A method and system for collecting hydrogeological engineering data

Abstract

The present invention relates to the technical field of electrical digital data processing, and particularly relates to a method and system for collecting geological data of water conservancy projects. The method determines multiple target points according to the surveying and mapping reference points, obtains various types of data of the target points, and then, according to the fluctuations of the geological data, obtains the degree of interference of the target points; constructs a feature space for the geological attributes in the geological data of the target points, and obtains the anomaly factor of the target points according to the distribution of the data points in the feature space and the degree of interference of the target points; obtains the anomaly degree of the target points according to the terrain complexity degree and the anomaly factor of the target points; obtains the weighted adjusted distance between the target points and the interpolation points according to the anomaly degree of the target points and the actual distance between the target points and the interpolation points; finally, performs interpolation processing on the weighted adjusted distance between the target points and the interpolation points to obtain the data of all geological points. The present invention can improve the accuracy of geological data collection.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical digital data processing, and particularly relates to a method and system for collecting geological data of water conservancy projects. Background Art

[0002] The collection of geological data for water conservancy projects is a key activity during the construction of water conservancy projects. It aims to provide basic data and scientific basis for engineering design, construction, and management through detailed investigation and analysis of the geological environment. The collection of geological data for water conservancy projects plays a crucial role in aspects such as risk assessment, design optimization, and construction guidance of water conservancy projects.

[0003] When mapping the geology in water conservancy projects, geological profiles are obtained by collecting various types of information at geological points. However, when obtaining various information data at geological points, due to significant differences in soil composition and corresponding terrain in different places, it is easy to be interfered by noise when sampling some soils or terrains, resulting in low accuracy of the obtained geological point information data. This leads to errors when obtaining all geological point information data through inverse distance weighted interpolation of some geological points, thereby reducing the accuracy of geological data collection. Summary of the Invention

[0004] In order to solve the technical problem of low accuracy in collecting geological data in the prior art, the purpose of the present invention is to provide a method and system for collecting geological data of water conservancy projects. The specific technical solutions adopted are as follows:

[0005] In a first aspect, a method for collecting geological data of water conservancy projects is provided. The method includes:

[0006] Step S1: Determine multiple target points according to the surveying and mapping reference points, and obtain various types of data of the target points;

[0007] Step S2: Obtain the degree of interference of the target points according to the fluctuations of the various types of data;

[0008] Step S3: Construct a feature space for the geological attributes in the various types of data of the target points, and obtain the anomaly factor of the target points according to the distribution of data points in the feature space and the degree of interference of the target points;

[0009] Step S4: Obtain the anomaly degree of the target points according to the terrain complexity and anomaly factor of the target points;

[0010] Step S5: Obtain the weighted adjusted distance between the target points and the points to be interpolated according to the anomaly degree of the target points, and interpolate to obtain various types of data of the points to be interpolated according to the weighted adjusted distance.

[0011] Further, the step S1 specifically includes:

[0012] Determine the surveying and mapping reference points, and determine multiple target points at a preset interval distance threshold through triangulation or grid method;

[0013] Use a total station to obtain the coordinates, height, angle and distance of the target points, and obtain the geological horizons, geological properties, meteorological data and groundwater level data of the target points through geological exploration; among them, the geological properties include the density, porosity and permeability of soil or rock.

[0014] Further, the specific steps of step S2 include:

[0015] According to a type of data of the target point, the mean value of this type of data of all neighboring target points corresponding to the target point, and the standard deviation of this type of data of all neighboring target points corresponding to the target point, obtain the disturbance degree of this type of data;

[0016] According to the disturbance degree of all types of data of the target point, obtain the initial disturbance degree of the target point;

[0017] Correct the initial disturbance degree of the target point through the distribution of the neighboring target points of the target point in the feature space to obtain the disturbance degree of the target point.

[0018] Further, the step of correcting the initial disturbance degree of the target point through the distribution of the neighboring target points of the target point in the feature space to obtain the disturbance degree of the target point is specifically:

[0019] Multiply the standardized data of the porosity, permeability of the rock or soil of each target point and the thickness of the geological layer, and record it as the high abnormal dimension feature of each target point. Multiply the standardized data of the density of each target point, and record it as the low abnormal dimension feature of each target point;

[0020] Construct a feature space of the target point with the high abnormal dimension feature of the target point as the vertical axis and the low abnormal dimension feature as the horizontal axis, and map all target points in the feature space;

[0021] According to the distance between a target point and a corresponding neighboring target point in the feature space, the number of neighboring target points, and the initial disturbance degree of the target point, obtain the disturbance degree of the target point.

