Multi-source to multi-destination pipeline path mapping method and system based on multiple weights

Abstract

The application provides a multi-source-to-multi-destination pipeline path drawing method and system based on multiple weights, which comprises the following steps: acquiring at least two starting points, at least two ending points and a to-be-passed position in a target engineering drawing; constructing the end points and branch intersection points of a channel region as common nodes, and constructing the starting points, ending points and to-be-passed position as main nodes; respectively calculating two-point optimal paths, and taking the lengths of the two-point optimal paths as the path edge lengths of corresponding path edges; adopting a comprehensive weight composed of path edge length, path edge use frequency and length tolerance degree, updating the path edge use frequency according to the overlapping frequency of each path edge in each round of calculation result; and converting the multi-point optimal path into pipeline network path coordinate data in the target engineering drawing. The optimal path planning of the pipeline network can be automatically completed in a complex pipeline layout scene from multiple sources to multiple destinations, and the design efficiency of the pipeline network conveying path planning is improved.

Description

Technical Field

[0001] This application relates to the field of chemical pipeline design technology, specifically to a method and system for drawing multi-source to multi-endpoint pipeline paths based on multi-weighting. Background Technology

[0002] Chemical engineering design involves extensive pipeline network planning, which is a crucial step in determining the project's workload and total investment. In practice, this involves planning the pipeline routes from the material source unit to the material destination unit on engineering drawings that already have pre-determined pipe gallery locations and plant layouts.

[0003] In practical engineering applications of pipeline transportation systems, pipeline networks often face complex layout scenarios connecting multiple starting points and multiple ending points. Such multi-source to multi-endpoint pipeline route planning scenarios frequently occur in large-scale chemical projects, placing high demands on the integrity and coordination of the final route planning scheme, as well as the man-hours required to develop the scheme.

[0004] As the scale of chemical projects continues to expand, the number of source and end-point devices that need to be connected in a single project continues to increase, and the overall workload of pipeline network route planning in multi-source to multi-end-point scenarios increases significantly. Summary of the Invention

[0005] In view of this, the embodiments of this application provide a method and system for drawing pipeline paths from multiple sources to multiple destinations based on multiple weights. This method can automatically complete the optimal path planning of pipeline networks in complex pipeline layout scenarios with multiple sources to multiple destinations, thereby improving the design efficiency of pipeline network transportation path planning.

[0006] The first aspect of this application provides a method for drawing multi-source to multi-endpoint pipeline paths based on multi-weighting, including: Obtain at least two starting points, at least two ending points, and the locations to be traversed from the target project drawings; In the target engineering drawings, identify the passage areas that allow priority passage for pipelines and the obstacle areas that prohibit pipeline passage, construct the endpoints and branch intersections of the passage areas as ordinary nodes, and construct the starting point, the ending point and the location to be traversed as master nodes; Under the constraint of prioritizing the passage area and avoiding the obstacle area, the optimal path between each pair of adjacent nodes is calculated, and the length of the optimal path between the two points is used as the path edge length of the corresponding path edge. Based on the master node, the ordinary node, and the path edge, a comprehensive weight consisting of the path edge length, the number of times the path edge is used, and the length tolerance is used to perform multiple rounds of calculation on the optimal multi-point path between all the master nodes, and the number of times the path edge is used is updated according to the number of times each path edge overlaps in the calculation results of each round. The optimal path at multiple points is converted into pipeline network path coordinate data in the target engineering drawing, and then drawn and displayed in the target engineering drawing.

[0007] Preferably, obtaining at least two starting points, at least two ending points, and the locations to be traversed from the target engineering drawings includes: Obtain at least one pathfinding task as input, each pathfinding task including the location of the starting point and the location of the ending point, and at least one of the attribute data of the location to be traversed and the corresponding pipeline; The entity coordinates in the target engineering drawing are identified, and the starting point, ending point, and traversed location in the pathfinding task are associated with the corresponding entity coordinates.

