A method for sampling and automatic screening of geological exploration point data

Abstract

The present invention relates to the technical field of data processing, and in particular to a method for sampling and automatically screening geological exploration point data, comprising: step S1: collecting relevant data during geological exploration, and processing to obtain a transmission signal and echo data of each exploration point; step S2: analyzing the echo data and combining the transmission signal to obtain the reflection intensity of the echo signal at the corresponding exploration point, calculating the difference of the echo signals at any two exploration points, obtaining the credibility of the echo signal at each exploration point, and generating a credibility sequence; determining the authenticity of the echo data through the credibility sequence; step S3: if the authenticity of the echo data is poor, obtaining a segmentation point based on the credibility sequence to segment the credibility sequence into a target data set and a non-target data set; step S4: re-collecting data at the exploration point corresponding to the target data set, and repeating step S2 until a focus position is obtained; and processing the abnormal data through the above method to ensure the accuracy of the sampled data.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, and in particular to a method for sampling and automatically screening geological prospecting point data. Background Art

[0002] The sampling of geological exploration data involves the use of various exploration methods such as drilling, geophysics, geochemistry and remote sensing technology; through the comprehensive use of advanced technologies such as the Global Positioning System (GPS), Geological Information System (GIS), and three-dimensional geological modeling, it is possible to accurately locate and describe geological structures, rock types, mineralization characteristics, and chemical compositions, thereby obtaining underground geological information and understanding the distribution of underground mineral resources and geological structures; during the sampling process, data on strata, rocks, minerals, and other geological characteristics can be collected. These data play a vital role in the exploration, development, and management of mineral resources, and are also of great value for the prediction and prevention of geological disasters.

[0003] In current geological exploration sampling practices, geological radar detectors are used to collect geological data in specific geographical areas. However, when using radar for sampling, the accuracy of the data at the exploration point may be affected by environmental factors, resulting in low accuracy and anomalies, which in turn affect subsequent exploration operations. Summary of the invention

[0004] In order to solve the technical problems that the data at the existing exploration points are affected by environmental factors, have low accuracy and exist abnormalities, the purpose of the present invention is to provide a method for sampling and automatically screening geological exploration point data. The technical scheme adopted is as follows:

[0005] Step S1: Collect relevant data during geological exploration and process them to obtain the transmission signal and echo data of each exploration point;

[0006] Step S2: Analyze the echo data and combine it with the transmission signal to obtain the reflection intensity of the echo signal at the corresponding exploration point, calculate the difference between the echo signals at any two exploration points, obtain the credibility of the echo signal at each exploration point, and generate a credibility sequence; determine the authenticity of the echo data through the credibility sequence;

[0007] Step S3: if the authenticity of the echo data is poor, obtaining segmentation points based on the credibility sequence to segment the credibility sequence into a target data set and a non-target data set;

[0008] Step S4: re-collect data at the exploration point corresponding to the target data set, and repeat step S2 until the focus position is obtained.

[0009] Preferably, step S1 includes: obtaining longitude and latitude information of the current exploration area, determining the position coordinates of each exploration point distributed in the array based on the exploration area, and obtaining the transmission signal and echo data of each exploration point by analyzing and processing through the drone.

[0010] Preferably, step S2 includes:

[0011] Analyze the echo data and combine it with the transmission signal to obtain the reflection intensity of the echo signal at the corresponding exploration point;

[0012] Determine the local extreme point of each echo signal, analyze the average distance between adjacent extreme points to obtain the difference of echo signals at any two exploration points;

[0013] Construct a three-dimensional coordinate system, map each exploration point to the three-dimensional coordinate system based on the echo data combined with the difference, obtain the spatial distance between the exploration point corresponding to each echo signal and the exploration point corresponding to the adjacent echo signal, calculate the credibility of the echo signal at each exploration point, and generate a credibility sequence;

[0014] The amplitude difference range is obtained based on the credibility sequence, and a screening threshold is set. If the amplitude difference range is less than the screening threshold, it indicates that the authenticity of the echo data is good; if the amplitude difference range is greater than or equal to the screening threshold, it indicates that the authenticity of the echo data is poor, and step S3 is entered.

