Pumped storage power station cable three-dimensional laying obstacle avoidance path planning method

Abstract

The invention relates to the technical field of data processing, and discloses a pumped storage power station cable three-dimensional laying obstacle avoidance path planning method, which comprises the following steps: carrying out standardized integration on multi-source basic data to obtain standardized data; performing obstacle correlation analysis on the standardized data to obtain obstacle feature data, and performing feature vector mapping on the obstacle feature data to obtain a classification feature vector set; performing hierarchical spatial clustering on the classification feature vector set to obtain a hierarchical barrier space tree; performing constraint matching mapping on the hierarchical obstacle space tree to obtain a multi-dimensional constraint set; based on the multi-dimensional constraint set, performing connectivity topology construction on the hierarchical barrier space tree to obtain a candidate path network; performing multi-dimensional collaborative evaluation on candidate paths in the candidate path network to obtain path evaluation data, and performing situational decision on the path evaluation data to obtain an optimal cable laying path; according to the invention, the planning efficiency of the pumped storage power station cable three-dimensional laying obstacle avoidance path can be improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method for planning obstacle avoidance paths for three-dimensional cable laying in pumped storage power stations. Background Technology

[0002] In the cable laying design of large-scale power projects such as pumped storage power stations, traditional path planning methods mainly rely on two-dimensional plan drawings and engineers' on-site experience for manual planning. Existing technologies typically employ simplified two-dimensional projections or linear planning based on fixed rules, which struggles to accurately handle the problem of avoiding dense obstacles in complex three-dimensional space. These methods do not adequately consider the mechanical performance constraints of cables, construction safety requirements, and long-term operating environment factors, resulting in planned paths that often have problems such as excessively small turning radii, insufficient safety distances from equipment, or crossing high-risk areas. This not only increases construction difficulty and safety risks but may also affect the long-term service life of cables and the overall reliability of the power station.

[0003] Existing technologies lack systematic support for multi-objective collaborative optimization in engineering projects, failing to effectively balance constraints such as construction feasibility, economic cost, safety level, and ease of operation and maintenance during the planning phase. Traditional methods are rigid in dealing with dynamically changing construction conditions and environmental factors, struggling to generate optimal path solutions with engineering adaptability. This often leads to frequent adjustments to the design during the construction phase, significantly increasing project costs and schedule uncertainty. As pumped storage power stations develop towards large-scale and highly complex designs, existing technologies are insufficient to meet the engineering requirements of intelligent and refined cable laying design. Therefore, improving the planning efficiency of three-dimensional cable laying obstacle avoidance paths has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a method for planning obstacle avoidance paths in three-dimensional cable laying for pumped storage power stations, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a method for three-dimensional obstacle avoidance path planning for cable laying in pumped storage power stations, comprising: S1. Standardize and integrate the multi-source basic data of the cable laying area in the pumped storage power station to obtain standardized multi-basic data of the cable laying area; S2. Perform obstacle correlation analysis on the standardized basic data to obtain obstacle feature data of the cable laying area, and perform feature vector mapping on the obstacle feature data to obtain the classification feature vector set of the obstacle feature data; S3. Perform hierarchical spatial clustering on the classification feature vector set to obtain a hierarchical obstacle spatial tree of the cable laying area; S4. Based on the preset laying constraint rules, perform constraint matching mapping on the hierarchical obstacle space tree to obtain a multi-dimensional constraint set for the cable laying area; S5. Based on the multidimensional constraint set, the connectivity topology of the hierarchical obstacle space tree is constructed to obtain the candidate path network of the cable laying area. S6. Perform multi-dimensional collaborative evaluation on the candidate paths in the candidate path network to obtain the path evaluation data of the candidate paths, and make contextualized decisions on the path evaluation data to obtain the optimal cable laying path for the pumped storage power station.

[0006] In a preferred embodiment, the standardization and integration of multi-source basic data on the cable laying area in the pumped storage power station to obtain standardized basic data for the cable laying area includes: Spatial normalization was performed on the multi-source basic data of the cable laying area in the pumped storage power station to obtain the unified spatial basic data of the cable laying area. The spatial unified basic data is processed to standardize the format, resulting in structured basic data of the cable laying area; Data cleaning is performed on the structured basic data to obtain clean basic data of the cable laying area; Multidimensional information synchronization and registration are performed on the cleanroom basic data to obtain standardized basic data for the cable laying area.

[0007] In a preferred embodiment, the step of performing obstacle correlation analysis on standardized basic data to obtain obstacle feature data of the cable laying area, and performing feature vector mapping on the obstacle feature data to obtain a classification feature vector set of the obstacle feature data, includes: Obstacle correlation analysis was performed on standardized basic data to obtain an obstacle dataset for the cable laying area; Geometric features were extracted from the obstacle dataset to obtain obstacle feature data for the cable laying area; Based on the feature attributes of the obstacle feature data, attribute-driven classification is performed on the obstacle feature data to obtain classified obstacle feature data of the cable laying area. The obstacle feature data is vectorized to obtain the classification feature vector set of the obstacle feature data.

[0008] In a preferred embodiment, the hierarchical spatial clustering of the classification feature vector set to obtain a hierarchical obstacle spatial tree for the cable laying area includes: Based on the spatial layout of the cable laying area, the classification feature vector set is spatially grouped to obtain the regional feature vector group of the cable laying area. Based on the semantic classification system of obstacles in cable laying areas, multi-level semantic annotation is performed on the regional feature vector groups to obtain the semantic hierarchical structure of the regional feature vector groups. Based on the spatial adjacency relationship of obstacles in the semantic hierarchical structure, a topological connection relationship is constructed in the semantic hierarchical structure to obtain the spatial connection network of obstacles in the cable laying area. The obstacle spatial connection network is transformed into a tree structure to obtain the obstacle tree structure data of the cable laying area. Then, a hierarchical index is constructed on the obstacle tree structure data to obtain the hierarchical obstacle spatial tree of the cable laying area.

[0009] In a preferred embodiment, the obstacle engineering semantic classification system based on cable laying areas performs multi-layer semantic annotation on the regional feature vector groups to obtain a semantic hierarchical structure of the regional feature vector groups, including: Based on the engineering semantic classification system of obstacles in cable laying areas, the functional attributes of obstacles in the regional feature vector group are identified to obtain the functional semantic data of obstacles in the regional feature vector group. Based on the construction safety impact level in the obstacle engineering semantic classification system, the obstacle functional semantic data is labeled with safety level to obtain the obstacle safety semantic data of the regional feature vector group. Based on the operation and maintenance accessibility evaluation rules in the obstacle engineering semantic classification system, the operation and maintenance attributes of obstacle safety semantic data are identified to obtain obstacle operation and maintenance semantic data of regional feature vector groups. Hierarchical node association is performed on obstacle operation and maintenance semantic data, obstacle safety semantic data, and obstacle function semantic data to obtain a semantic hierarchical structure of regional feature vector groups.

[0010] In a preferred embodiment, the constraint matching mapping of the hierarchical obstacle space tree based on preset laying constraint rules to obtain a multidimensional constraint set of the cable laying area includes: Based on the cable mechanical performance constraint rules in the preset laying constraint rules, the spatial parameters of the obstacle nodes in the hierarchical obstacle space tree are geometrically matched and verified to obtain the spatial geometric constraints of the obstacle nodes. Based on the construction safety operation specifications in the laying constraint rules, a safety impact assessment is conducted on the spatial attributes of obstacle nodes to obtain the construction safety constraints of obstacle nodes. Based on the equipment operating environment standards in the laying constraint rules, the environmental parameters of the obstacle nodes are evaluated for environmental adaptability, and the thermal environment constraints of the obstacle nodes are obtained. By performing corresponding node-structured mapping of spatial geometric constraints, construction constraints, and thermal environment constraints, a multidimensional constraint set for the cable laying area is obtained.