[0008] Preferably, for each master node, the corresponding child nodes are constructed in the following manner: When the coordinate data of at least two connection exits of the entity corresponding to the main node are known, the at least two connection exits are respectively constructed as child nodes of the main node; When the coordinate data of the connection exit of the entity corresponding to the main node is unknown, the center coordinates of the entity corresponding to the main node are used as the starting position, and the optimal connection point position is automatically found as the child node of the main node.

[0009] Preferably, the step of calculating the optimal path between every two adjacent nodes includes: For each pair of adjacent nodes, one is taken as the starting point and the other as the target point. Accessibility of the path is explored in eight directions around the starting point. The estimated total cost to reach the target point is used as a weight to gradually determine the feasible path from the starting point to the target point. The overall cost of at least one of the obtained feasible paths is compared, and the feasible path with the minimum overall cost is determined as the optimal path between the two points. The optimal path between the two points is denormalized and converted into the corresponding coordinate data in the target engineering drawing.

[0010] Preferably, the step of performing multiple rounds of calculation on the optimal multi-point path between all the master nodes, and updating the path edge usage count based on the overlap count of each path edge in each round of calculation results, includes: Initialize the number of times each path edge is used to zero for all of the aforementioned path edges; Based on all the nodes, the path edge length, and the length tolerance, the shortest path algorithm is used to calculate the shortest path between all the main nodes, and the number of times the path edge is used is updated by accumulating the number of times the path edge overlaps in the current calculation result. Using the path edge length, the updated number of times the path edge is used, and the length tolerance as the comprehensive weight, the minimum spanning tree algorithm is used to construct a minimum spanning tree for all the ordinary nodes, resulting in a simplified set of path edges. Based on the simplified set of path edges, the optimal path between all the main nodes is recalculated; For a master node that corresponds to at least two child nodes, select the optimal child node corresponding to the master node from the at least two child nodes; Based on all the master nodes and the simplified optimal child node set, redundant path edges not included in the simplified path edge set are pruned to obtain the core shortest path between all the master nodes.

[0011] Preferably, the formula for calculating the comprehensive weight is: in, This represents the combined weight of path x relative to path y. This represents the length of the path edge in path x. This represents the length of the path edge in path y. This indicates the number of times the path edge of path x is used. The path edge of path y is used the most times, and T represents the length tolerance. When the absolute value of the difference between the path edge length of path x and the path edge length of path y is not greater than the length tolerance, the comprehensive weight is equal to the difference between the number of times the path edge of path x is used and the number of times the path edge of path y is used. When the absolute value of the difference between the path edge length of path x and the path edge length of path y is greater than the length tolerance, the comprehensive weight is equal to the difference between the path edge length of path x and the path edge length of path y.

[0012] The more preferred options also include: When the value of the comprehensive weight is greater than zero, the larger the value of the comprehensive weight, the higher the priority of the corresponding path. For any two paths, if the overall weight of one path relative to the other path is greater than the overall weight of the other path relative to the first path, and both are greater than zero, the path with the larger overall weight value shall be selected first. Paths with zero edge length or zero edge usage count are discarded.

[0013] Preferably, for a master node corresponding to at least two child nodes, selecting the optimal child node corresponding to the master node from the at least two child nodes includes: Calculate the sum of distances between each child node of the current master node and the nearest child node of each other master node, and determine the child node with the smallest sum of distances as the optimal child node corresponding to the current master node; And / or, calculate the total distance between each child node of the current master node and all child nodes of every other master node, and determine the child node with the smallest total distance value as the optimal child node corresponding to the current master node; And / or, enumerate all the combinations of the current master node's child nodes with all the child nodes of each other master node, calculate the total distance for each combination, and determine the child node corresponding to the combination with the smallest total distance as the optimal child node for the current master node.