[0015] Preferably, the reflection intensity of the echo signal at each exploration point is calculated, and the corresponding calculation formula is:

[0016]

[0017] in, Indicates The reflection intensity of the echo signal at each exploration point; Indicates The mean value of the echo signal amplitude at each exploration point; Indicates The mean amplitude of the corresponding transmission signal of the echo signal at each exploration point; Represents a constant used to prevent the denominator from being 0; express The dynamic time warping matching distance between the echo signal and the transmitted signal at each exploration point.

[0018] Preferably, the difference of the echo signals at any two exploration points is calculated by the following formula:

[0019]

[0020] in, Indicates The echo signal at the exploration point and the The difference of echo signals at each exploration point; , Respectively represent The reflection intensity of the echo signal at each exploration point and the The reflection intensity of the echo signal at each exploration point; , Respectively represent The average distance between adjacent extreme points of the echo signal at each exploration point and the The average distance between adjacent extreme points of the echo signal at each exploration point.

[0021] Preferably, the credibility of the echo signal at each exploration point is calculated, and the corresponding calculation formula is:

[0022]

[0023] in, Indicates The credibility of the signal at the echo point of each exploration point; represents the linear normalization function; Indicates the number of nearest exploration points selected when performing credibility analysis at each exploration point; Indicates The echo signal at the exploration point and the The difference of echo signals at each exploration point; Indicates At the exploration point and the adjacent The spatial distance between the exploration points.

[0024] Preferably, step S3 includes:

[0025] If the authenticity of the echo data is poor, traverse the credibility sequence and calculate the segmentation effect evaluation value corresponding to each credibility;

[0026] Sorting is performed from large to small based on the segmentation effect evaluation value, and the largest segmentation effect evaluation value is defined as the best segmentation point. Based on the best segmentation point, the credibility sequence is divided into a high-credibility part and a low-credibility part, wherein the high-credibility part is the non-target data set, and the low-credibility part is the target data set.

[0027] Preferably, the segmentation effect evaluation value corresponding to each credibility is calculated, and the corresponding calculation formula is:

[0028]

[0029] in, Indicates the first The segmentation effect evaluation value at each data position; represents the linear normalization function; Represents a constant used to prevent the denominator from being 0; Indicates the first The credibility of the data; Represents the total number of data in the credibility sequence; Indicates the first Data to The standard deviation of the sequence fragments formed between the data; Indicates the first data to the first data in the credibility sequence The standard deviation of the sequence segments formed between the data.

[0030] Preferably, step S4 includes:

[0031] Calculate the number of repeated verification samplings based on the target data set, and resample the exploration points corresponding to the target data set in combination with the number of repeated verification samplings, repeat step S2, obtain the credibility of each repeated verification sampling number at the exploration point to be verified, and obtain the mean as the credibility of the exploration point to be verified;

[0032] Set a judgment threshold, calculate the difference between the credibility of the exploration point to be verified and the corresponding data in the target data set, and if the difference is less than the judgment threshold, mark the exploration point to be verified as a key focus location.

[0033] Preferably, the number of repeated validation samplings is calculated based on the target data set, and the corresponding calculation formula is:

[0034]

[0035] in, Indicates the target data set The number of repeated validation samplings for each data; Indicates the target data set The credibility of the data; Indicates the number of sampling times set for the data to be verified in the target data set when verification is required; Indicates the round-up symbol.

[0036] The present invention has the following beneficial effects:

[0037] When exploring geological data, the geological information of different geographical locations is different, and the echo data collected by the geological radar also behaves differently. First, when detecting at different locations, the collected echo data and the transmitted signal are analyzed to obtain the reflection intensity of the echo signal at different exploration points. For a normal geographical location, the echo data sampled at similar exploration points may be relatively close. Therefore, according to the difference between different echo data and the relationship between the geographical locations, the credibility of each exploration point is obtained, thereby obtaining a credibility sequence. The credibility sequence is further analyzed and processed, and then the target data set that may be abnormal is screened out. For the corresponding exploration points in the target data set, a certain number of repetitions of sampling are performed on them, and the verification results are further analyzed to obtain the key focus positions. Through the above method, the time for sampling data of the geographical location can be saved and the accuracy of the sampling data can be improved, so as to obtain more accurate information on the geology of the corresponding geographical location from the sampling data in the future. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] 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 embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 A system flow chart of a geological exploration point data sampling and automatic screening method provided by one embodiment of the present invention;

