Exploration operation path intelligent planning method combined with geological risk assessment

Abstract

This invention relates to the field of exploration operation path planning technology, specifically to an intelligent exploration operation path planning method combined with geological risk assessment. The method includes: collecting environmental information of each task point in the exploration operation; calculating the geological safety characteristic value of each task point based on the environmental information; determining whether the task point meets the path planning conditions based on the geological safety characteristic value; if so, recording the task point as a node to be planned, and forming a set of all nodes to be planned; determining the start and end points of the planned path from the set of nodes to be planned based on the start and end points of the exploration operation; and determining the exploration operation path based on the start and end points of the planned path and the path planning algorithm, thereby improving the efficiency and safety assurance capabilities of exploration operation path planning.

Description

Technical Field

[0001] This invention relates to the field of exploration operation path planning, and more specifically to an intelligent exploration operation path planning method that incorporates geological risk assessment. Background Technology

[0002] In fields such as geological exploration, mineral development, and engineering construction, field exploration is a crucial step in obtaining firsthand geological data. The rational planning of exploration routes is essential for ensuring the safety of personnel and equipment, improving exploration efficiency, and reducing operating costs.

[0003] Traditional exploration route planning methods often focus on geometric topology and traffic efficiency, typically optimizing for shortest routes, least time, or lowest energy consumption. These methods often rely on digital elevation models or simple topographic slope analysis, failing to adequately consider the complex and dynamically changing geomechanical environment within the work area, such as slope stability and rock mass stress state. Therefore, the planned routes may traverse potentially high-risk geological areas, such as landslide zones and collapse hazard zones, posing serious safety threats to exploration operations.

[0004] Therefore, there is an urgent need to solve the above problems by combining intelligent planning methods for exploration operation paths with geological risk assessment. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent planning method for exploration operation paths that combines geological risk assessment: based on real-time geological monitoring data, it aims to dynamically and accurately assess the safety risks of each potential operation point, and on this basis, automatically generate an optimized operation path that is both efficient and safe and reliable, thereby improving the efficiency of exploration operation path planning and safety assurance capabilities.

[0006] Intelligent planning methods for exploration operation paths combined with geological risk assessment include:

[0007] Collect environmental information at each task point during exploration operations, and calculate the geological safety characteristic value of each task point based on the environmental information;

[0008] Based on the geological safety characteristic value, determine whether the task point meets the path planning conditions. If so, record the task point as a path node to be planned, and form a set of all path nodes to be planned.

[0009] Based on the starting and ending points of the exploration operation, the starting and ending points of the planned path are determined from the set of nodes to be planned, and the exploration operation path is determined based on the starting and ending points of the planned path and the path planning algorithm.

[0010] Furthermore, the environmental information includes slope displacement data at the locations of each task point.

[0011] Furthermore, the calculation of geological safety characteristic values ​​for each task point based on environmental information specifically includes the following process:

[0012] Obtain slope displacement data at the location of each task point based on environmental information;

[0013] The slope displacement data is analyzed by Bayesian inversion to obtain posterior samples of random field model parameters. Reliability analysis is performed based on the posterior samples to calculate the posterior failure probability of slope stability reliability. The slope stability reliability of each task point is obtained based on the posterior failure probability.

[0014] The stability reliability of the slope is recorded as the geological safety characteristic value.

[0015] Furthermore, the slope displacement data is analyzed using Bayesian inversion to obtain posterior samples of the random field model parameters. Based on the posterior samples, reliability analysis is performed to calculate the posterior failure probability of the slope stability reliability. The slope stability reliability at each task point is then obtained based on the posterior failure probability. The specific process includes the following steps:

[0016] make This is a set of slope displacement data corresponding to different measurement times at the location of the task point, where... To measure the number of time points, Indicates the task point is at The slope displacement data at the measured location is used to update the random variable using Bayesian theory. : ;

[0017] in, This represents the set of slope displacement data. Provided about The posterior probability density function; To be independent The scaling factor is set to 0.8; Representing the prior probability density function for quantization Prior information; Let be the likelihood function, representing the given... Occasionally The possibility;

[0018] ;in, For measurement error;

[0019] Perform reliability analysis to calculate the posterior failure probability of slope stability reliability. :

[0020] ;

[0021] Establish an inverse proportional function between the posterior failure probability and the slope stability reliability: ;in, This indicates the stability and reliability of the slope.

