Rock mass mechanical parameter acquisition method and system, and electronic device and storage medium

Abstract

A rock mass mechanical parameter acquisition method, comprising: determining n actually measured mechanical parameters of a target mine slope, and constructing a target vector corresponding to the target mine slope; acquiring a plurality of reference vectors; on the basis of the variance of dimensions corresponding to the n actually measured mechanical parameters, partitioning all the reference vectors, and on the basis of partitioning results, constructing a topological relationship tree corresponding to all the reference vectors, and setting partitioning dimension flags for all the reference vectors; on the basis of the partitioning dimension flags, querying the topological relationship tree for k reference vectors closest to the target vector, and setting as alternative mechanical parameter vectors the k reference vectors closest to the target vector; and performing weighted calculation on rock mass internal friction angles and rock mass cohesive forces of all the alternative mechanical parameter vectors, so as to obtain a rock mass internal friction angle and a rock mass cohesive force of the target mine slope. The method can improve the acquisition efficiency and reliability of mechanical parameters. Further provided are a rock mass mechanical parameter acquisition system, an electronic device and a storage medium.

Description

A method, system, electronic device and storage medium for obtaining rock mass mechanical parameters Technical Field

[0001] This application relates to the field of mining technology, and in particular to a method, system, electronic device and storage medium for obtaining rock mass mechanical parameters. Background Technology

[0002] With the continued large-scale mining of open-pit metal mines, steep slopes have formed in the mining areas, reaching hundreds of meters and even exceeding one kilometer in height. Mining under such steep slopes carries a constant risk of landslides. The steep slopes in the mining industry differ from those in other industries primarily because their formation is intertwined with mining operations, and their spatial location is determined by mining activities, making it difficult to choose freely. Therefore, mining operations must be conducted under high-risk conditions. As mining operations continue, quickly and accurately assessing slope stability is crucial to ensuring the safety of mining operations.

[0003] Rock mass shear strength parameters, such as internal friction angle and cohesion, are important for analyzing slope stability. In related technologies, these parameters are primarily obtained through indoor rock mechanics tests. However, obtaining these parameters requires extensive indoor testing and field investigations of weak points, followed by numerous calculations based on these findings. This process is time-consuming and has low reliability.

[0004] Therefore, how to improve the efficiency and reliability of obtaining the internal friction angle and cohesion of rock mass is a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0005] The purpose of this application is to provide a method, system, electronic device and storage medium for obtaining rock mass mechanical parameters, which can improve the efficiency and reliability of obtaining the internal friction angle and cohesion of rock mass.

[0006] To address the aforementioned technical problems, this application provides a method for obtaining rock mass mechanical parameters, which includes:

[0007] Determine n measured mechanical parameters of the target mine slope and construct the target vector corresponding to the target mine slope; wherein, the dimensions of the target vector include the internal friction angle of the rock mass, the cohesion of the rock mass, the sectional dimension marker, and the n measured mechanical parameters;

[0008] Multiple reference vectors are obtained from the database; wherein the reference vectors have the same dimension as the target vector.

[0009] All reference vectors are segmented based on the variance of the dimensions corresponding to n measured mechanical parameters. A topological relationship tree corresponding to all reference vectors is constructed based on the segmentation results, and a segmentation dimension flag is set for all reference vectors based on the segmentation results. The topological relationship tree is a binary tree, and the segmentation dimension flag is used to describe the segmentation dimension of the nodes in the topological relationship tree.

[0010] Based on the segmentation dimension flag, query the k reference vectors that are closest to the target vector in the topological relationship tree, and set the k reference vectors closest to the target vector as candidate mechanical parameter vectors;

[0011] The internal friction angle and cohesion of the rock mass are weighted and calculated for all the candidate mechanical parameter vectors to obtain the internal friction angle and cohesion of the rock mass of the target mine slope.

[0012] Optionally, all the reference vectors are segmented based on the variance of the dimensions corresponding to the n measured mechanical parameters. A topological tree corresponding to all the reference vectors is constructed based on the segmentation results. The segmentation dimension flags of all the reference vectors are set according to the segmentation results, including:

[0013] Construct a current data set containing all the aforementioned reference vectors;

[0014] Calculate the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current dataset, and select the dimension corresponding to the largest variance as the current split dimension;

[0015] Sort all the reference vectors in ascending order according to the current splitting dimension, select the middle reference vector in the sorting result as the splitting node of the current data set, and set the splitting dimension flag of the splitting node to the dimension number of the current splitting dimension.

[0016] The left subtree set of the splitting node is constructed based on the reference vector before the intermediate reference vector in the sorting result, and the right subtree set of the splitting node is constructed based on the reference vector after the intermediate reference vector in the sorting result.

[0017] If the left subtree set is not empty, then the left subtree set is used as the new current data set, and the process re-enters the step of calculating the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current data set;

[0018] If the right subtree set is not empty, then the right subtree set is used as the new current data set, and the process re-enters the step of calculating the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current data set;

[0019] The topology tree is generated based on the hierarchical relationship between all the split nodes.

[0020] Optionally, querying the k nearest reference vectors to the target vector in the topological relationship tree based on the segmentation dimension flag includes:

[0021] Set the root node of the topological relationship tree as the current node;

[0022] Add a preset identifier to the current node;

[0023] Determine if there are empty slots in the ordered list; wherein, the maximum number of nodes stored in the candidate node column is k; k < n, and the candidate nodes in the ordered list are sorted according to vector distance, wherein the vector distance is the distance between the reference vector corresponding to the candidate node and the target vector;

[0024] If there is an empty slot, add the current node to the ordered list;

[0025] If there are no empty slots, determine whether the distance between the reference vector corresponding to the current node and the target vector is less than the critical distance; wherein, the critical distance is the maximum distance between the reference vector corresponding to the candidate node in the ordered list and the target vector.

[0026] If the distance is less than the critical distance, the candidate node with the largest distance to the target vector is removed from the ordered list, and the current node is added to the ordered list.

[0027] Determine if the current node has child nodes;

[0028] If child nodes exist, select a new current node from the child nodes of the current node and proceed to the step of adding a preset identifier to the current node;

[0029] If no child node exists, then recursively query the parent node that meets the preset condition from the current node in the topology tree; wherein, the preset condition is that there is a child node that has not been added with the preset identifier;

[0030] Determine whether the absolute value of the difference between the value of the i-th dimension of the parent node that meets the preset conditions and the value of the target vector in the i-th dimension is less than the critical distance; if yes, set the child node of the parent node that meets the preset conditions without the preset label as the new current node, and proceed to the step of adding the preset label to the current node; if no, set the candidate nodes in the ordered list as the k reference vectors closest to the target vector; wherein, the value of the split dimension label of the parent node that meets the preset conditions is i.

[0031] Optionally, if the current node has left-branch child nodes and left-branch child nodes, then a new current node is selected from the child nodes of the current node, including:

[0032] The value of the j-th dimension of the current node is used as the reference value based on the value j of the segmentation dimension flag;

[0033] Determine whether the value of the target vector in the j-th dimension is less than the reference value;

[0034] If it is less than the reference value, then the left branch child node of the current node is set as the new current node, and the step of adding a preset identifier to the current node is entered;

[0035] If the value is greater than or equal to the reference value, then the right branch child node of the current node is set as the new current node, and the process proceeds to the step of adding a preset identifier to the current node.

[0036] Optionally, if the current node only has left-branch child nodes, then a new current node is selected from the child nodes of the current node, including:

[0037] The value of the j-th dimension of the current node is used as the reference value based on the value j of the segmentation dimension flag;

[0038] Determine whether the value of the target vector in the j-th dimension is less than the reference value;

[0039] If it is less than the reference value, then the left branch child node of the current node is set as the new current node, and the step of adding a preset identifier to the current node is entered;

[0040] If the value is greater than or equal to the reference value, then determine whether the absolute value of the difference between the value of the j-th dimension of the current node and the value of the target vector in the j-th dimension is less than the critical distance; if yes, then set the right branch child node of the current node as the new current node and proceed to the step of adding a preset identifier to the current node; if no, then proceed to the step of recursively querying the parent node that meets the preset conditions in the topological relationship tree.

[0041] Optionally, if the current node only has right-branch child nodes, then a new current node is selected from the child nodes of the current node, including:

[0042] The value of the j-th dimension of the current node is used as the reference value based on the value j of the segmentation dimension flag;

[0043] Determine whether the value of the target vector in the j-th dimension is less than the reference value;

[0044] If the value is greater than or equal to the reference value, then the right branch child node of the current node is set as the new current node, and the step of adding a preset identifier to the current node is initiated.

[0045] If the value is less than the reference value, then determine whether the absolute value of the difference between the value of the j-th dimension of the current node and the value of the target vector in the j-th dimension is less than the critical distance; if yes, then set the left branch child node of the current node as the new current node and proceed to the step of adding a preset identifier to the current node; if no, then proceed to the step of recursively querying the parent node that meets the preset conditions in the topological relationship tree.

[0046] Optional, also includes:

[0047] If the current node has no child nodes and the result of recursively querying the parent node that meets the preset conditions from the current node is empty, then the query is considered complete, and the candidate nodes in the ordered list are set as the k reference vectors closest to the target vector.

[0048] Optionally, the internal friction angle and cohesion of the rock mass are weighted and calculated for all the candidate mechanical parameter vectors to obtain the internal friction angle and cohesion of the rock mass of the target mine slope, including:

[0049] The reciprocal of the distance between each candidate mechanical parameter vector and the target vector is set as the weighting influence factor;

[0050] The weight value of each candidate mechanical parameter vector is obtained by calculating the ratio of the weight influence factor of each candidate mechanical parameter vector to the sum of the weight influence factors of all candidate mechanical parameter vectors.

[0051] The internal friction angle of the rock mass of the target mine slope is obtained by weighting the rock mass friction angle of all the candidate mechanical parameter vectors according to the weight values.

[0052] The rock mass cohesion of the target mine slope is obtained by weighting the rock mass cohesion of all the candidate mechanical parameter vectors according to the weight values.

[0053] This application also provides a rock mass mechanics parameter acquisition system, the system comprising:

[0054] A vector construction module is used to determine n measured mechanical parameters of a target mine slope and construct a target vector corresponding to the target mine slope; wherein, the dimensions of the target vector include the internal friction angle of the rock mass, the cohesion of the rock mass, the sectional dimension marker, and the n measured mechanical parameters;

[0055] A vector acquisition module is used to acquire multiple reference vectors from a database; wherein the reference vectors have the same dimension as the target vector.