[0040] Figure 2 A flowchart of the steps of a geological exploration point data sampling and automatic screening method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of a geological exploration point data sampling and automatic screening method proposed by the present invention, its specific implementation method, structure, features and effects, in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0042] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0043] The specific scheme of the geological exploration point data sampling and automatic screening method provided by the present invention is described in detail below in conjunction with the accompanying drawings.

[0044] Please combine Figure 1 and Figure 2 , which respectively show a system flow chart and a step flow chart of a geological exploration point data sampling and automatic screening method provided by an embodiment of the present invention, the method comprising:

[0045] Step S1: Collect relevant data during geological exploration and process them to obtain the transmission signal and echo data of each exploration point;

[0046] Step S2: Analyze the echo data and combine it with the transmission signal to obtain the reflection intensity of the echo signal at the corresponding exploration point, calculate the difference between the echo signals at any two exploration points, obtain the credibility of the echo signal at each exploration point, and generate a credibility sequence; determine the authenticity of the echo data through the credibility sequence;

[0047] Step S3: if the authenticity of the echo data is poor, obtaining segmentation points based on the credibility sequence to segment the credibility sequence into a target data set and a non-target data set;

[0048] Step S4: re-collect data at the exploration point corresponding to the target data set, and repeat step S2 until the focus position is obtained.

[0049] It is understandable that in today's geological exploration sampling work, geological radar detectors are widely used to carry out detailed geological data collection tasks in specific geographical areas. However, in actual operation, when using geological radar for sampling, the data accuracy at the exploration point may be interfered and affected by various environmental factors, including but not limited to topography, soil moisture, electromagnetic interference, etc. Due to the existence of these factors, the geological radar detector may not be able to provide sufficiently accurate data in some cases, resulting in abnormal data; and these abnormal data will directly affect the subsequent operation and analysis of geological exploration, and thus affect the accuracy and reliability of the entire exploration project; therefore, a geological exploration point data sampling and automatic screening method is proposed in this embodiment, and further verification and correction are carried out for the abnormal data in the sampled data to ensure the reliability of the collected data; that is, the exploration data is analyzed to effectively improve the accuracy and credibility of the data, thereby providing a more scientific and accurate basis for geological exploration.

[0050] Furthermore, step S1 includes: obtaining longitude and latitude information of the current exploration area, determining the position coordinates of each exploration point distributed in the array based on the exploration area, and obtaining the transmission signal and echo data of each exploration point by analyzing and processing through the drone.

[0051] To clarify, exploration points refer to specific locations used for various measurements and sampling during geological exploration. They undergo detailed geological surveys and analyses to ensure that the most representative and valuable geological information can be obtained. Through in-depth research on these specific locations, geologists can better understand the distribution, structure and properties of underground rocks, thereby providing important scientific basis for resource development, engineering construction and other related fields.

[0052] Specifically, in this embodiment, 50 exploration points are determined based on the exploration area for analysis. The exploration points are determined based on the size and accuracy of the exploration geographic area. System, namely Geographic Information System, is a system for capturing, storing, operating, analyzing, managing and displaying all geographic spatial data), obtains the longitude and latitude information of the exploration area, determines the position coordinates of 50 exploration points based on the longitude and latitude information, among which the 50 exploration points are distributed in the exploration area; takes the position coordinate information of the exploration points as the input of the UAV data reception, and uses the geological radar detector deployed inside the UAV to collect the geographical location data at these input exploration points according to the GPS system and processing system inside the UAV. The data collection process is as follows: first, the geological radar inside the UAV transmits a certain high-frequency electromagnetic wave (microwave) to the underground at the exploration point, and at the same time uses the receiving module deployed inside the UAV to receive and record the reflected signal of the transmitted wave through different underground media, so that different echo data can be obtained for each exploration point; based on the efficient collection of detailed geological information of each exploration point by the UAV, not only the efficiency of data collection is improved, but also the accuracy and reliability of the data are ensured, providing a strong technical guarantee for geological exploration.