[0022] Furthermore, determining whether a task point meets the path planning conditions based on geological safety characteristic values ​​specifically includes the following process:

[0023] Load the geological safety feature value threshold, and determine whether the geological safety feature value exceeds the geological safety feature value threshold. If it does, determine that the task point meets the path planning conditions; otherwise, determine that the task point does not meet the path planning conditions.

[0024] Furthermore, determining the start and end points of the planned path from the set of nodes to be planned based on the start and end points of the exploration operation specifically includes the following process:

[0025] In the set of nodes to be planned, determine the node that is closest to the starting point of the exploration operation and mark it as the starting point of the planned path. Also determine the node that is closest to the ending point of the exploration operation and mark it as the ending point of the planned path.

[0026] Furthermore, determining the exploration operation path based on the starting point, ending point, and path planning algorithm of the planned path specifically includes the following process:

[0027] Step 1: Set the corresponding initial pheromone values ​​for the path nodes to be planned in the set of path nodes to be planned according to the first association formula;

[0028] Step 2: Calculate the distance between each node in the set of nodes to be planned and the starting point of the planned path, and sort them in ascending order of distance to obtain the arrangement order of the nodes to be planned.

[0029] Step 3, each The nodes of the path to be planned are initially combined according to the order of arrangement to obtain several preliminary combination groups;

[0030] Step four: Calculate the initial pheromone value difference between the first and second path nodes to be planned in each preliminary combination group, and determine whether the difference exceeds a preset difference threshold. If not, then form a reference vector from the first and second path nodes to be planned in each preliminary combination group. The remaining first group in each initial combination The node to be planned and the first A vector composed of nodes of the path to be planned ,in Calculate separately and Angle between Among them, angle The calculation formula is as follows: ;in, Represents the reference vector The modulus, Representing vectors The modulus;

[0031] Step 5, With threshold angle Compare, if the first One path node to be planned Angle greater than the threshold Then it will be arranged in the th order. The path nodes to be planned before each point are subdivided into groups and arranged in order. Repeat steps three and four to subdivide the initial combination group for each planned path node in front of the point, and connect the planned path nodes in each subdivided group to form the exploration operation path.

[0032] Furthermore, setting the corresponding initial pheromone values ​​for the path nodes to be planned in the set of path nodes to be planned according to the first association formula specifically includes the following process:

[0033] ;in, Indicates the node of the path to be planned Initial pheromone value, Indicates the starting point of the planned path The Euclidean distance between the destination and the planned route endpoint. Indicates the starting point of the planned path and nodes of the path to be planned The Euclidean distance between them Indicates the node of the path to be planned The Euclidean distance between the destination and the planned route endpoint.

[0034] Compared to existing solutions, the beneficial effects achieved by this invention are:

[0035] This invention collects environmental information from various task points during exploration operations, calculates geological safety characteristic values ​​for each task point based on the environmental information, determines whether the task point meets the path planning conditions based on the geological safety characteristic values, and if so, records the task point as a node to be planned for the path, and forms a set of all nodes to be planned for the path. Based on the starting and ending positions in the exploration operation, the starting and ending points of the planned path are determined from the set of nodes to be planned for the path, and the exploration operation path is determined based on the starting and ending points of the planned path and the path planning algorithm. This invention can exclude high-risk task points in exploration operations and, by combining pheromone initial value setting, node sorting, and vector angle judgment, ensures the global guidance of the path. By subdividing and reorganizing the path through vector angle, the planned path can better adapt to complex local terrain changes, avoid unreasonable sharp turns, and generate a smooth path that is both safe and efficient and meets actual traffic needs, thereby improving the intelligence level and safety assurance capability of exploration operations. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0037] Figure 1 This is a flowchart of the first intelligent planning method for exploration operation paths combined with geological risk assessment according to an embodiment of the present invention.