[0056] The topology tree construction module is used to segment all the reference vectors based on the variance of the dimensions corresponding to n measured mechanical parameters, construct a topology tree corresponding to all the reference vectors according to the segmentation results, and set the segmentation dimension flag of all the reference vectors according to the segmentation results; wherein, the topology tree is a binary tree, and the segmentation dimension flag is used to describe the segmentation dimension of the nodes in the topology tree;

[0057] The query module is used to query the k reference vectors closest to the target vector in the topological relationship tree based on the segmentation dimension flag, and set the k reference vectors closest to the target vector as candidate mechanical parameter vectors;

[0058] The weighted calculation module is used to perform weighted calculations on the internal friction angle and cohesion of the rock mass for all the candidate mechanical parameter vectors, so as to obtain the internal friction angle and cohesion of the rock mass of the target mine slope.

[0059] This application also provides a storage medium storing a computer program thereon, which, when executed, performs the steps of the above-described method for obtaining rock mass mechanics parameters.

[0060] This application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor, when calling the computer program in the memory, implements the steps of the above-described method for obtaining rock mechanics parameters.

[0061] This application provides a method for obtaining rock mass mechanics parameters, including: determining n measured mechanical parameters of a target mine slope and constructing a target vector corresponding to the target mine slope; wherein the dimensions of the target vector include the internal friction angle of the rock mass, the cohesion of the rock mass, a segmentation dimension marker, and the n measured mechanical parameters; obtaining multiple reference vectors from a database; wherein the dimensions of the reference vectors are the same as those of the target vector; segmenting all the reference vectors based on the variance of the dimensions corresponding to the n measured mechanical parameters, and constructing a topological relationship tree corresponding to all the reference vectors based on the segmentation results. The segmentation dimension flags of all reference vectors are set according to the segmentation results; wherein, the topology graph relationship tree is a binary tree, and the segmentation dimension flags are used to describe the segmentation dimension of the nodes in the topology relationship tree; based on the segmentation dimension flags, the k reference vectors closest to the target vector in the topology relationship tree are queried, and the k reference vectors closest to the target vector are set as candidate mechanical parameter vectors; the internal friction angle and cohesion of the rock mass of all candidate mechanical parameter vectors are weighted and calculated to obtain the internal friction angle and cohesion of the target mine slope.

[0062] This application acquires n measured mechanical parameters of a target mine slope and constructs a corresponding target vector. It also retrieves multiple reference vectors with the same dimensions as the target vector from a database, segments all reference vectors using the variance of the dimensions corresponding to the n measured mechanical parameters, and constructs a corresponding topological tree based on the segmentation results. The topological tree is a binary tree. This application identifies the k reference vectors closest to the target vector in the topological tree, thereby determining the internal friction angle and cohesion of the target mine slope based on these k closest reference vectors. This process constructs a topological tree describing the similarity of measured mechanical parameters between the reference vectors. Utilizing the structural advantages of the topological tree, it can quickly locate reference vectors similar to the target mine slope. Therefore, this application can improve the efficiency and reliability of acquiring the internal friction angle and cohesion of the rock mass. This application also provides a rock mass mechanical parameter acquisition system, a storage medium, and an electronic device, all with the above-mentioned beneficial effects, which will not be elaborated further here. Attached Figure Description

[0063] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 is a flowchart of a method for obtaining rock mass mechanical parameters provided in an embodiment of this application;

[0065] Figure 2 is a logical relationship diagram of the left subtree of a data center provided in an embodiment of this application;

[0066] Figure 3 is a logical relationship diagram of the right subtree in a dataset provided in an embodiment of this application;

[0067] Figure 4 is a schematic diagram of a topological relationship tree provided in an embodiment of this application. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0069] Please refer to Figure 1 below. Figure 1 is a flowchart of a method for obtaining rock mass mechanical parameters provided in an embodiment of this application.

[0070] Specific steps may include:

[0071] S101: Determine n measured mechanical parameters of the target mine slope and construct the target vector corresponding to the target mine slope;

[0072] This embodiment can be applied to electronic devices with data analysis capabilities. By comparing the measured mechanical parameters with the parameters in the database, a reference vector that is closer to the target vector is determined, thereby deriving the internal friction angle and cohesion of the target mine slope.

[0073] The target mine slope is a rock mass whose stability needs to be analyzed. Prior to this step, n measured mechanical parameters of the target mine slope can be collected. These measured mechanical parameters may include any one or a combination of any of the following: internal friction angle of the rock, rock cohesion, degree of rock weathering, uniaxial compressive strength of the rock, slope height, softening coefficient, weak surface characteristics, water action within the rock mass, impact of blasting vibration, internal friction angle of the rock mass, and rock cohesion. All of these measured mechanical parameters can be obtained using measuring equipment or through assessment by personnel.

[0074] After obtaining n measured mechanical parameters of the target mine slope, a corresponding target vector can be established. The dimensions of the target vector include the internal friction angle of the rock mass, the rock mass cohesion, the dividing dimension marker, and the n measured mechanical parameters. In the target vector, the n measured mechanical parameters are known quantities, the internal friction angle of the rock mass and the rock mass cohesion are unknown quantities, and the dividing dimension marker can be a preset value (such as -1).

[0075] For example, the target vector can be {the first measured mechanical parameter, the second measured mechanical parameter, ..., the nth measured mechanical parameter, the internal friction angle of the rock mass, the cohesion of the rock mass, and the dividing dimension marker}.

[0076] S102: Retrieve multiple reference vectors from the database;

[0077] This step involves retrieving multiple reference vectors from a database. These reference vectors share the same dimension as the target vector, such as: {first measured mechanical parameter, second measured mechanical parameter, ..., nth measured mechanical parameter, internal friction angle of the rock mass, rock mass cohesion, and dimensional marker}. All elements in all dimensions of the reference vectors (internal friction angle of the rock mass, rock mass cohesion, dimensional marker, and n measured mechanical parameters) are known quantities. The dimensional marker of the reference vectors can be a preset value (e.g., -1).

[0078] S103: Based on the variance of the dimensions corresponding to the n measured mechanical parameters, all the reference vectors are segmented, a topological relationship tree corresponding to all the reference vectors is constructed according to the segmentation results, and the segmentation dimension flag of all the reference vectors is set according to the segmentation results.

[0079] This embodiment can calculate the variance of each dimension corresponding to the measured mechanical parameter. The variance is used to describe the dispersion of the data. Based on the variance of the dimensions corresponding to the n measured mechanical parameters, a recursive binary space partition (i.e., data space segmentation) can be performed on all the reference vectors to obtain the partitioning result. According to the partitioning result, a topological relationship tree corresponding to all the reference vectors can be constructed. The above topological relationship tree is a binary tree. If the partitioning dimension of a certain node A is i, then the value of the i-th dimension of all nodes in the left subtree of node A is less than the value of the i-th dimension of node A, and the value of the i-th dimension of all nodes in the right subtree of node A is greater than or equal to the value of the i-th dimension of node A.

[0080] In the above-mentioned generation of the topology graph relationship tree, each node has its corresponding splitting dimension. This application can set the splitting dimension flag of all the reference vectors according to the splitting result. The splitting dimension flag is used to describe the splitting dimension of the node in the topology relationship tree. That is, from multiple reference vectors, a reference vector whose numerical sorting is in the middle is selected as the parent node according to the dimension corresponding to the splitting dimension flag, and then the left subtree set and the right subtree set are divided by the parent node.

[0081] S104: Based on the segmentation dimension flag, query the k reference vectors that are closest to the target vector in the topological relationship tree, and set the k reference vectors that are closest to the target vector as candidate mechanical parameter vectors;

[0082] Based on the obtained topological relationship tree, a query can be performed on the topological relationship tree using the segmentation dimension flag to obtain the k reference vectors in the topological relationship tree that are closest to the target vector. In this scheme, there is a one-to-one correspondence between the reference vectors and the nodes in the topological relationship tree.

[0083] The distance between the reference vector and the target vector is determined based on the values ​​of n measured mechanical parameters. Specifically, in this embodiment, the n measured mechanical parameters in the target vector can be used as target mechanical parameter sub-vectors, and the n measured mechanical parameters in the reference vector can be used as reference mechanical parameter sub-vectors. The distance between the target mechanical parameter sub-vector and each reference mechanical parameter sub-vector is used as the distance between the target vector and the reference vector in S104. In this embodiment, the reference vectors corresponding to the k reference mechanical parameter sub-vectors closest to the target mechanical parameter sub-vector can be used as the k reference vectors closest to the target vector in the topological relationship tree. This application sets the k reference vectors closest to the target vector as candidate mechanical parameter vectors so as to calculate the internal friction angle and cohesion of the rock mass in the target vector based on the candidate mechanical parameter vectors.

[0084] The split dimension flag is used to describe the split dimension of the nodes in the topological relationship tree. In this embodiment, node search can be performed according to the split dimension flag of each node to avoid the calculation of invalid nodes.

[0085] S105: Perform a weighted calculation on the internal friction angle and cohesion of the rock mass for all the candidate mechanical parameter vectors to obtain the internal friction angle and cohesion of the rock mass of the target mine slope.

[0086] The distance between the reference vector and the target vector is used to determine the similarity between the rock mass corresponding to the reference vector and the target mine slope. Similar rock masses have similar internal friction angles and cohesion; that is, the similarity of rock masses is positively correlated with the similarity of their internal friction angles and cohesion. This application performs weighted calculations on the internal friction angles and cohesion of all the candidate mechanical parameter vectors to obtain the numerical values ​​of the internal friction angles and cohesion of the target mine slope.

[0087] This embodiment can compare the values ​​of the internal friction angle and the cohesion of the rock mass with the safe value range; if the values ​​of the internal friction angle and / or the cohesion of the rock mass are not within the safe value range, it is determined that the stability of the target mine slope does not meet the requirements and a prompt message is output; if the values ​​of the internal friction angle and the cohesion of the rock mass are both within the safe value range, it is determined that the stability of the target mine slope meets the requirements.

[0088] This embodiment acquires n measured mechanical parameters of the target mine slope and constructs a corresponding target vector. It also retrieves multiple reference vectors with the same dimensions as the target vector from a database, segments all reference vectors using the variance of the dimensions corresponding to the n measured mechanical parameters, and constructs a corresponding topological relationship tree based on the segmentation results. Based on the obtained topological relationship tree, this embodiment identifies the k nearest reference vectors to the target vector in the topological relationship tree, thereby determining the internal friction angle and cohesion of the target mine slope based on these k nearest reference vectors. The above process constructs a topological relationship tree describing the similarity of the measured mechanical parameters between the reference vectors. Utilizing the structural advantages of the topological relationship tree, it can quickly locate reference vectors similar to the target mine slope. Therefore, this embodiment can improve the efficiency and reliability of acquiring the internal friction angle and cohesion of the rock mass.