[0011] In a preferred embodiment, the step of constructing a connectivity topology for a hierarchical obstacle space tree based on a multidimensional constraint set to obtain a candidate path network for the cable laying area includes: Based on spatial geometric constraints and construction safety constraints, spatial reachability analysis is performed on adjacent nodes in a hierarchical obstacle spatial tree to obtain the preliminary connectivity relationship between adjacent nodes. Based on thermal environment constraints, environmental feasibility screening is performed on the preliminary connectivity relationships to obtain feasible connection relationships between adjacent nodes; A multi-level topology network is constructed based on the hierarchical obstacle space tree and feasible connection relationships to obtain the path topology network of the cable laying area. Redundant paths are eliminated from the path topology network to obtain the candidate path network for the cable laying area.

[0012] In a preferred embodiment, the step of constructing a multi-level topology network from the hierarchical obstacle space tree and feasible connection relationships to obtain the path topology network of the cable laying area includes: Based on the hierarchical obstacle space tree, the cable laying area is spatially mapped to obtain the hierarchical spatial partitions of the hierarchical obstacle space tree; Based on feasible connectivity, a topological relationship is constructed for the connection paths between obstacle nodes in the hierarchical spatial partition, resulting in a hierarchical connected subnet of the hierarchical spatial partition. By performing hierarchical structure fusion on the hierarchical connected subnets, an aggregated topology network with hierarchical spatial partitioning is obtained; Global path connectivity verification is performed on the aggregated topology network to obtain the path topology network of the cable laying area.

[0013] In a preferred embodiment, the step of performing multi-dimensional collaborative evaluation on candidate paths in the candidate path network to obtain path evaluation data for the candidate paths, and then performing contextualized decision-making based on the path evaluation data to obtain the optimal cable laying path for the pumped storage power station, includes: Based on the evaluation index system for cable laying engineering of pumped storage power stations, the candidate paths in the candidate path network are quantified in multiple dimensions to obtain multi-dimensional score data of the candidate paths. The multi-dimensional score data is then structured and integrated to obtain the path score matrix of the candidate paths. Based on the design conditions and environmental conditions of the cable laying of pumped storage power stations, the multi-dimensional weights in the path scoring matrix are dynamically adjusted to obtain the weighted scoring matrix of the candidate paths. A comprehensive utility evaluation is performed on the weighted scoring matrix and candidate paths to obtain a comprehensive utility score for the candidate paths. Candidate paths with a comprehensive utility score exceeding a preset threshold are considered feasible laying paths. Based on the preset engineering decision-making criteria, the feasible laying paths are adaptively optimized to obtain the optimal cable laying path for the pumped storage power station.

[0014] In a preferred embodiment, the step of dynamically adjusting the multi-dimensional weights in the path scoring matrix based on the design and environmental conditions for pumped storage power station cable laying to obtain a weighted scoring matrix for candidate paths includes: Based on the design working condition plan for cable laying of pumped storage power stations, the weights of the construction feasibility dimension in the path scoring matrix are configured in a phased adaptation manner to obtain the construction weight scheme of candidate paths. Based on the environmental condition contingency plan for cable laying in pumped storage power stations, the weights of the safety risk dimension in the path scoring matrix are configured in a scenario-responsive manner to obtain the environmental scenario weight scheme for candidate paths. Based on the resource scheduling scheme in the design working condition plan, the resource optimization weight scheme of the economic dimension in the path scoring matrix is ​​optimized and allocated to obtain the resource optimization weight scheme of the candidate path. Based on the construction weight scheme, the environmental scenario weight scheme, and the resource optimization weight scheme, the path scoring matrix is ​​coupled with multi-dimensional weights to obtain the weighted scoring matrix of the candidate paths.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. By constructing a "hierarchical obstacle space tree" and a "multi-dimensional constraint set," a precise digital representation and systematic constraint integration of the complex three-dimensional laying environment of pumped storage power stations were achieved. This technical approach transforms multi-source heterogeneous engineering data into a structured spatial semantic model and couples multi-dimensional engineering rules such as mechanical performance, construction safety, and operating environment, thereby ensuring a deep adaptation of the solution to the physical space and engineering specifications from the source of path planning. This effectively improves the engineering feasibility, safety compliance, and long-term operational reliability of the path solution, laying a solid foundation for generating a high-quality construction plan in one go.

[0016] 2. The "multi-level topology network construction" and "contextualized dynamic decision-making" mechanisms employed in this method significantly enhance the intelligence and adaptability of path planning. A candidate path network is generated through recursive topology fusion, and the evaluation weights are dynamically adjusted based on design conditions and environmental contingency plans, ultimately achieving optimal path selection under multi-objective collaborative optimization. This process not only greatly improves planning efficiency and automation but also ensures that the output solution possesses excellent robustness and economy when facing complex construction conditions and changing environmental factors, providing scientific, efficient, and reliable intelligent design support for cable laying projects in large pumped storage power stations. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a method for planning obstacle avoidance paths in three-dimensional cable laying for pumped storage power stations, as provided in an embodiment of the present invention.

[0018] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0020] This application provides a method for planning obstacle avoidance paths for three-dimensional cable laying in pumped storage power stations. The execution entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0021] Reference Figure 1 The diagram shown is a flowchart illustrating a three-dimensional obstacle avoidance path planning method for pumped storage power station cables according to an embodiment of the present invention. In this embodiment, the three-dimensional obstacle avoidance path planning method for pumped storage power station cables includes: S1. Standardize and integrate the multi-source basic data of the cable laying area in the pumped storage power station to obtain standardized multi-basic data of the cable laying area; In this embodiment of the invention, the standardization and integration of multi-source basic data of the cable laying area in the pumped storage power station to obtain standardized basic data of the cable laying area includes: Spatial normalization was performed on the multi-source basic data of the cable laying area in the pumped storage power station to obtain the unified spatial basic data of the cable laying area. The spatial unified basic data is processed to standardize the format, resulting in structured basic data of the cable laying area; Data cleaning is performed on the structured basic data to obtain clean basic data of the cable laying area; Multidimensional information synchronization and registration are performed on the cleanroom basic data to obtain standardized basic data for the cable laying area.

[0022] Basic data from various sensors, design drawings, and engineering survey reports were acquired in the cable laying area of ​​the pumped storage power station. This data differed in coordinate systems, scales, and units of measurement. All data was transformed and unified into a single three-dimensional Cartesian coordinate system. The data transformation process involved calculating the corresponding coordinate transformation matrix for each data record, based on the definition of its original coordinate system and the spatial vector relationship between the origin and the target origin. This matrix was then used to convert the original three-dimensional coordinates into values ​​in the new coordinate system. Through this process, all data possessed a unified spatial reference benchmark, forming unified spatial basic data for the cable laying area.

[0023] The unified spatial foundation data includes various formats such as 3D point clouds, CAD model line segments, and equipment attribute tables. All this data is unified and transformed into an internally structured data model. For 3D geometric data, it is represented as a set of points with 3D coordinates, line segments composed of points, and polygonal faces enclosed by these line segments, establishing topological connections between points, lines, and faces. For attribute data, it is organized into a two-dimensional table, where each row corresponds to an entity and each column corresponds to an attribute field. Each row of this table is associated with a corresponding geometric entity in the structured data model through a unique identifier. This structured set, establishing the correspondence between geometry and attributes, constitutes the structured foundation data for the cable laying area.