[0053] Preferably, the transmission signal and echo data are transmitted to the analysis and processing system inside the drone for analysis and processing, so as to facilitate subsequent verification sampling of the positions that need to be verified, and transmit the final verification results and data to the remote system end, so as to obtain data information that may focus on the positions and be re-collected.

[0054] It is understandable that due to the different geographical locations of the exploration points, the collected transmission signals and echo data will also perform differently. When there is a significant difference between an echo signal in the echo data and the other echo signals, the geographical location corresponding to the echo signal may have certain particularities, and additional detection may be required to further verify the detailed information and particularity of the geographical information.

[0055] Furthermore, step S2 includes:

[0056] Step S21: Analyze the echo data and combine it with the transmission signal to obtain the reflection intensity of the echo signal at the corresponding exploration point.

[0057] To clarify, the reflection intensity of the echo signal refers to the signal intensity of the reflected wave received during detection. By analyzing the reflection intensity of the echo signal, the existence, position and characteristics of the target can be determined.

[0058] Furthermore, in step S21, the reflection intensity of the echo signal at each exploration point is calculated, and the corresponding calculation formula is:

[0059]

[0060] in, Indicates The reflection intensity of the echo signal at each exploration point; Indicates The mean value of the echo signal amplitude at each exploration point; Indicates The amplitude mean of the corresponding transmission signal of the echo signal at each exploration point and the value is not 0; Represents a constant used to prevent the denominator from being 0; express The dynamic time warping matching distance between the echo signal and the transmitted signal at each exploration point.

[0061] To explain, represents a constant used to prevent the denominator from being 0. In this embodiment, ; express The dynamic time warping matching distance between the echo signal and the transmission signal at each exploration point, namely the DTW (Dynamic Time Warping, referred to as DTW) matching distance, is a measurement method used to measure the similarity between two time series. By elastically stretching or compressing the time series, the two series are aligned on the time axis to find the best matching path. It allows the time series to be nonlinearly deformed on the time axis to eliminate the difference in time scale and more accurately evaluate the similarity of the two series. The smaller the value, the better. The larger the value, the closer the echo signal at the exploration point is to the transmitted signal, indicating that during the geological exploration of the exploration point, the penetration attenuation loss of the transmitted signal may be smaller, and the reflection intensity of the echo signal at this point is greater; Indicates The ratio of the mean amplitude of the echo signal at each exploration point to the mean amplitude of the corresponding transmitted signal of the echo signal at that location. The larger the value, the greater the reflection intensity of the echo signal at that exploration point.

[0062] Step S22: determine the local extreme value point of each echo signal, and analyze the average distance between adjacent extreme value points to obtain the difference of the echo signals at any two exploration points.

[0063] It can be understood that based on the above steps, the echo signal at each exploration point is determined, and its reflection intensity is different, indicating that the geology of the geographical location of the exploration point is different, so the difference is further analyzed to obtain the difference between the echo signal and the geographical location.

[0064] Specifically, the automatic multi-scale peak detection (Adaptive Moving Peak Detection, AMPD) algorithm is used to obtain the local peak values ​​of all echo signals, where the AMPD algorithm is an algorithm specifically used to find local maximum values ​​(peaks) in time series signals; then the sign of the amplitude of each echo signal is reversed, that is, the positive amplitude is changed to a negative amplitude, and the echo signal is processed in a mirror-symmetrical manner in terms of time series, that is, the echo signal is flipped on the time axis, and through this symmetrical change, the local extreme value points of the corresponding symmetrical data are obtained, and then the local extreme value points of each echo signal are obtained; it can be explained that if the local extreme value points of any two echo signals are different, their reflection intensity and change frequency are different, indicating that the geological information between the two may also be different.