[0022] Further, the distance between a target point and a corresponding neighboring target point in the feature space and the initial disturbance degree of the target point are both positively correlated with the disturbance degree of the target point.

[0023] Further, the specific steps of step S3 include:

[0024] Obtain the anomaly factor of a target point based on the degree of interference of the target point, the difference between the high-anomaly dimension feature of the target point and the minimum high-anomaly dimension feature, and the difference between the low-anomaly dimension feature of the target point and the maximum low-anomaly dimension feature.

[0025] Furthermore, the degree of interference of a target point, the difference between the high-anomaly dimension feature of the target point and the minimum high-anomaly dimension feature, and the difference between the low-anomaly dimension feature of the target point and the maximum low-anomaly dimension feature are all positively correlated with the anomaly factor of the target point.

[0026] Furthermore, step S4 specifically includes:

[0027] Obtain the terrain complexity of the target point according to the cosine value of the angle between the tendency vector of a target point and the tendency vector of a corresponding neighborhood target point and the number of neighborhood target points;

[0028] Obtain the anomaly degree of each target point according to the terrain complexity and anomaly factor of each target point.

[0029] Furthermore, step S5 specifically includes:

[0030] Obtain the weighted adjusted distance between the target point and the interpolation point according to the anomaly degree of the target point and the actual distance between the target point and the interpolation point;

[0031] Interpolate using the inverse distance weighted interpolation method according to the weighted adjusted distance between the target point and the interpolation point to obtain various types of data of the interpolation point.

[0032] On the other hand, the present invention provides a water conservancy engineering geological data acquisition system, and the system includes:

[0033] A data acquisition module, configured to determine multiple target points according to the surveying and mapping reference points and obtain various types of data of the target points;

[0034] An interference degree acquisition module, configured to obtain the interference degree of the target point according to the fluctuation of the geological data;

[0035] An anomaly factor acquisition module, configured to construct a feature space for the geological attributes in various types of data of the target point, and obtain the anomaly factor of the target point according to the distribution of data points in the feature space and the interference degree of the target point;

[0036] An anomaly degree acquisition module, configured to obtain the anomaly degree of the target point according to the terrain complexity and anomaly factor of the target point;

[0037] A distance acquisition module, configured to obtain the weighted adjusted distance between the target point and the interpolation point according to the anomaly degree of the target point and the actual distance between the target point and the interpolation point;

[0038] The interpolation point data acquisition module is used to perform interpolation processing on the weighted adjusted distance between the target point and the point to be interpolated, and obtain various types of data of the interpolation point;

[0039] The interference degree acquisition module specifically includes: obtaining the perturbation degree of a certain type of data according to a certain type of data of the target point, the mean value of this type of data of all neighboring target points corresponding to the target point, and the standard deviation of this type of data of all neighboring target points corresponding to the target point; obtaining the initial interference degree of the target point according to the perturbation degrees of all types of data of the target point; and correcting the initial interference degree of the target point through the distribution of the neighboring target points of the target point in the feature space to obtain the interference degree of the target point.

[0040] The present invention has the following beneficial effects: obtaining the initial interference degree of each target point through the fluctuation of data; constructing a feature space for the geological attributes of the target points, and obtaining the anomaly factor of each target point through the distribution of data points in the feature space and the initial interference degree, reducing the influence of geological stability, and improving the accuracy of geological stability analysis; obtaining the anomaly degree of each target point according to the anomaly factor of each target point and the degree of tendency consistency of the geological target points, reducing the interference of terrain complexity on data collection, and improving the accuracy of terrain complexity analysis; weighting the distance between the target point and the point to be interpolated by the anomaly degree and performing interpolation to complete the data collection of all geological points, effectively improving the accuracy of geological data collection. Description of the Drawings

[0041] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0042] Figure 1 It is a flowchart of a method for collecting water conservancy engineering geological data provided by an embodiment of the present invention;

[0043] Figure 2 It is a block diagram of a system for collecting water conservancy engineering geological data provided by an embodiment of the present invention. Detailed Embodiments

[0044] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following will, in conjunction with the accompanying drawings and preferred embodiments, elaborate in detail on a method and system for collecting water conservancy engineering geological data proposed according to the present invention, its specific implementation manner, structure, characteristics and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0045] The scenario targeted by the present invention is as follows: During the process of collecting water conservancy engineering geological data, due to the different degrees of terrain complexity and geological stability in different regions, data interference analysis is performed based on terrain features.