[0089] As a further description of the embodiment corresponding to Figure 1, the topological relationship tree can be constructed in the following way, and the split dimension flag of the reference vector can be set:

[0090] Step A1: Construct the current data set containing all the aforementioned reference vectors;

[0091] Step A2: Calculate the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current dataset, and select the dimension corresponding to the largest variance as the current split dimension;

[0092] Step A3: Sort all the reference vectors in ascending order according to the current splitting dimension, select the middle reference vector in the sorting result as the splitting node of the current data set, and set the splitting dimension flag of the splitting node to the dimension number of the current splitting dimension;

[0093] If the number of reference vectors *m* in the current dataset is odd, then the reference vector at position (m+1) / 2 in the sorting result is the intermediate reference vector; if the number of reference vectors *m* in the current dataset is odd, then the reference vector at position (m / 2) or (m+2) / 2 in the sorting result is the intermediate reference vector. This step also uses the dimension index corresponding to the maximum variance as the value of the split dimension flag for the split node. For example, if the maximum variance occurs in the 3rd dimension, then the value of the split dimension flag is set to 3.

[0094] Step A4: Construct the set of left subtrees of the splitting node based on the reference vectors before the intermediate reference vector in the sorting result, and construct the set of right subtrees of the splitting node based on the reference vectors after the intermediate reference vector in the sorting result;

[0095] The intermediate reference vector is located in the middle of the sorting result. This step can construct the left subtree set of the splitting node based on the reference vectors in the sorting result before the intermediate reference vector, and can also construct the right subtree set of the splitting node based on the reference vectors in the sorting result after the intermediate reference vector. For example, if there are 7 reference vectors, the reference vector ranked 4th is used as the splitting node, the reference vectors ranked 1st to 3rd are used as the left subtree set, and the reference vectors ranked 5th to 7th are used as the right subtree set.

[0096] Step A5: If the left subtree set is not empty, then the left subtree set is used as the new current data set, and the process re-enters step A2 to calculate the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current data set;

[0097] Step A6: If the right subtree set is not empty, then the right subtree set is used as the new current data set, and the process re-enters step A2 to calculate the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current data set;

[0098] If the left and right subtree sets of all split nodes are empty, then stop the splitting operation (i.e., stop the binary space splitting operation) and proceed to step A7.

[0099] Step A7: Generate the topology tree based on the hierarchical relationship between all the split nodes.

[0100] During the execution of steps A1 to A6, multiple levels of splitting nodes are generated. The first splitting node determined is the root node. The splitting nodes determined from the left and right subtrees of the root node are first-level child nodes. The splitting nodes determined from the left and right subtrees of the first-level child nodes are second-level child nodes, and so on. The splitting nodes determined from the left and right subtrees of the p-th level child nodes are p+1-th level child nodes, and so on, with the last level of splitting nodes being leaf nodes. The root node is the parent node of the first-level child nodes, the first-level child nodes are the parent nodes of the second-level child nodes, and so on, until the p-th level child node is the parent node of the p+1-th level child node.

[0101] As a further description of the embodiment corresponding to Figure 1, the k reference vectors closest to the target vector in the topological relationship tree can be queried in the following way:

[0102] Step B1: Set the root node of the topological relationship tree as the current node;

[0103] Step B2: Add a preset identifier to the current node;

[0104] Step B3: Determine if there are any empty spaces in the ordered list; if there are empty spaces, proceed to step B4; if there are no empty spaces, proceed to step B5.

[0105] Wherein, the maximum number of nodes stored in the candidate node column is k; k < n, and the candidate nodes in the ordered list are sorted according to vector distance, where the vector distance is the distance between the reference vector corresponding to the candidate node and the target vector;

[0106] Step B4: Add the current node to the ordered list, then proceed to step B7;

[0107] Step B5: Determine whether the distance between the reference vector corresponding to the current node and the target vector is less than the critical distance; if it is less than the critical distance, proceed to step B6; if it is greater than or equal to the critical distance, proceed to step B7.

[0108] Wherein, the critical distance is the maximum distance between the reference vector corresponding to the candidate node in the ordered list and the target vector;

[0109] Step B6: Remove the candidate node with the largest distance from the target vector from the ordered list, and add the current node to the ordered list, then proceed to step B7;

[0110] Step B7: Determine if the current node has child nodes; if child nodes exist, proceed to step B8; if no child nodes exist, proceed to step B9.

[0111] Step B8: Select a new current node from the child nodes of the current node, and proceed to step B2 to add a preset identifier to the current node;

[0112] Step B9: Recursively query the parent node that meets the preset conditions from the current node in the topological relationship tree;

[0113] The preset condition is that there are child nodes that have not been added with the preset identifier, that is, the child nodes of the parent node have not been added with the preset identifier.

[0114] Step B10: Determine whether the absolute value of the difference between the value of the i-th dimension of the parent node that meets the preset conditions and the value of the target vector in the i-th dimension is less than the critical distance; if yes, proceed to step B11; if no, proceed to step B12.

[0115] Step B11: Set the child nodes of the parent node that meet the preset conditions but have not been marked with a preset identifier as the new current node, and proceed to step B2 to add a preset identifier to the current node;

[0116] Step B12: Then set the candidate nodes in the ordered list to the k reference vectors closest to the target vector; wherein, the value of the split dimension flag of the parent node that meets the preset conditions is i.

[0117] A node in a topological tree can have left and right branch child nodes, or it can have only left branch child nodes, or it can have only right branch child nodes.

[0118] If the current node has a left branch child node and a right branch child node, the following scheme can be adopted: take the value of the j-th dimension of the current node as a reference value according to the value j of the split dimension flag; determine whether the value of the target vector in the j-th dimension is less than the reference value; if it is less than the reference value, set the left branch child node of the current node as the new current node and proceed to the step of adding a preset flag to the current node; if it is greater than or equal to the reference value, set the right branch child node of the current node as the new current node and proceed to the step of adding a preset flag to the current node.

[0119] If the current node only has left branch child nodes, the following approach can be taken: Use the value of the j-th dimension of the current node as a reference value based on the value j of the split dimension marker; determine if the value of the target vector in the j-th dimension is less than the reference value; if it is less than the reference value, set the left branch child node of the current node as the new current node and proceed to the step of adding a preset identifier to the current node; if it is greater than or equal to the reference value, determine if the absolute value of the difference between the value of the current node in the j-th dimension and the value of the target vector in the j-th dimension is less than the critical distance; if yes, set the right branch child node of the current node as the new current node and proceed to the step of adding a preset identifier to the current node; if no, proceed to the step of recursively querying the parent node that meets the preset conditions in the topological relationship tree.

[0120] If the current node only has a right branch child node, the following approach can be taken: Use the value of the j-th dimension of the current node as a reference value based on the value j of the split dimension marker; determine if the value of the target vector in the j-th dimension is less than the reference value; if it is greater than or equal to the reference value, set the right branch child node of the current node as the new current node and proceed to the step of adding a preset identifier to the current node; if it is less than the reference value, determine if the absolute value of the difference between the value of the current node in the j-th dimension and the value of the target vector in the j-th dimension is less than the critical distance; if yes, set the left branch child node of the current node as the new current node and proceed to the step of adding a preset identifier to the current node; if no, proceed to the step of recursively querying the parent node that meets the preset conditions in the topological relationship tree.

[0121] During the process of querying the k nearest reference vectors to the target vector, if the current node has no child nodes and the result of recursively querying the parent node that meets the preset conditions from the current node is empty (i.e., no parent node that meets the preset conditions is found), then the query is determined to be complete, and the candidate nodes in the ordered list are set as the k nearest reference vectors to the target vector.

[0122] The above embodiments can be applied to the acquisition of mechanical parameters of various rock masses. The following uses a complex weak-faced, strongly cut rock mass as an example to illustrate the process described in the above embodiments.

[0123] The physical and mechanical parameters of slope rock masses depend on factors such as rock properties, structural plane characteristics, structural plane development, groundwater influence, and weathering degree. Open-pit metal mine rock masses are often subjected to varying degrees of cutting by complex weak planes, and the characteristics of these complex weak planes directly affect the overall strength of the three-dimensional slope rock mass. For production mines, relevant personnel have accumulated abundant data on the characteristics of complex weak planes and the physical and mechanical properties of rocks. Utilizing this large amount of existing basic data to intelligently and efficiently identify the mechanical parameters of rock masses with strong cutting by weak planes can effectively reduce the manpower and material resources required for structural plane investigations, significantly shorten the time required to obtain rock mass mechanical parameters, and avoid serious safety accidents when measuring weak planes on steep slopes. This method revolutionizes the traditional long process of obtaining three-dimensional physical and mechanical parameters of slope rock masses, which involves indoor rock mechanics testing, on-site structural plane investigation, rock mass quality classification, rock mass mechanical parameter estimation, and on-site in-situ verification of rock mass mechanical parameters.

[0124] The existing methods for obtaining rock mass mechanical parameters mainly include the following two methods: Method 1: Obtaining rock physical and mechanical parameters through indoor rock mechanics tests, conducting on-site investigations of weak surface characteristic parameters to obtain weak surface physical and mechanical characteristic parameters, and using a combination of methods such as RQD (Rock Quality Designation), standard methods, RMR (Rock Mass Rating), and Q system classification to conduct overall quality grading of the in-situ rock mass, and using methods such as the Hoek Brown strength criterion to calculate the in-situ rock mass physical and mechanical parameters; Method 2: Selecting representative rock mass locations on-site to conduct in-situ rock mass physical and mechanical tests, obtaining the physical and mechanical parameters of the rock mass under test conditions, and converting the in-situ test results into in-situ rock mass physical and mechanical parameter indices through empirical conversion methods.

[0125] Method 1 is currently the mainstream calculation method in the industry, characterized by its wide application range. However, its process is lengthy, requiring extensive indoor testing and on-site weak surface investigation to obtain the mechanical parameters of the rock mass. This process is time-consuming and costly. Furthermore, it necessitates extensive calculations based on the indoor tests and on-site investigations, resulting in a large workload and high reliance on the engineering experience of technical personnel. Consequently, its reliability is low, and it cannot meet the requirements of efficient rock mass parameter acquisition for intelligent analysis of overall slope stability. Method 2 primarily involves in-situ rock mechanics testing. However, in practice, this method requires large equipment, involves significant investment, has a long cycle, exhibits considerable randomness in the results, and demands high representativeness of the test site. In-situ testing technology has a relatively short history of development, making it difficult to control boundary conditions (drainage and stress conditions of the surrounding soil and rock layers). The relationship between the data obtained from in-situ testing and the engineering properties of the soil and rock remains largely based on extensive statistical experience.

[0126] To address the technical problems existing in the aforementioned related technologies, this application provides an intelligent method for acquiring three-dimensional mechanical parameters of complex weak-faced, strongly cut rock masses. This method enables efficient and intelligent acquisition of mechanical parameters of complex weak-faced rock masses, improves the accuracy and timeliness of rock mass mechanical parameters, reduces the cost of acquiring physical and mechanical parameters of complex weak-faced rock masses, and provides basic data for intelligent three-dimensional stability analysis of complex weak-faced slopes.

[0127] The intelligent method for acquiring three-dimensional mechanical parameters of complex, weak-surface, strongly sheared rock masses includes the following steps:

[0128] Step C1: Determine the main factors affecting the mechanical parameters of complex weak-faced rock masses.

