A mine exploration method and system based on three-pole advanced detection of direct current resistivity method

Abstract

The present invention discloses a mine exploration method and system based on direct current resistivity three-pole advanced detection, which obtains first detection position information and constructs a first coordinate system; according to the first coordinate system, obtains first distribution position information of the power supply electrodes; obtains a first measurement electrode distance of the measurement electrodes, and performs data measurement along a first predetermined trajectory based on the first measurement electrode distance to obtain a first data measurement result; inputs the first distribution position information, the first measurement electrode distance, and the first data measurement result into an anomaly analysis model to obtain a first output result; obtains a first set of abnormal positions, and matches a second measurement electrode distance according to the first set of abnormal positions; obtains a second data measurement result through the measurement electrodes based on the second measurement electrode distance; and performs mine exploration anomaly detection according to the second data measurement result. It solves the technical problem in the prior art that during the process of mine exploration, it is impossible to accurately identify and distinguish abnormal features, and thus accurately identify water hazards.

Description

Technical Field

[0001] The present invention relates to the field of electrical variable measurement, and in particular to a mine exploration method and system based on three-pole advanced detection of direct current resistivity method. Background Art

[0002] Coal is the main source of energy in China and plays a crucial role in the national economy. Coal mines are characterized by a wide distribution range, complex geological conditions, and being severely threatened by water hazards, which makes a large amount of coal resources unable to be mined. Coal mine water hazards are one of the five major safety disasters in mines second only to gas. Therefore, how to predict water hazards in a timely and accurate manner and liberate the coal restricted by water hazards is an urgent problem to be solved.

[0003] However, in the process of implementing the technical solutions of the invention in this application, it is found that the above technologies have at least the following technical problems:

[0004] In the process of existing technologies for mine exploration, there are technical problems that abnormal characteristics cannot be accurately identified and distinguished, and thus water hazards cannot be accurately identified. Summary of the Invention

[0005] This application provides a mine exploration method and system based on three-pole advanced detection of direct current resistivity method, which solves the technical problems that in the process of existing technologies for mine exploration, abnormal characteristics cannot be accurately identified and distinguished, and thus water hazards cannot be accurately identified, and achieves the technical effects of accurately analyzing and identifying abnormal characteristics, accurately identifying water hazards, and accurately positioning the location of water hazards.

[0006] In view of the above problems, this application provides a mine exploration method and system based on three-pole advanced detection of direct current resistivity method.

[0007] In a first aspect, this application provides a mine exploration method based on three-pole advanced detection of direct current resistivity method. The method is applied to a detection optimization analysis system, and the detection optimization analysis system is communicatively connected to a power supply electrode and a measurement electrode. The method includes: obtaining first detection position information, and constructing a first coordinate system according to the first detection position information; obtaining first distribution position information of the power supply electrode according to the first coordinate system; obtaining a first measurement electrode distance of the measurement electrode, and performing data measurement along a first predetermined trajectory based on the first measurement electrode distance to obtain a first data measurement result; inputting the first distribution position information, the first measurement electrode distance, and the first data measurement result into an abnormal analysis model to obtain a first output result; obtaining a first set of abnormal positions according to the first output result, and matching a second measurement electrode distance according to the first set of abnormal positions; obtaining a second data measurement result by the measurement electrode based on the second measurement electrode distance; and performing mine exploration abnormal detection according to the second data measurement result.

[0008] On the other hand, the present application also provides a mine exploration system based on the three-pole advanced detection of the direct current resistivity method. The system includes: a first acquisition unit configured to acquire first detection position information and construct a first coordinate system according to the first detection position information; a second acquisition unit configured to acquire first distribution position information of a power supply electrode according to the first coordinate system; a third acquisition unit configured to acquire a first measurement electrode distance of a measurement electrode, perform data measurement along a first predetermined trajectory based on the first measurement electrode distance, and obtain a first data measurement result; a first input unit configured to input the first distribution position information, the first measurement electrode distance, and the first data measurement result into an anomaly analysis model to obtain a first output result; a fourth acquisition unit configured to obtain a first set of anomaly positions according to the first output result and match a second measurement electrode distance according to the first set of anomaly positions; a fifth acquisition unit configured to obtain a second data measurement result through the measurement electrode based on the second measurement electrode distance; and a first detection unit configured to perform mine exploration anomaly detection according to the second data measurement result.

[0009] In a third aspect, the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the method according to any one of the first aspects are implemented.