[0065] Furthermore, in step S22, the difference of the echo signals at any two exploration points is calculated by the following formula:

[0066]

[0067] in, Indicates The echo signal at the exploration point and the The difference of echo signals at each exploration point; , Respectively represent The reflection intensity of the echo signal at each exploration point and the The reflection intensity of the echo signal at each exploration point; , Respectively represent The average distance between adjacent extreme points of the echo signal at each exploration point and the The average distance between adjacent extreme points of the echo signal at each exploration point.

[0068] It is explained that the average distance between adjacent extreme points can indirectly reflect the frequency of the echo signal; Indicates The reflection intensity of the echo signal at each exploration point and the The absolute value of the difference in reflection intensity of the echo signals at the two exploration points. The larger the value, the greater the difference in reflection intensity of the echo signals at the two exploration points, and the greater the difference in geological properties at the two exploration points. Indicates The average distance between adjacent extreme points of the echo signal at each exploration point and the The absolute value of the difference in the average distance between adjacent extreme points of the echo signal at the exploration point is greater, indicating that the difference in the frequency of change of the echo signals at the two exploration points is greater, and there is a greater difference in the geological properties of the two geographical locations.

[0069] Step S23: construct a three-dimensional coordinate system, map each exploration point to the three-dimensional coordinate system based on the echo data combined with the difference, obtain the spatial distance between the exploration point corresponding to each echo signal and the exploration point corresponding to the adjacent echo signal, calculate the credibility of the echo signal at each exploration point, and generate a credibility sequence.

[0070] It is explained that in a three-dimensional coordinate system, the horizontal axis is the dimension, the vertical axis is the longitude, and the vertical axis is the difference; and then each exploration point is mapped to the three-dimensional coordinate system, which can not only intuitively display the specific location of each exploration point and the difference between them, but also obtain the spatial distance between different exploration points.

[0071] Furthermore, in step S23, the credibility of the echo signal at each exploration point is calculated, and the corresponding calculation formula is:

[0072]

[0073] in, Indicates The credibility of the signal at the echo point of each exploration point; represents the linear normalization function; Indicates the number of nearest exploration points selected when performing credibility analysis at each exploration point; Indicates The echo signal at the exploration point and the The difference of echo signals at each exploration point; Indicates At the exploration point and the adjacent The spatial distance between the exploration points.

[0074] As an optional implementation, represents the number of the nearest exploration points selected when performing credibility analysis at each exploration point. In this embodiment, .

[0075] To explain, Indicates The echo signal at the exploration point and the The difference of echo signals at the exploration points is At the exploration point and the adjacent The ratio of the spatial distances at the exploration points, assuming that Exploration point and If the distance between the two exploration points is close in the actual space, then the geological information attributes between the two exploration points may also be close, indicating that the echo signals of the two exploration points are also close. At this time, if the difference between the echo signals of the two exploration points is large, but the actual position distance is relatively small, it means that the echo signal collected at one of the two exploration points may have a deviation, or the corresponding geographical location attribute may have an actual obvious difference with the attribute of the adjacent geographical location; therefore The larger the ratio is, the At the exploration point and the adjacent The greater the difference in properties at each exploration point; Indicates exploration points and their selected adjacent The mean of the sum of the differences in the location attributes of the exploration points. The smaller the value, the The smaller the difference between the attribute at the first exploration point and the attribute at the adjacent exploration points, the smaller the difference between the first exploration point and the adjacent exploration points. The higher the credibility of the echo signal collected at each exploration point, the higher the credibility of the echo signal collected at each exploration point; and then the credibility of the echo signal at each exploration point is obtained to generate a credibility sequence.

[0076] Step S24: Obtain the amplitude difference range based on the credibility sequence and set a screening threshold. If the amplitude difference range is less than the screening threshold, it indicates that the authenticity of the echo data is good; if the amplitude difference range is greater than or equal to the screening threshold, it indicates that the authenticity of the echo data is poor, and enter step S3.

[0077] It is understandable that when exploring a geographical location, the credibility of the data collected accurately at the exploration point is higher. Conversely, the data collected at the geographical location with lower credibility needs to be collected and verified again.