[0129] The above-mentioned main factor indicators are the following nine measured mechanical parameters:

[0130] (1) Rock shear strength index: rock internal friction angle , unit °;

[0131] (2) Rock cohesion c, in MPa;

[0132] (3) Degree of rock weathering We:

[0133] If the rock is strongly weathered, the value of We is 0; if the rock is moderately weathered, the value of We is 1; if the rock is slightly weathered, the value of We is 2; if the rock is fresh, the value of We is 3.

[0134] (4) Uniaxial compressive strength of rock: UCS, unit MPa;

[0135] (5) Slope height: h, unit m;

[0136] (6) Softening coefficient: k, unit dimensionless;

[0137] (7) Weak surface characteristics: Joint density ρ, unit joints / m;

[0138] (8) Water action on the rock mass (Wa):

[0139] If the rock mass water action is characterized by dryness or localized groundwater inflow through joints (i.e., water head < 10m), then Wa's value is 0; if the rock mass water action is characterized by a moderate inflow with localized erosion of jointed infill material (i.e., water head 10-25m), then Wa's value is 1; if the rock mass water action is characterized by a large inflow through joints in the infill material (i.e., water head 25-100m), then Wa's value is 2; if the rock mass water action is characterized by a large inflow accompanied by significant erosion of jointed infill material (i.e., water head 25-100m), then Wa's value is 3; if the rock mass water action is characterized by an extremely large inflow of groundwater that weathers over time (i.e., water head > 100m), then Wa's value is 4; if the rock mass water action is characterized by a large, continuous inflow without significant weathering (i.e., water head > 100m), then Wa's value is 5.

[0140] (9) The impact of blasting vibration on B;

[0141] If the blasting vibration effect is an open-pit blast, then the value of B is 1; if the blasting vibration effect is a controlled blast, then the value of B is 2.

[0142] Step C2: Construct the basic vector T of rock mass mechanics parameters.

[0143] T={ ,c,We,UCS,h,k,ρ,Wa,B, m, ,split};

[0144] The vector T mentioned above involves 11 parameters, which are represented by numbers 1, 2, 3...11 in sequence. The split dimension flag `split` is used to indicate the dimension value of the split, and its value is 1, 2, 3...9, corresponding to... c, We, UCS, h, k, ρ, Wa, B; Initialize, split = -1. m represents the friction angle within the rock mass. It represents the cohesion of the rock mass.

[0145] Step C3: Construct a rock mass mechanics parameter database.

[0146] The rock mechanics parameter database is constructed according to the format of the basic vector in step two, as follows:

[0147] T1={ 1,c1,We1,UCS1,h1,k1,ρ1,Wa1,B1, m1, ,-1};

[0148] T2={ 2,c2,We2,UCS2,h2,k2,ρ2,Wa2,B2, m2, ,-1};

[0149] …… ……

[0150] Tk={ k,ck,Wek,UCSk,hk,kk,ρ3,Wak,Bk, mk, ,-1};

[0151] …… ……

[0152] Tn={ t,ct,Wet,UCSt,ht,kt,ρt,Wat,Bt, mt, ,-1}.

[0153] T1~Tn are reference vectors.

[0154] Step C4: Determine the initial splitting axis.

[0155] This step calculates the variance of all data in the database in the first 9 dimensions, selects the dimension M where the maximum variance is located as the first split axis, and sets the split value to M, split=M.

[0156] Step 5: Determine the root node T_point for all data.

[0157] Sort all data in the database in ascending order according to the dimension with the largest variance in step C4 (randomly sort when there are duplicate data). Select the median of all data (when the number of data is odd, select the middle value as the median; when the number of data is even, select the first of the two middle data as the median). Use this median data as the root node of all data.

[0158] Step C6: Spatial data segmentation.

[0159] This step can be done by dividing the entire data space into two parts using a plane Face=M: the dataset with data smaller than the median is the left subtree dataset (Data_Left), and the dataset with data larger than or equal to the median is the right subtree dataset (Data_Right).

[0160] Step C7: Recursively divide the data space (left subtree and right subtree) according to the method of steps C4 to C6 until it can no longer be divided, and construct the topological relationship tree of all data.

[0161] Step C8: Abstract the slope engineering to be acquired (i.e., the target mine slope) into a target vector (i.e., the target vector of rock mechanics parameters) T_Target.

[0162] T_Target={ ,c,We,UCS,h,k, ρ,Wa,B, m_Target,c m _Target, -1};

[0163] Step C9: Determine the number k of the target slope engineering rock mechanics parameter vectors used to calculate the target slope.

[0164] The value of k can be any value, such as 3, 4, 5, 6, 7 or 8.

[0165] Step C10: Set an ordered list List_k of size k to store the k sample points that are closest to the current search point.

[0166] Step C11: Starting from the root node T_point, set it as the current node.

[0167] Step C12: If the current node is empty, the list List_k stops updating and proceeds to step C17; if the current node is not empty, proceed to either step C12 or step C16.

[0168] Step C13: If the list List_k is not full, insert the current sample directly into the list; if the list is full, determine whether the distance from the current sample to the target vector is less than the distance from the last element of the list to the target vector. If true, delete the last element of the list and insert the current sample.

[0169] Step C14: Sort the elements in List_k by their distance Dist to the target vector in ascending order;

[0170] ;

[0171] In the above formula, 1 ≤ s ≤ t, where t is the total number of reference vectors in the parameter database. s Dist represents the distance between the s-th reference vector and the target vector. s, cs, Wes, UCSs, hs, ks, ρs, Was and Bs represent the rock shear strength index, rock cohesion, rock weathering degree, rock uniaxial compressive strength, slope height, softening coefficient, weak surface characteristics, rock mass water action and blasting vibration effect in the s-th reference vector, respectively.

[0172] Step C15: If the data corresponding to the partition dimension of the target vector is less than the data corresponding to the partition dimension of the current node, then set the left branch of the current node as the new current node, and proceed to step C12 to further execute steps C13 to C15 or step 16; otherwise, set the right branch of the current node as the new current node, and proceed to step C12 to further execute steps C13 to C15 or step 16.

[0173] Step C16: If the list List_k is full, or if the distance from the target vector to the current node's partition dimension is less than the distance from the last element in the list to the target vector, then set the other branch of the current node as the current node, and proceed to step C12 to further execute steps C13 to C15 or step 16.

[0174] Step 17: For the target vector m_Target and c m The calculation is performed using the two parameters _Target.

[0175] The target vector is calculated using all elements in List_k as the basic data. m_Target and c m _Target, the calculation formula is as follows:

[0176] ;

[0177] ;

[0178] m_Targe is the friction angle within the rock mass in the target vector, in degrees;

[0179] c m _Target represents the rock mass cohesion in the target vector, in MPa;

[0180] k represents the number of elements in the list List_k, in units of numbers;

[0181] m i This represents the angle of internal friction of the i-th element in the list List_k, in degrees.

[0182] cm i This represents the cohesive force of the i-th element in the list List_k, in MPa.

[0183] Dist i This represents the distance between the i-th element in the list List_k and the target vector, and has no unit.

[0184] The process described in the above embodiments is illustrated below using examples from practical applications.

[0185] If an open-pit metal mine slope is arc-shaped with a height ranging from 190m to 465m, and the lithology includes gabbro, quartz hornblende syenite, diabase, pegmatite, and ore-bearing gabbro, some rock mass mechanical parameters are selected as follows to illustrate the principle of intelligent determination of three-dimensional mechanical parameters. A database of partial three-dimensional mechanical parameters of rock mass is constructed. During engineering applications, relevant data on metal mine slopes can be continuously collected to enrich the data information. The larger the amount of data, the easier it is for this method to demonstrate its superior performance.

[0186] The first data point: {43.29,10.51,2,76.73,220,0.8,9.9,0,2,34.03,0.48,-1};

[0187] The second data point: {43.29,10.51,2,76.73,190,0.8,9.9,0,2,33.11,0.46,-1};

[0188] The third data point: {44.32,9.48,2,75.42,330,0.71,10.32,0,2,32.26,0.41,-1};

[0189] The fourth data point: {44.32,9.48,2,75.42,190,0.71,9.9,0,2,33.15,0.40,-1};

[0190] The 5th data point: {44.32,9.48,2,75.42,220,0.71,9.9,0,2,33.62,0.41,-1};

[0191] The 6th data point: {44.32,9.48,2,75.42,318,0.71,10.25,0,2,32.94,0.43,-1};

[0192] The 7th data point: {44.32,9.48,2,75.42,230,0.71,5.35,0,2,33.23,0.47,-1};

[0193] The 8th data point: {43.29,10.51,2,76.73,230,0.8,9.9,0,2,33.05,0.54,-1};

[0194] The 9th data point: {43.29,10.51,2,76.73,318,0.8,10.25,0,2,33.99,0.52,-1};

[0195] Data entry number 10: {43.29,10.51,2,76.73,465,0.8,7.73,0,2,33.38,0.62,-1}.

[0196] The data items 1 to 10 above are the 10 reference vectors.

[0197] The target mine has a slope height of 300m, with dry rock mass or localized areas with small amounts of water inflow. The joint density in the rock mass is 10 joints / m. The mine employs controlled blasting technology. The rock is slightly weathered. Physical and mechanical parameters of the rock obtained after sampling at the mine are as follows: =44°, c=8.8MPa, UCS=75.8MPa, softening coefficient 0.75, written in the form of target vector as follows:

[0198] T_Target={44,8.8,2,75.8,300,0.75,10,0,2, m_Target,c m _Target,-1}.

[0199] The dimensions of the above reference vector and target vector are, in order: rock shear strength index, rock cohesion, rock weathering degree, rock uniaxial compressive strength, slope height, softening coefficient, weak surface characteristics, rock mass water action, blasting vibration influence, rock mass internal friction angle, rock mass cohesion, and slicing dimension marker.

[0200] The shear strength parameters of the rock mass on the target mine slope include the internal friction angle and cohesion of the rock mass. The specific calculation process is as follows:

[0201] Step D1: Construct a rock mass mechanics parameter database.

[0202] The first data entry is: {43.29,10.51,2,76.73,220,0.8,9.9,0,2,34.03,0.48,-1};

[0203] The second data entry: {43.29,10.51,2,76.73,190,0.8,9.9,0,2,33.11,0.46,-1};

[0204] The third data entry: {44.32,9.48,2,75.42,330,0.71,10.32,0,2,32.26,0.41,-1};

[0205] The 4th data entry: {44.32,9.48,2,75.42,190,0.71,9.9,0,2,33.15,0.40,-1};

[0206] The 5th data entry: {44.32,9.48,2,75.42,220,0.71,9.9,0,2,33.62,0.41,-1};

[0207] The 6th data entry: {44.32,9.48,2,75.42,318,0.71,10.25,0,2,32.94,0.43,-1};

[0208] The 7th data entry: {44.32,9.48,2,75.42,230,0.71,5.35,0,2,33.23,0.47,-1};

[0209] The 8th data entry: {43.29,10.51,2,76.73,230,0.8,9.9,0,2,33.05,0.54,-1};

[0210] The 9th data entry: {43.29,10.51,2,76.73,318,0.8,10.25,0,2,33.99,0.52,-1};

[0211] The 10th data entry: {43.29,10.51,2,76.73,465,0.8,7.73,0,2,33.38,0.62,-1}.