[0014] A second aspect of this application provides a multi-weighted, multi-source to multi-destination pipeline path drawing system, comprising: The initial input module is used to obtain at least two starting points, at least two ending points, and the locations to be traversed from the target engineering drawings. The data acquisition module is communicatively connected to the starting input module and is used to identify in the target engineering drawings the passage areas that allow priority passage for pipelines and the obstacle areas that prohibit pipeline passage. The node construction module, which is communicatively connected to the data acquisition module, is used to construct the endpoints and branch intersections of the channel area as ordinary nodes, and to construct the starting point, the ending point and the location to be traversed as master nodes. The two-point optimal path calculation module is communicatively connected to the node construction module. It is used to calculate the two-point optimal path between each two adjacent nodes under the constraints of prioritizing the channel area and avoiding the obstacle area, and use the length of the two-point optimal path as the path edge length of the corresponding path edge. The multi-point optimal path calculation module is communicatively connected to the two-point optimal path calculation module. It is used to perform multi-round calculations on the multi-point optimal path between all the main nodes based on the main node, the ordinary node, and the path edge, using a comprehensive weight composed of the path edge length, the number of times the path edge is used, and the length tolerance. The number of times the path edge is used is updated according to the number of times each path edge overlaps in the calculation results of each round. The path construction module is communicatively connected to the multi-point optimal path calculation module and is used to convert the multi-point optimal path into pipeline network path coordinate data in the target engineering drawing. The visual display module is communicatively connected to the path construction module and is used to draw and display the pipeline network path corresponding to the pipeline network path coordinate data in the target engineering drawing.

[0015] Preferably, the multi-point optimal path calculation module is specifically used for: Initialize the number of times each path edge is used to zero for all of the aforementioned path edges; Based on all the nodes, the path edge length, and the length tolerance, the shortest path algorithm is used to calculate the shortest path between all the main nodes, and the number of times the path edge is used is updated by accumulating the number of times the path edge overlaps in the current calculation result. Using the path edge length, the updated number of times the path edge is used, and the length tolerance as the comprehensive weight, the minimum spanning tree algorithm is used to construct a minimum spanning tree for all the ordinary nodes, resulting in a simplified set of path edges. Based on the simplified set of path edges, the optimal path between all the main nodes is recalculated; For a master node that corresponds to at least two child nodes, select the optimal child node corresponding to the master node from the at least two child nodes; Based on all the master nodes and the simplified optimal child node set, redundant path edges not included in the simplified path edge set are pruned to obtain the core shortest path between all the master nodes.

[0016] The first aspect of this application's embodiments involves obtaining multiple starting points, multiple ending points, and locations to be traversed from the target engineering drawings as input. It identifies channel areas and obstacle areas, constructs the endpoints and branch intersections of the channel areas as ordinary nodes, and constructs the starting points, ending points, and locations to be traversed as master nodes. Under the constraint of prioritizing channel areas and avoiding obstacle areas, it calculates the optimal path between every two adjacent nodes and uses its length as the path edge length. It performs multiple rounds of calculations on the optimal path between all master nodes using a comprehensive weight composed of path edge length, path edge usage frequency, and length tolerance. It updates the path edge usage frequency based on the overlap frequency of each path edge in each round of calculation. Finally, it completes the result display through coordinate transformation and engineering drawing. This approach can automatically complete optimal path planning in complex pipeline layout scenarios with multiple sources to multiple endpoints, simplifying the pipeline network path planning process in such scenarios and improving the design efficiency of pipeline network transportation path planning. It is particularly suitable for the pipeline general layout design of large-scale chemical projects such as coal chemical, petrochemical, and fine chemical industries.

[0017] It is understandable that the beneficial effects of the second aspect mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art 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.