[0010] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0011] By adopting the overall solution of constructing a first coordinate system based on the target position to be detected and using the first coordinate system as the benchmark for detection, the position coordinates of the power supply electrode, the position trajectory coordinates of the measurement electrode, and the measurement electrode distance information are obtained. Then, data testing is started through the measurement electrode to obtain the first data measurement result. Combining the current measurement result with the basic measurement parameters, they are input into the anomaly analysis model, that is, the measurement anomalies occurring under the same-precision measurement are monitored and analyzed to obtain the first output result. The set of anomaly positions in the first output result is obtained, and a higher-precision measurement electrode distance is matched according to the set of positions. Based on the newly matched measurement electrode distance, a secondary measurement is performed on the set of anomaly positions to obtain a second data measurement result. Anomaly identification at the current precision is performed on the second data measurement result, and a mine exploration anomaly detection result is generated according to the anomaly identification result, accurately identifying and positioning water hazards and other anomalies, achieving the technical effect of accurately analyzing and identifying anomaly characteristics, and then accurately identifying water hazards and accurately positioning the water hazard location.

[0012] The above description is only an overview of the technical solution of the present application. In order to better understand the technical means of the present application, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically given below. Description of the Drawings

[0013] Figure 1 It is a schematic flow chart of a mine exploration method based on the three-pole advanced detection of direct current resistivity method of the present application;

[0014] Figure 2 It is a schematic flow chart of constructing the abnormal analysis model of a mine exploration method based on the three-pole advanced detection of direct current resistivity method of the present application;

[0015] Figure 3 It is a schematic flow chart of selecting the associated area of a mine exploration method based on the three-pole advanced detection of direct current resistivity method of the present application;

[0016] Figure 4 It is a schematic flow chart of identifying the qualitative analysis result of a mine exploration method based on the three-pole advanced detection of direct current resistivity method of the present application;

[0017] Figure 5 It is a schematic structural diagram of a mine exploration system based on the three-pole advanced detection of direct current resistivity method of the present application;

[0018] Figure 6 It is a schematic structural diagram of an electronic device of the present application.

[0019] Description of the reference numerals: the first acquisition unit 11, the second acquisition unit 12, the third acquisition unit 13, the first input unit 14, the fourth acquisition unit 15, the fifth acquisition unit 16, the first detection unit 17, the electronic device 50, the processor 51, the memory 52, the input device 53, the output device 54. Detailed Embodiments

[0020] By providing a mine exploration method and system based on the three-pole advanced detection of direct current resistivity method, the present application solves the technical problem that in the process of mine exploration in the prior art, it is impossible to accurately identify and distinguish abnormal features, and thus accurately identify water hazards. It achieves the technical effect of accurately analyzing and identifying abnormal features, thereby accurately identifying water hazards and accurately locating the positions of water hazards. The embodiments of the present application will be described below with reference to the accompanying drawings. Those skilled in the art know that with the development of technology and the emergence of new scenarios, the technical solutions provided by the present application are also applicable to similar technical problems.

[0021] In the description, claims and the above-mentioned drawings of this application, terms such as "first" and "second" are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that these terms can be interchanged under appropriate circumstances, which is only a way of distinguishing objects with the same attributes when describing embodiments of this application. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion, so that a process, method, system, product or device including a series of units does not have to be limited to those units, but may include other units not clearly listed or inherent to these processes, methods, products or devices.

[0022] Application Overview

[0023] Coal is the main source of energy in China and plays a crucial role in the national economy. Coal mines are characterized by a wide distribution range, complex geological conditions, and being severely threatened by water hazards, which makes a large amount of coal resources unexploitable. Coal mine water hazard is one of the five major safety disasters in mines second only to gas. Therefore, how to accurately predict water hazards in a timely manner and liberate the coal restricted by water hazards is an urgent problem to be solved. In the process of mine exploration in the prior art, there are technical problems that abnormal characteristics cannot be accurately identified and distinguished, and thus water hazards cannot be accurately identified.

[0024] In view of the above technical problems, the general idea of the technical solution provided in this application is as follows:

[0025] This application provides a mine exploration method based on three-pole advanced detection of direct current method. The method is applied to a detection optimization analysis system, and the detection optimization analysis system is communicatively connected to a power supply electrode and a measurement electrode. The method includes: obtaining first detection position information, and constructing a first coordinate system according to the first detection position information; obtaining first distribution position information of the power supply electrode according to the first coordinate system; obtaining a first measurement electrode distance of the measurement electrode, and performing data measurement along a first predetermined trajectory based on the first measurement electrode distance to obtain a first data measurement result; inputting the first distribution position information, the first measurement electrode distance, and the first data measurement result into an abnormal analysis model to obtain a first output result; obtaining a first set of abnormal positions according to the first output result, and matching a second measurement electrode distance according to the first set of abnormal positions; obtaining a second data measurement result through the measurement electrode based on the second measurement electrode distance; and performing abnormal detection of mine exploration according to the second data measurement result.

[0026] After introducing the basic principle of this application, the various non-limiting embodiments of this application will be specifically introduced below in conjunction with the drawings in the specification.