[0212] Step D2: Determine the initial splitting axis.

[0213] This step calculates the variance of the data across nine dimensions, as follows:

[0214] The data for dimension 1 are: 43.29, 43.29, 44.32, 44.32, 44.32, 44.32, 44.32, 43.29, 43.29, 43.29, with a variance of 0.542858.

[0215] The data for dimension 2 are: 10.51, 10.51, 9.48, 9.48, 9.48, 9.48, 9.48, 10.51, 10.51, 10.51, with a variance of 0.542858.

[0216] The data for dimension 3 are: 2, 2, 2, 2, 2, 2, 2, 2, 2, and the variance of the data is 0.

[0217] The data for dimension 4 are: 76.73, 76.73, 75.42, 75.42, 75.42, 75.42, 75.42, 76.73, 76.73, 76.73, with a variance of 0.690431.

[0218] The data for dimension 5 are: 220, 190, 330, 190, 220, 318, 230, 230, 318, 465, and the variance of the data is 84.19791.

[0219] The data for dimension 6 are: 0.8, 0.8, 0.71, 0.71, 0.71, 0.71, 0.71, 0.8, 0.8, 0.8, with a variance of 0.047434.

[0220] The data for dimension 7 are: 9.9, 9.9, 10.32, 9.9, 9.9, 10.25, 5.35, 9.9, 10.25, 7.73, and the variance of the data is 2.194356;

[0221] The data for dimension 8 are 0, 0, 0, 0, 0, 0, 0, 0, 0, and the variance of the data is 0.

[0222] The data for dimension 9 are 2, 2, 2, 2, 2, 2, 2, 2, and the variance of the data is 0.

[0223] The axis with the largest variance among the nine dimensions is dimension 5, with a variance of 84.19791. Therefore, we determine that the initial split axis is dimension 5 and set the split value to 5, so split=5.

[0224] Step D3: Determine the root node for all data.

[0225] Sort all data (10 data points) in ascending order according to dimension 5. The sorted data order is as follows:

[0226] serial number The second data point: {43.29,10.51,2,76.73,190,0.8,9.9,0,2,33.11,0.46,-1};

[0227] serial number The fourth data point: {44.32,9.48,2,75.42,190,0.71,9.9,0,2,33.15,0.40,-1};

[0228] serial number The first data point: {43.29,10.51,2,76.73,220,0.8,9.9,0,2,34.03,0.48,-1};

[0229] serial number The 5th data point: {44.32,9.48,2,75.42,220,0.71,9.9,0,2,33.62,0.41,-1};

[0230] serial number The 7th data point: {44.32,9.48,2,75.42,230,0.71,5.35,0,2,33.23,0.47,-1};

[0231] serial number The 8th data point: {43.29,10.51,2,76.73,230,0.8,9.9,0,2,33.05,0.54,-1};

[0232] serial number The third data point: {44.32,9.48,2,75.42,330,0.71,10.32,0,2,32.26,0.41,-1};

[0233] serial number The 6th data point: {44.32,9.48,2,75.42,318,0.71,10.25,0,2,32.94,0.43,-1};

[0234] serial number The 9th data point: {43.29,10.51,2,76.73,318,0.8,10.25,0,2,33.99,0.52,-1};

[0235] serial number The 10th data point: {43.29,10.51,2,76.73,465,0.8,7.73,0,2,33.38,0.62,-1};

[0236] The two data entries in the middle are the 5th and 6th. We select the 5th data entry as the root node and change its `split` attribute to 5. The root node is as follows:

[0237] The root node is numbered 7th data entry: {44.32,9.48,2,75.42,230,0.71,5.35,0,2,33.23,0.47,5}.

[0238] Step D4: Spatial data segmentation.

[0239] The left subtree dataset after spatial partitioning is as follows:

[0240] serial number The second data point: {43.29,10.51,2,76.73,190,0.8,9.9,0,2,33.11,0.46,-1};

[0241] serial number The fourth data point: {44.32,9.48,2,75.42,190,0.71,9.9,0,2,33.15,0.40,-1};

[0242] serial number The first data point: {43.29,10.51,2,76.73,220,0.8,9.9,0,2,34.03,0.48,-1};

[0243] serial number The 5th data point: {44.32,9.48,2,75.42,220,0.71,9.9,0,2,33.62,0.41,-1};

[0244] The right subtree dataset after spatial partitioning is as follows:

[0245] serial number The 8th data point: {43.29,10.51,2,76.73,230,0.8,9.9,0,2,33.05,0.54,-1};

[0246] serial number The third data point: {44.32,9.48,2,75.42,330,0.71,10.32,0,2,32.26,0.41,-1};

[0247] serial number The 6th data point: {44.32,9.48,2,75.42,318,0.71,10.25,0,2,32.94,0.43,-1};

[0248] serial number The 9th data point: {43.29,10.51,2,76.73,318,0.8,10.25,0,2,33.99,0.52,-1};

[0249] serial number Data entry number 10: {43.29,10.51,2,76.73,465,0.8,7.73,0,2,33.38,0.62,-1}.

[0250] Step D5: Find the root node of the left and right subtrees respectively.

[0251] The left subtree dataset after spatial partitioning is as follows:

[0252] serial number The second data point: {43.29,10.51,2,76.73,190,0.8,9.9,0,2,33.11,0.46,-1};

[0253] serial number The fourth data point: {44.32,9.48,2,75.42,190,0.71,9.9,0,2,33.15,0.40,-1};

[0254] serial number The first data point: {43.29,10.51,2,76.73,220,0.8,9.9,0,2,34.03,0.48,-1};

[0255] serial number The 5th data point: {44.32,9.48,2,75.42,220,0.71,9.9,0,2,33.62,0.41,-1};

[0256] The variances of the nine dimensions are calculated as follows:

[0257] The data for dimension 1 are 43.29, 44.32, 43.29, 44.32, with a variance of 0.594671.

[0258] The data for dimension 2 are: 10.51, 9.48, 10.51, 9.48, with a variance of 0.594671.

[0259] The data for dimension 3 are: 2, 2, 2, 2, with a variance of 0.

[0260] The data for dimension 4 are 76.73, 75.42, 76.73, and 75.42, with a variance of 0.756329.

[0261] The data for dimension 5 are: 190, 190, 220, 220, with a variance of 17.32051.

[0262] The values ​​for dimension 6 are 0.8, 0.71, 0.8, and 0.71, with a variance of 0.051962.

[0263] The data for dimension 7 are: 9.9, 9.9, 9.9, 9.9, with a variance of 0.

[0264] The data for dimension 8 are: 0, 0, 0, 0, and the variance is 0.

[0265] The data for dimension 9 are: 2, 2, 2, 2, with a variance of 0.

[0266] The fifth dimension has the largest variance, with a data variance of 0.051962.

[0267] The data is sorted according to dimension 5 as follows:

[0268] serial number The second data point: {43.29,10.51,2,76.73,190,0.8,9.9,0,2,33.11,0.46,-1};

[0269] serial number The fourth data point: {44.32,9.48,2,75.42,190,0.71,9.9,0,2,33.15,0.40,-1};

[0270] serial number The first data point: {43.29,10.51,2,76.73,220,0.8,9.9,0,2,34.03,0.48,-1};

[0271] serial number The 5th data point: {44.32,9.48,2,75.42,220,0.71,9.9,0,2,33.62,0.41,-1};

[0272] The root node data is determined as follows:

[0273] serial number The fourth data point: {44.32,9.48,2,75.42,190,0.71,9.9,0,2,33.15,0.40,5};

[0274] root node The following dataset is as follows:

[0275] Left subtree dataset:

[0276] serial number The second data point: {43.29,10.51,2,76.73,190,0.8,9.9,0,2,33.11,0.46,-1};

[0277] Right subtree dataset:

[0278] serial number The first data point: {43.29,10.51,2,76.73,220,0.8,9.9,0,2,34.03,0.48,-1};

[0279] serial number The 5th data point: {44.32,9.48,2,75.42,220,0.71,9.9,0,2,33.62,0.41,-1};

[0280] The dimension with the largest variance in the dataset is 4, 0.92631;

[0281] The sorted data is as follows:

[0282] serial number The 5th data point: {44.32,9.48,2,75.42,220,0.71,9.9,0,2,33.62,0.41,-1};

[0283] serial number The first data point: {43.29,10.51,2,76.73,220,0.8,9.9,0,2,34.03,0.48,-1};

[0284] Therefore, the root node is .

[0285] serial number The 5th data point: {44.32,9.48,2,75.42,220,0.71,9.9,0,2,33.62,0.41,4};

[0286] data root node The right subtree;

[0287] serial number The first data entry is: {43.29,10.51,2,76.73,220,0.8,9.9,0,2,34.03,0.48,-1}.

[0288] Starting from the root node of the entire dataset, the logical relationship between the root node and the left subtree is shown in Figure 2. Figure 2 is a logical relationship diagram of the left subtree in a dataset provided by an embodiment of this application. In the figure, ①, ②, ④, ⑤ and ⑦ represent the nodes corresponding to the 1st, 2nd, 4th, 5th and 7th data, respectively. 5, 4 and -1 represent the split dimension (i.e., the value of the split dimension flag in the reference vector corresponding to the node).

[0289] The right subtree dataset after spatial partitioning is as follows:

[0290] serial number The 8th data point: {43.29,10.51,2,76.73,230,0.8,9.9,0,2,33.05,0.54,-1};

[0291] serial number The third data point: {44.32,9.48,2,75.42,330,0.71,10.32,0,2,32.26,0.41,-1};

[0292] serial number The 6th data point: {44.32,9.48,2,75.42,318,0.71,10.25,0,2,32.94,0.43,-1};

[0293] serial number The 9th data point: {43.29,10.51,2,76.73,318,0.8,10.25,0,2,33.99,0.52,-1};

[0294] serial number The 10th data point: {43.29,10.51,2,76.73,465,0.8,7.73,0,2,33.38,0.62,-1};

[0295] The variances for each dimension are calculated as follows:

[0296] The data for dimension 1 are: 43.29, 44.32, 44.32, 43.29, 43.29, with a variance of 0.564154.

[0297] The data for dimension 2 are: 10.51, 9.48, 9.48, 10.51, 10.51, with a variance of 0.564154.

[0298] The data for dimension 3 are: 2, 2, 2, 2, with a variance of 0.