[0024] The structured foundation data may contain some errors or incomplete records. Check and correct topological errors in the geometric data and logical errors in the attribute data. For records lacking key attributes such as equipment type or size, complete them according to the standard equipment library in the engineering database. After these identification, correction, and completion operations, the resulting dataset is geometrically and logically complete and consistent, forming the clean foundation data for the cable laying area.

[0025] While the geometric and attribute information in the cleanroom infrastructure data are corresponding in terms of data volume, it is crucial to ensure their precise alignment in spatial location and logical meaning. This involves accurately binding the attribute description information of each device to its 3D geometric model. For each device entry in the attribute table, a corresponding geometric entity within its theoretical installation area is searched in the 3D geometric model. Matching is verified by calculating the spatial distance between the centroid of the geometric entity and the coordinates recorded in the device entry. A successful match is confirmed when the distance is less than a set tolerance threshold, and a one-to-one association is established in the database. Furthermore, for the same physical entity described in data from different periods or sources, such as a valve, which may exist in both the device table and piping diagram, their spatial locations and key identifiers are compared to identify them as the same object, and their attribute information is merged. After completing these precise spatial associations and logical mergings, a standardized infrastructure data set for the cable laying area is obtained, where geometry, attributes, and semantics are fully synchronized and aligned.

[0026] The above steps achieve deep fusion and high-precision structuring of multi-source heterogeneous engineering data. Spatial normalization unifies data from different sources into a common three-dimensional coordinate system, laying the foundation for accurate spatial analysis. Format standardization transforms diverse data into a unified structural model, achieving an organic combination of geometric and attribute information. The data cleaning process identifies and corrects errors and missing data, ensuring data integrity and logical consistency. The multi-dimensional information synchronization criterion ensures complete alignment of all information at both spatial and logical levels through precise matching of spatial location and semantic identifiers. The resulting standardized basic data provides an accurate, complete, and reliable single data source for subsequent obstacle analysis and path planning.

[0027] S2. Perform obstacle correlation analysis on the standardized basic data to obtain obstacle feature data of the cable laying area, and perform feature vector mapping on the obstacle feature data to obtain the classification feature vector set of the obstacle feature data; In this embodiment of the invention, the step of performing obstacle correlation analysis on standardized basic data to obtain obstacle feature data of the cable laying area, and performing feature vector mapping on the obstacle feature data to obtain a classification feature vector set of the obstacle feature data, includes: Obstacle correlation analysis was performed on standardized basic data to obtain an obstacle dataset for the cable laying area; Geometric features were extracted from the obstacle dataset to obtain obstacle feature data for the cable laying area; Based on the feature attributes of the obstacle feature data, attribute-driven classification is performed on the obstacle feature data to obtain classified obstacle feature data of the cable laying area. The obstacle feature data is vectorized to obtain the classification feature vector set of the obstacle feature data.

[0028] From the standardized baseline data that has already been registered, all entities that may obstruct cable laying are identified according to pre-defined engineering semantic rules. These rules clearly define the types of obstacles, such as walls, large pipes, load-bearing columns, installed electrical cabinets, and ventilation ducts. The system traverses each geometric entity and its associated attribute table in the standardized baseline data, comparing the entity type with the list of obstacle types. Entities that match successfully, along with all their attribute information, are extracted. The collection of all these identified entities constitutes the obstacle dataset for the cable laying area.

[0029] For each entity in the obstacle dataset, the system extracts key information describing its spatial shape and occupied area from its 3D geometric model. For a cuboid-shaped equipment cabinet, the system calculates the 3D coordinates of its eight vertices and determines the minimum bounding box of its circumscribed cuboid, recording the length, width, height, and spatial position and orientation of this bounding box. For a cylindrical pipe, the system extracts the coordinates of its starting and ending points, the pipe radius, and the axial direction vector. This collection of geometric descriptions, calculated from each obstacle entity, accurately characterizing its 3D dimensions, shape, position, and orientation, constitutes the obstacle feature data for the cable laying area.

[0030] The obstacle feature data is grouped based on the inherent attributes of each entity, according to the commonalities they exhibit in cable laying projects and their similar impact on path planning. For example, all immovable permanent structures, such as concrete walls and load-bearing columns, are categorized as rigid fixed obstacles. All facilities that may allow cables to cross or attach under certain conditions, such as cable trays and ventilation ducts, are categorized as negotiable obstacles. Furthermore, all equipment areas with specific requirements for electromagnetic or thermal environments, such as the vicinity of main transformers, are categorized as environmentally sensitive areas. This process of classifying each entry in the obstacle feature data into a specific project category according to preset attribute rules ultimately produces categorized obstacle feature data for cable laying areas.

[0031] For each entry in the obstacle feature data, it is transformed into a vector consisting of a series of ordered numerical values ​​for subsequent mathematical processing. Each dimension of this vector corresponds to a quantified feature. The first few values ​​of the vector can represent the coordinates of the center point of the bounding box of the obstacle, the following values ​​can represent the dimensions of the bounding box in three directions, and the subsequent values ​​can be a code representing its category, for example, using number one to represent a rigid fixed obstacle and number two to represent a negotiable obstacle. The system arranges these feature values ​​of each obstacle in a fixed, predefined order to form a complete numerical sequence. The set of such numerical sequences corresponding to all obstacles is the classification feature vector set of the obstacle feature data.

[0032] The beneficial effect is the systematic transformation from raw data to structured feature vectors, laying a precise data foundation for intelligent path planning. Through semantic filtering of standardized data, all relevant obstacles are systematically identified, forming a complete obstacle set. Precise geometric feature extraction transforms each obstacle into a measurable spatial description, ensuring the accuracy of subsequent analysis. Classification based on engineering attributes summarizes complex environmental information into categories with clear engineering significance, simplifying the problem's complexity. The final feature vectorization process unifies heterogeneous geometric and attribute information into a standardized mathematical expression, constructing a standardized feature dataset that can be directly used for subsequent spatial clustering and path search.

[0033] S3. Perform hierarchical spatial clustering on the classification feature vector set to obtain a hierarchical obstacle spatial tree of the cable laying area; In this embodiment of the invention, the hierarchical spatial clustering of the classification feature vector set to obtain a hierarchical obstacle spatial tree of the cable laying area includes: Based on the spatial layout of the cable laying area, the classification feature vector set is spatially grouped to obtain the regional feature vector group of the cable laying area. Based on the semantic classification system of obstacles in cable laying areas, multi-level semantic annotation is performed on the regional feature vector groups to obtain the semantic hierarchical structure of the regional feature vector groups. Based on the spatial adjacency relationship of obstacles in the semantic hierarchical structure, a topological connection relationship is constructed in the semantic hierarchical structure to obtain the spatial connection network of obstacles in the cable laying area. The obstacle spatial connection network is transformed into a tree structure to obtain the obstacle tree structure data of the cable laying area. Then, a hierarchical index is constructed on the obstacle tree structure data to obtain the hierarchical obstacle spatial tree of the cable laying area.