[0038] Figure 2 This is a flowchart of the second intelligent planning method for exploration operation paths combined with geological risk assessment, according to an embodiment of the present invention.

[0039] Figure 3 This is a structural block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more exemplary embodiments. Numerous specific details are provided in the following description to give a full understanding of exemplary embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced with one or more of the specific details omitted, or other methods, components, steps, etc., can be employed. In other instances, well-known structures, methods, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0042] This embodiment provides an intelligent planning method for exploration operation paths that incorporates geological risk assessment. Figure 1 This is a flowchart of the first intelligent exploration operation path planning method combined with geological risk assessment according to an embodiment of the present invention, as shown below. Figure 1 As shown, the method includes the following steps:

[0043] Step S101: Collect environmental information of each task point in the exploration operation, and calculate the geological safety characteristic value of each task point based on the environmental information;

[0044] The environmental information includes slope displacement data at each task point. The inclinometer uses a built-in accelerometer or gravity sensor to measure the change in the tilt angle of the guide pipe (usually buried in the slope borehole). When the slope shifts, the guide pipe tilts accordingly. By measuring this tilt angle and combining it with the segment length, the inclinometer can calculate the horizontal displacement value of each segment.

[0045] Step S102: Determine whether the task point meets the path planning conditions based on the geological safety characteristic value. If so, record the task point as a path node to be planned, and form a set of path nodes to be planned from all the path nodes to be planned.

[0046] It is worth noting that if a task point does not meet the path planning conditions, it will not be included in the path planning considerations for exploration operations.

[0047] Step S103: Based on the starting and ending positions in the exploration operation, determine the starting and ending points of the planned path from the set of nodes to be planned, and determine the exploration operation path based on the starting and ending points of the planned path and the path planning algorithm.

[0048] In summary, this invention collects environmental information from various task points during exploration operations, calculates geological safety characteristic values ​​for each task point based on the environmental information, determines whether the task point meets the path planning conditions based on the geological safety characteristic values, and if so, records the task point as a node to be planned for the path, and forms a set of all nodes to be planned for the path. Based on the starting and ending positions in the exploration operation, the starting and ending points of the planned path are determined from the set of nodes to be planned for the path, and the exploration operation path is determined based on the starting and ending points of the planned path and the path planning algorithm. This invention can exclude high-risk task points in exploration operations and, by combining pheromone initial value setting, node sorting, and vector angle judgment, ensures the global guidance of the path; thus improving the efficiency and safety assurance capabilities of path planning in exploration operations.

[0049] In some embodiments, Figure 2 This is a flowchart of the second intelligent planning method for exploration operation paths combined with geological risk assessment according to an embodiment of the present invention, as shown below. Figure 2 As shown, the calculation of geological safety characteristic values ​​for each task point based on environmental information specifically includes the following process:

[0050] Step S201: Obtain slope displacement data at the location of each task point based on environmental information;

[0051] Step S202: Obtain posterior samples of random field model parameters by performing Bayesian inversion analysis on slope displacement data, perform reliability analysis based on posterior samples to calculate the posterior failure probability of slope stability reliability, and obtain the slope stability reliability of each task point based on the posterior failure probability.

[0052] Specifically, let This is a set of slope displacement data corresponding to different measurement times at the location of the task point, where... To measure the number of time points, Indicates the task point is at The slope displacement data at the measured location is used to update the random variable using Bayesian theory. : ;

[0053] in, This represents the set of slope displacement data. Provided information about random variables The posterior probability density function; To be independent The scaling factor is set to 0.8; Representing the prior probability density function for quantization Prior information; Let be the likelihood function, representing the given... Occasionally The possibility;

[0054] Among these, core samples and soil samples collected in the current exploration area are subjected to laboratory tests (such as rock mass direct shear test, triaxial compression test to measure cohesion / internal friction angle, and pore water pressure meter to measure pore water pressure) to obtain data. The specific test values; statistical analysis of multiple sets of experimental results to determine... The range of values, central tendency (mean), and dispersion (standard deviation) are then used to construct... —For example, if experimental data show If it follows a normal distribution, then The normal probability density function is used, and its mean and variance are directly determined from the experimental statistical results.