[0299] The data for dimension 4 are: 76.73, 75.42, 75.42, 76.73, 76.73, with a variance of 0.717517.

[0300] The data for dimension 5 are: 230, 330, 318, 318, 465, with a variance of 84.39313.

[0301] The values ​​for dimension 6 are: 0.8, 0.71, 0.71, 0.8, 0.8, with a variance of 0.049295.

[0302] The values ​​for dimension 7 are: 9.9, 10.32, 10.25, 10.25, 7.73, with a variance of 1.107903.

[0303] The data for dimension 8 are: 0, 0, 0, 0, 0, with a variance of 0.

[0304] The data for dimension 9 are: 2, 2, 2, 2, 2, with a variance of 0.

[0305] The largest variance is found in dimension 5, with a variance of 84.39313. The data is as follows after sorting by dimension 5 in ascending order:

[0306] serial number The 8th data point: {43.29,10.51,2,76.73,230,0.8,9.9,0,2,33.05,0.54,-1};

[0307] serial number The 6th data point: {44.32,9.48,2,75.42,318,0.71,10.25,0,2,32.94,0.43,-1};

[0308] serial number The 9th data point: {43.29,10.51,2,76.73,318,0.8,10.25,0,2,33.99,0.52,-1};

[0309] serial number The third data point: {44.32,9.48,2,75.42,330,0.71,10.32,0,2,32.26,0.41,-1};

[0310] serial number The 10th data point: {43.29,10.51,2,76.73,465,0.8,7.73,0,2,33.38,0.62,-1};

[0311] Therefore, the root node is as follows:

[0312] serial number 9th data point: {43.29,10.51,2,76.73,318,0.8,10.25,0,2,33.99,0.52,5};

[0313] The dataset of the left subtree of the root node is as follows:

[0314] serial number The 8th data point: {43.29,10.51,2,76.73,230,0.8,9.9,0,2,33.05,0.54,-1};

[0315] serial number The 6th data point: {44.32,9.48,2,75.42,318,0.71,10.25,0,2,32.94,0.43,-1};

[0316] The dimension with the largest variance is 5, therefore, As the root node, the data is as follows:

[0317] serial number Data entry number 8: {43.29,10.51,2,76.73,230,0.8,9.9,0,2,33.05,0.54,5};

[0318] root node The right subtree is The data is as follows:

[0319] serial number The 6th data point: {44.32,9.48,2,75.42,318,0.71,10.25,0,2,32.94,0.43,-1};

[0320] The dataset of the right subtree of the root node is as follows:

[0321] serial number The third data point: {44.32,9.48,2,75.42,330,0.71,10.32,0,2,32.26,0.41,-1};

[0322] serial number The 10th data point: {43.29,10.51,2,76.73,465,0.8,7.73,0,2,33.38,0.62,-1};

[0323] The dimension with the largest variance is 5, therefore, The root node has the following data:

[0324] serial number The third data point: {44.32,9.48,2,75.42,330,0.71,10.32,0,2,32.26,0.41,5};

[0325] root node The right subtree is The data is as follows:

[0326] serial number Data entry number 10: {43.29,10.51,2,76.73,465,0.8,7.73,0,2,33.38,0.62,-1}.

[0327] Starting from the root node of the entire dataset, the logical relationship between the root node and the right subtree is shown in Figure 3. Figure 3 is a logical relationship diagram of the right subtree in a dataset provided by an embodiment of this application. In the figure, ③, ⑥, ⑦, ⑧, ⑨, and ⑩ represent the nodes corresponding to the 3rd, 6th, 7th, 8th, 9th, and 10th data points, respectively. 5 and -1 represent the split dimension (i.e., the value of the split dimension flag in the reference vector corresponding to the node).

[0328] By concatenating the logical relationships of the left and right subtrees, we can obtain all the logical relationships of the data in the dataset, i.e., the topological relationship tree. Please refer to Figure 4, which is a schematic diagram of the structure of a topological relationship tree provided in an embodiment of this application.

[0329] Step D6: Abstract the slope engineering data to be obtained into a target vector of rock mechanics parameters, T_Target;

[0330] T_Target={44,8.8,2,75.8,300,0.75,10,0,2, m_Target,c m _Target,-1}.

[0331] Step D7: Determine the number k of the target slope engineering rock mass mechanics parameter vectors used to calculate;

[0332] To illustrate the principle of the solution, this embodiment sets the value of k to 3;

[0333] Step D8: Set an ordered list List_k of size 3 to store the 3 sample points closest to the current search point.

[0334] After executing step D8, the initial list List_k has 3 empty cells.

[0335] Step D9: From the root node Begin, Set as the current node;

[0336] Step D10: The current node value is as follows, and is not empty;

[0337] serial number The 7th data point: {44.32,9.48,2,75.42,230,0.71,5.35,0,2,33.23,0.47,-1};

[0338] Step D11: [The text appears to be incomplete and contains several grammatical errors. A more accurate translation would require the full context.] Insert into the ordered list List_k.

[0339] After executing step D11, the contents of the ordered list List_k are as follows:

[0340] The first cell contains the 7th data entry: {44.32, 9.48, 2, 75.42, 230, 0.71, 5.35, 0, 2, 33.23, 0.47, -1}. The second and third cells are empty.

[0341] Step D12: Compare along the 5th dimension. The value of the 5th dimension of the target vector is 300, which is greater than the value of the 5th dimension of the current node (230). Therefore, set the current node as... The right subtree of a node (i.e., the right branch node) ;

[0342] T_Target={44, 8.8, 2, 75.8, 300, 0.75, 10, 0, 2, m_Target, c m _Target, -1};

[0343] serial number Data entry number 9: {43.29, 10.51, 2, 76.73, 318, 0.8, 10.25, 0, 2, 33.99, 0.52, 5}.

[0344] Step D13: When the ordered list List_k is not full, The data is put into List_k, and the updated list content is as follows:

[0345] The first cell contains the 7th data entry: {44.32, 9.48, 2, 75.42, 230, 0.71, 5.35, 0, 2, 33.23, 0.47, -1}. The second cell contains the 9th data entry: {43.29, 10.51, 2, 76.73, 318, 0.8, 10.25, 0, 2, 33.99, 0.52, 5}. The third cell is empty.

[0346] Step D14: Sort the data in the list in ascending order according to their distance from the target vector. The sorted list is as follows:

[0347] T_Target={44, 8.8, 2, 75.8, 300, 0.75, 10, 0, 2, m_Target, c m _Target, -1};

[0348] Dist(T_Target, 7) =

[0349] ;

[0350] Dist(T_Target, 9) =

[0351] ;

[0352] Dist(T_Target, 7) is the distance between the reference vector and the target vector corresponding to the 7th data point, and Dist(T_Target, 9) is the distance between the reference vector and the target vector corresponding to the 7th data point.

[0353] The sorted list List_k contains the following data:

[0354] The first cell contains the 9th data entry: {43.29, 10.51, 2, 76.73, 318, 0.8, 10.25, 0, 2, 33.99, 0.52, 5}. The second cell contains the 7th data entry: {44.32, 9.48, 2, 75.42, 230, 0.71, 5.35, 0, 2, 33.23, 0.47, -1}. The third cell is empty.

[0355] Step D15: The current data node is The segmentation dimension is 5. In the data, dimension 5 has 318 data points, while the target vector's dimension 5 has 300 data points. Since 300 is less than 318,... The left subtree of a node (i.e., the left branch node) is As follows, The node is set as the current node, and the data is added to the list List_k as follows:

[0356] serial number Data entry number 8: {43.29,10.51,2,76.73,230,0.8,9.9,0,2,33.05,0.54,5};

[0357] After adding the 8th data item to the last empty position (i.e., the third cell) of the sorted list, the data in list_k is as follows:

[0358] The first cell stores the 9th data entry: {43.29, 10.51, 2, 76.73, 318, 0.8, 10.25, 0, 2, 33.99, 0.52, 5}. The second cell stores the 7th data entry: {44.32, 9.48, 2, 75.42, 230, 0.71, 5.35, 0, 2, 33.23, 0.47, -1}. The third cell stores the 8th data entry: {43.29, 10.51, 2, 76.73, 230, 0.8, 9.9, 0, 2, 33.05, 0.54, 5}.

[0359] Step D16: Calculate the distance between each data in the list List_k and the target vector, and sort them in ascending order.

[0360] Dist(T_Target, 8) =

[0361] ;

[0362] Dist(T_Target, 8) is the distance between the reference vector and the target vector corresponding to the 8th data point.

[0363] The contents of the sorted list are as follows:

[0364] The first cell stores the 9th data entry: {43.29, 10.51, 2, 76.73, 318, 0.8, 10.25, 0, 2, 33.99, 0.52, 5}. The second cell stores the 8th data entry: {43.29, 10.51, 2, 76.73, 230, 0.8, 9.9, 0, 2, 33.05, 0.54, 5}. The third cell stores the 7th data entry: {44.32, 9.48, 2, 75.42, 230, 0.71, 5.35, 0, 2, 33.23, 0.47, -1}.

[0365] Step D17: The current node is The partition dimension is 5, and the data in the target vector dimension 5 is 300, which is greater than... The data in node dimension 5 is 230, therefore, the current node is set as node 230. ;

[0366] T_Target={44, 8.8, 2, 75.8, 300, 0.75, 10, 0, 2, m_Target, c m _Target, -1};

[0367] serial number Data entry number 6: {44.32, 9.48, 2, 75.42, 318, 0.71, 10.25, 0, 2, 32.94, 0.43, -1}.

[0368] Step D18: Since List_k is full, calculate... The distance between the node and the target vector is as follows:

[0369] Dist(T_Target, 6) =

[0370] ;

[0371] Dist(T_Target, 6) is the distance between the reference vector and the target vector corresponding to the 6th data point.

[0372] The distance between a node and the target vector is less than that of the last node in the ordered list List_k. The distance to the target vector is 70.159, therefore the node... Remove nodes from the ordered list List_k. Add the elements to the ordered list List_k, and then sort all elements in the ordered list List_k in ascending order of their distance from the target vector, as follows:

[0373] The first cell stores the 6th data entry: {44.32, 9.48, 2, 75.42, 318, 0.71, 10.25, 0, 2, 32.94, 0.43, -1}. The second cell stores the 9th data entry: {43.29, 10.51, 2, 76.73, 318, 0.8, 10.25, 0, 2, 33.99, 0.52, 5}. The third cell stores the 8th data entry: {43.29, 10.51, 2, 76.73, 230, 0.8, 9.9, 0, 2, 33.05, 0.54, 5}.

