. The resolution analysis model will search and determine whether the number of historical tests of these parameters is sufficient, whether the data of each historical test is the same, whether the experimental conditions of the laboratory measurement are reasonable, and whether the amount of data and the type of data of each historical test are the same through the historical test data. The data resolution of the geological survey data of the corresponding detection sub-area is obtained by combining the above judgment results.

[0064] Furthermore, the preset resolution analysis model will also conduct a preliminary analysis of the background geological conditions of the target area, that is, a resolution analysis of the background geological conditions of the entire foundation pit in the target area, because before the excavation of the foundation pit is carried out, the geological environmental conditions of the assessment area and the type, scale and construction method of the proposed project will be evaluated in advance to predict the types of geological disasters that may be caused during the construction process and after the completion of the project. In addition, some of the geological survey data in the detection sub-area may be based on the background geological conditions. Therefore, if the background geological conditions of the entire foundation pit in the target area are not accurate, it may also cause errors in the final detection results. Therefore, a resolution analysis is performed on the background geological conditions of the entire foundation pit in the target area based on the resolution analysis model to obtain an initial pre-resolution. When the data resolution of each detection sub-area is subsequently obtained, the data resolution of each detection sub-area is adjusted using the initial pre-resolution, for example, by taking an average value.

[0065] S30: Calculate the stability coefficient according to the data resolution and the corresponding geological survey data to obtain the stability coefficient.

[0066] Specifically, after obtaining the data resolution, the geological survey data with lower resolution is adjusted based on the data resolution. The method of adjusting the geological survey data can be to directly adjust the geological survey data with lower resolution, or to set a numerical range for the geological survey data with lower resolution so that the final stability coefficient is also a numerical range. In this embodiment, the method of setting a numerical range for the geological survey data with lower resolution is selected for adjustment. The amplitude and direction of the adjustment can be pre-set based on other areas with geological conditions similar to or related to the current target area. In this way, the stability coefficient is calculated using the adjusted geological survey data, and the obtained stability coefficient is a numerical range.

[0067] S40: Obtain foundation pit slope collapse detection results based on the stability coefficient.

[0068] Specifically, after obtaining the stability coefficient, the evaluation standard can be used to analyze the stability coefficient to obtain the foundation pit slope collapse detection result. The evaluation standard is the grading standard for the stability coefficient. For example, the evaluation standard includes multiple numerical ranges, each numerical range corresponds to a foundation pit slope collapse detection result, and the foundation pit slope collapse detection result can be obtained by judging the numerical range that the stability coefficient falls into. In this embodiment, the stability coefficient is also a numerical range. Therefore, if the numerical range representing the stability coefficient completely falls into a certain numerical range of the evaluation standard, the foundation pit slope collapse detection result corresponding to the numerical range of the evaluation standard can be used as the current foundation pit slope collapse detection result. If the numerical range representing the stability coefficient falls into two numerical ranges of the evaluation standard (in this embodiment, the numerical range set for the geological survey data is usually much smaller than the numerical range of the evaluation standard), the ratio of the numerical range representing the stability coefficient falling into the two numerical ranges of the evaluation standard is judged, and the foundation pit slope collapse detection result corresponding to the numerical range with a higher ratio is selected as the current foundation pit slope collapse detection result.

[0069] Exemplarily, the implementation process in this embodiment is explained by analyzing and calculating a proposed project:

[0070] Collect and analyze information on the geological environment conditions in the assessment area and the type, scale and construction method of the proposed project. It is determined that a two-story basement is set up on the west side of the assessment area, with an area of ​​about 173,430 square meters and an excavation depth of about 9.0m. There is slope space around the foundation pit. The foundation pit adopts slope excavation with a slope ratio of 1:1. The soil layers on the side walls of the foundation pit are mainly plain fill, fine sand and silty soil. The bottom of the foundation pit is mainly located in silty soil, and partially in fine sand or medium-coarse sand layers. The engineering performance of the rock and soil layer of the foundation pit slope is poor. Therefore, if the foundation pit slope support measures are improper or not timely, it will induce the foundation pit slope collapse / landslide geological disasters;