[0027] Embodiment 1

[0028] AsFigure 1 As shown in Figure 1 , the present application provides a mine exploration method based on three - electrode DC resistivity advanced detection. The method is applied to a detection optimization analysis system, which is communicatively connected to a power supply electrode and a measurement electrode. The method includes:

[0029] Step S100: Obtain first detection position information and construct a first coordinate system according to the first detection position information;

[0030] Step S200: Obtain first distribution position information of the power supply electrode according to the first coordinate system;

[0031] Specifically, the detection optimization analysis system is a system for controlling the detection process, analyzing the detection results based on the collected data, accurately identifying anomalies and locating detections. The power supply electrode is a connection power supply selected to supply power to the ground during the resistivity detection process. Since this solution is three - electrode DC resistivity advanced detection, the number of power supply electrodes is three, and the three power supply electrodes are distributed in a straight line with a first predetermined distance. The measurement electrode is a grounding electrode capable of measuring potential difference. Further, the device further includes another power supply electrode set at infinity. The detection optimization analysis system is communicatively connected to the power supply electrode and the measurement electrode, enabling mutual information interaction. The first detection position is the target position information for detection. According to the position information of the target, a three - dimensional rectangular coordinate system is constructed.

[0032] Furthermore, the positions of the power supply electrodes are distributed. The power supply electrodes include three power supply electrodes with a certain spacing. Generally, the size of the spacing is selected according to the height and width information of the intersection point. The power supply electrodes further include a power supply electrode set at infinity, and the power supply electrode set at infinity is on the same straight line as the three power supply electrodes. Through the constructed three - dimensional rectangular coordinate system, the position coordinate information of the three power supply electrodes, that is, the first distribution position information, is obtained. By constructing the three - dimensional coordinate system, data support is provided for the subsequent electrode distribution, which further makes the subsequent determination of the electrode position more accurate, and then provides accurate analysis data, providing data support for accurately detecting and locating anomalies.

[0033] Step S300: Obtain the first measurement electrode distance of the measurement electrode and perform data measurement along a first predetermined trajectory based on the first measurement electrode distance to obtain a first data measurement result;

[0034] Step S400: Input the first distribution position information, the first measurement electrode distance, and the first data measurement result into an anomaly analysis model to obtain a first output result;

[0035] Specifically, the measurement electrode distance affects the measurement accuracy and the measurement range. For accurate measurement, first, a relatively large measurement electrode distance is set to facilitate sufficient data acquisition. According to the detection range of the first detection position information, the distance of the measurement electrode distance is set to obtain the first measurement electrode distance. Keeping the distance of the first measurement electrode distance unchanged, the measurement electrode distance is moved in the direction of the infinite far power supply electrode at a predetermined set spacing.

[0036] Furthermore, for the three power supply electrodes, first, power is supplied to one power supply electrode, and the other two power supply electrodes are turned off to obtain the potential data of the acquisition measurement electrode. At this time, the current power supply electrode is turned off, and one of the non-powered electrodes is turned on until the potential data of all three power supply electrodes are measured. Then, the measurement electrode is moved to the next measurement point, and the process of separately supplying power to the three power supply electrodes is repeated until the separate power supply data of the three power supply electrodes are collected at each measurement point, completing the data acquisition and obtaining the first data measurement result. The first data measurement result, the first distribution position information, and the first measurement electrode distance are input into the anomaly analysis model to obtain the first output result. The anomaly analysis model is a model for performing anomaly analysis with different measurement accuracies (the measurement electrode distance of the measurement electrode is used as a constraint parameter). The model is a neural network model in machine learning, and the anomaly data under different accuracies are separately trained to make the anomaly detection more accurate. Through data acquisition, data support is provided for preliminary anomaly analysis. By constructing the anomaly analysis model with different accuracies for sub-accuracies, the identification of anomalies is made more sensitive and accurate, thereby laying a solid foundation for subsequent accurate water disaster detection.

[0037] Step S500: Obtain the first anomaly position set according to the first output result, and match the second measurement electrode distance according to the first anomaly position set;

[0038] Step S600: Obtain the second data measurement result based on the second measurement electrode distance through the measurement electrode;

[0039] Step S700: Perform mine exploration anomaly detection according to the second data measurement result.

[0040] Specifically, according to the first output result, a set of positions for preliminary anomaly localization is determined, that is, the first anomaly position set. By obtaining the first anomaly position set, corresponding position expansion is performed on the anomaly position points according to different anomalies. According to the position expansion result, the distance of the measurement electrode spacing is adjusted to obtain a second measurement electrode spacing. The second measurement electrode spacing is used to perform another data measurement on the first anomaly position set and the expanded area of the first anomaly position set to obtain the second data measurement result. The second data measurement result is input into the anomaly analysis model to obtain the anomaly analysis result with the accuracy under the second data measurement result. The anomaly detection of the mine exploration is completed according to the analysis result. Through the anomaly recognition of the preliminary positioning, the range area is determined, and then high-precision anomaly information is collected to achieve the technical effect of accurately analyzing and identifying the anomaly characteristics, and then accurately identifying the water hazard and accurately locating the position of the water hazard.