[0055] ;in, The measurement error is determined by the inclinometer. ,in, The measurement deviation of an inclinometer varies depending on the type of inclinometer. For example, the error range of a resistance inclinometer is ±5 to 10 mm. It's worth noting that the calculations described above have been dimensionally normalized before being applied to the formulas.

[0056] Perform reliability analysis to calculate the posterior failure probability of slope stability reliability. :

[0057] ;

[0058] Establish an inverse proportional function between the posterior failure probability and the slope stability reliability: ;in, This indicates the stability and reliability of the slope.

[0059] Step S203: Record the slope stability reliability as the geological safety characteristic value.

[0060] It is worth noting that the introduction of the Bayesian inversion analysis algorithm transforms slope stability risk into quantifiable and comparable geological safety characteristic values. Compared to the traditional qualitative classification of "high / medium / low risk," this scheme significantly improves the accuracy of risk assessment, effectively avoids misjudgments caused by ambiguous qualitative judgments, and ensures that the geological safety characteristic values ​​truly reflect the actual risk level of the task site.

[0061] In some embodiments, determining whether a task point meets the path planning conditions based on geological safety characteristic values ​​specifically includes the following process:

[0062] A geological safety feature value threshold is loaded, and it is determined whether the geological safety feature value exceeds the threshold. If it does, the task point is deemed to meet the path planning conditions; otherwise, it is deemed not to meet the path planning conditions. It is worth noting that the geological safety feature value threshold setting process involves collecting historical case data, extensively collecting historical slope engineering cases with similar geological conditions to the current exploration area, including both successful and failed cases. From these cases, the monitoring displacement data under steady-state conditions, the posterior failure probability obtained through inversion calculation, and the corresponding stability reliability are extracted. The value is the final state of each historical case (e.g., "stable", "critically unstable", "failed") and its calculated stability reliability. The values ​​are correlated to form a database. For cases in a "stable" state, their... Distribution of values ​​(e.g., minimum, average, 5th percentile). For cases in a "critically unstable" or "failed" state, calculate their... The distribution of values ​​(e.g., maximum, average, 95th quantile) determines the threshold baseline range: Based on the above statistical analysis, a threshold baseline range [bpmin, bpmax] is determined. The geological safety characteristic value threshold should be greater than that of the "critical instability" case. Set an upper limit for the value (e.g., the 95th percentile) and leave an appropriate safety margin; at the same time, refer to the "stable" state case. Lower bounds (such as the 5th percentile) are used as auxiliary verification.

[0063] In some embodiments, determining the start and end points of a planned path from the set of nodes to be planned based on the start and end points of the exploration operation specifically includes the following process:

[0064] In the set of nodes to be planned, determine the node that is closest to the starting point of the exploration operation and mark it as the starting point of the planned path. Also determine the node that is closest to the ending point of the exploration operation and mark it as the ending point of the planned path.

[0065] In some embodiments, determining the exploration operation path based on the starting point, ending point, and path planning algorithm of the planned path specifically includes the following process:

[0066] Step 1: Set the corresponding initial pheromone values ​​for the path nodes to be planned in the set of path nodes to be planned according to the first association formula;

[0067] ;in, Indicates the node of the path to be planned Initial pheromone value, Indicates the starting point of the planned path The Euclidean distance between the destination and the planned route endpoint. Indicates the starting point of the planned path and nodes of the path to be planned The Euclidean distance between them Indicates the node of the path to be planned The Euclidean distance between the destination and the planned route endpoint.

[0068] Step 2: Calculate the distance between each node in the set of nodes to be planned and the starting point of the planned path, and sort them in ascending order of distance to obtain the arrangement order of the nodes to be planned.

[0069] Step 3, each The nodes of the path to be planned are initially combined according to the order of arrangement to obtain several preliminary combination groups;

[0070] It is worth noting that, The number of nodes in the planned path is taken into account; if the number of nodes in the planned path is greater than or equal to 20, then... If the number of nodes in the path to be planned is less than 20, then the value is 5. Take 4.