[0046] The following will specifically describe the specific solutions of a method and system for collecting water conservancy engineering geological data provided by the present invention in conjunction with the accompanying drawings.

[0047] In a first aspect, please refer to Figure 1 , which shows a flowchart of a method for collecting water conservancy engineering geological data provided by an embodiment of the present invention. The method includes the following steps:

[0048] Step S1: Determine multiple target points based on the surveying and mapping reference points, and obtain various types of data of the target points.

[0049] Among them, step S1 specifically includes: determining the surveying and mapping reference points, determining multiple target points at a preset interval distance threshold through triangulation or grid method, using a total station to obtain types of data such as the coordinates, heights, angles and distances of the target points, and obtaining types of data such as the geological horizons, geological properties, meteorological data and groundwater level data of the target points through geological exploration. Among them, the geological properties include the density, porosity and permeability of soil or rock.

[0050] More specifically, first determine the surveying and mapping reference points, obtain all coordinate data and geological data of each reference point, and then uniformly determine multiple target points at a preset interval distance threshold. For example, the preset distance threshold can be 100 meters, that is, the interval between target points is 100 meters. Then, use a total station to obtain various types of data such as the coordinates, heights, angles and distances of all target points based on the reference point coordinates using triangulation or grid method; then explore and obtain the geological horizons (the thickness and arrangement order of each geological layer), geological properties (density, porosity, permeability), meteorological data and groundwater level data of each reference point and target point. Among them, the geological horizons and geological properties are obtained by drilling, sampling at the target points and sending them to the laboratory for measurement and analysis, and the meteorological data and groundwater level data are collected by corresponding sensors.

[0051] Since when collecting various types of data at the target points, information such as the water content and temperature in the soil affect the characteristics of electromagnetic wave propagation and reflection, and due to the differences in the geological properties of the soil and the complexity of the terrain, the stability of the soil is different. Therefore, it is necessary to assist in analyzing and judging the degree of interference suffered during data collection at different target points based on geological data such as geological horizons, geological properties, meteorological data, and groundwater level data. Based on this, the following steps are further set in this embodiment.

[0052] Step S2: Obtain the degree of interference of the target point according to the fluctuations of the various types of data.

[0053] Among them, step S2 specifically includes: obtaining the degree of perturbation of a certain type of data according to a certain type of data of the target point, the mean value of this type of data of all neighboring target points corresponding to the target point, and the standard deviation of this type of data of all neighboring target points corresponding to the target point; obtaining the initial degree of interference of the target point according to the degrees of perturbation of all types of data of the target point; and correcting the initial degree of interference of the target point through the distribution of neighboring target points of the target point in the feature space to obtain the degree of interference of the target point.

[0054] When obtaining the initial degree of interference of the target point, since information such as the water content and temperature in general soil affects the characteristics of electromagnetic wave propagation and reflection, the fluctuations of various data types of the geological points collected are relatively large. Therefore, the degree of interference is analyzed through the differences between the data of each geological point and its neighboring geological points.

[0055] More specifically, first, obtain all neighboring target points (including the target point itself) within a radius of 1000 meters of each target point; calculate the mean value of each type of data corresponding to all neighboring target points and the standard deviation ; preset a fluctuation threshold ; when the value of each type of data of each target point is within this fluctuation range, it is considered that there is no anomaly, and the degree of interference is considered to be 0; when the value of each type of data of each target point is not within this fluctuation range, it is considered that there is an anomaly.

[0056] The mathematical calculation formula for the degree of perturbation of each type of data of each target point constructed in this embodiment is as follows:

[0057] ;

[0058] In the formula, represents the th type of data of each target point; represents the mean value of the th type of data of all neighboring target points corresponding to each target point; Indicates the standard deviation of the type of data corresponding to each target point for all neighboring target points; since the data corresponding to each target point for all neighboring target points cannot be exactly the same, obviously, ; Indicates the degree of perturbation of the type of data for each target point.