[0071] The stability prediction and evaluation of the collapse / landslide of the foundation pit slope that may be caused during the foundation pit excavation process is carried out under the most unfavorable working conditions, that is, under the conditions of heavy atmospheric rainfall. Considering that the factors affecting the slope stability analysis include not only deadweight, cohesion and internal friction angle, but also groundwater and earthquake intensity, the stability of the foundation pit slope is calculated by taking the east side wall of the foundation pit as an example. A borehole close to the east side wall of the foundation pit is selected to represent the geotechnical structure there. The borehole elevation is 6.90m, and the soil layers exposed from top to bottom are: 2.20m thick plain fill layer; 7.90m thick silty sand layer; 3.80m thick silty soil layer; 6.30m thick medium-coarse sand layer, and the underlying bedrock is slightly weathered limestone. The soil layers of the foundation pit side walls are plain fill and silty sand, the bottom plate is located in the silty sand layer, and the groundwater depth is 1.60m;

[0072] Since there is slope space around the foundation pit, the foundation pit is excavated with a slope ratio of 1:1. Therefore, the target area is determined by automatically searching for the most dangerous sliding surface, and several detection sub-areas are determined;

[0073] For example, the geological survey data of a detection sub-area obtained for calculating the stability coefficient is shown in Table 1:

[0074]

[0075] Table 1 Selection of calculation indexes for rock and soil layers on the side wall of foundation pit

[0076] After the geological survey data is input into the preset resolution analysis model, the data resolution corresponding to each detection sub-area is obtained based on the resolution analysis model, and the geological survey data after the data resolution is adjusted is shown in Table 2:

[0077]

[0078] Table 2 Calculation index selection of the rock and soil layer on the side wall of the foundation pit after adjustment

[0079] After completing the adjustment of geological survey data, the stability coefficient is calculated based on the following formula:

[0080] The impact of earthquake intensity.

[0081] N i =(G i +G bi )cosθ i +P wi sin(α i -θ i ), formula 2;

[0082] T i =(G i +G bi )sinθ i +P wi cos(α i -θ i ), Formula 3;

[0083]

[0084] In the formula, K S —slope stability coefficient;

[0085] c i —Standard value of the cohesion of the rock and soil mass on the sliding surface of the i-th calculation strip (kPa);

[0086] —Standard value of internal friction angle of rock and soil on the sliding surface of the i-th calculated strip (°);

[0087] l i —The length of the sliding surface of the i-th calculated strip (m);

[0088] θ i , α i —The inclination angle of the bottom surface of the i-th calculation strip and the inclination angle of the groundwater level (°);

[0089] G i —The self-weight of rock and soil mass per unit width of the ith calculation block (kN / m);

[0090] G bi —The deadweight per unit width of the building on the sliding surface of the i-th calculation strip (kN / m);

[0091] P wi — dynamic water pressure per unit width of the ith calculation strip (kN / m);

[0092] N i —The reaction force of the i-th calculated strip-block sliding body on the normal line of the sliding surface (kN / m);

[0093] T i —The reaction force of the i-th calculated strip-block sliding body on the tangent line of the sliding surface (kN / m);

[0094] R i —Anti-sliding force on the sliding surface of the i-th calculated strip (kN / m).

[0095] In one embodiment, if Figure 2 As shown, in step S20, the geological survey data is input into a preset resolution analysis model, and based on the resolution analysis model, the data resolution corresponding to each detection sub-area is obtained, specifically including:

[0096] S21: Input the geological survey data into a preset resolution analysis model, and based on the resolution analysis model, determine the visualization degree of each detection sub-area, as well as the data clarity, data integrity and data reliability of the geological survey data corresponding to each detection sub-area.