[0041] Furthermore, as Figure 2 shown, step S400 of this application further includes:

[0042] Step S410: Construct an anomaly feature set;

[0043] Step S420: Obtain an anomaly signal set corresponding to the anomaly feature set through big data, where the anomaly signal set includes corresponding anomaly signal sets under multiple measurement accuracies;

[0044] Step S430: Construct the anomaly analysis model based on the anomaly signal set. When the output accuracy rate of the anomaly analysis model meets the first preset threshold, the construction of the anomaly analysis model ends;

[0045] Step S440: Perform anomaly detection on the first data measurement result and the second data measurement result according to the constructed anomaly analysis model.

[0046] Specifically, the anomaly feature set includes fault zones, broken zones, subsidence columns, water accumulation characteristics, floating coal characteristics, etc. The anomaly feature set is constructed through big data, and the anomaly feature set has a corresponding anomaly signal set. The anomaly signal set includes multiple signals corresponding to the anomaly features. Different signals are manifested as anomaly features corresponding to different measurement accuracies, that is, each anomaly feature corresponds to anomaly signal manifestations under multiple accuracies.

[0047] Furthermore, taking the abnormal features as the identification result, classifying abnormal signals with different precisions according to the precision to obtain a first-precision abnormal signal set, a second-precision abnormal signal set... an N-precision abnormal signal set, where N is a positive integer greater than 2. Respectively, using the abnormal features as the identification data according to the identification result, and using the first-precision abnormal signal set as the input data to construct an abnormal analysis model at the first precision. When the output result of the abnormal analysis model at the first precision meets the expected accuracy rate, the construction of the abnormal analysis model at the first precision is completed. Similarly, the corresponding abnormal analysis models are constructed for the second-precision abnormal signal set... the N-precision abnormal signal set in the same way. After performing corresponding matching precision abnormal analysis model matching on the first data measurement result and the second data measurement result, abnormal detection is performed based on the matched abnormal analysis model. By constructing the abnormal analysis model with different precisions, the identification of abnormal signals is made more accurate, and thus the identification result of abnormal features is more accurate, laying a foundation for subsequent accurate mine exploration.

[0048] Furthermore, as Figure 3 shown, step S700 of this application further includes:

[0049] Step S710: Obtain the abnormal identification information of the first abnormal position set according to the first output result;

[0050] Step S720: Screen the areas in the first abnormal position set that need to have their associated positions measured according to the abnormal identification information to obtain a first screening result;

[0051] Step S730: Obtain a first associated position set according to the first screening result;

[0052] Step S740: Obtain the second data measurement result based on the first associated position set and the first abnormal position set according to the second measurement electrode spacing.

[0053] Specifically, according to the first output result, obtain the preliminary abnormal determination result of the first abnormal position set. When the preliminary abnormal determination result is a non-continuous abnormal feature, such as the identification result of a collapse column feature, no screening of the associated area of the corresponding abnormal position is performed at this time; when the preliminary abnormal determination result is a continuous abnormal feature, such as a floating coal feature or a water hazard feature, at this time, according to the continuous change situation of the first data acquisition result, combined with the position and size of the abnormal feature, the associated area is associated.

[0054] Furthermore, after the associated regions are associated, the associated regions and the corresponding abnormal position regions are regarded as the same position region, and the first set of abnormal positions for abnormal detection is expanded according to the same position region, that is, data acquisition of the second measurement electrode distance is performed through the first associated position set and the first set of abnormal positions to obtain the second data measurement result. By obtaining the associated regions, the subsequent collected data is made more comprehensive, and thus the features with continuity can be accurately identified, and further the technical effect of making the obtained abnormal detection result more accurate is achieved.

[0055] Further, as Figure 4 shown, step S700 of the present application further includes:

[0056] Step S750: Obtain the associated data of the abnormal data mutation identifier;

[0057] Step S760: Perform qualitative identification of abnormal analysis on the second data result according to the associated data of the abnormal data mutation identifier to obtain the qualitative analysis result of mine exploration.

[0058] Specifically, in the process of qualitative identification of abnormal features, not only the data features of the position of the abnormal features themselves need to be considered, but also the feature data of the adjacent regions of the abnormal features need to be deeply analyzed to ensure the accuracy of the abnormal feature identification. For example, when the identified feature is a discontinuous feature, it is necessary to judge whether the data of the associated data of the abnormal data mutation identifier is mutant data. When the data is mutant data, it indicates that the feature judgment result is correct at this time; when the identified feature is a water hazard feature, there should be water-rich areas before and after the water hazard feature. Therefore, the data before and after the water hazard feature identification result should be associated and gradually changed, and the measurement of associated data is required when making a determination of the feature identification with continuous change. Through the determination of the associated data of the abnormal data mutation identifier, the obtained qualitative analysis result of mine exploration is made more accurate.