[0019] Figure 1 This is a flowchart illustrating the multi-source to multi-endpoint pipeline path drawing method based on multi-weighting provided in this embodiment of the invention. Figure 2 This is a schematic diagram of the structure of the multi-source to multi-endpoint pipeline path drawing system based on multi-weighting provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the multi-point optimal path calculation process provided in an embodiment of the present invention; Figure 4 This is an example diagram of an engineering problem provided in an embodiment of the present invention; Figure 5 This is an example diagram of node numbering provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of a two-dimensional grid mathematical model provided in an embodiment of the present invention. Detailed Implementation

[0020] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0021] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0022] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0023] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0024] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0025] The multi-weighted, multi-source to multi-endpoint pipeline path drawing method provided in this invention can be applied to scenarios in chemical engineering design where optimal path planning is needed for pipeline networks with multiple starting points to multiple ending points on a system diagram. Examples include overall pipeline network planning in large-scale chemical projects, overall path design of material transport networks between chemical plants, and overall pipeline layout design for large chemical plants such as coal chemical, petrochemical, and fine chemical plants. This method assists chemical engineers in completing optimal path planning for pipeline networks in complex multi-source to multi-endpoint scenarios. Specifically, it can be executed by the processor of a terminal device running a computer program with corresponding functions. This invention does not impose any restrictions on the specific type, scale, or type of carrying medium of the pipeline transport system.

[0026] like Figure 1 As shown, the multi-weighted multi-source to multi-endpoint pipeline path drawing method provided in this embodiment of the invention includes the following steps S101 to S105 executed by the processor of the terminal device: Step S101: Obtain at least two starting points, at least two ending points, and the locations to be traversed from the target engineering drawings.

[0027] In applications, the target engineering drawings are typically system diagrams or general layout plans for piping arrangements in the field of chemical engineering design, usually in 2D CAD format. The starting point corresponds to the material output device in the pipeline network, the ending point corresponds to the material receiving device, and the locations to be traversed correspond to intermediate devices or critical equipment that the pipeline must pass through in the process flow. In scenarios with multiple sources and multiple endpoints, there are at least two starting points and two ending points, while the number of locations to be traversed is determined according to process requirements. Designers input or select each starting point, each ending point, and each location to be traversed through the starting input module to obtain all the basic input information required for this step.

[0028] By acquiring multiple starting points, multiple ending points, and locations to be traversed from the target engineering drawings as the basic input for subsequent path planning, this method supports complex scenarios of "multiple sources to multiple ending points" in chemical pipeline design. Compared with one-to-one pathfinding algorithms of "single source to single destination," it expands the application scope of path optimization algorithms in the overall layout optimization of pipeline networks. By introducing input information such as locations to be traversed, subsequent path planning naturally incorporates these locations into the set of master nodes and participates in the solution, ensuring that the optimal path covers the locations of key equipment that must be passed through in the process flow. By simultaneously supporting multiple starting points and multiple ending points as input, the algorithm can perform overall planning of the entire pipeline network from a global perspective, rather than solving for the optimal path between each pair of starting and ending points in isolation.

[0029] In one embodiment, step S101 includes: Obtain at least one pathfinding task as input, each pathfinding task including the location of the starting point and the location of the ending point, and at least one of the attribute data of the location to be traversed and the corresponding pipeline; The entity coordinates in the target engineering drawing are identified, and the starting point, ending point, and traversed location in the pathfinding task are associated with the corresponding entity coordinates.

[0030] In the application, the initial input module identifies and organizes multiple pathfinding tasks based on the designer's input. Each pathfinding task requires a starting point and an ending point as mandatory information, while optional information includes the location to be traversed and the corresponding pipeline's attribute data (such as pipe diameter, material, pressure rating, and media type). Then, by recognizing CAD drawings with entity coordinates, the positional information in each pathfinding task is precisely correlated with the entity coordinates on the drawing, thus completing the mapping from positional data to drawing coordinates.