[0034] The obstacle engineering semantic classification system based on cable laying areas performs multi-layer semantic annotation on the regional feature vector groups to obtain a semantic hierarchical structure of the regional feature vector groups, including: Based on the engineering semantic classification system of obstacles in cable laying areas, the functional attributes of obstacles in the regional feature vector group are identified to obtain the functional semantic data of obstacles in the regional feature vector group. Based on the construction safety impact level in the obstacle engineering semantic classification system, the obstacle functional semantic data is labeled with safety level to obtain the obstacle safety semantic data of the regional feature vector group. Based on the operation and maintenance accessibility evaluation rules in the obstacle engineering semantic classification system, the operation and maintenance attributes of obstacle safety semantic data are identified to obtain obstacle operation and maintenance semantic data of regional feature vector groups. Hierarchical node association is performed on obstacle operation and maintenance semantic data, obstacle safety semantic data, and obstacle function semantic data to obtain a semantic hierarchical structure of regional feature vector groups.

[0035] Based on the natural division of the power plant's physical structure, including buildings, corridors, and shafts, the entire cable laying area is divided into several continuous subspaces in three-dimensional space. The system determines which subspace each feature vector in the classification feature vector set belongs to, based on its spatial coordinates, and merges all feature vectors within the same subspace. Through this spatial attribution and merging operation based on physical location, a set of regional feature vectors corresponding one-to-one with the physical area of ​​the cable laying area is formed.

[0036] A predefined obstacle engineering semantic classification system is invoked. This system contains the functional definitions of various obstacles in the design. Based on this system, each obstacle in the region feature vector group is assigned a clear functional attribute label. After this annotation is completed, each obstacle is supplemented with semantic information describing its engineering function. This information, together with the original feature vector, constitutes the obstacle functional semantic data of the region feature vector group.

[0037] Further, based on the classification standards for safety risk levels during construction within the semantic classification system, the functional semantic data of obstacles with already labeled functional attributes are evaluated and marked. This process determines the degree of risk that an obstacle may pose to construction personnel or equipment based on its type, state, and location. After this evaluation and marking, each obstacle gains additional semantic information describing its impact on construction safety, thus forming obstacle safety semantic data for a set of regional feature vectors.

[0038] Continuing to use the evaluation rules regarding accessibility and ease of operation for later equipment operation and maintenance within the semantic classification system, the safety semantic data of obstacles already containing safety information is further labeled with operational dimensions. The evaluation rules consider whether obstacles are easily accessible to maintenance personnel for operation. After this labeling, each obstacle is further supplemented with semantic information describing its operational characteristics. This information, combined with the previous data, forms the obstacle operational semantic data for the regional feature vector group.

[0039] The three layers of semantic information of the same obstacle—functional attributes, safety level, and operational attributes—are organized into a hierarchical tree structure. The obstacle itself is used as the root node, and three child nodes are created and attached to the root node. The first child node stores its functional attribute data, the second its safety level data, and the third its operational attribute data. This process is repeated for all obstacles, establishing independent semantic units. These semantic units are then aggregated according to their physical regions. The semantic units of all obstacles within the same region collectively form a larger tree structure. This structure clearly displays the multi-layered engineering semantics of each obstacle within the region; this is the semantic hierarchical structure of the region feature vector group.

[0040] Within the established semantic hierarchical structure, the geometric relationship between any two obstacles in three-dimensional space is analyzed. The shortest distance between the bounding boxes of the two obstacles is calculated, and it is determined whether this distance is less than a set spatial proximity threshold to classify them as spatially adjacent. For example, two side-by-side distribution cabinets with very close bounding boxes are considered spatially adjacent. When two obstacles are determined to be adjacent, the system establishes a bidirectional connection edge between the root nodes representing these two obstacles, indicating a direct spatial obstruction relationship between them. After traversing all obstacle pairs and establishing connections, the spatial adjacency relationships between obstacles throughout the entire area are fully depicted in the form of a network graph, forming the spatial connection network of obstacles in the cable laying area.

[0041] Based on an obstacle spatial connection network, an obstacle physically located at the area's entrance or core is selected as the root node of the entire network. Starting from this root node, all nodes in the network are traversed using a depth-first strategy, based on the established connections. During the traversal, a clear parent-child relationship is established between consecutive nodes on each access path, with the first visited node becoming the parent and the second visited node becoming the child, ensuring that each child node has only one parent node. This traversal and relationship establishment process transforms the potentially loop-ridden mesh graph into a loop-free tree graph with a clear hierarchical relationship. This graph structure and all the node and parent-child relationship information it contains constitute the obstacle tree structure data for the cable laying area.

[0042] A mechanism for rapid retrieval and location of the aforementioned tree-structured data is established. Starting from the root node, the root node is labeled as the first level, all child nodes directly connected to the root node are labeled as the second level, all child nodes of the second level nodes are labeled as the third level, and so on, assigning a number representing the level to each node in the tree. Simultaneously, nodes within the same level are numbered according to a certain spatial order, such as from left to right or from front to back. This process of assigning a level number and an intra-level number to each node constructs a hierarchical obstacle spatial tree for the cable laying area. This tree not only expresses the spatial adjacency and hierarchy relationships between obstacles but also clarifies the hierarchical position of each obstacle within the overall structure through indexing.

[0043] By employing structured and hierarchical organization, complex spatial obstacle information is transformed into a clear and orderly engineering semantic model. Grouping based on physical spatial layout decomposes the global problem into manageable local problems. A multi-layered semantic annotation system assigns multi-dimensional engineering attributes, including functionality, safety, and maintenance, to each obstacle, elevating it from geometric information to engineering knowledge. A spatial adjacency network is constructed and converted into a tree structure, clearly expressing the spatial relationships and hierarchical logic between obstacles. Finally, a hierarchical spatial tree with a hierarchical index is established, providing a structured environment model with clear semantic and topological relationships for subsequent efficient constraint matching and connectivity analysis.

[0044] S4. Based on the preset laying constraint rules, perform constraint matching mapping on the hierarchical obstacle space tree to obtain a multi-dimensional constraint set for the cable laying area; In this embodiment of the invention, the step of performing constraint matching mapping on the hierarchical obstacle space tree based on preset laying constraint rules to obtain a multidimensional constraint set for the cable laying area includes: Based on the cable mechanical performance constraint rules in the preset laying constraint rules, the spatial parameters of the obstacle nodes in the hierarchical obstacle space tree are geometrically matched and verified to obtain the spatial geometric constraints of the obstacle nodes. Based on the construction safety operation specifications in the laying constraint rules, a safety impact assessment is conducted on the spatial attributes of obstacle nodes to obtain the construction safety constraints of obstacle nodes. Based on the equipment operating environment standards in the laying constraint rules, the environmental parameters of the obstacle nodes are evaluated for environmental adaptability, and the thermal environment constraints of the obstacle nodes are obtained. By performing corresponding node-structured mapping of spatial geometric constraints, construction constraints, and thermal environment constraints, a multidimensional constraint set for the cable laying area is obtained.

[0045] Based on the minimum bending radius requirement in the cable mechanical performance constraint rules, the three-dimensional spatial dimensions and positional information of each obstacle node in the hierarchical obstacle space tree are verified. These rules clearly define the bending limits that cannot be exceeded during the laying of specific cable types. The system extracts the geometric shape of the obstacle node, calculates the curvature of the possible bending trajectory formed when the cable is laid close to the obstacle surface, and compares this curvature with the curvature corresponding to the allowable minimum bending radius. If the calculated trajectory curvature is greater than the allowable limit curvature, the obstacle node is determined to constitute a spatial geometric constraint on cable laying, and the specific direction and positional information affected by this constraint are recorded. These determinations regarding the spatial bending constraints caused by the obstacle node constitute the spatial geometric constraints of that obstacle node.