[0097] Specifically, the geological survey data is input into a preset resolution analysis model, which is used to analyze the clarity and reliability of the geological survey data from multiple dimensions. In terms of the clarity of the geological survey data, it can be judged from the degree of visualization of each detection sub-area and the data clarity of the geological survey data of each detection sub-area. In terms of the reliability of the geological survey data, it can be judged from the data integrity and data reliability of the geological survey data of each detection sub-area. For example, the degree of visualization of each detection sub-area represents the integrity of the current geological map of the detection sub-area, that is, the integrity of the drawn geological map of all strata and surface layers in the detection sub-area. If the geological maps of all strata and surface layers in the detection sub-area are more marked and have clear evidence, the visualization degree of the detection sub-area is high, which means that the parameter data of the soil layer in the geological survey data is clearer. If the geological maps of all strata and surface layers in the detection sub-area are less marked or are only drawn without clear evidence, then it is judged that the clarity of the geological maps of all strata and surface layers in the detection sub-area is not high. In addition, if the consistency of the geological maps of all strata and surface layers in the detection sub-area from multiple sources is low, it can also be judged that the clarity of the geological maps of all strata and surface layers in the detection sub-area is not high.

[0098] S22: The data resolution corresponding to each detection sub-region is obtained by comprehensively considering the visualization degree of each detection sub-region and the data clarity, data completeness and data reliability of the geological survey data corresponding to each detection sub-region.

[0099] Specifically, the data resolution corresponding to each detection sub-region is determined by comprehensively considering the degree of visualization of each detection sub-region, as well as the data clarity, data completeness and data reliability of the geological survey data corresponding to each detection sub-region. For example, the degree of visualization of each detection sub-region, as well as the weights of the data clarity, data completeness and data reliability of the geological survey data corresponding to each detection sub-region can be set, and then the data resolution of each detection sub-region can be comprehensively obtained based on the analysis results.

[0100] In one embodiment, if Figure 3 As shown, in step S30, the stability coefficient is calculated according to the data resolution and the corresponding geological survey data to obtain the stability coefficient, which specifically includes:

[0101] S31: Comprehensively consider the data resolution corresponding to each detection sub-area, and determine whether the comprehensive data resolution of the target area meets the preset resolution threshold. If it is judged as yes, calculate the stability coefficient based on the data resolution and the corresponding geological survey data to obtain the stability coefficient. If it is judged as no, extract the highest data resolution.

[0102] Specifically, the data resolution of each detection sub-region in the target area may be completely the same or different. Therefore, first determine whether the data resolution of each detection sub-region is completely the same. In the case of being completely the same, it means that the current geological detection, investigation and research of each detection sub-region in the target area are completely the same. If the same data resolution is high, it is determined that the geological conditions of each detection sub-region are the same, and the geological survey data may not be adjusted, and the original data may be used to calculate the stability coefficient. If the same data resolution is low, it is determined that the research on the detection sub-region is less, and therefore, the geological survey data may be adjusted using the same adjustment range based on the data resolution.

[0103] If the data resolution of each detection sub-area is not exactly the same, after obtaining the data resolution of each detection sub-area, the data resolution corresponding to each detection sub-area is comprehensively considered to determine the comprehensive data resolution of the target area, and then whether the comprehensive data resolution of the target area meets the preset resolution threshold is determined. For example, the average value of the data resolution of each detection sub-area can be calculated to determine whether the average value of the data resolution of each detection sub-area is greater than the resolution threshold (the resolution threshold at this time is the threshold for determining the average value), or the number of detection sub-areas that meet the data resolution standard can be calculated to determine whether it is greater than the resolution threshold (the resolution threshold at this time is the threshold for determining the number of sub-areas that meet the standard). If the judgment is yes, the stability coefficient is calculated based on the data resolution and the corresponding geological survey data to obtain the stability coefficient. If the judgment is no, the highest data resolution is extracted.

[0104] S32: Adjust the resolution of other data according to the highest data resolution.