[0059] In the mathematical formula for calculating the degree of perturbation of each type of data for each target point constructed above, represents the process of subtracting a number from the average and then dividing by the standard deviation, that is, the calculation of the standard score, and its result can reflect the type of data relative standard distance from the average of each target point, that is, it can reflect the degree of perturbation of the type of data for each target point; when the value of each type of data for each target point is within the range, it is considered that there is no abnormality and the degree of interference is considered to be 0; when the value of each type of data for each target point is within the range, it is considered that there is an abnormality.

[0060] Then, according to the degree of perturbation of all types of data of the target point, the initial degree of interference of the target point is obtained. The mathematical formula for calculating the initial degree of interference of each target point constructed in this embodiment is as follows:

[0061] ;

[0062] In the formula, represents the number of all types of data, represents the initial degree of interference of each target point, represents the normalization function.

[0063] In the mathematical formula for calculating the initial degree of interference of each target point constructed above, represents the product of the normalization of the degree of perturbation of all types of data. The greater the fluctuation difference between the mean of each type of data of each target point and the mean of each type of data of the corresponding neighboring target points, the greater the interference. When all types of data are more interfered, the initial degree of interference of this target point is greater.

[0064] When obtaining the initial degree of interference of the target points, due to the differences between different soil types, the stability of the physical state of the soil is affected differently, and the interference during data collection is also different. For example, when the high-density soil type means that the soil is more compact and the electromagnetic wave propagation is relatively stable, the degree of interference may be lower, while the low-density soil may result in more pores and air, unstable electromagnetic wave propagation, and increased interference; in the soil with high porosity, there is more water and air, and the electromagnetic wave may be more scattered and attenuated, thus increasing data interference; the highly permeable soil is prone to water flow and frequent changes in water content, which may lead to increased data fluctuations during measurement, while the lower the porosity and permeability of the soil, the higher the stability, that is, the smaller the degree of interference; the thick soil layer causes multiple reflection and refraction phenomena, increasing the uncertainty and interference degree of measurement, and the thin soil layer has fewer layer changes, and the electromagnetic wave propagation is relatively simple, with a lower degree of interference. Therefore, according to the collected soil type characteristics, the initial degree of interference is corrected to obtain the degree of interference of each target point after correction.

[0065] Among them, the initial degree of interference of the target points is corrected by the distribution of the neighboring target points of the target points in the feature space to obtain the degree of interference of the target points. Specifically: the product of the standardized data of the porosity, permeability, and thickness of the geological layer of the rock or soil at each target point is denoted as the high-abnormal dimension feature of each target point, and the product of the standardized data of the density at each target point is denoted as the low-abnormal dimension feature of each target point; a feature space of the target points is constructed with the high-abnormal dimension feature of the target point as the vertical axis and the low-abnormal dimension feature as the horizontal axis, and all target points are mapped in the feature space; according to the distance between a target point and a corresponding neighboring target point in the feature space, the number of neighboring target points, and the initial degree of interference of the target point, the degree of interference of the target point is obtained.

[0066] More specifically, first, the density, porosity, permeability, and thickness of the geological layer are respectively standardized; the product of the standardized data of the porosity, permeability, and thickness of the geological layer at each target point is denoted as the high-abnormal dimension feature of each target point, and the product of the standardized data of the density at each target point is denoted as the low-abnormal dimension feature of each target point. Then, a feature space of the target points is constructed with the high-abnormal dimension feature of the target point as the vertical axis and the low-abnormal dimension feature as the horizontal axis; all target points are mapped in the feature space. Since when the geological feature attributes corresponding to the neighboring target points of each target point are more similar, the distance between the neighboring target points corresponding to each target point in the feature space is smaller, it indicates that the uniformity and stability of the geological environment corresponding to the target point are better, that is, the interference received is smaller. Therefore, the initial degree of interference of each target point is corrected by the distribution of the neighboring target points of each target point in the feature space to obtain the degree of interference of each target point after correction.

[0067] In this embodiment, the mathematical formula for calculating the degree of interference of the target point after correction is as follows;

[0068] ;

[0069] In the formula, represents the distance between the th target point and the corresponding th neighboring target point in the feature space; represents the number of neighboring target points. Since neighboring target points must exist, so ; represents the initial degree of interference of the th target point, and represents the degree of interference of the th target point after correction.

[0070] In the above mathematical formula for calculating the degree of interference of the target point after correction, represents traversing all neighboring target points, and the average distance between the th target point and the corresponding neighboring target point in the feature space. The closer the distance between each target point and all neighboring target points in the feature space, the better the uniformity and stability of the geological environment around the target point, that is, the smaller the degree of interference. Therefore, its value is positively correlated with the degree of interference of the th target point after correction; Obviously, the initial degree of interference of the th target point is also positively correlated with the degree of interference of the th target point after correction.