[0031] By associating the starting point, ending point, and traversed locations in the pathfinding task with the coordinates of entities in the CAD drawing, the abstract location information can establish a precise correspondence with the specific entities in the CAD drawing, providing a data foundation for subsequent coordinate-based path calculations and the final drawing of the results. By allowing the pathfinding task to carry the attribute data of the corresponding pipeline, the process attribute information of the pipeline can be included in the processing object during the path planning process, making it easier to associate the pipeline attribute data with the path coordinate data and pass it to the subsequent path construction stage.

[0032] Step S102: Identify the passage areas for priority passage of pipelines and the obstacle areas where pipelines are prohibited from passing through in the target engineering drawings. Construct the endpoints and branch intersections of the passage areas as ordinary nodes, and construct the starting point, the ending point and the location to be traversed as master nodes.

[0033] like Figure 4 As shown, Figure 4 The diagram illustrates an example of an engineering problem before the chemical pipeline design problem addressed in the embodiments of the present invention is transformed into a mathematical model. Figure 4 It contains nine rounded rectangles, labeled A, B, C, D, E, F, G, H, and I. Each rounded rectangle represents a device entity that needs to be connected by a pipe. The nine rounded rectangles are arranged in a 3x3 grid. There are horizontal and vertical connecting lines between the rounded rectangles. The connecting lines represent the passage area for priority pipe passage (i.e., the pre-laid pipe gallery location). The area occupied by the nine rounded rectangles represents the obstacle area where pipe passage is prohibited (i.e., the area occupied by the device).

[0034] like Figure 5 As shown, Figure 5 exist Figure 4 Based on this, the four branch intersections located at the intersection of the channels are labeled as number ①, number ②, number ③, and number ④, respectively. Numbers ① to ④ correspond to the four ordinary nodes constructed in this step. Numbering each node is to facilitate subsequent indexing and path calculation of the nodes using graph theory.

[0035] In the application, the data acquisition module identifies graphic elements in the CAD drawings, recognizing pre-laid pipe gallery locations as priority passageways for pipelines and pre-planned equipment areas as obstacle zones prohibiting pipeline passage. The node construction module constructs ordinary nodes from the endpoints and branch intersections of the pipe gallery passageways, and constructs master nodes from the starting point, ending point, and equipment data corresponding to the locations to be traversed, obtained from the initial input module. All master nodes and ordinary nodes are only connected to adjacent nodes, thus constructing a data model composed of master nodes, ordinary nodes, and the connections between nodes. The coordinates of each node can be obtained after node recognition is complete.

[0036] By explicitly identifying passage and obstacle areas in engineering drawings, and constructing ordinary nodes at the endpoints and branch intersections of passage areas, and main nodes at the starting point, ending point, and locations to be traversed, the pipeline layout information originally scattered in the drawings is converged into a topological structure composed of main nodes, ordinary nodes, and the connections between nodes. This provides a complete data foundation for subsequent optimal path planning using graph theory algorithms. By clearly distinguishing between main nodes and ordinary nodes, subsequent multi-point optimal path calculations can focus only on the optimal connections between main nodes without considering all ordinary nodes along the way, reducing the computational complexity in multi-source and multi-endpoint scenarios. By pre-setting the identification rule of "passage priority, obstacle avoidance," subsequent path calculations naturally follow the engineering practice requirements of "pipelines should be laid along the pipeline corridor first and absolutely avoid equipment areas" in chemical engineering design, avoiding optimal paths that cross equipment areas or deviate from the pipeline corridor, resulting in engineeringly infeasible solutions.

[0037] In one embodiment, for each master node, the corresponding child nodes are constructed as follows: When the coordinate data of at least two connection exits of the entity corresponding to the main node are known, the at least two connection exits are respectively constructed as child nodes of the main node; When the coordinate data of the connection exit of the entity corresponding to the main node is unknown, the center coordinates of the entity corresponding to the main node are used as the starting position, and the optimal connection point position is automatically found as the child node of the main node.