[0105] Specifically, because the highest data resolution represents a more in-depth and thorough detection and research on the target area, and even if other detection sub-areas and the detection sub-areas corresponding to the highest data resolution are not the same area, they are all closely spaced in the same target area, and adjacent detection sub-areas are close to each other. Therefore, it can be considered that the data resolution of each detection sub-area in the target area is relatively high, and the reason for the low data resolution of other detection sub-areas may be data loss or data omission under the same geological conditions. Therefore, according to the highest data resolution, the other data resolutions are adjusted. For example, the average of the highest data resolution and each other data resolution is taken to replace the original each other data resolution accordingly.

[0106] S33: Calculate the stability coefficient according to the highest data resolution, the adjusted resolutions of other data and the corresponding geological survey data to obtain the stability coefficient.

[0107] Specifically, the highest data resolution and other adjusted data resolutions are used to adjust the geological survey data accordingly, and then the stability coefficient is calculated based on the adjusted geological survey data to obtain the stability coefficient.

[0108] In one embodiment, if Figure 4 As shown, in step S32, according to the highest data resolution, other data resolutions are adjusted, specifically including:

[0109] S321: adjusting other data resolutions according to the highest data resolution to obtain a first adjusted data resolution, and calculating a stability coefficient based on the highest data resolution and corresponding geological survey data to obtain a highest stability coefficient.

[0110] Specifically, the reason why the highest data resolution is different from other data resolutions may be that data is lost or data is omitted under the same geological conditions. In this case, the resolutions of other data can be directly increased. However, if this is not the case, directly increasing the resolutions of other data may cause the corresponding geological survey data to be inaccurate. In general, the probability of data loss or data omission under the same geological conditions is small. Therefore, it is necessary to further analyze the specific conditions of the target area and then adjust the resolutions of other data according to the highest data resolution.

[0111] Based on this, other data resolutions are adjusted according to the highest data resolution to obtain a first adjusted data resolution, which is the adjusted other data resolutions, and the stability coefficient is calculated based on the highest data resolution and the corresponding geological survey data to obtain the highest stability coefficient. It should be noted that because the calculation of the stability coefficient requires geological survey data of each detection sub-area, the highest stability coefficient at this time includes the first highest stability coefficient calculated using other data resolutions and the highest data resolution before adjustment, and the corresponding geological survey data, and also includes the second highest stability coefficient calculated using other data resolutions after adjustment, that is, the first adjusted data resolution and the highest data resolution, and the corresponding geological survey data.

[0112] S322: Based on the highest stability coefficient, determine whether the adjustment of the first adjustment data resolution is accurate. If it is judged to be yes, calculate the stability coefficient based on the first adjustment data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient. If it is judged to be no, obtain historical geological survey data, and based on the historical geological survey data, obtain the data sensitivity information corresponding to each type of geological survey data.

[0113] Specifically, according to the highest stability coefficient, it is judged whether the adjustment of the resolution of the first adjustment data is accurate, that is, firstly, the ratio of the resolutions of other data that do not meet the standard to those that meet the standard before the adjustment is judged as the first ratio, and the ratio of the resolutions of the first adjustment data that do not meet the standard to those that meet the standard is judged as the second ratio, the ratio between the first ratio and the second ratio is judged as the third ratio, the ratio between the first highest stability coefficient and the first ratio is judged as the fourth ratio, the ratio between the second highest stability coefficient and the second ratio is judged as the fifth ratio, and the ratio between the fourth ratio and the fifth ratio is judged as the sixth ratio. At this time, if it is judged that the adjustment of the resolution of the first adjustment data is accurate, the third ratio and the sixth ratio should be the same. Therefore, if it is judged that the adjustment of the resolution of the first adjustment data is accurate, the third ratio and the sixth ratio should be the same. If the ratios are the same, it is judged that the first adjusted data resolution is accurate and reasonable, and the stability coefficient is calculated based on the first adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient; if it is judged that the third ratio is different from the sixth ratio, the historical geological survey data is obtained, and the historical geological survey data includes historical geological survey data and corresponding historical foundation pit slope collapse detection results. According to the historical geological survey data, each time the foundation pit slope collapse detection result of the assessment area where the target area is located changes or the stability coefficient changes (but no foundation pit slope collapse accident actually occurs), the degree of change of each type of geological survey data is judged to obtain the data sensitivity information corresponding to each type of geological survey data.