[0059] Further, step S500 of the present application further includes:

[0060] Step S510: Obtain the first set of matching measurement electrode distances according to the first measurement electrode distance;

[0061] Step S520: Obtain the first predetermined measurement accuracy parameter;

[0062] Step S530: Obtain the first screening parameter according to the first predetermined measurement accuracy parameter and the first set of abnormal positions;

[0063] Step S540: Screen the first set of matching measurement electrode distances according to the first screening parameter to obtain the second measurement electrode distance.

[0064] Specifically, during the process of secondary selection of electrode spacing, in order to make the measurement results more accurate, it is necessary to perform secondary selection of electrode spacing according to the actual situation and requirements. The first matching measurement electrode spacing set is obtained by preliminary screening of electrode spacing, that is, the second measurement electrode spacing must be smaller than the first measurement electrode spacing in order to further analyze the first measurement parameter. The first predetermined measurement accuracy parameter is the minimum accuracy requirement information for mine exploration at the current position, and the first abnormal position set is the set of position identification of the abnormal positions. According to the position distance of the first abnormal position set, the appropriate electrode spacing parameters are selected.

[0065] Furthermore, when the position information in the first abnormal position set has too large a span and cannot be accurately screened with a single electrode spacing, two electrode spacings can be used for measurement according to the distance. The first screening parameter is obtained based on the first predetermined measurement accuracy parameter and the first abnormal position set. Based on the first screening parameter, the first matching measurement electrode set is screened to obtain the second measurement electrode spacing. By comparing and screening the second measurement electrode spacing, the selection of the second measurement electrode spacing is made more accurate, and thus the data obtained by measuring with the second measurement electrode spacing is more accurately adapted, and further the purpose of accurately collecting and analyzing the secondary parameters of the abnormal position is achieved, realizing the technical effects of accurately identifying the abnormality and positioning the position.

[0066] Further, step S700 of the present application further includes:

[0067] Step S770: Obtain roadway slope parameter information;

[0068] Step S780: Based on the roadway slope parameter information, perform abnormal position compensation on the second data measurement result to obtain a first position compensation result;

[0069] Step S790: Obtain a mine exploration abnormal detection result according to the first position compensation result.

[0070] Specifically, the roadway slope parameter information is the roadway slope change parameter information during the process of probing, when driving piles backward at the probing point. The greater the roadway slope information, the greater the impact on the position and distance of positioning anomalies in the measurement results. Determine whether the roadway slope parameter meets the first preset threshold. When the roadway slope parameter does not meet the first preset threshold, no consideration and compensation processing for the roadway slope are performed; when the roadway slope parameter meets the first preset threshold, at this time, according to the historical data of the influence of the roadway slope parameter on distance positioning, obtain the position compensation parameter, and according to the position compensation parameter, compensate the position information of each abnormal feature in the currently obtained mine exploration result to obtain the first position compensation result. Through the first position compensation result, obtain the final mine exploration anomaly detection result. By performing position analysis and comparison of the roadway slope parameter information, the positioning information in the obtained mine exploration anomaly detection result is made more accurate, thereby achieving the technical effect of improving the accuracy of anomaly detection.

[0071] Further, step S800 of this application further includes:

[0072] Step S810: Obtain the first data acquisition quality evaluation parameter according to the data acquisition process;

[0073] Step S820: Obtain the interference signal information of the data acquisition process;

[0074] Step S830: Obtain the second data acquisition quality evaluation parameter according to the interference signal information;

[0075] Step S840: Obtain the credibility identification result of mine exploration anomaly detection according to the first data acquisition quality evaluation parameter and the second data acquisition quality evaluation parameter.

[0076] Specifically, before the process of outputting the final mine exploration result, it is necessary to perform a self-check of the overall data to accurately reflect the final measurement and analysis result. The self-check of the data includes the verification of the data acquisition quality during the acquisition process, that is, whether there is a position deviation and whether the operation of the instrument is appropriate during the actual measurement data process. Obtain the first data acquisition quality evaluation parameter according to the acquisition parameter process. The interference signal refers to whether there is signal data that interferes with the measurement data during the data acquisition process. According to the strength and occurrence frequency of the interference signal, obtain the second data acquisition quality evaluation parameter. Obtain the credibility identification result of mine exploration anomaly detection according to the first data acquisition quality evaluation parameter and the second data acquisition quality evaluation parameter, and perform the credibility identification of the final anomaly detection.