[0046] Based on the specific provisions of the construction safety operation specifications regarding personnel operating space and equipment safety distances, the spatial attributes of each obstacle node in the hierarchical obstacle space tree are evaluated. This specification clearly defines the minimum safe operating distances that must be reserved around different types of obstacles during cable laying. The system reads the semantic attributes of the obstacle nodes to identify whether they are specific types such as live equipment, high-voltage pipelines, or heavy machinery. Based on the identified type, the system determines the corresponding minimum safe distance requirement. Then, a virtual restricted area boundary is generated around the 3D model of the obstacle node based on this minimum safe distance. Any cable path planning that crosses this restricted area is considered a violation of construction safety constraints. This safety restricted area information defined for each obstacle node constitutes the construction safety constraint for that obstacle node.

[0047] The system evaluates the environmental parameters of each obstacle node in the hierarchical obstacle space tree based on the allowable operating temperature range for cables specified in the equipment operating environment standard. This standard clearly defines the upper limit of the ambient temperature for long-term cable operation. The system acquires the ambient temperature data associated with the obstacle node and compares this data with the cable's maximum allowable operating temperature. If the ambient temperature consistently exceeds the cable's allowable operating temperature, the area where the obstacle node is located is determined to be a high-temperature risk area, and the cable path should avoid long-term passage through or close contact with this area. This determination of whether an obstacle node causes thermal environmental exceedances and its impact range constitutes the thermal environmental constraint for that obstacle node.

[0048] Based on design drawings and engineering specifications, the three-dimensional coordinate ranges of all fixed obstacle boundaries and permissible passage space within the cable laying area were identified. These spatial geometric constraints were recorded one by one as structured node data with location attributes and boundary descriptions. Requirements regarding minimum working face width, required clearance height for installation operations, and turning angle limits were extracted from construction regulations. These construction constraints were also transformed into structured node data with specific thresholds and applicable conditions. Simultaneously, steady-state temperature distribution and heat dissipation parameters at various locations within the area were calculated based on environmental monitoring data and thermodynamic models. These thermal environment constraints were also processed into structured node data containing temperature thresholds and influence range information. All structured node data from spatial geometric constraints, construction constraints, and thermal environment constraints were integrated and organized according to their spatial location or logical association. This integration and organization process formed a multi-dimensional constraint set for the cable laying area. This multi-dimensional constraint set fully describes all spatial restrictions, construction conditions, and thermal environment requirements that the laying path must simultaneously meet.

[0049] The system systematically transforms engineering rules into concrete and executable spatial constraints, providing precise physical limitations for path planning. By performing geometric matching verification on each obstacle node, the spatial morphological constraints imposed by cable mechanical performance requirements are precisely quantified. Through safety impact assessment, construction safety specifications are transformed into safety exclusion zones defined in three-dimensional space. Through environmental adaptability assessment, equipment operating standards are transformed into explicit requirements for the path's thermal environment. Ultimately, a complete constraint description integrating geometric constraints, safety prohibitions, and thermal environment requirements is generated for each obstacle node, forming a multi-dimensional constraint set that must be followed in subsequent path searches.

[0050] S5. Based on the multidimensional constraint set, the connectivity topology of the hierarchical obstacle space tree is constructed to obtain the candidate path network of the cable laying area. In this embodiment of the invention, the step of constructing a connectivity topology for a hierarchical obstacle space tree based on a multidimensional constraint set to obtain a candidate path network for the cable laying area includes: Based on spatial geometric constraints and construction safety constraints, spatial reachability analysis is performed on adjacent nodes in a hierarchical obstacle spatial tree to obtain the preliminary connectivity relationship between adjacent nodes. Based on thermal environment constraints, environmental feasibility screening is performed on the preliminary connectivity relationships to obtain feasible connection relationships between adjacent nodes; A multi-level topology network is constructed based on the hierarchical obstacle space tree and feasible connection relationships to obtain the path topology network of the cable laying area. Redundant paths are eliminated from the path topology network to obtain the candidate path network for the cable laying area.

[0051] The construction of a multi-level topology network based on the hierarchical obstacle space tree and feasible connection relationships yields the path topology network of the cable laying area, including: Based on the hierarchical obstacle space tree, the cable laying area is spatially mapped to obtain the hierarchical spatial partitions of the hierarchical obstacle space tree; Based on feasible connectivity, a topological relationship is constructed for the connection paths between obstacle nodes in the hierarchical spatial partition, resulting in a hierarchical connected subnet of the hierarchical spatial partition. By performing hierarchical structure fusion on the hierarchical connected subnets, an aggregated topology network with hierarchical spatial partitioning is obtained; Global path connectivity verification is performed on the aggregated topology network to obtain the path topology network of the cable laying area.

[0052] The system analyzes each pair of adjacent obstacle nodes with parent-child or sibling relationships in the hierarchical obstacle space tree. For each pair, it checks whether the cable can form a smooth three-dimensional curve extending from the vicinity of the parent node to the vicinity of the child node, based on its spatial geometric constraints. The curvature of this curve cannot exceed the minimum bending radius limit of the cable. Simultaneously, the system checks whether the potential curve lies entirely outside the safety restricted areas defined by the two nodes, based on construction safety constraints. Only when at least one three-dimensional curve simultaneously satisfies the above geometric bendability and safety distance requirements is the system determined that the two adjacent nodes are spatially reachable, and this reachability relationship is recorded. The set of all recorded reachability determination results between node pairs constitutes the preliminary connectivity relationship between adjacent nodes.

[0053] Based on thermal environment constraints, each pair of connected nodes in the initial connectivity relationship undergoes a secondary review. The system checks whether the ambient temperature of the spatial region traversed by any possible path connecting the pair of nodes is within the cable's permissible operating temperature range. The review process involves acquiring temperature data at key points along the path and determining whether these temperature values ​​are all below the cable's maximum permissible operating temperature. If the temperature at any point on the path exceeds the limit, the connection is deemed environmentally infeasible. Only node pairs deemed reachable in the initial connectivity relationship, and whose all possible connection paths meet the thermal environment requirements, are retained. These node pairs that simultaneously satisfy spatial reachability and environmental feasibility constitute the feasible connection relationships between adjacent nodes.

[0054] Based on the inherent hierarchical node division in the layered obstacle space tree, the entire cable laying area is logically divided into different levels. The area containing the root node of the tree is mapped to the top-level total area, the areas containing its child nodes are mapped to the secondary sub-regions, and so on. This mapping does not re-divide the physical space, but rather defines a corresponding logical spatial range for each level of the node set in the tree. This range includes the area occupied by the physical obstacles represented by all nodes in that level and their adjacent surrounding space. Through the establishment of this correspondence, the hierarchical spatial partitioning of the layered obstacle space tree, which corresponds one-to-one with the tree structure levels, is obtained.

[0055] Within each hierarchical spatial partition, a topology of connecting paths is constructed based on the feasible connections between obstacle nodes within that partition. Each obstacle node within the partition is considered a topological node. If a feasible connection exists between two nodes, an undirected edge is established between them. The system appends a geometric description of the 3D spatial path it actually represents to this edge. After traversing all node pairs and establishing connecting edges within a partition, a network graph consisting of nodes and edges is formed within that partition. This mesh structure, representing all feasible connecting paths within that hierarchical spatial partition, is the hierarchically connected subnet of that hierarchical spatial partition.