[0114] S323: According to the data sensitivity information, the corresponding first adjusted data resolution is adjusted, and the stability coefficient is calculated according to the adjusted first adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient.

[0115] Specifically, data sensitivity information refers to the degree to which each type of geological survey data changes after the geological stability coefficient assessment changes. The higher the data sensitivity information, the lower the stability of the geological survey data, and the lower the reliability of the geological survey data. Therefore, according to the data sensitivity information, the corresponding first adjustment data resolution is adjusted, and then the stability coefficient is calculated based on the adjusted first adjustment data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient.

[0116] It should be noted that when the corresponding first adjustment data resolution is adjusted based on the data sensitivity information, the adjustment range is relatively small.

[0117] In one embodiment, if Figure 5 As shown, in step S323, according to the data sensitivity information, the corresponding first adjusted data resolution is adjusted, and the stability coefficient is calculated according to the adjusted first adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient, which specifically includes:

[0118] S3231: According to the data sensitivity information, adjust the corresponding first adjusted data resolution to obtain a second adjusted data resolution.

[0119] Specifically, according to the data sensitivity information, the corresponding first adjusted data resolution is adjusted, and the adjusted first adjusted data resolution is used as the second adjusted data resolution.

[0120] S3232: Combining the second adjusted data resolution and the highest data resolution, determine whether the comprehensive data resolution of the target area meets the preset resolution threshold; if it is judged as yes, calculate the stability coefficient based on the second adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient; if it is judged as no, calculate the stability coefficient based on the comprehensive data resolution of the target area and the corresponding geological survey data to obtain the sensitivity stability coefficient.

[0121] Specifically, the second adjusted data resolution and the highest data resolution are comprehensively considered to determine whether the comprehensive data resolution of the target area meets the preset resolution threshold. If the judgment is yes, it means that the accuracy of the geological survey data corresponding to the second adjusted data resolution at this time is guaranteed after adjustment, and the stability coefficient is calculated based on the second adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient; if the judgment is no, it means that the accuracy of the geological survey data corresponding to the second adjusted data resolution at this time still cannot meet the requirements of actual engineering monitoring after adjustment, and therefore, the stability coefficient is first calculated based on the second adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain the sensitivity stability coefficient.

[0122] S3233: According to the sensitivity stability coefficient, a third adjusted data resolution is selected from the second adjusted data resolution, and a stability coefficient is calculated based on the third adjusted data resolution, the highest data resolution and corresponding geological survey data to obtain a stability coefficient.

[0123] Specifically, the accuracy of the currently acquired sensitivity stability coefficient is unknown. Therefore, the sensitivity stability coefficient is used to infer all possible data resolution situations, that is, a data resolution is randomly assigned to each geological exploration data, and the comprehensive data resolution of the data resolution of each geological exploration data after random assignment is the same as the comprehensive data resolution obtained by combining the second adjusted data resolution and the highest data resolution, thereby obtaining multiple possible data resolution groups, and then judging and extracting the possible data resolution with the smallest corresponding difference between each possible data resolution in the data resolution group and the original data resolution as the third adjusted data resolution, replacing the second adjusted data resolution with the third adjusted data resolution, and then calculating the stability coefficient based on the third adjusted data resolution, the highest data resolution and the corresponding geological exploration data to obtain the stability coefficient.

[0124] Furthermore, the ratio of the third adjusted data resolution to the corresponding second adjusted data resolution may be calculated and used as the final data resolution, and then the highest data resolution and the corresponding geological survey data may be used to calculate the stability coefficient to obtain the stability coefficient.