[0077] In summary, the mine exploration method and system based on the three-pole advanced detection of direct current resistivity method provided by this application have the following technical effects:

[0078] 1. By adopting the overall scheme of constructing the first coordinate system based on the target position to be detected, constructing the benchmark of the detection through the first coordinate system, obtaining the position coordinates of the power supply electrodes, the position trajectory coordinates of the measurement electrodes, the measurement electrode spacing information, and starting data testing through the measurement electrodes to obtain the first data measurement result. Combining the current measurement result with the basic measurement parameters and inputting them into the anomaly analysis model, that is, monitoring and analyzing the measurement anomalies occurring under the same-precision measurement to obtain the first output result. Obtain the set of abnormal positions in the first output result, match a higher-precision measurement electrode spacing according to the set of positions, perform secondary measurement on the set of abnormal positions based on the newly matched measurement electrode spacing to obtain the second data measurement result, perform anomaly identification at the current precision on the second data measurement result, generate the mine exploration anomaly detection result according to the anomaly identification result, accurately identify and locate water disasters and other anomalies, achieve accurate analysis and identification of anomaly characteristics, and further accurately identify water disasters and accurately locate the positions of water disasters.

[0079] 2. By constructing the anomaly analysis model with different precisions, the identification of abnormal signals is made more accurate, and then the identification result of anomaly characteristics is made more accurate, laying a foundation for subsequent accurate mine exploration.

[0080] 3. By obtaining the associated area, the subsequent collected data is made more comprehensive, and then the characteristics with continuity can be accurately identified, and further the technical effect of making the obtained anomaly detection result more accurate is achieved.

[0081] 4. By comparing and screening the second measurement electrode spacing, the selection of the second measurement electrode spacing is made more accurate, and then the data measured through the second measurement electrode spacing is made more accurately adapted, and further the purpose of accurately collecting and analyzing secondary parameters of abnormal positions is achieved, realizing the technical effects of accurately identifying anomalies and positioning positions.

[0082] 5. By analyzing and comparing the position of the roadway slope parameter information, the positioning information in the obtained mine exploration anomaly detection result is made more accurate, and further the technical effect of improving the accuracy of anomaly detection is achieved.

[0083] Embodiment 2

[0084] Based on the same inventive concept as the mine exploration method based on the three-pole advanced detection of direct current resistivity method in the foregoing embodiment, the present invention also provides a mine exploration system based on the three-pole advanced detection of direct current resistivity method, as Figure 5 shown, the system includes:

[0085] The first acquisition unit 11 is configured to acquire first detection position information and construct a first coordinate system according to the first detection position information;

[0086] The second acquisition unit 12 is configured to acquire first distribution position information of the power supply electrodes according to the first coordinate system;

[0087] The third acquisition unit 13 is configured to acquire a first measurement electrode distance of the measurement electrode, perform data measurement through a first predetermined trajectory based on the first measurement electrode distance, and obtain a first data measurement result;

[0088] The first input unit 14 is configured to input the first distribution position information, the first measurement electrode distance, and the first data measurement result into an anomaly analysis model to obtain a first output result;

[0089] The fourth acquisition unit 15 is configured to obtain a first set of abnormal positions according to the first output result, and match a second measurement electrode distance according to the first set of abnormal positions;

[0090] The fifth acquisition unit 16 is configured to obtain a second data measurement result through the measurement electrode based on the second measurement electrode distance;

[0091] The first detection unit 17 is configured to perform mine exploration anomaly detection according to the second data measurement result.

[0092] Further, the system further includes:

[0093] The first construction unit is configured to construct an anomaly feature set;

[0094] The sixth acquisition unit is configured to obtain a set of anomaly signals corresponding to the anomaly feature set through big data, where the set of anomaly signals includes corresponding sets of anomaly signals under multiple measurement precisions;

[0095] The seventh acquisition unit is configured to construct the anomaly analysis model based on the set of anomaly signals. When the output accuracy rate of the anomaly analysis model meets a first preset threshold, the construction of the anomaly analysis model is ended;

[0096] The second detection unit is configured to perform anomaly detection on the first data measurement result and the second data measurement result according to the constructed anomaly analysis model.

[0097] Further, the system further includes:

[0098] An eighth acquisition unit, configured to acquire abnormal identification information of the first abnormal position set according to the first output result;

[0099] A ninth acquisition unit, configured to screen, according to the abnormal identification information, a region in the first abnormal position set that needs to be measured for associated positions, and obtain a first screening result;

[0100] A tenth acquisition unit, configured to obtain a first associated position set according to the first screening result;

[0101] An eleventh acquisition unit, configured to obtain a second data measurement result based on the first associated position set and the first abnormal position set according to the second measurement electrode distance.

[0102] Further, the system further includes:

[0103] A twelfth acquisition unit, configured to acquire abnormal data mutation identification associated data;

[0104] A thirteenth acquisition unit, configured to perform qualitative identification of abnormal analysis on the second data result according to the abnormal data mutation identification associated data, and obtain a qualitative analysis result of mine exploration.

[0105] Further, the system further includes:

[0106] A fourteenth acquisition unit, configured to obtain a first matching measurement electrode distance set according to the first measurement electrode distance;

[0107] A fifteenth acquisition unit, configured to obtain a first predetermined measurement accuracy parameter;

[0108] A sixteenth acquisition unit, configured to obtain a first screening parameter according to the first predetermined measurement accuracy parameter and the first abnormal position set;

[0109] A seventeenth acquisition unit, configured to screen the first matching measurement electrode distance set according to the first screening parameter, and obtain the second measurement electrode distance.