[0071] Step four: Calculate the initial pheromone value difference between the first and second path nodes to be planned in each preliminary combination group, and determine whether the difference exceeds a preset difference threshold. If not, then form a reference vector from the first and second path nodes to be planned in each preliminary combination group. The remaining first group in each initial combination The node to be planned and the first A vector composed of nodes of the path to be planned ,in Calculate separately and Angle between Among them, angle The calculation formula is as follows: ;in, Represents the reference vector The modulus, Representing vectors The modulus;

[0072] Step 5, With threshold angle Compare, if the first One path node to be planned Angle greater than the threshold Then it will be arranged in the th order. The path nodes to be planned before each point are subdivided into groups and arranged in order. Repeat steps three and four to subdivide the initial combination group for each planned path node in front of the point, and connect the planned path nodes in each subdivided group to form the exploration operation path.

[0073] Among them, the threshold angle The settings are as follows: Determine the minimum turning radius of the equipment with the worst turning performance (such as large drilling rig vehicles or heavy off-road vehicles) in this exploration operation. This parameter is provided by the equipment manufacturer or obtained through field testing; define the effective path width: determine the effective passage width W of the planned path, which is usually the width of the equipment plus a safety margin of 0.5, and discretize the continuous path into a series of line segments (i.e., vectors connecting the nodes of the path to be planned). Based on the minimum turning radius and path width, calculate the maximum angle of change in direction (i.e., the critical turning angle) that the equipment can withstand when traveling on two adjacent line segments. A commonly used and conservative geometric model is to approximate the path with a radius of... The arc's chord length is related to the spacing between path nodes. A more direct calculation formula is: Where L is the average Euclidean distance between any two adjacent nodes in the above path planning algorithm, which is obtained by calculating the average of the Euclidean distances between all pairs of adjacent nodes of the path to be planned.

[0074] The above formulas are all dimensionless calculations, and the preset parameters in the formulas should be set by those skilled in the art according to the actual situation.

[0075] In some embodiments, Figure 3 This is a structural block diagram of an electronic device according to an embodiment of the present invention, such as... Figure 3 As shown, the electronic device includes a memory 301 and a processor 302. The memory 301 stores a computer program. When the computer program is executed by the processor 302, the processor 302 executes an intelligent exploration operation path planning method that combines geological risk assessment as described in any of the above embodiments.

[0076] The memory 301 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. The memory 301 has storage space 303 for program code 313 for performing any of the method steps described above. For example, the storage space 303 for program code may include individual program codes 313 for implementing the various steps in the methods described above. This program code can be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, CDs, memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When run by a computing processing device, this code causes the computing processing device to perform the various steps in the methods described above. This program code can be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, CDs, memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When this code is run by a computing device, it causes the device to execute the steps of the intelligent planning method for exploration operation paths that incorporates geological risk assessment, as described above.

[0077] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0078] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0079] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0080] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0081] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0082] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An intelligent planning method for exploration operation paths combined with geological risk assessment, characterized in that, The methods include: Collect environmental information at each task point during exploration operations, and calculate the geological safety characteristic value of each task point based on the environmental information; Based on the geological safety characteristic value, determine whether the task point meets the path planning conditions. If so, record the task point as a path node to be planned, and form a set of all path nodes to be planned. Based on the starting and ending points of the exploration operation, the starting and ending points of the planned path are determined from the set of nodes to be planned, and the exploration operation path is determined based on the starting and ending points of the planned path and the path planning algorithm.

2. The intelligent exploration operation path planning method combined with geological risk assessment as described in claim 1, characterized in that, Environmental information includes slope displacement data at the locations of each task point.

3. The intelligent planning method for exploration operation paths combined with geological risk assessment as described in claim 1, characterized in that, Specific calculations of geological safety characteristic values ​​for each task point based on environmental information. Includes the following processes: Obtain slope displacement data at the location of each task point based on environmental information; The slope displacement data is analyzed by Bayesian inversion to obtain posterior samples of random field model parameters. Reliability analysis is performed based on the posterior samples to calculate the posterior failure probability of slope stability reliability. The slope stability reliability of each task point is obtained based on the posterior failure probability. The stability reliability of the slope is recorded as the geological safety characteristic value.