[0125] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0126] In one embodiment, a foundation pit slope collapse detection system is provided, and the foundation pit slope collapse detection system corresponds to the foundation pit slope collapse detection method in the above embodiment. Figure 6 As shown, the foundation pit slope collapse detection system includes a region division module, a resolution analysis module, a stability coefficient calculation module and a detection result analysis module. The detailed description of each functional module is as follows:

[0127] A region division module is used to divide the target region into several detection sub-regions;

[0128] A resolution analysis module is used to obtain geological survey data corresponding to each detection sub-area, input the geological survey data into a preset resolution analysis model, and obtain the data resolution corresponding to each detection sub-area based on the resolution analysis model;

[0129] The stability coefficient calculation module is used to calculate the stability coefficient according to the data resolution and the corresponding geological survey data to obtain the stability coefficient;

[0130] The detection result analysis module is used to obtain the foundation pit slope collapse detection results based on the stability coefficient.

[0131] Optional, resolution analysis module includes:

[0132] The model analysis submodule is used to input the geological survey data into a preset resolution analysis model, and based on the resolution analysis model, determine the visualization degree of each detection sub-area, as well as the data clarity, data integrity and data reliability of the geological survey data corresponding to each detection sub-area;

[0133] The comprehensive analysis submodule is used to comprehensively analyze the visualization degree of each detection sub-area, as well as the data clarity, data integrity and data reliability of the geological survey data corresponding to each detection sub-area, to obtain the data resolution corresponding to each detection sub-area.

[0134] Optionally, the stability factor calculation module includes:

[0135] The highest extraction submodule is used to comprehensively consider the data resolution corresponding to each detection sub-area, and judge whether the comprehensive data resolution of the target area meets the preset resolution threshold. If it is judged to be yes, the stability coefficient is calculated based on the data resolution and the corresponding geological survey data to obtain the stability coefficient. If it is judged to be no, the highest data resolution is extracted;

[0136] A highest adjustment submodule, used for adjusting other data resolutions according to the highest data resolution;

[0137] The highest calculation submodule is used to calculate the stability coefficient according to the highest data resolution, the adjusted other data resolutions and the corresponding geological survey data to obtain the stability coefficient.

[0138] Optional, highest adjustment submodules include:

[0139] A maximum coefficient calculation unit, used for adjusting other data resolutions according to the highest data resolution to obtain a first adjusted data resolution, and performing stability coefficient calculation based on the highest data resolution and corresponding geological survey data to obtain a maximum stability coefficient;

[0140] A sensitivity analysis unit is used to determine whether the adjustment of the first adjustment data resolution is accurate according to the highest stability coefficient. If it is determined to be accurate, a stability coefficient is calculated based on the first adjustment data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient. If it is determined to be unaccurate, historical geological survey data is obtained, and data sensitivity information corresponding to each type of geological survey data is obtained according to the historical geological survey data.

[0141] The sensitivity calculation unit is used to adjust the corresponding first adjustment data resolution according to the data sensitivity information, and calculate the stability coefficient according to the adjusted first adjustment data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient.

[0142] Optionally, the sensitivity calculation unit includes:

[0143] A first resolution adjustment subunit, configured to adjust the corresponding first adjusted data resolution according to the data sensitivity information to obtain a second adjusted data resolution;

[0144] A sensitivity coefficient calculation subunit is used to comprehensively determine whether the comprehensive data resolution of the target area meets a preset resolution threshold by combining the second adjusted data resolution and the highest data resolution. If the determination is yes, a stability coefficient is calculated based on the second adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain a stability coefficient. If the determination is no, a stability coefficient is calculated based on the comprehensive data resolution of the target area and the corresponding geological survey data to obtain a sensitivity stability coefficient.

[0145] The sensitivity calculation subunit is used to select a third adjusted data resolution from the second adjusted data resolution according to the sensitivity stability coefficient, and calculate the stability coefficient based on the third adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient.

[0146] For the specific definition of the foundation pit slope collapse detection system, please refer to the definition of the foundation pit slope collapse detection method above, which will not be repeated here. Each module in the above foundation pit slope collapse detection system can be implemented in whole or in part by software, hardware and their combination. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0147] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store detection sub-areas, data resolution, stability coefficient and foundation pit slope collapse detection results. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a foundation pit slope collapse detection method is implemented.