[0110] Further, the system further includes:

[0111] An eighteenth acquisition unit, configured to obtain roadway slope parameter information;

[0112] The nineteenth acquisition unit is configured to perform abnormal position compensation on the second data measurement result based on the roadway slope parameter information to obtain a first position compensation result;

[0113] The twentieth acquisition unit is configured to obtain a mine exploration anomaly detection result according to the first position compensation result.

[0114] Furthermore, the system further includes:

[0115] The twenty-first acquisition unit is configured to obtain a first data acquisition quality evaluation parameter according to the data acquisition process;

[0116] The twenty-second acquisition unit is configured to obtain interference signal information of the data acquisition process;

[0117] The twenty-third acquisition unit is configured to obtain a second data acquisition quality evaluation parameter according to the interference signal information;

[0118] The twenty-fourth acquisition unit is configured to obtain a credibility identification result for mine exploration anomaly detection according to the first data acquisition quality evaluation parameter and the second data acquisition quality evaluation parameter.

[0119] The foregoing Figure 1 All the various change modes and specific examples of a mine exploration method based on DC resistivity three-pole advanced detection in Embodiment 1 also apply to a mine exploration system based on DC resistivity three-pole advanced detection in this embodiment. Through the foregoing detailed description of a mine exploration method based on DC resistivity three-pole advanced detection, those skilled in the art can clearly know the implementation method of a mine exploration system based on DC resistivity three-pole advanced detection in this embodiment. Therefore, for the sake of simplicity of the specification, it will not be elaborated herein.

[0120] Exemplary electronic device

[0121] Next, refer to Figure 6 to describe the electronic device of the present application.

[0122] Figure 6 The structural schematic diagram of an electronic device according to the present application is illustrated.

[0123] Based on the inventive concept of a mine exploration method based on DC resistivity three-pole advanced detection in the foregoing embodiment, the present invention further provides an electronic device. Next, refer to Figure 6To describe the electronic device according to the present application. The electronic device may be the movable device itself, or a stand-alone device independent thereof, on which a computer program is stored, and when the program is executed by a processor, the steps of any of the methods described above are implemented.

[0124] As Figure 6 shown, the electronic device 50 includes one or more processors 51 and a memory 52.

[0125] The processor 51 may be a central processing unit (CPU) or other form of processing unit having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 50 to perform desired functions.

[0126] The memory 52 may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage media, and the processor 51 may run the program instructions to implement the methods of the various embodiments of the present application described above and / or other desired functions.

[0127] In one example, the electronic device 50 may further include: an input device 53 and an output device 54, and these components are interconnected through a bus system and / or other forms of connection mechanisms (not shown).

[0128] A mine exploration method based on three-pole advanced detection of direct current resistivity method provided by an embodiment of the present invention. The method is applied to a detection optimization analysis system, and the detection optimization analysis system is communicatively connected to a power supply electrode and a measurement electrode. The method includes: obtaining first detection position information, and constructing a first coordinate system according to the first detection position information; obtaining first distribution position information of the power supply electrode according to the first coordinate system; obtaining a first measurement electrode spacing of the measurement electrode, and performing data measurement along a first predetermined trajectory based on the first measurement electrode spacing to obtain a first data measurement result; inputting the first distribution position information, the first measurement electrode spacing, and the first data measurement result into an anomaly analysis model to obtain a first output result; obtaining a first set of anomaly positions according to the first output result, and matching a second measurement electrode spacing according to the first set of anomaly positions; obtaining a second data measurement result through the measurement electrode based on the second measurement electrode spacing; and performing mine exploration anomaly detection according to the second data measurement result. This solves the technical problem in the prior art that during the process of mine exploration, it is impossible to accurately identify and distinguish anomaly characteristics, and thus accurately identify water hazards, achieving the technical effect of accurately analyzing and identifying anomaly characteristics, thereby accurately identifying water hazards and accurately locating the positions of water hazards.

[0129] Through the description of the above embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general hardware, and of course, it can also be implemented by dedicated hardware including application-specific integrated circuits, dedicated CPUs, dedicated memories, dedicated components, etc. Generally, functions completed by computer programs can be easily implemented by corresponding hardware, and the specific hardware structures for implementing the same function can also be diverse, such as analog circuits, digital circuits, or dedicated circuits. However, for this application, in more cases, software program implementation is a better implementation method. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a readable storage medium, such as a floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disc of a computer, and includes several instructions for causing a computer device to execute the methods described in various embodiments of this application.

[0130] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product.

[0131] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, they wholly or partly generate a process or function as described in this application. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a Solid State Disk (SSD)), etc.

[0132] It should be understood that the term "one embodiment" or "an embodiment" mentioned throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, the appearances of "in one embodiment" or "in an embodiment" throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of this application, the order numbers of the above processes do not indicate the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of this application.