[0056] Starting with the lowest-level connected subnet, it is merged upwards into the connected subnet of its parent level. All nodes and edges of the subnet are added to the parent level network, and boundary nodes connecting the subnet to the parent level network are connected to ensure cross-level connectivity. This merged network is then merged upwards with higher-level networks in the same way. This bottom-up, layer-by-layer merging operation continues until all connected subnets at all levels are integrated into a single network structure. This final, complete network, integrating all feasible paths at all levels, is the hierarchical spatial partitioning aggregate topology network.

[0057] A global path search test is performed on the aggregated topology network to verify its connectivity. Two nodes representing the cable's start and end points are randomly selected in the network, and an attempt is made to find a path consisting of continuous edges connecting them. The system starts from the start node and traverses the network edges. If the end node can be reached, the path is considered connected. The system tests multiple different combinations of start and end points. Only when at least one connected path can be found for all preset key start and end point combinations is the aggregated topology network considered globally connected. This verified, globally connected network is then finally confirmed as the path topology network for the cable laying area.

[0058] The system simplifies multiple functionally equivalent parallel paths in the path topology network by identifying redundant edges that connect the same pair of nodes and have very similar path lengths and turning complexities. The system retains the parallel path with the lowest overall cost, typically the one with the fewest turns, shortest length, and furthest from high-risk areas, while removing other functionally similar but slightly more expensive path edges from the network. This process of identifying and removing redundant connections aims to simplify the network structure, reduce the complexity of subsequent path evaluation, and ensure that the network still connects all necessary nodes. The network obtained after this simplification is the candidate path network for the cable laying area.

[0059] A candidate path space was constructed that satisfies multidimensional engineering constraints while maintaining a streamlined structure. Hierarchical accessibility analysis and environmental screening ensured the basic feasibility of paths in terms of geometry, safety, and thermal environment. Hierarchical partitioning and subnetting decomposed the connectivity problem in complex 3D space into a hierarchical topology construction problem. Subnet fusion and global verification ensured the establishment of a globally connected network from the starting point to the destination. Finally, by eliminating redundant paths, the network structure was optimized, providing a clear and high-quality set of highly feasible paths for subsequent multidimensional evaluation and decision-making, significantly improving the efficiency and quality of path search.

[0060] S6. Perform multi-dimensional collaborative evaluation on the candidate paths in the candidate path network to obtain the path evaluation data of the candidate paths, and make contextualized decisions on the path evaluation data to obtain the optimal cable laying path for the pumped storage power station.

[0061] In this embodiment of the invention, the step of performing multi-dimensional collaborative evaluation on candidate paths in the candidate path network to obtain path evaluation data for the candidate paths, and then performing contextualized decision-making on the path evaluation data to obtain the optimal cable laying path for the pumped storage power station, includes: Based on the evaluation index system for cable laying engineering of pumped storage power stations, the candidate paths in the candidate path network are quantified in multiple dimensions to obtain multi-dimensional score data of the candidate paths. The multi-dimensional score data is then structured and integrated to obtain the path score matrix of the candidate paths. Based on the design conditions and environmental conditions of the cable laying of pumped storage power stations, the multi-dimensional weights in the path scoring matrix are dynamically adjusted to obtain the weighted scoring matrix of the candidate paths. A comprehensive utility evaluation is performed on the weighted scoring matrix and candidate paths to obtain a comprehensive utility score for the candidate paths. Candidate paths with a comprehensive utility score exceeding a preset threshold are considered feasible laying paths. Based on the preset engineering decision-making criteria, the feasible laying paths are adaptively optimized to obtain the optimal cable laying path for the pumped storage power station.

[0062] The design and environmental condition contingency plan based on the cable laying of pumped storage power stations dynamically adjusts the multi-dimensional weights in the path scoring matrix to obtain a weighted scoring matrix for candidate paths, including: Based on the design working condition plan for cable laying of pumped storage power stations, the weights of the construction feasibility dimension in the path scoring matrix are configured in a phased adaptation manner to obtain the construction weight scheme of candidate paths. Based on the environmental condition contingency plan for cable laying in pumped storage power stations, the weights of the safety risk dimension in the path scoring matrix are configured in a scenario-responsive manner to obtain the environmental scenario weight scheme for candidate paths. Based on the resource scheduling scheme in the design working condition plan, the resource optimization weight scheme of the economic dimension in the path scoring matrix is ​​optimized and allocated to obtain the resource optimization weight scheme of the candidate path. Based on the construction weight scheme, environmental scenario weight scheme, and resource optimization weight scheme, a multi-dimensional weight coupling is performed on the path scoring matrix to obtain the weighted scoring matrix of the candidate paths. The calculation formula of the weighted scoring matrix is ​​as follows: ; In the formula, Indicates the first The weighted scoring matrix of candidate paths, Indicates the first The construction weight scheme values ​​of the candidate paths, Indicates the first The environmental scenario weighting scheme values ​​for each candidate path. Indicates the first The resource optimization weight scheme values ​​for each candidate path. This indicates the preset construction feasibility adjustment index. This indicates the preset safety risk adjustment index. This represents the preset economic adjustment index. Indicates the first The construction weight scheme values ​​corresponding to each candidate path Power of 1 Indicates the first The candidate paths correspond to the environmental scenario weight scheme values. Power of 1 Indicates the first The resource optimization weight scheme values ​​corresponding to each candidate path Power of 1 Represents the coupling strength coefficient. This represents the preset weighted divergence penalty index. This represents an exponential function.

[0063] The system invokes a pre-defined evaluation index system for cable laying projects, which includes multiple quantitative dimensions such as path length, number of turns, minimum bending radius margin, distance to hazard sources, adequacy of construction space, and estimated material costs. For each candidate path in the candidate path network, the system calculates a score for each dimension based on its three-dimensional geometric model and attribute information, according to the specific calculation rules for each dimension. After the calculation for each dimension is completed, the score values ​​of the path across all dimensions are recorded as an ordered list of values. Arranging and combining these multi-dimensional score lists corresponding to all candidate paths in order of path identifier forms the path score matrix for the candidate paths.

[0064] The design work plan is reviewed, which defines different construction phases, such as the civil engineering coordination period, the peak equipment installation period, and the cable laying period. Based on the specific construction phase corresponding to the current planned task, the importance of each dimension in the path scoring matrix is ​​adjusted. During the peak equipment installation period, the weights of sub-items such as construction space adequacy and installation complexity within the construction feasibility dimension are increased to reflect the higher requirements for workspace and efficiency at this stage. This configuration, which assigns appropriate weight coefficients to the construction feasibility dimension and its sub-items based on the characteristics of the construction phase, constitutes the construction weight scheme for the candidate path.

[0065] The environmental condition contingency plan is retrieved, which describes environmental scenarios under different seasons or special weather conditions, such as high-temperature summer scenarios or humid rainy season scenarios. Based on the environmental scenario targeted by the current plan, the weight allocation of the safety risk dimension in the path scoring matrix is ​​adjusted. In the high-temperature summer scenario, the weights of the sub-items related to cable heat dissipation conditions and distance from nearby heat sources in the safety risk dimension are significantly increased to strengthen the prevention of overheating risks. This configuration result of dynamically adjusting the weights of each sub-item within the safety risk dimension according to specific environmental scenarios is the environmental scenario weight scheme for candidate paths.