[0148] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0149] Divide the target area to obtain several detection sub-areas;

[0150] Acquire geological survey data corresponding to each detection sub-area, input the geological survey data into a preset resolution analysis model, and obtain the data resolution corresponding to each detection sub-area based on the resolution analysis model;

[0151] The stability coefficient is calculated according to the data resolution and the corresponding geological survey data to obtain the stability coefficient;

[0152] According to the stability coefficient, the foundation pit slope collapse detection results are obtained.

[0153] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0154] Divide the target area to obtain several detection sub-areas;

[0155] Acquire geological survey data corresponding to each detection sub-area, input the geological survey data into a preset resolution analysis model, and obtain the data resolution corresponding to each detection sub-area based on the resolution analysis model;

[0156] The stability coefficient is calculated according to the data resolution and the corresponding geological survey data to obtain the stability coefficient;

[0157] According to the stability coefficient, the foundation pit slope collapse detection results are obtained.

[0158] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0159] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0160] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for detecting foundation pit slope collapse, characterized in that: The foundation pit slope collapse detection method comprises: Divide the target area to obtain several detection sub-areas; Acquire geological survey data corresponding to each of the detection sub-areas, input the geological survey data into a preset resolution analysis model, and obtain data resolution corresponding to each of the detection sub-areas based on the resolution analysis model; Calculating the stability coefficient according to the data resolution and the corresponding geological survey data to obtain the stability coefficient specifically includes: Comprehensively judging whether the comprehensive data resolution of the target area meets a preset resolution threshold by comprehensively judging the data resolution of each detection sub-area; if it is judged to be yes, calculating the stability coefficient based on the data resolution and the corresponding geological survey data to obtain the stability coefficient; if it is judged to be no, extracting the highest data resolution; According to the highest data resolution, adjusting other data resolutions; The stability coefficient is calculated according to the highest data resolution, the adjusted other data resolutions and the corresponding geological survey data to obtain the stability coefficient, which specifically includes: Adjusting other data resolutions according to the highest data resolution to obtain a first adjusted data resolution, and calculating a stability coefficient based on the highest data resolution and corresponding geological survey data to obtain a highest stability coefficient; According to the highest stability coefficient, judging whether the adjustment of the first adjustment data resolution is accurate, if it is judged to be yes, calculating the stability coefficient based on the first adjustment data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient, if it is judged to be no, obtaining historical geological survey data, and obtaining data sensitivity information corresponding to each type of geological survey data according to the historical geological survey data; According to the data sensitivity information, the corresponding first adjusted data resolution is adjusted, and the stability coefficient is calculated according to the adjusted first adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient, specifically including: According to the data sensitivity information, adjusting the corresponding first adjusted data resolution to obtain a second adjusted data resolution; Combining the second adjusted data resolution and the highest data resolution, determining whether the comprehensive data resolution of the target area meets a preset resolution threshold, if determined to be yes, calculating a stability coefficient based on the second adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain a stability coefficient, if determined to be no, calculating a stability coefficient based on the comprehensive data resolution of the target area and the corresponding geological survey data to obtain a sensitivity stability coefficient; According to the sensitivity stability coefficient, a third adjustment data resolution is selected from the second adjustment data resolution to obtain a stability coefficient, and a stability coefficient is calculated based on the third adjustment data resolution, the highest data resolution and the corresponding geological survey data to obtain a stability coefficient; According to the stability coefficient, the foundation pit slope collapse detection result is obtained.

2. The method for detecting foundation pit slope collapse according to claim 1, characterized in that: The step of inputting the geological survey data into a preset resolution analysis model and obtaining the data resolution corresponding to each detection sub-area based on the resolution analysis model specifically includes: Inputting the geological survey data into a preset resolution analysis model, and judging the degree of visualization of each detection sub-area, as well as the data clarity, data integrity and data reliability of the geological survey data corresponding to each detection sub-area based on the resolution analysis model; The data resolution corresponding to each detection sub-region is obtained by comprehensively considering the visualization degree of each detection sub-region and the data clarity, data completeness and data reliability of the geological survey data corresponding to each detection sub-region.