[0133] In addition, the terms "system" and "network" are often used interchangeably in this document. The term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after.

[0134] It should be understood that in this application, "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A. B can also be determined according to A and / or other information.

[0135] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this document can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0136] In summary, the above description is only a preferred embodiment of the technical solution of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A mine exploration method based on the three-pole advanced detection of direct current resistivity method, characterized in that, The method is applied to a detection optimization analysis system, which is communicatively connected to a power supply electrode and a measurement electrode. The method includes: Obtain first detection position information and construct a first coordinate system according to the first detection position information; According to the first coordinate system, obtain first distribution position information of the power supply electrode; Obtain a first measurement electrode distance of the measurement electrode, and perform data measurement along a first predetermined trajectory based on the first measurement electrode distance to obtain a first data measurement result; Input the first distribution position information, the first measurement electrode distance, and the first data measurement result into an anomaly analysis model to obtain a first output result; Obtain a first set of abnormal positions according to the first output result, and match a second measurement electrode distance according to the first set of abnormal positions; Obtain a second data measurement result through the measurement electrode based on the second measurement electrode distance; Perform abnormal detection of mine exploration according to the second data measurement result; The method further includes: constructing a set of abnormal features; obtaining a set of abnormal signals corresponding to the set of abnormal features through big data, where the set of abnormal signals includes corresponding sets of abnormal signals under multiple measurement precisions; constructing the anomaly analysis model based on the set of abnormal signals.

2. The method according to claim 1, wherein When the output accuracy rate of the anomaly analysis model meets a first preset threshold, end the construction of the anomaly analysis model; Perform abnormal detection of the first data measurement result and the second data measurement result according to the constructed anomaly analysis model.

3. The method according to claim 2, wherein The method includes: Obtain abnormal identification information of the first set of abnormal positions according to the first output result; Perform screening on the areas in the first set of abnormal positions that need to have their associated positions determined according to the abnormal identification information to obtain a first screening result; Obtain a first set of associated positions according to the first screening result; Obtain the second data measurement result through the first set of associated positions and the first set of abnormal positions based on the second measurement electrode distance.

4. The method according to claim 3, wherein The method includes: Obtain associated data of abnormal data mutation identification; Perform qualitative identification of the abnormal analysis of the second data measurement result according to the associated data of abnormal data mutation identification to obtain a qualitative analysis result of mine exploration.

5. The method according to claim 1, characterized in that, The method includes: Obtain a first set of matching measurement electrode distances according to the first measurement electrode distance; Obtain a first predetermined measurement accuracy parameter; Obtain a first screening parameter according to the first predetermined measurement accuracy parameter and the first set of abnormal positions; Perform screening on the first set of matching measurement electrode distances according to the first screening parameter to obtain the second measurement electrode distance.

6. The method according to claim 1, characterized in that, The method includes: Obtain roadway slope parameter information; Perform abnormal position compensation on the second data measurement result based on the roadway slope parameter information to obtain a first position compensation result; Obtain a mine exploration abnormal detection result according to the first position compensation result.

7. The method according to claim 1, wherein The method includes: Obtain a first data acquisition quality evaluation parameter according to the data acquisition process; Obtain interference signal information of the data acquisition process; Obtain a second data acquisition quality evaluation parameter according to the interference signal information; Obtain the credibility identification result of mine exploration anomaly detection according to the first data acquisition quality evaluation parameter and the second data acquisition quality evaluation parameter.

8. A mine exploration system based on the three-pole advanced detection of direct current resistivity method, characterized in that, The system includes: A first acquisition unit, which is used to obtain first detection position information and construct a first coordinate system according to the first detection position information; A second acquisition unit, which is used to obtain the first distribution position information of the power supply electrode according to the first coordinate system; A third acquisition unit, which is used to obtain the first measurement electrode distance of the measurement electrode, perform data measurement through a first predetermined trajectory based on the first measurement electrode distance, and obtain a first data measurement result; A first input unit, which is used to input the first distribution position information, the first measurement electrode distance, and the first data measurement result into an anomaly analysis model to obtain a first output result. It also includes constructing an anomaly feature set; obtaining an anomaly signal set corresponding to the anomaly feature set through big data, where the anomaly signal set includes corresponding anomaly signal sets under multiple measurement precisions; constructing the anomaly analysis model based on the anomaly signal set; A fourth acquisition unit, which is used to obtain a first anomaly position set according to the first output result and match a second measurement electrode distance according to the first anomaly position set; A fifth acquisition unit, which is used to obtain a second data measurement result through the measurement electrode based on the second measurement electrode distance; A first detection unit, which is used to perform mine exploration anomaly detection according to the second data measurement result.

9. An electronic device, characterized in that, It includes a processor and a memory; the memory is used for storage; the processor is used to execute the method according to any one of claims 1 to 7 by calling.

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