[0066] The analysis of the resource scheduling schemes, including manpower, machinery, and material supply plans, within the design and operational scenario plans allows for targeted allocation of weights to the economic dimension of the path scoring matrix based on resource availability and cost constraints. For instance, during periods of high demand for large machinery, the weight of the sub-item related to the cost of using large machinery within the economic dimension is increased to guide the selection of paths that rely less on large machinery. This allocation of economic dimension weights based on resource availability and cost control objectives constitutes the resource optimization weight scheme for candidate paths.

[0067] The weight coefficients for each dimension defined in the construction weight scheme, environmental scenario weight scheme, and resource optimization weight scheme are integrated. The weight coefficients for the same dimension obtained from different schemes are superimposed to form the final composite weight for that dimension. This composite weight set is used to perform a weighted calculation on the original multi-dimensional scores of each row (each path) in the path scoring matrix. The weighting calculation involves multiplying the original score of each dimension by its corresponding composite weight, and then summing all the weighted scores to generate a single weighted total score for each path. The weighted total scores of all paths are arranged in their identifier order to form the weighted scoring matrix of the candidate paths.

[0068] A comprehensive utility score is calculated for each candidate path based on a weighted scoring matrix. The weighted total score corresponding to that path in the matrix is ​​then combined with additional adjustment values ​​reflecting other non-quantitative factors, such as path regularity or compatibility with future expansion. This comprehensive utility score is a final numerical value that comprehensively reflects the overall merits of a path under weighted quantitative indicators and qualitative engineering judgments. The system compares the comprehensive utility score of each path with a pre-set qualification threshold. Candidate paths whose comprehensive utility scores reach or exceed this threshold are considered generally feasible in terms of technology, safety, economy, and adaptability; this set of selected paths constitutes the feasible deployment paths.

[0069] Based on pre-defined engineering decision-making standards, a final selection of feasible laying paths is performed. These standards specify criteria for determining a unique optimal solution among multiple feasible paths, prioritizing the path with the highest comprehensive utility score. If multiple paths have the highest score, the shortest path is selected first. Following the steps and priorities defined in these standards, feasible laying paths are sorted and compared. The path with the highest comprehensive utility score is identified; if there is only one, it is directly selected; if there are multiple paths, the shortest path is selected from among these parallel paths. Through this multi-level sorting and filtering, the path that is most advantageous under the given standards is ultimately determined as the optimal cable laying path for the pumped storage power station.

[0070] In the formula, the construction feasibility adjustment index is derived from the phased adaptability configuration process in the design working condition plan. The safety risk adjustment index is derived from the scenario responsiveness configuration process in the environmental working condition plan. The economic adjustment index is derived from the resource optimization configuration process in the resource scheduling plan. The coupling strength coefficient is derived from the process of determining the interaction strength between the construction weight scheme, the environmental scenario weight scheme, and the resource optimization weight scheme. The weight divergence penalty index is derived from the process of setting the tolerance for differences between the construction weight scheme value, the environmental scenario weight scheme value, and the resource optimization weight scheme value.

[0071] This calculation formula is used to generate a weighted scoring matrix for candidate paths. It calculates the feasibility adjustment exponent for the construction weight scheme value, the safety risk adjustment exponent for the environmental scenario weight scheme value, and the economic adjustment exponent for the resource optimization weight scheme value. The results of these three exponentiations are summed and divided by three to obtain an average value. This average value is multiplied by the coupling strength coefficient and used as input to an exponential function to obtain the first product factor. The absolute values ​​of the differences between the construction weight scheme value and the environmental scenario weight scheme value are calculated. The absolute values ​​of the differences between the environmental scenario weight scheme value and the resource optimization weight scheme value are also calculated. The absolute values ​​of the differences between the resource optimization weight scheme value and the construction weight scheme value are summed and divided by three to obtain an average difference value. This average difference value is incremented by one and used as the base to perform a weight divergence penalty exponentiation to obtain the second product factor. The first and second product factors are multiplied to obtain the weighted scoring matrix value for that candidate path. Repeat this calculation process for all candidate paths to generate a complete weighted score matrix.

[0072] The beneficial effects are as follows: Based on a pre-defined evaluation index system for cable laying projects, multi-dimensional scores are calculated for each candidate path to form a path scoring matrix. By reading the design working condition plan, the weights of the construction feasibility dimension are adjusted according to the specific construction stage to generate a construction weight scheme. Combined with the environmental working condition plan, the weights of the safety risk dimension are adjusted for specific environmental scenarios to generate an environmental scenario weight scheme. Resource scheduling schemes are analyzed, and economic dimension weights are configured according to resource scarcity and cost control objectives to generate a resource optimization weight scheme. The coefficients in the three weight schemes are integrated to perform weighted calculations on the path scoring matrix to generate a weighted scoring matrix. Based on the weighted scoring matrix, the comprehensive utility score of each path is calculated and compared with the qualified threshold to select a set of feasible laying paths. Finally, according to the engineering decision-making specifications, the path with the highest comprehensive utility score is selected first among the feasible paths, and if the scores are the same, the path with the shortest length is selected, thus determining the optimal cable laying path. This process realizes a systematic decision-making process for path evaluation, from quantitative calculation to dynamic weight adaptation, and then to multi-scheme coupling and final selection.

[0073] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0074] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0075] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for planning obstacle avoidance paths in three-dimensional cable laying for pumped storage power stations, characterized in that, The method includes: S1. Standardize and integrate the multi-source basic data of the cable laying area in the pumped storage power station to obtain standardized multi-basic data of the cable laying area; S2. Perform obstacle correlation analysis on the standardized basic data to obtain obstacle feature data of the cable laying area, and perform feature vector mapping on the obstacle feature data to obtain the classification feature vector set of the obstacle feature data; S3. Perform hierarchical spatial clustering on the classification feature vector set to obtain a hierarchical obstacle spatial tree of the cable laying area; S4. Based on the preset laying constraint rules, perform constraint matching mapping on the hierarchical obstacle space tree to obtain a multi-dimensional constraint set for the cable laying area; S5. Based on the multidimensional constraint set, the connectivity topology of the hierarchical obstacle space tree is constructed to obtain the candidate path network of the cable laying area. S6. Perform multi-dimensional collaborative evaluation on the candidate paths in the candidate path network to obtain the path evaluation data of the candidate paths, and make contextualized decisions on the path evaluation data to obtain the optimal cable laying path for the pumped storage power station.

2. The method for planning obstacle avoidance paths for three-dimensional cable laying in pumped storage power stations as described in claim 1, characterized in that, The process of standardizing and integrating multi-source basic data on cable laying areas in pumped storage power stations yields standardized basic data for the cable laying areas, including: Spatial normalization was performed on the multi-source basic data of the cable laying area in the pumped storage power station to obtain the unified spatial basic data of the cable laying area. The spatial unified basic data is processed to standardize the format, resulting in structured basic data of the cable laying area; Data cleaning is performed on the structured basic data to obtain clean basic data of the cable laying area; Multidimensional information synchronization and registration are performed on the cleanroom basic data to obtain standardized basic data for the cable laying area.

3. The method for planning obstacle avoidance paths for three-dimensional cable laying in pumped storage power stations as described in claim 1, characterized in that, The standardization of basic data is used to perform obstacle correlation analysis to obtain obstacle feature data of the cable laying area. Feature vector mapping is then performed on this obstacle feature data to obtain a classification feature vector set, including: Obstacle correlation analysis was performed on standardized basic data to obtain an obstacle dataset for the cable laying area; Geometric features were extracted from the obstacle dataset to obtain obstacle feature data for the cable laying area; Based on the feature attributes of the obstacle feature data, attribute-driven classification is performed on the obstacle feature data to obtain the classified obstacle feature data of the cable laying area. The obstacle feature data is vectorized to obtain the classification feature vector set of the obstacle feature data.