[0071] Therefore, the distance between a target point and a corresponding neighboring target point in the feature space, and the initial degree of interference of the target point are both positively correlated with the degree of interference of the target point.

[0072] The data anomaly situation of the target point is not limited to the degree of interference of the target point. In the feature space of geology, the higher the value of the high anomaly dimension feature, the more abnormal it is, while the lower the value of the low anomaly dimension feature, the more abnormal it is. Therefore, it is necessary to adjust the degree of interference of the target point according to the high and low of two feature values corresponding to each target point. Therefore, this embodiment further sets the following steps.

[0073] Step S3: Construct a feature space for the geological attributes in various types of data of the target point, and obtain the anomaly factor of the target point according to the distribution of data points in the feature space and the degree of interference of the target point.

[0074] Among them, step S3 specifically includes: obtaining the anomaly factor of a target point according to the interference degree of the target point, the difference between the high anomaly dimension feature of the target point and the minimum high anomaly dimension feature, and the difference between the low anomaly dimension feature of the target point and the maximum low anomaly dimension feature.

[0075] In this embodiment, the mathematical calculation formula for the anomaly factor of the constructed target point is as follows:

[0076] ;

[0077] In the formula, represents the anomaly factor of the th target point; represents the corrected interference degree of the th target point; , represent weight coefficients; represents the high anomaly dimension feature of the th target point; represents the low anomaly dimension feature of the th target point; represents the minimum value of the high anomaly dimension features of all target points; represents the maximum value of the high anomaly dimension features of all target points; represents the maximum value among the low anomaly dimension features of all target points; represents the minimum value among the low anomaly dimension features of all target points.

[0078] In the above mathematical calculation formula for the anomaly factor of the constructed target point, the corrected interference degree of the th target point is positively correlated with the anomaly factor of the th target point; represents the difference between the maximum value and the minimum value among the high anomaly dimension features of all target points, and its value is obviously not 0. represents the normalization of the difference between each target point and the minimum high anomaly dimension feature. The larger the high anomaly feature of the target point, the larger the result, indicating that it is more abnormal. represents the difference between the maximum value and the minimum value among the low anomaly dimension features of all target points, and its value is obviously not 0. It represents the difference between each target point and the maximum low - anomaly - dimension feature, which is then normalized. The smaller the low - anomaly feature of the target point, the larger the result, indicating that it is more anomalous. The high - anomaly - dimension feature of the target point is the product of the porosity, permeability, and thickness of the geological layer of each target point after standardization, and it has three features. The low - anomaly - dimension feature of the target point is the product of the density of each target point after standardization, and it has one feature. Therefore, the weight between the two is 3:1. So, define , .

[0079] Therefore, the degree of interference of a target point, the difference between the high - anomaly - dimension feature of the target point and the minimum high - anomaly - dimension feature, and the difference between the low - anomaly - dimension feature of the target point and the maximum low - anomaly - dimension feature are all positively correlated with the anomaly factor of the target point.

[0080] When there are terrains such as faults, folds, and rock - layer contacts in the local terrain, the terrain is relatively complex at this time. Also, because the height difference between such terrains is large, the consistency of the directionality and tendency of the target points is worse. Therefore, the anomaly degree of each target point can be obtained through the degree of direction consistency and the anomaly situation of the target points. Accordingly, the present embodiment further sets the following steps.

[0081] Step S4: Obtain the anomaly degree of the target point according to the terrain complexity and anomaly factor of the target point.

[0082] Among them, step S4 specifically includes: obtaining the terrain complexity of the target point according to the cosine value of the angle between the tendency vector of a target point and the tendency vector of a corresponding neighborhood target point, and the number of neighborhood target points; obtaining the anomaly degree of each target point according to the terrain complexity and anomaly factor of each target point.

[0083] More specifically, first, obtain the height vector between each target point and each neighborhood target point. The magnitude of the vector is the height difference between the two points, and the direction is from the point with higher altitude to the point with lower altitude. Perform a vector - sum operation on the vectors between each target point and all neighborhood target points to obtain the tendency vector of each target point. Similarly, obtain the tendency vector of the neighborhood target points of the target point. Then, obtain the terrain complexity of each target point through the difference between the tendency vector of each target point and the tendency vector of the corresponding neighborhood target point.