[0374] Step D19: The current node is Since the split value is -1, this node is the lowest level node. The node's parent node is ,node The partition dimension is 5, and the left branch of this node is empty, so the current node is set to... The parent node ;

[0375] Step D20: The current node is The node has a segmentation dimension of 5, and the target vector has a dimension of 5 and a value of 300. The absolute value of the difference between nodes with dimension 5 and a value of 318 is 18, which is less than the last node in List_k. The distance to the target vector is 70.03. The last node in List_k... Remove, and at the same time Another branch node Put it into List_k and calculate. Distance to the target vector;

[0376] serial number The third data point: {44.32, 9.48, 2, 75.42, 330, 0.71, 10.32, 0, 2, 32.26, 0.41, 5};

[0377] Dist(T_Target, 3) =

[0378] ;

[0379] Dist(T_Target, 3) is the distance between the reference vector and the target vector corresponding to the 3rd data point.

[0380] Update the ordered list List_k based on Dist(T_Target, 3) as follows:

[0381] The first cell stores the 6th data entry: {44.32, 9.48, 2, 75.42, 318, 0.71, 10.25, 0, 2, 32.94, 0.43, -1}. The second cell stores the 9th data entry: {43.29, 10.51, 2, 76.73, 318, 0.8, 10.25, 0, 2, 33.99, 0.52, 5}. The third cell stores the 3rd data entry: {44.32, 9.48, 2, 75.42, 330, 0.71, 10.32, 0, 2, 32.26, 0.41, 5}.

[0382] Step D21: The current node is The segmentation dimension is 5, the value of dimension 5 is 330, and the value of the target vector in dimension 5 is 300, which is less than... The node has a dimension of 5, therefore, the current node is set as the left branch, and the left branch is empty.

[0383] Step D22: The node splitting dimension is 5, and its value is 330. The target vector, with a dimension of 5, has a value of 300. The absolute value of the difference is 30, which is less than the last node in List_k. The distance is 30.01, therefore, the right branch may have a distance smaller than that of the node. The point at which the distance to the target vector is used to set the current node. The distance is calculated as follows;

[0384] serial number The 10th data point: {43.29,10.51,2,76.73,465,0.8,7.73,0,2,33.38,0.62,-1};

[0385] Dist(T_Target, 10) =

[0386] ;

[0387] Dist(T_Target, 10) is the distance between the reference vector and the target vector corresponding to the 10th data point.

[0388] Target vector and nodes The distance of 165.02 is greater than the distance of the last node in List_k. The distance to the target vector is used to keep the data in List_k unchanged.

[0389] Step D23: Current node The parent node is ,node ,node and nodes All left branch nodes have been visited; set the current node as the node. The parent node ⑦.

[0390] Step D24: Set the current node as parent node , The split dimension is 5, and the value is 230. The target vector has a dimension of 5 and a value of 300. The absolute value of the difference is 70, which is greater than the last node in List_k. The distance is 30.01, therefore The left branch of a node does not exist compared to the node. For points closer to the target vector, the list List_k is not updated. At this point, the root node of all data has been reached, and the access is complete.

[0391] Step D21: For the target vector m_Target and c m The calculation is performed using the two parameters _Target.

[0392] serial number Data point number 6: {44.32, 9.48, 2, 75.42, 318, 0.71, 10.25, 0, 2, 32.94, 0.43, -1};

[0393] serial number Data entry number 9: {43.29, 10.51, 2, 76.73, 318, 0.8, 10.25, 0, 2, 33.99, 0.52, 5};

[0394] serial number The third data point: {44.32, 9.48, 2, 75.42, 330, 0.71, 10.32, 0, 2, 32.26, 0.41, 5}.

[0395] The target vector is calculated using all elements in List_k as the basic data. m_Target, c m _Target, the calculation formula is as follows:

[0396]

[0397]

[0398] This embodiment proposes an intelligent acquisition scheme for weak-plane rock mass mechanical parameters based on historical big data from mines, as well as a scheme for the data infrastructure relationship to achieve efficient management and calculation of big data. It simplifies the process of solving rock mass mechanical parameters from rock mechanics parameters, considering that the more historical data available, the more accurate the calculated rock mass parameters, and it can efficiently process large amounts of data. This embodiment can intelligently, efficiently, and quickly solve slope rock mass mechanical parameters based on historical weak-plane rock mass mechanical parameters from mines, without the need for extensive in-situ rock mechanics tests or reliance on engineers' experience. It improves the accuracy and timeliness of rock mass mechanical parameters and reduces the cost of acquiring physical and mechanical parameters for complex weak-plane rock masses.

[0399] This application provides a rock mass mechanics parameter acquisition system, including:

[0400] A vector construction module is used to determine n measured mechanical parameters of a target mine slope and construct a target vector corresponding to the target mine slope; wherein, the dimensions of the target vector include the internal friction angle of the rock mass, the cohesion of the rock mass, the sectional dimension marker, and the n measured mechanical parameters;

[0401] A vector acquisition module is used to acquire multiple reference vectors from a database; wherein the reference vectors have the same dimension as the target vector.

[0402] The topology tree construction module is used to segment all the reference vectors based on the variance of the dimensions corresponding to n measured mechanical parameters, construct a topology tree corresponding to all the reference vectors according to the segmentation results, and set the segmentation dimension flag of all the reference vectors according to the segmentation results; wherein, the topology tree is a binary tree, and the segmentation dimension flag is used to describe the segmentation dimension of the nodes in the topology tree;

[0403] The query module is used to query the k reference vectors closest to the target vector in the topological relationship tree based on the segmentation dimension flag, and set the k reference vectors closest to the target vector as candidate mechanical parameter vectors;

[0404] The weighted calculation module is used to perform weighted calculations on the internal friction angle and cohesion of the rock mass for all the candidate mechanical parameter vectors, so as to obtain the internal friction angle and cohesion of the rock mass of the target mine slope.

[0405] This embodiment acquires n measured mechanical parameters of the target mine slope and constructs a corresponding target vector. It also retrieves multiple reference vectors with the same dimensions as the target vector from a database, segments all reference vectors using the variance of the dimensions corresponding to the n measured mechanical parameters, and constructs a corresponding topological relationship tree based on the segmentation results. Based on the obtained topological relationship tree, this embodiment identifies the k nearest reference vectors to the target vector in the topological relationship tree, thereby determining the internal friction angle and cohesion of the target mine slope based on these k nearest reference vectors. The above process constructs a topological relationship tree describing the similarity of the measured mechanical parameters between the reference vectors. Utilizing the structural advantages of the topological relationship tree, it can quickly locate reference vectors similar to the target mine slope. Therefore, this embodiment can improve the efficiency and reliability of acquiring the internal friction angle and cohesion of the rock mass.

[0406] Optionally, the query module segments all the reference vectors based on the variance of the dimensions corresponding to the n measured mechanical parameters, constructs a topological relationship tree corresponding to all the reference vectors based on the segmentation results, and sets the segmentation dimension flags of all the reference vectors based on the segmentation results, including:

[0407] Construct a current data set containing all the aforementioned reference vectors; calculate the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current data set, and select the dimension corresponding to the largest variance as the current splitting dimension; sort all the reference vectors in ascending order according to the current splitting dimension, select the middle reference vector in the sorting result as the splitting node of the current data set, and set the splitting dimension flag of the splitting node to the dimension index of the current splitting dimension; construct the left subtree set of the splitting node based on the reference vectors before the middle reference vector in the sorting result, and based on the sorting result... If the left subtree set is not empty, then the left subtree set is used as the new current data set, and the process of calculating the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current data set is repeated. If the right subtree set is not empty, then the right subtree set is used as the new current data set, and the process of calculating the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current data set is repeated. The topology tree is generated based on the hierarchical relationship between all the splitting nodes.

[0408] Furthermore, the process by which the query module queries the k nearest reference vectors to the target vector in the topological relationship tree based on the segmentation dimension flag includes: setting the root node of the topological relationship tree as the current node; adding a preset identifier to the current node; determining whether there are empty slots in the ordered list; wherein, the maximum number of nodes stored in the candidate node column is k; k < n, the candidate nodes in the ordered list are sorted according to vector distance, where the vector distance is the distance between the reference vector corresponding to the candidate node and the target vector; if there are empty slots, the current node is added to the ordered list; if there are no empty slots, it is determined whether the distance between the reference vector corresponding to the current node and the target vector is less than a critical distance; wherein, the critical distance is the maximum distance between the reference vector corresponding to the candidate node in the ordered list and the target vector; if it is less than the critical distance, the candidate node with the largest distance to the target vector is deleted from the ordered list. The process involves: adding the current node to an ordered list; determining if the current node has child nodes; if child nodes exist, selecting a new current node from its child nodes and adding a preset identifier to the current node; if no child nodes exist, recursively querying the parent node in the topological tree to find a parent node that meets a preset condition, where the preset condition is the existence of a child node without the preset identifier; determining if the absolute value of the difference between the value of the i-th dimension of the parent node that meets the preset condition and the value of the target vector in the i-th dimension is less than the critical distance; if yes, setting the child node of the parent node that meets the preset condition without the preset identifier as the new current node and adding the preset identifier to the current node; if no, setting the candidate nodes in the ordered list as the k reference vectors closest to the target vector; where the value of the splitting dimension identifier of the parent node that meets the preset condition is i.

[0409] Furthermore, if the current node has left branch child nodes and left branch child nodes, the process of the query module selecting a new current node from the child nodes of the current node includes: taking the value of the j-th dimension of the current node as a reference value according to the value j of the split dimension marker; determining whether the value of the target vector in the j-th dimension is less than the reference value; if it is less than the reference value, setting the left branch child node of the current node as the new current node and proceeding to the step of adding a preset identifier to the current node; if it is greater than or equal to the reference value, setting the right branch child node of the current node as the new current node and proceeding to the step of adding a preset identifier to the current node.

[0410] Furthermore, if the current node only has left branch child nodes, the process of the query module selecting a new current node from the child nodes of the current node includes: taking the value of the j-th dimension of the current node as a reference value according to the value j of the split dimension marker; determining whether the value of the target vector in the j-th dimension is less than the reference value; if it is less than the reference value, setting the left branch child node of the current node as the new current node and proceeding to the step of adding a preset identifier to the current node; if it is greater than or equal to the reference value, determining whether the absolute value of the difference between the value of the j-th dimension of the current node and the value of the target vector in the j-th dimension is less than the critical distance; if yes, setting the right branch child node of the current node as the new current node and proceeding to the step of adding a preset identifier to the current node; if no, proceeding to the step of recursively querying the parent node that meets the preset conditions in the topological relationship tree.

[0411] Furthermore, if the current node only has right-branch child nodes, the process of the query module selecting a new current node from the child nodes of the current node includes: taking the value of the j-th dimension of the current node as a reference value according to the value j of the split dimension marker; determining whether the value of the target vector in the j-th dimension is less than the reference value; if it is greater than or equal to the reference value, then setting the right-branch child node of the current node as the new current node, and proceeding to the step of adding a preset identifier to the current node; if it is less than the reference value, then determining whether the absolute value of the difference between the value of the j-th dimension of the current node and the value of the target vector in the j-th dimension is less than the critical distance; if yes, then setting the left-branch child node of the current node as the new current node, and proceeding to the step of adding a preset identifier to the current node; if no, then proceeding to the step of recursively querying the parent node that meets the preset conditions in the topological relationship tree.