3. A foundation pit slope collapse detection system, characterized in that: The foundation pit slope collapse detection system comprises: A region division module is used to divide the target region into several detection sub-regions; A resolution analysis module, used to obtain geological survey data corresponding to each of the detection sub-areas, input the geological survey data into a preset resolution analysis model, and obtain the data resolution corresponding to each of the detection sub-areas based on the resolution analysis model; A stability coefficient calculation module is used to calculate the stability coefficient according to the data resolution and the corresponding geological survey data to obtain the stability coefficient. The stability coefficient calculation module includes: The highest extraction submodule is used to comprehensively judge whether the comprehensive data resolution of the target area meets the preset resolution threshold by comprehensively comparing the data resolution corresponding to each of the detection sub-areas; if it is judged to be yes, a stability coefficient is calculated based on the data resolution and the corresponding geological survey data to obtain the stability coefficient; if it is judged to be no, the highest data resolution is extracted; A highest adjustment submodule, used for adjusting other data resolutions according to the highest data resolution; The highest calculation submodule is used to calculate the stability coefficient according to the highest data resolution, the adjusted other data resolutions and the corresponding geological survey data to obtain the stability coefficient. The highest adjustment submodule includes: A maximum coefficient calculation unit, used for adjusting other data resolutions according to the highest data resolution to obtain a first adjusted data resolution, and performing stability coefficient calculation based on the highest data resolution and corresponding geological survey data to obtain a maximum stability coefficient; A sensitivity analysis unit is used to determine whether the adjustment of the first adjustment data resolution is accurate according to the highest stability coefficient. If it is determined to be accurate, a stability coefficient is calculated based on the first adjustment data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient. If it is determined to be incorrect, historical geological survey data is obtained, and data sensitivity information corresponding to each type of geological survey data is obtained according to the historical geological survey data. A sensitivity calculation unit is used to adjust the corresponding first adjustment data resolution according to the data sensitivity information, and calculate the stability coefficient according to the adjusted first adjustment data resolution, the highest data resolution and the corresponding geological survey data to obtain the stability coefficient. The sensitivity calculation unit includes: A first resolution adjustment subunit, configured to adjust the corresponding first adjusted data resolution according to the data sensitivity information to obtain a second adjusted data resolution; A sensitivity coefficient calculation subunit is used to comprehensively determine whether the comprehensive data resolution of the target area meets a preset resolution threshold by combining the second adjusted data resolution and the highest data resolution. If the determination is yes, a stability coefficient is calculated based on the second adjusted data resolution, the highest data resolution and the corresponding geological survey data to obtain a stability coefficient. If the determination is no, a stability coefficient is calculated based on the comprehensive data resolution of the target area and the corresponding geological survey data to obtain a sensitivity stability coefficient. A sensitivity calculation subunit, configured to select a third adjusted data resolution from the second adjusted data resolution according to the sensitivity stability coefficient, and calculate a stability coefficient based on the third adjusted data resolution, the highest data resolution and corresponding geological survey data to obtain a stability coefficient; The detection result analysis module is used to obtain the foundation pit slope collapse detection result according to the stability coefficient.

4. The foundation pit slope collapse detection system according to claim 3, characterized in that: The resolution analysis module comprises: A model analysis submodule, used for inputting the geological survey data into a preset resolution analysis model, and judging the degree of visualization of each detection sub-area, as well as the data clarity, data integrity and data reliability of the geological survey data corresponding to each detection sub-area based on the resolution analysis model; The comprehensive analysis submodule is used to comprehensively analyze the visualization degree of each detection sub-area, as well as the data clarity, data integrity and data reliability of the geological survey data corresponding to each detection sub-area, to obtain the data resolution corresponding to each detection sub-area.

5. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the foundation pit slope collapse detection method as described in any one of claims 1 to 2 are implemented.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the foundation pit slope collapse detection method as described in any one of claims 1 to 2 are implemented.

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