[0084] In this embodiment, the mathematical calculation formula for the terrain complexity of each target point is constructed as follows:

[0085] ;

[0086] In the formula, represents the th target point corresponding to the The cosine value of the angle between the tendency vectors of the neighboring target points; represents the number of neighboring target points. Since neighboring target points necessarily exist, so ; represents the -th target point's terrain complexity; represents the exponential function with the natural constant e as the base.

[0087] In the above-mentioned mathematical calculation formula for the terrain complexity of each target point constructed, the cosine value of the angle between the tendency vectors of the -th target point and the corresponding -th neighboring target point , when this cosine value is larger, it indicates that this angle is smaller, indicating that the terrain near this target point is less complex, the terrain complexity factor of this target point is also smaller, and the degree to which the data of this target point is interfered by terrain complexity is smaller; in addition, the exponential function with the natural constant as the base facilitates restricting the result to between.

[0088] Furthermore, in this embodiment, the mathematical calculation formula for the anomaly degree of each target point is constructed as follows:

[0089] ;

[0090] In the formula, represents the anomaly degree of the -th target point; represents the terrain complexity of the -th target point; represents the anomaly factor of the -th target point; represents the linear normalization function.

[0091] In the above-mentioned mathematical calculation formula for the anomaly degree of each target point constructed, the terrain complexity of the -th target point , the anomaly factor of the -th target point are both positively correlated with the anomaly degree of the -th target point , when the terrain complexity of the target point is larger and the anomaly factor of the target point is larger, the anomaly degree of this target point is larger.

[0092] Step S5: According to the anomaly degree of the target point, obtain the weighted adjusted distance between the target point and the point to be interpolated, and interpolate various types of data of the point to be interpolated according to the weighted adjusted distance.

[0093] Among them, step S5 specifically includes: obtaining the weighted adjusted distance between the target point and the interpolation point according to the abnormality degree of the target point and the actual distance between the target point and the interpolation point; and performing interpolation using the inverse distance weighted interpolation method according to the weighted adjusted distance between the target point and the interpolation point to obtain various types of data of the interpolation point.

[0094] When the abnormality degree of each target point is greater, it indicates that the credibility of the data passing through this point is lower, that is, it means that the target point is farther from the interpolation point. Therefore, the actual distance between the target point and the interpolation point can be weighted and adjusted to ensure the accuracy of the difference data of the interpolation point.

[0095] In this embodiment, the mathematical calculation formula for constructing the weighted adjusted distance between the target point and the interpolation point is as follows:

[0096] ;

[0097] In the formula, represents the abnormality degree of the th target point; represents the actual distance between the target point and the interpolation point, represents the weighted adjusted distance between the target point and the interpolation point.

[0098] In the above-mentioned mathematical calculation formula for constructing the weighted adjusted distance between the target point and the interpolation point, the actual distance between the target point and the interpolation point is used as the reference value, represents the weight. The greater the abnormality degree of the target point, the farther the target point is from the interpolation point. Therefore, on the basis of the actual distance between the target point and the interpolation point, the farther the additional distance needs to be.

[0099] Furthermore, according to the weighted adjusted distance between the target point and the interpolation point, interpolation is performed using the inverse distance weighted interpolation method to obtain various types of data of the interpolation point; based on the various types of data of the interpolation point and the target point, data of all geological points is obtained.

[0100] In a second aspect, this embodiment provides a water conservancy engineering geological data acquisition system. Please refer to Figure 2 , which shows a block diagram of a water conservancy engineering geological data acquisition system provided by an embodiment of the present invention. The system includes:

[0101] A data acquisition module 101, configured to determine multiple target points according to the surveying and mapping reference points and obtain various types of data of the target points;

[0102] An interference degree acquisition module 102, configured to obtain the interference degree of the target point according to the fluctuation of the geological data;

[0103] Anomaly factor acquisition module 103 is configured to construct a feature space for geological attributes in the geological data of a target point, and acquire the anomaly factor of the target point according to the distribution of data points in the feature space and the degree of interference of the target point.

[0104] Anomaly degree acquisition module 104 is configured to obtain the anomaly degree of the target point according to the terrain complexity degree of the target point and the anomaly factor.

[0105] Distance acquisition module 105 is configured to acquire the weighted adjusted distance between the target point and the interpolation point according to the anomaly degree of the target point and the actual distance between the target point and the interpolation point.