[0412] Furthermore, it also includes:

[0413] The determination module is used to determine that the query is complete if the current node has no child nodes and the result of recursively querying the parent node that meets the preset conditions from the current node is empty, and to set the candidate nodes in the ordered list as the k reference vectors closest to the target vector.

[0414] Furthermore, the weighted calculation module performs weighted calculations on the internal friction angle and cohesion of all the candidate mechanical parameter vectors to obtain the internal friction angle and cohesion of the target mine slope. This process includes: setting the reciprocal of the distance between each candidate mechanical parameter vector and the target vector as a weighting factor; calculating the ratio of the weighting factor of each candidate mechanical parameter vector to the sum of the weighting factors of all candidate mechanical parameter vectors to obtain the weight value of each candidate mechanical parameter vector; performing weighted calculations on the internal friction angle of all the candidate mechanical parameter vectors based on the weight values ​​to obtain the internal friction angle of the target mine slope; and performing weighted calculations on the cohesion of all the candidate mechanical parameter vectors based on the weight values ​​to obtain the cohesion of the target mine slope.

[0415] Since the embodiments of the system part correspond to the embodiments of the method part, please refer to the description of the embodiments of the method part for the embodiments of the system part, and they will not be repeated here.

[0416] This application also provides a storage medium on which a computer program is stored, which, when executed, can perform the steps provided in the above embodiments. The storage medium may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0417] This application also provides an electronic device that may include a memory and a processor. The memory stores a computer program, and when the processor calls the computer program in the memory, it can implement the steps provided in the above embodiments. Of course, the electronic device may also include various network interfaces, power supplies, and other components.

[0418] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

[0419] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A method for obtaining rock mass mechanical parameters, characterized in that, include: Determine n measured mechanical parameters of the target mine slope and construct the target vector corresponding to the target mine slope; wherein, the dimensions of the target vector include the internal friction angle of the rock mass, the cohesion of the rock mass, the sectional dimension marker, and the n measured mechanical parameters; Multiple reference vectors are obtained from the database; wherein the reference vectors have the same dimension as the target vector. All reference vectors are segmented based on the variance of the dimensions corresponding to n measured mechanical parameters. A topological relationship tree corresponding to all reference vectors is constructed based on the segmentation results, and a segmentation dimension flag is set for all reference vectors based on the segmentation results. The topological relationship tree is a binary tree, and the segmentation dimension flag is used to describe the segmentation dimension of the nodes in the topological relationship tree. Based on the segmentation dimension flag, query the k reference vectors that are closest to the target vector in the topological relationship tree, and set the k reference vectors closest to the target vector as candidate mechanical parameter vectors; The internal friction angle and cohesion of the rock mass are weighted and calculated for all the candidate mechanical parameter vectors to obtain the internal friction angle and cohesion of the rock mass of the target mine slope.

2. The method for obtaining rock mass mechanical parameters according to claim 1, characterized in that, All reference vectors are segmented based on the variance of the dimensions corresponding to n measured mechanical parameters. A topological relationship tree corresponding to all reference vectors is constructed based on the segmentation results. Segmentation dimension flags for all reference vectors are set based on the segmentation results, including: Construct a current data set containing all the aforementioned reference vectors; Calculate the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current dataset, and select the dimension corresponding to the largest variance as the current split dimension; Sort all the reference vectors in ascending order according to the current splitting dimension, select the middle reference vector in the sorting result as the splitting node of the current data set, and set the splitting dimension flag of the splitting node to the dimension number of the current splitting dimension. The left subtree set of the splitting node is constructed based on the reference vector before the intermediate reference vector in the sorting result, and the right subtree set of the splitting node is constructed based on the reference vector after the intermediate reference vector in the sorting result. If the left subtree set is not empty, then the left subtree set is used as the new current data set, and the process re-enters the step of calculating the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current data set; If the right subtree set is not empty, then the right subtree set is used as the new current data set, and the process re-enters the step of calculating the variance of the dimensions corresponding to the n measured mechanical parameters of all reference vectors in the current data set; The topology tree is generated based on the hierarchical relationship between all the split nodes.

3. The method for obtaining rock mass mechanical parameters according to claim 1, characterized in that, Based on the segmentation dimension flag, query the k nearest reference vectors to the target vector in the topological relationship tree, including: Set the root node of the topological relationship tree as the current node; Add a preset identifier to the current node; Determine if there are empty slots in the ordered list; wherein, the maximum number of nodes stored in the candidate node column is k; k < n, and the candidate nodes in the ordered list are sorted according to vector distance, wherein the vector distance is the distance between the reference vector corresponding to the candidate node and the target vector; If there is an empty slot, the current node is added to the ordered list; If there are no empty slots, determine whether the distance between the reference vector corresponding to the current node and the target vector is less than the critical distance; wherein, the critical distance is the maximum distance between the reference vector corresponding to the candidate node in the ordered list and the target vector. If the distance is less than the critical distance, the candidate node with the largest distance to the target vector is removed from the ordered list, and the current node is added to the ordered list. Determine if the current node has child nodes; If child nodes exist, select a new current node from the child nodes of the current node and proceed to the step of adding a preset identifier to the current node; If no child node exists, then recursively query the parent node that meets the preset condition from the current node in the topology tree; wherein, the preset condition is that there is a child node that has not been added with the preset identifier; Determine whether the absolute value of the difference between the value of the i-th dimension of the parent node that meets the preset conditions and the value of the target vector in the i-th dimension is less than the critical distance; if yes, set the child node of the parent node that meets the preset conditions without the preset label as the new current node, and proceed to the step of adding the preset label to the current node; if no, set the candidate nodes in the ordered list as the k reference vectors closest to the target vector; wherein, the value of the split dimension label of the parent node that meets the preset conditions is i.

4. The method for obtaining rock mass mechanical parameters according to claim 3, characterized in that, If the current node has left-branch child nodes and left-branch child nodes, then a new current node is selected from the child nodes of the current node, including: The value of the j-th dimension of the current node is used as the reference value based on the value j of the segmentation dimension flag; Determine whether the value of the target vector in the j-th dimension is less than the reference value; If it is less than the reference value, then the left branch child node of the current node is set as the new current node, and the step of adding a preset identifier to the current node is entered; If the value is greater than or equal to the reference value, then the right branch child node of the current node is set as the new current node, and the process proceeds to the step of adding a preset identifier to the current node.

5. The method for obtaining rock mass mechanical parameters according to claim 3, characterized in that, If the current node has only left-branch child nodes, then a new current node is selected from the child nodes of the current node, including: The value of the j-th dimension of the current node is used as the reference value based on the value j of the segmentation dimension flag; Determine whether the value of the target vector in the j-th dimension is less than the reference value; If it is less than the reference value, then the left branch child node of the current node is set as the new current node, and the step of adding a preset identifier to the current node is entered; If the value is greater than or equal to the reference value, then determine whether the absolute value of the difference between the value of the j-th dimension of the current node and the value of the target vector in the j-th dimension is less than the critical distance; if yes, then set the right branch child node of the current node as the new current node and proceed to the step of adding a preset identifier to the current node; if no, then proceed to the step of recursively querying the parent node that meets the preset conditions in the topological relationship tree.

6. The method for obtaining rock mass mechanical parameters according to claim 3, characterized in that, If the current node has only right-branch child nodes, then a new current node is selected from the child nodes of the current node, including: The value of the j-th dimension of the current node is used as the reference value based on the value j of the segmentation dimension flag; Determine whether the value of the target vector in the j-th dimension is less than the reference value; If the value is greater than or equal to the reference value, then the right branch child node of the current node is set as the new current node, and the step of adding a preset identifier to the current node is initiated. If the value is less than the reference value, then determine whether the absolute value of the difference between the value of the j-th dimension of the current node and the value of the target vector in the j-th dimension is less than the critical distance; if yes, then set the left branch child node of the current node as the new current node and proceed to the step of adding a preset identifier to the current node; if no, then proceed to the step of recursively querying the parent node that meets the preset conditions in the topological relationship tree.

7. The method for obtaining rock mass mechanical parameters according to claim 3, characterized in that, Also includes: If the current node has no child nodes and the result of recursively querying the parent node that meets the preset conditions from the current node is empty, then the query is considered complete, and the candidate nodes in the ordered list are set as the k reference vectors closest to the target vector.

8. The method for obtaining rock mass mechanical parameters according to claim 1, characterized in that, The internal friction angle and cohesion of the rock mass are weighted and calculated for all the candidate mechanical parameter vectors to obtain the internal friction angle and cohesion of the rock mass of the target mine slope, including: The reciprocal of the distance between each candidate mechanical parameter vector and the target vector is set as the weighting influence factor; The weight value of each candidate mechanical parameter vector is obtained by calculating the ratio of the weight influence factor of each candidate mechanical parameter vector to the sum of the weight influence factors of all candidate mechanical parameter vectors. The internal friction angle of the rock mass of the target mine slope is obtained by weighting the internal friction angle of all the candidate mechanical parameter vectors according to the weight values. The rock mass cohesion of the target mine slope is obtained by weighting the rock mass cohesion of all the candidate mechanical parameter vectors according to the weight values.

9. A system for acquiring rock mass mechanical parameters, characterized in that, include: A vector construction module is used to determine n measured mechanical parameters of a target mine slope and construct a target vector corresponding to the target mine slope; wherein, the dimensions of the target vector include the internal friction angle of the rock mass, the cohesion of the rock mass, the sectional dimension marker, and the n measured mechanical parameters; A vector acquisition module is used to acquire multiple reference vectors from a database; wherein the reference vectors have the same dimension as the target vector. The topology tree construction module is used to segment all the reference vectors based on the variance of the dimensions corresponding to n measured mechanical parameters, construct a topology tree corresponding to all the reference vectors according to the segmentation results, and set the segmentation dimension flag of all the reference vectors according to the segmentation results; wherein, the topology tree is a binary tree, and the segmentation dimension flag is used to describe the segmentation dimension of the nodes in the topology tree; The query module is used to query the k reference vectors closest to the target vector in the topological relationship tree based on the segmentation dimension flag, and set the k reference vectors closest to the target vector as candidate mechanical parameter vectors; The weighted calculation module is used to perform weighted calculations on the internal friction angle and cohesion of the rock mass for all the candidate mechanical parameter vectors, so as to obtain the internal friction angle and cohesion of the rock mass of the target mine slope.

10. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor, when calling the computer program in the memory, implements the steps of the rock mass mechanics parameter acquisition method as described in any one of claims 1 to 8.

11. A storage medium, characterized in that, The storage medium stores computer-executable instructions, which, when loaded and executed by a processor, implement the steps of the rock mass mechanical parameter acquisition method as described in any one of claims 1 to 8.

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