4. The intelligent planning method for exploration operation paths combined with geological risk assessment as described in claim 1, characterized in that, Slope displacement data are analyzed using Bayesian inversion to obtain posterior samples of random field model parameters. Reliability analysis is then performed based on these posterior samples to calculate the posterior failure probability of slope stability reliability. Finally, the specific slope stability reliability at each task point is obtained based on the posterior failure probability. Includes the following processes: make This is a set of slope displacement data corresponding to different measurement times at the location of the task point, where... To measure the number of time points, Indicates the task point is at The slope displacement data at the measured location is used to update the random variable using Bayesian theory. : ; in, This represents the set of slope displacement data. Provided about The posterior probability density function; To be independent of The scaling factor is set to 0.8; Representing the prior probability density function for quantization Prior information; Let be the likelihood function, representing the given... Occasionally The possibility; ;in, For measurement error; Perform reliability analysis to calculate the posterior failure probability of slope stability reliability. : ； Establish an inverse proportional function between the posterior failure probability and the slope stability reliability: ;in, This indicates the stability and reliability of the slope.

5. The intelligent planning method for exploration operation paths combined with geological risk assessment as described in claim 1, characterized in that, Based on geological safety characteristic values, determine whether the task point meets the path planning conditions. Includes the following processes: Load the geological safety feature value threshold, and determine whether the geological safety feature value exceeds the geological safety feature value threshold. If it does, determine that the task point meets the path planning conditions; otherwise, determine that the task point does not meet the path planning conditions.

6. The intelligent exploration operation path planning method combined with geological risk assessment according to claim 1, characterized in that, Determining the start and end points of a planned path from the set of nodes to be planned, based on the start and end points of the exploration operation, specifically includes the following process: In the set of nodes to be planned, determine the node that is closest to the starting point of the exploration operation and mark it as the starting point of the planned path. Also determine the node that is closest to the ending point of the exploration operation and mark it as the ending point of the planned path.

7. The intelligent planning method for exploration operation paths combined with geological risk assessment as described in claim 1, characterized in that, Determining the exploration operation path based on the starting point, ending point, and path planning algorithm of the planned path specifically includes the following process: Step 1: Set the corresponding initial pheromone values ​​for the path nodes to be planned in the set of path nodes to be planned according to the first association formula; Step 2: Calculate the distance between each node in the set of nodes to be planned and the starting point of the planned path, and sort them in ascending order of distance to obtain the arrangement order of the nodes to be planned. Step 3, each The nodes of the path to be planned are initially combined according to the order of arrangement to obtain several preliminary combination groups; Step four: Calculate the initial pheromone value difference between the first and second path nodes to be planned in each preliminary combination group, and determine whether the difference exceeds a preset difference threshold. If not, then form a reference vector from the first and second path nodes to be planned in each preliminary combination group. The remaining number in each initial combination group The node to be planned and the first A vector composed of nodes of the path to be planned ,in Calculate separately and Angle between Among them, angle The calculation formula is as follows: ;in, Represents the reference vector The modulus, Representing vectors The modulus; Step 5, With threshold angle Compare, if the first One path node to be planned Angle greater than the threshold Then it will be arranged in the th order. The path nodes to be planned before each point are subdivided into groups and arranged in order. Repeat steps three and four to subdivide the initial combination group for each planned path node in front of the point, and connect the planned path nodes in each subdivided group to form the exploration operation path.

8. The intelligent planning method for exploration operation paths combined with geological risk assessment as described in claim 7, characterized in that, Setting the initial pheromone values ​​for the nodes in the set of nodes to be planned according to the first association formula specifically includes the following process: ;in, Indicates the node of the path to be planned Initial pheromone value, Indicates the starting point of the planned path The Euclidean distance between the destination and the planned route endpoint. Indicates the starting point of the planned path and nodes of the path to be planned The Euclidean distance between them Indicates the node of the path to be planned The Euclidean distance between the destination and the planned route endpoint.

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