[0078] Specifically, the amplitude difference range is obtained based on the credibility sequence, that is, the credibility sequence is analyzed to find out the amplitude change therein, and the maximum and minimum values ​​of the amplitude change are determined by calculating the difference between adjacent data points to obtain the amplitude difference range; in this embodiment, the screening threshold is 0.6. If the amplitude difference range is less than 0.6, it means that the authenticity of the echo data is good, that is, the credibility is high; if the amplitude difference range is greater than or equal to the screening threshold, it means that the authenticity of the echo data is poor, that is, the credibility is low, and the subsequent step S3 is entered for further analysis.

[0079] Furthermore, step S3 includes:

[0080] Step S31: If the authenticity of the echo data is poor, traverse the credibility sequence and calculate the segmentation effect evaluation value corresponding to each credibility.

[0081] It is explained that the segmentation effect evaluation value refers to an indicator for evaluating the segmentation of the credibility sequence, which is used to measure the performance and accuracy of the algorithm. In this embodiment, the credibility sequence is segmented into two parts, high credibility and low credibility, based on the segmentation effect evaluation value. The low credibility part indicates that there may be anomalies to be verified, which need to be collected again for verification to ensure the accuracy of the data.

[0082] Furthermore, in step S31, the segmentation effect evaluation value corresponding to each credibility is calculated, and the corresponding calculation formula is:

[0083]

[0084] in, Indicates the first The segmentation effect evaluation value at each data position; represents the linear normalization function; Represents a constant used to prevent the denominator from being 0; Indicates the first The credibility of the data; Represents the total number of data in the credibility sequence; Indicates the first Data to The standard deviation of the sequence fragments formed between the data; Indicates the first data to the first data in the credibility sequence The standard deviation of the sequence segments formed between the data.

[0085] To explain, Indicates the first data to the first data in the credibility sequence The mean of the credibility of the sequence segments formed between the data is Data to The ratio of the mean of the credibility of the sequence fragments formed between the data, the denominator is not 0, the larger the value, the higher the credibility sequence The better the segmentation effect is at the data point, the larger the ratio is, indicating that the The more obvious the contrast is, the better the segmentation effect is. Indicates the first Data to The standard deviation of the sequence fragments formed between the first data to the The ratio of the standard deviation of the sequence fragments formed between the data is that for conventional exploration points, their credibility may be equivalent, so the credibility of such exploration points is smaller than that of data points that may have abnormalities. Correspondingly, the credibility standard deviation of such exploration points is smaller than that of exploration points that may have abnormalities. Therefore, the larger the ratio, the better the credibility of the first exploration point. The effect of using data as split points is better.

[0086] Step S32: Sort the segments from large to small based on the segmentation effect evaluation value, define the largest segmentation effect evaluation value as the best segmentation point, and divide the credibility sequence into a high-credibility part and a low-credibility part based on the best segmentation point, wherein the high-credibility part is the non-target data set, and the low-credibility part is the target data set.

[0087] Furthermore, step S4 includes:

[0088] Step S41: Calculate the number of repeated verification samplings based on the target data set, and resample the exploration points corresponding to the target data set in combination with the number of repeated verification samplings, repeat step S2, obtain the credibility of each repeated verification sampling number at the exploration point to be verified, and obtain the mean as the credibility of the exploration point to be verified.

[0089] It can be understood that further analysis and verification based on the data in the above-mentioned target data set is to return to the exploration point where such data points were originally collected and re-collect data to check and verify the accuracy of the data in the target data set again at the same location. When verifying the target data set, it is necessary to analyze a reasonable number of collection times based on its existing data to ensure the reliability and accuracy of subsequent data.

[0090] Furthermore, in step S41, the number of repeated verification sampling is calculated based on the target data set, and the corresponding calculation formula is:

[0091]

[0092] in, Indicates the target data set The number of repeated validation samplings for each data; Indicates the target data set The credibility of the data; Indicates the number of sampling times set for the data to be verified in the target data set when verification is required; Indicates the round-up symbol.