[0106] Interpolation point data acquisition module 106 is configured to perform interpolation processing on the weighted adjusted distance between the target point and the interpolation point, and acquire various types of data of the interpolation point.

[0107] The interference degree acquisition module 102 specifically includes: acquiring the perturbation degree of a certain type of data according to a certain type of data of the target point, the mean value of this type of data of all neighboring target points corresponding to the target point, and the standard deviation of this type of data of all neighboring target points corresponding to the target point; obtaining the initial interference degree of the target point according to the perturbation degrees of all types of data of the target point; and correcting the initial interference degree of the target point through the distribution of neighboring target points of the target point in the feature space to obtain the interference degree of the target point.

[0108] Furthermore, the system further includes a terrain complexity degree acquisition module, configured to obtain the terrain complexity degree of the target point according to the cosine value of the angle between the trend vectors of a target point and a corresponding neighboring target point and the number of neighboring target points.

[0109] It should be further noted that the interference degree acquisition module 102 is used to obtain the interference degree of the target point according to the fluctuation of the geological data, specifically as follows: according to a certain type of data of the target point, the mean value of this type of data of all neighboring target points corresponding to the target point, and the standard deviation of this type of data of all neighboring target points corresponding to the target point, obtain the perturbation degree of this type of data; according to the perturbation degrees of all types of data of the target point, obtain the initial interference degree of the target point; record the product of the normalized data of the porosity, permeability of the rock or soil and the thickness of the geological layer of each target point as the high-abnormality dimension feature of each target point, and record the product of the normalized data of the density of each target point as the low-abnormality dimension feature of each target point; construct the feature space of the target point with the high-abnormality dimension feature of the target point as the vertical axis and the low-abnormality dimension feature as the horizontal axis, and map all target points in the feature space; according to the distance between a target point and a corresponding neighboring target point in the feature space, the number of neighboring target points, and the initial interference degree of this target point, obtain the interference degree of this target point.

[0110] A method and system for collecting hydrogeological data provided in this embodiment determine multiple target points according to the surveying and mapping reference points, and obtain various types of data of the target points; obtain the interference degree of the target points according to the fluctuation of the geological data; construct a feature space based on the geological attributes in the geological data of the target points, and obtain the anomaly factor of the target points according to the distribution of the data points in the feature space and the interference degree of the target points; obtain the anomaly degree of the target points according to the terrain complexity and anomaly factor of the target points; obtain the weighted adjusted distance between the target point and the interpolation point according to the anomaly degree of the target point and the actual distance between the target point and the interpolation point; perform interpolation processing on the weighted adjusted distance between the target point and the interpolation point to obtain the data of all geological points. Thus, the accuracy of geological data collection is effectively improved.

[0111] It should be noted that: the above-mentioned sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0112] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the 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 collecting hydrogeological engineering geological data, characterized in that The method includes: Step S1: Determine a plurality of target points according to the surveying and mapping reference points, and obtain various types of data of the target points; Step S2: Obtain the degree of interference of the target points according to the fluctuations of the various types of data; Step S3: Construct a feature space based on the geological attributes in the various types of data of the target points, and obtain the anomaly factor of the target points according to the distribution of data points in the feature space and the degree of interference of the target points; Step S4: Obtain the anomaly degree of the target points according to the terrain complexity degree and anomaly factor of the target points; Step S5: Obtain the weighted adjusted distance between the target points and the points to be interpolated according to the anomaly degree of the target points, and interpolate to obtain various types of data of the points to be interpolated according to the weighted adjusted distance; The specific content of step S2 includes: Obtain the disturbance degree of a certain type of data according to a certain type of data of the target point, the mean value of this type of data of all neighboring target points corresponding to the target point, and the standard deviation of this type of data of all neighboring target points corresponding to the target point; Obtain the initial interference degree of the target point according to the disturbance degrees of all types of data of the target point; Correct the initial interference degree of the target point through the distribution of neighboring target points of the target point in the feature space to obtain the interference degree of the target point. The interference degree of the target point is determined according to the distance between the target point and neighboring target points in the feature space, the number of neighboring target points, and the initial interference degree of the target point. The distance between the target point and neighboring target points in the feature space is used to characterize the uniformity and stability of the geological environment corresponding to the target point. The feature space is constructed with the high-anomaly dimension feature of the target point as the vertical axis and the low-anomaly dimension feature as the horizontal axis. The high-anomaly dimension feature is the product of the standardized data of the porosity, permeability of the rock or soil of the target point, and the thickness of the geological layer. The low-anomaly dimension feature is the product of the standardized data of the density of the target point.