[0038] In practice, two common scenarios exist in chemical engineering. In the first scenario, the connection point design on the equipment drawings is complete, and the coordinates of the reserved connection outlets for pipelines on each unit are clear. In this case, each connection outlet is directly constructed as a child node of the corresponding master node for subsequent calculations. In the second scenario, only the unit number connected to the pipeline is known, but the specific connection point location is not yet determined. In this case, the center coordinates of the unit entity corresponding to the master node are used as the starting position to automatically find the optimal connection point location around the unit as the child node of the master node. For a master node with multiple child nodes, all child nodes of the master node will participate in the subsequent child node simplification process.

[0039] By constructing sub-nodes separately for the cases of "known connection outlet coordinates" and "unknown connection outlet coordinates," this method supports both mature engineering scenarios where the connection point design has been completed and preliminary design scenarios where only the device location is known but the specific connection point is not determined, thus expanding the algorithm's engineering applicability at different stages of chemical engineering design. By automatically finding the optimal connection point location using the center coordinates of the device entity as the starting position when the connection outlet coordinates are unknown, the algorithm incorporates the task of "connection point location selection," which was originally decided by human experience, into the scope of automatic solution. By allowing the same master node to correspond to multiple sub-nodes, multiple candidate connection points of the device can simultaneously enter the path planning optimization process, and the optimal sub-node is finally selected by the sub-node simplification process.

[0040] Step S103: Under the constraint of prioritizing the channel area and avoiding the obstacle area, calculate the optimal path between each pair of adjacent nodes, and use the length of the optimal path between the two points as the path edge length of the corresponding path edge.

[0041] like Figure 6 As shown, Figure 6 It shows that Figure 4 and Figure 5 The engineering problem in the text is transformed into an undirected graph after being modeled mathematically. The undirected graph contains nine circles A, B, C, D, E, F, G, H, and I, corresponding to... Figure 4 The main nodes corresponding to the nine device entities are represented by four circles: numbered 1, 2, 3, and 4. Figure 5 The ordinary nodes corresponding to the branch intersection points ①, ②, ③, and ④ are connected by line segments. Each line segment between adjacent nodes is the path edge described in this step, and the length of each path edge is the length of the optimal path between the two points calculated in this step.

[0042] In the application, the two-point optimal path calculation module is used to calculate and plan the optimal path between a specified starting point and a specified ending point of a single pipeline, using a two-dimensional pathfinding method on a graph. Specific calculation principles include: pre-setting paths on the pipeline corridor as having higher priority and lower overall cost; pre-setting prohibition of passage within the device's obstacle range; exploring nearby accessible passages in eight directions from the starting point, using the estimated overall cost to reach the target point as a weight to determine the next reachable location; continuing to search for the next reachable location from the next possible location until the target point is reached; and by comparing the overall cost of all feasible paths from the starting point to the target point, determining the feasible path with the lowest overall cost as the two-point optimal path between the two nodes.

[0043] By explicitly incorporating the engineering constraints of "channel priority and obstacle avoidance" into the calculation principle of two-point optimal path, the calculated path between each adjacent node naturally meets the engineering rationality requirements of chemical pipeline design, avoiding infeasible paths that traverse plant areas or deviate from the pipe gallery. By calculating the two-point optimal path between each pair of adjacent nodes separately, and using the path length as the path edge length of the corresponding path edge for subsequent multi-point optimal path calculation, the complex multi-point path optimization problem is decomposed into two levels: "two-point optimal path calculation" and "multi-point optimal path selection". This method can both use mature two-point path optimization algorithms as the underlying support and provide accurate path edge length data for the upper-level multi-point optimization, forming a clear and reusable algorithm architecture.