[0093] It can be explained that, in the target data set, the lower the credibility of the data to be verified, the higher the number of repeated verification sampling.

[0094] It is explained that based on the number of repeated verification samplings, step S2 is repeated, that is, the exploration points corresponding to each credibility in the target data set are repeatedly sampled a corresponding number of times through repeated verification samplings to obtain the corresponding echo data and transmission signals, and new credibility is obtained through further analysis through step S2. For the exploration points with a large number of repeated verification samplings, the mean value of the new credibility is obtained as the credibility of the exploration point to be verified, so as to have a more comprehensive understanding of the actual situation at the exploration point to be verified, and provide data support for subsequent decision-making and analysis.

[0095] Step S42: setting a judgment threshold, calculating the difference between the credibility of the exploration point to be verified and the corresponding data in the target data set, and if the difference is less than the judgment threshold, marking the exploration point to be verified as a key focus position.

[0096] Preferably, in this embodiment, the judgment threshold is 0.3.

[0097] It can be explained that the difference between the credibility of the exploration point to be verified and the corresponding data in the target data set is calculated, that is, the difference between the credibility of the exploration point to be verified and the credibility of the target data set obtained above is obtained as the difference value, and the difference value is compared with the judgment threshold. If the difference value is less than the judgment threshold, it means that the geology at the exploration point to be verified is relatively special, and it is marked as a key focus position for further detailed exploration, so as to deeply reveal the geographical information, geological structure and other relevant characteristics of these positions, that is, it may be expected to discover more valuable geological data, thereby providing an important reference basis for future geological exploration and resource development; on the contrary, if the difference value is greater than the judgment threshold, the credibility obtained after repeated sampling based on the number of repeated verification samplings will be used as the credibility of the exploration point.

[0098] It can be understood that when geological data is explored, the geological information of different geographical locations is different, and the echo data collected by the geological radar also behaves differently; first, when detecting at different locations, the collected echo data and the transmitted signal are analyzed to obtain the reflection intensity of the echo signal at different exploration points. For a normal geographical location, the echo data sampled at similar exploration points may be relatively close. Therefore, according to the difference between different echo data and the relationship between the geographical locations, the credibility of each exploration point is obtained, thereby obtaining a credibility sequence; the credibility sequence is further analyzed and processed, and then the target data set that may be abnormal is screened out, and the corresponding exploration points in the target data set are sampled a certain number of times, and the verification results are further analyzed to obtain the key focus positions. Through the above method, the time for sampling data of the geographical location can be saved and the accuracy of the sampling data can be improved, so as to obtain more accurate information on the geology of the corresponding geographical location from the sampling data in the future.

[0099] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying 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.

[0100] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for sampling and automatically screening geological exploration point data, characterized in that: The method comprises: Step S1: Collect relevant data during geological exploration and process them to obtain the transmission signal and echo data of each exploration point; Step S2: Analyze the echo data and combine it with the transmission signal to obtain the reflection intensity of the echo signal at the corresponding exploration point, calculate the difference between the echo signals at any two exploration points, obtain the credibility of the echo signal at each exploration point, and generate a credibility sequence; determine the authenticity of the echo data through the credibility sequence; Step S3: if the authenticity of the echo data is poor, obtaining segmentation points based on the credibility sequence to segment the credibility sequence into a target data set and a non-target data set; Step S4: re-collect data at the exploration point corresponding to the target data set, and repeat step S2 until the focus position is obtained; Step S2 includes: Analyze the echo data and combine it with the transmission signal to obtain the reflection intensity of the echo signal at the corresponding exploration point; Determine the local extreme point of each echo signal, analyze the average distance between adjacent extreme points to obtain the difference of echo signals at any two exploration points; Construct a three-dimensional coordinate system, map each exploration point to the three-dimensional coordinate system based on the echo data combined with the difference, obtain the spatial distance between the exploration point corresponding to each echo signal and the exploration point corresponding to the adjacent echo signal, calculate the credibility of the echo signal at each exploration point, and generate a credibility sequence; Based on the credibility sequence, the amplitude difference range is obtained, and a screening threshold is set. If the amplitude difference range is less than the screening threshold, it indicates that the authenticity of the echo data is good; if the amplitude difference range is greater than or equal to the screening threshold, it indicates that the authenticity of the echo data is poor, and step S3 is entered; Step S3 includes: If the authenticity of the echo data is poor, traverse the credibility sequence and calculate the segmentation effect evaluation value corresponding to each credibility; Sorting the data from large to small based on the segmentation effect evaluation value, defining the largest segmentation effect evaluation value as the best segmentation point, and dividing the credibility sequence into a high-credibility part and a low-credibility part based on the best segmentation point, wherein the high-credibility part is the non-target data set, and the low-credibility part is the target data set; Calculate the segmentation effect evaluation value corresponding to each credibility, and the corresponding calculation formula is: in, Indicates the first The segmentation effect evaluation value at each data position; represents the linear normalization function; Represents a constant used to prevent the denominator from being 0; Indicates the first The credibility of the data; Represents the total number of data in the credibility sequence; Indicates the first Data to The standard deviation of the sequence fragments formed between the data; Indicates the first data to the first data in the credibility sequence The standard deviation of the sequence segments formed between the data.