2. The method for collecting hydro-engineering geological data according to claim 1, wherein, The specific content of step S1 includes: Determine the surveying and mapping reference points, and determine a plurality of target points at a preset interval distance threshold by the triangulation method or the grid method; Use a total station to obtain the coordinates, height, angle, and distance of the target points, and obtain the geological horizons, geological attributes, meteorological data, and groundwater level data of the target points through geological exploration; Among them, the geological attributes include the density, porosity, and permeability of the soil or rock.

3. A method for collecting hydro-engineering geological data according to claim 1, characterized in that, The distance between the target point and neighboring target points in the feature space and the initial interference degree of the target point are both positively correlated with the interference degree of the target point.

4. A method for collecting hydraulic engineering geological data according to claim 1, characterized in that, The specific content of step S3 includes: Obtain the anomaly factor of a target point according to the interference degree of the target point, the difference between the high-anomaly dimension feature of the target point and the minimum high-anomaly dimension feature, and the difference between the low-anomaly dimension feature of the target point and the maximum low-anomaly dimension feature.

5. The method for collecting hydro-engineering geological data according to claim 4, wherein, The interference degree of a target point, the difference between the high-anomaly dimension feature of the target point and the minimum high-anomaly dimension feature, and the difference between the low-anomaly dimension feature of the target point and the maximum low-anomaly dimension feature are all positively correlated with the anomaly factor of the target point.

6. The method for collecting hydro-engineering geological data according to claim 1, characterized in that The specific content of step S4 includes: Obtain the terrain complexity of the target point according to the cosine value of the angle between a target point and the tendency vector corresponding to a neighboring target point, and the number of neighboring target points; Obtain the anomaly degree of each target point according to the terrain complexity and anomaly factor of each target point.

7. A method for collecting hydro-engineering geological data according to claim 1, characterized in that, The specific steps of step S5 include: Obtain the weighted adjusted distance between the target point and the point to be interpolated according to the anomaly degree of the target point and the actual distance between the target point and the point to be interpolated; Interpolate using the inverse distance weighted interpolation method according to the weighted adjusted distance between the target point and the point to be interpolated, and obtain various types of data of the interpolated point.

8. A water conservancy project geological data acquisition system, characterized in that The system includes: A data acquisition module, configured to determine multiple target points according to the surveying and mapping reference points, and acquire various types of data of the target points; An interference degree acquisition module, configured to acquire the interference degree of the target point according to the fluctuation of the geological data; An anomaly factor acquisition module, configured to construct a feature space for the geological attributes in various types of data of the target point, and acquire the anomaly factor of the target point according to the distribution of data points in the feature space and the interference degree of the target point; An anomaly degree acquisition module, configured to obtain the anomaly degree of the target point according to the terrain complexity and anomaly factor of the target point; A distance acquisition module, configured to obtain the weighted adjusted distance between the target point and the point to be interpolated according to the anomaly degree of the target point and the actual distance between the target point and the point to be interpolated; An interpolated point data acquisition module, configured to perform interpolation processing on the weighted adjusted distance between the target point and the point to be interpolated, and acquire various types of data of the interpolated point; The interference degree acquisition module specifically includes: obtaining the disturbance degree of a certain type of data according to a certain type of data of the target point, the mean value of this type of data of all neighboring target points corresponding to the target point, and the standard deviation of this type of data of all neighboring target points corresponding to the target point; obtaining the initial interference degree of the target point according to the disturbance degrees of all types of data of the target point; correcting the initial interference degree of the target point through the distribution of neighboring target points of the target point in the feature space to obtain the interference degree of the target point, where the interference degree of the target point is determined according to the distance between the target point and the neighboring target points in the feature space, the number of neighboring target points, and the initial interference degree of the target point, and the distance between the target point and the neighboring target points in the feature space is used to characterize the uniformity and stability of the geological environment corresponding to the target point, and the feature space is constructed with the high anomaly dimension feature of the target point as the vertical axis and the low anomaly dimension feature as the horizontal axis, the high anomaly dimension feature is the product of the porosity, permeability of the rock or soil of the target point and the standardized data of the thickness of the geological layer, and the low anomaly dimension feature is the product of the standardized data of the density of the target point.

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