4. The method for planning obstacle avoidance paths for three-dimensional cable laying in pumped storage power stations as described in claim 1, characterized in that, The hierarchical spatial clustering of the classification feature vector set to obtain a hierarchical obstacle spatial tree of the cable laying area includes: Based on the spatial layout of the cable laying area, the classification feature vector set is spatially grouped to obtain the regional feature vector group of the cable laying area. Based on the semantic classification system of obstacles in cable laying areas, multi-level semantic annotation is performed on the regional feature vector groups to obtain the semantic hierarchical structure of the regional feature vector groups. Based on the spatial adjacency relationship of obstacles in the semantic hierarchical structure, a topological connection relationship is constructed in the semantic hierarchical structure to obtain the spatial connection network of obstacles in the cable laying area. The obstacle spatial connection network is transformed into a tree structure to obtain the obstacle tree structure data of the cable laying area. Then, a hierarchical index is constructed on the obstacle tree structure data to obtain the hierarchical obstacle spatial tree of the cable laying area.

5. The method for planning obstacle avoidance paths for three-dimensional cable laying in pumped storage power stations as described in claim 4, characterized in that, The obstacle engineering semantic classification system based on cable laying areas performs multi-layer semantic annotation on the regional feature vector groups to obtain a semantic hierarchical structure of the regional feature vector groups, including: Based on the engineering semantic classification system of obstacles in cable laying areas, the functional attributes of obstacles in the regional feature vector group are identified to obtain the functional semantic data of obstacles in the regional feature vector group. Based on the construction safety impact level in the obstacle engineering semantic classification system, the obstacle functional semantic data is labeled with safety level to obtain the obstacle safety semantic data of the regional feature vector group. Based on the operation and maintenance accessibility evaluation rules in the obstacle engineering semantic classification system, the operation and maintenance attributes of obstacle safety semantic data are identified to obtain obstacle operation and maintenance semantic data of regional feature vector groups. Hierarchical node association is performed on obstacle operation and maintenance semantic data, obstacle safety semantic data, and obstacle function semantic data to obtain a semantic hierarchical structure of regional feature vector groups.

6. The method for planning obstacle avoidance paths for three-dimensional cable laying in pumped storage power stations as described in claim 1, characterized in that, The method, based on preset laying constraint rules, performs constraint matching mapping on the hierarchical obstacle space tree to obtain a multidimensional constraint set for the cable laying area, including: Based on the cable mechanical performance constraint rules in the preset laying constraint rules, the spatial parameters of the obstacle nodes in the hierarchical obstacle space tree are geometrically matched and verified to obtain the spatial geometric constraints of the obstacle nodes. Based on the construction safety operation specifications in the laying constraint rules, a safety impact assessment is conducted on the spatial attributes of obstacle nodes to obtain the construction safety constraints of obstacle nodes. Based on the equipment operating environment standards in the laying constraint rules, the environmental parameters of the obstacle nodes are evaluated for environmental adaptability, and the thermal environment constraints of the obstacle nodes are obtained. By performing corresponding node-structured mapping of spatial geometric constraints, construction constraints, and thermal environment constraints, a multidimensional constraint set for the cable laying area is obtained.

7. The method for planning obstacle avoidance paths for three-dimensional cable laying in pumped storage power stations as described in claim 6, characterized in that, The method of constructing a connectivity topology for a hierarchical obstacle space tree based on a multidimensional constraint set to obtain a candidate path network for the cable laying area includes: Based on spatial geometric constraints and construction safety constraints, spatial reachability analysis is performed on adjacent nodes in a hierarchical obstacle spatial tree to obtain the preliminary connectivity relationship between adjacent nodes. Based on thermal environment constraints, environmental feasibility screening is performed on the preliminary connectivity relationships to obtain feasible connection relationships between adjacent nodes; A multi-level topology network is constructed based on the hierarchical obstacle space tree and feasible connection relationships to obtain the path topology network of the cable laying area. Redundant paths are eliminated from the path topology network to obtain the candidate path network for the cable laying area.

8. The method for planning obstacle avoidance paths for three-dimensional cable laying in pumped storage power stations as described in claim 7, characterized in that, The construction of a multi-level topology network based on the hierarchical obstacle space tree and feasible connection relationships yields the path topology network of the cable laying area, including: Based on the hierarchical obstacle space tree, the cable laying area is spatially mapped to obtain the hierarchical spatial partitions of the hierarchical obstacle space tree; Based on feasible connectivity, a topological relationship is constructed for the connection paths between obstacle nodes in the hierarchical spatial partition, resulting in a hierarchical connected subnet of the hierarchical spatial partition. By performing hierarchical structure fusion on the hierarchical connected subnets, an aggregated topology network with hierarchical spatial partitioning is obtained; Global path connectivity verification is performed on the aggregated topology network to obtain the path topology network of the cable laying area.

9. The method for planning obstacle avoidance paths for three-dimensional cable laying in pumped storage power stations as described in claim 1, characterized in that, The process of performing multi-dimensional collaborative evaluation of candidate paths in the candidate path network to obtain path evaluation data, and then making contextualized decisions based on the path evaluation data to obtain the optimal cable laying path for the pumped storage power station includes: Based on the evaluation index system for cable laying engineering of pumped storage power stations, the candidate paths in the candidate path network are quantified in multiple dimensions to obtain multi-dimensional score data of the candidate paths. The multi-dimensional score data is then structured and integrated to obtain the path score matrix of the candidate paths. Based on the design conditions and environmental conditions of the cable laying of pumped storage power stations, the multi-dimensional weights in the path scoring matrix are dynamically adjusted to obtain the weighted scoring matrix of the candidate paths. A comprehensive utility evaluation is performed on the weighted scoring matrix and candidate paths to obtain a comprehensive utility score for the candidate paths. Candidate paths with a comprehensive utility score exceeding a preset threshold are considered feasible laying paths. Based on the preset engineering decision-making criteria, the feasible laying paths are adaptively optimized to obtain the optimal cable laying path for the pumped storage power station.

10. The method for planning obstacle avoidance paths for three-dimensional cable laying in pumped storage power stations as described in claim 9, characterized in that, The design and environmental condition contingency plan based on the cable laying of pumped storage power stations dynamically adjusts the multi-dimensional weights in the path scoring matrix to obtain a weighted scoring matrix for candidate paths, including: Based on the design working condition plan for cable laying of pumped storage power stations, the weights of the construction feasibility dimension in the path scoring matrix are configured in a phased adaptation manner to obtain the construction weight scheme of candidate paths. Based on the environmental condition contingency plan for cable laying in pumped storage power stations, the weights of the safety risk dimension in the path scoring matrix are configured in a scenario-responsive manner to obtain the environmental scenario weight scheme for candidate paths. Based on the resource scheduling scheme in the design working condition plan, the resource optimization weight scheme of the economic dimension in the path scoring matrix is ​​optimized and allocated to obtain the resource optimization weight scheme of the candidate path. Based on the construction weight scheme, the environmental scenario weight scheme, and the resource optimization weight scheme, the path scoring matrix is ​​coupled with multi-dimensional weights to obtain the weighted scoring matrix of the candidate paths.

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