2. A method for sampling and automatically screening geological prospecting point data as claimed in claim 1, characterized in that: Step S1 includes: obtaining the longitude and latitude information of the current exploration area, determining the position coordinates of each exploration point distributed in the array based on the exploration area, and obtaining the transmission signal and echo data of each exploration point by analyzing and processing through the drone.

3. A method for sampling and automatically screening geological prospecting point data as claimed in claim 1, characterized in that: Calculate the reflection intensity of the echo signal at each exploration point. The corresponding calculation formula is: in, Indicates The reflection intensity of the echo signal at each exploration point; Indicates The mean value of the echo signal amplitude at each exploration point; Indicates The mean amplitude of the corresponding transmission signal of the echo signal at each exploration point; Represents a constant used to prevent the denominator from being 0; express The dynamic time warping matching distance between the echo signal and the transmitted signal at each exploration point.

4. A method for sampling and automatically screening geological prospecting point data as claimed in claim 1, characterized in that: The difference of echo signals at any two exploration points is calculated by the following formula: in, Indicates The echo signal at the exploration point and the The difference of echo signals at each exploration point; , Respectively represent The reflection intensity of the echo signal at each exploration point and the The reflection intensity of the echo signal at each exploration point; , Respectively represent The average distance between adjacent extreme points of the echo signal at each exploration point and the The average distance between adjacent extreme points of the echo signal at each exploration point.

5. A method for sampling and automatically screening geological prospecting point data as claimed in claim 1, characterized in that: Calculate the credibility of the echo signal at each exploration point. The corresponding calculation formula is: in, Indicates The credibility of the signal at the echo point of each exploration point; represents the linear normalization function; Indicates the number of nearest exploration points selected when performing credibility analysis at each exploration point; Indicates The echo signal at the exploration point and the The difference of echo signals at each exploration point; Indicates At the exploration point and the adjacent The spatial distance between the exploration points.

6. A method for sampling and automatically screening geological prospecting point data as claimed in claim 1, characterized in that: Step S4 includes: Calculate the number of repeated verification samplings based on the target data set, and resample the exploration points corresponding to the target data set in combination with the number of repeated verification samplings, repeat step S2, obtain the credibility of each repeated verification sampling number at the exploration point to be verified, and obtain the mean as the credibility of the exploration point to be verified; Set a judgment threshold, calculate the difference between the credibility of the exploration point to be verified and the corresponding data in the target data set, and if the difference is less than the judgment threshold, mark the exploration point to be verified as a key focus location.

7. A method for sampling and automatically screening geological prospecting point data as claimed in claim 6, characterized in that: The number of repeated validation samplings is calculated based on the target data set. The corresponding calculation formula is: in, Indicates the target data set The number of repeated validation samplings for each data; Indicates the target data set The credibility of the data; Indicates the number of sampling times set for the data to be verified in the target data set when verification is required; Indicates the round-up symbol.

Images