[0044] In one embodiment, step S103 includes: For each pair of adjacent nodes, one is taken as the starting point and the other as the target point. Accessibility of the path is explored in eight directions around the starting point. The estimated total cost to reach the target point is used as a weight to gradually determine the feasible path from the starting point to the target point. The overall cost of at least one of the obtained feasible paths is compared, and the feasible path with the minimum overall cost is determined as the optimal path between the two points. The optimal path between the two points is denormalized and converted into the corresponding coordinate data in the target engineering drawing.

[0045] In application, at the mathematical model level, the continuous two-dimensional plane in the engineering drawings is normalized into discrete grid points, each representing a reachable location. Starting from the starting point, adjacent grid points are explored along eight directions: horizontal, vertical, and four diagonal directions. For each reachable grid point, the overall cost of reaching the target point from the starting point via that grid point is estimated as its weight. The reachable grid point with the minimum overall cost is selected progressively to advance towards the target point until it is reached, thus obtaining at least one feasible path from the starting point to the target point. The overall cost is compared among all feasible paths, and the feasible path with the minimum overall cost is determined as the two-point optimal path. Finally, the two-point optimal path on the normalized grid is denormalized and converted into the actual coordinate data of the engineering drawings, resulting in the two-point optimal path planning for the pipeline from the starting point to the target point.

[0046] By progressively exploring passable locations in eight directions around the starting point, this method grants complete directional freedom to the path in the engineering drawing, avoiding the detours caused by exploring only along horizontal and vertical directions. By gradually converging to the target point using the estimated total cost to reach it as a weight, the algorithm naturally possesses heuristic characteristics during the search process, reducing the computational load and improving the efficiency of calculating the optimal path between two points compared to blind search algorithms without directional bias. Through the final denormalization transformation, the optimal path calculated at the mathematical model level can be accurately restored to the actual coordinate data in the coordinate system of the engineering drawing, ensuring the geometric accuracy of the obtained path edge length data and providing reliable edge length input for subsequent multi-point optimal path calculations.

[0047] Step S104: Based on the master node, the ordinary node, and the path edge, a comprehensive weight consisting of the path edge length, the number of times the path edge is used, and the length tolerance is used to perform multiple rounds of calculation on the optimal multi-point path between all the master nodes, and update the number of times the path edge is used according to the number of times each path edge overlaps in the calculation results of each round.

[0048] like Figure 3 As shown, Figure 3 The complete process framework for multi-point optimal path calculation is shown. The process starts with "input all nodes" and proceeds through the following core calculation steps: "initialize the weights of all edges", "calculate the shortest path between all master node pairs", "count usage times", "calculate the optimal path for all ordinary nodes using weights", "recalculate the optimal path between all master node pairs based on the distribution of ordinary nodes", and "simplify nodes". The "simplify nodes" step branches to three parallel simplification strategy options: "minimum sum of nearest distance", "minimum sum of global distance", and "exhaustive optimization". Finally, it converges to "correct the optimal path" and ends with "display the path".

[0049] In the application, the multi-point optimal path calculation module performs multiple rounds of iterative calculations based on multiple weights between all the points that the pipeline needs to pass through to determine the optimal path between all master nodes. The core idea of ​​the multi-round calculation is as follows: First, starting with the basic shortest path calculation, the initial shortest path scheme between master nodes is obtained using the classic graph theory algorithm; then, the overlap of each path edge in all shortest paths is quantified as the number of times the path edge is used, which together with the original path edge length and length tolerance constitutes a comprehensive weight; then, based on the comprehensive weight, the optimal path is constructed for ordinary nodes using the minimum spanning tree algorithm, resulting in a simplified path edge set after trade-offs; based on the simplified path edge set, the optimal path between master nodes is recalculated, and the child nodes corresponding to each master node are simplified; finally, redundant path edges are pruned to obtain the global core shortest path.

[0050] By introducing a comprehensive weight composed of path edge length, path edge usage frequency, and length tolerance, the optimal path for multiple points is calculated in multiple rounds of iterations. This ensures that the selection of the optimal path no longer relies solely on the "shortest edge length" criterion, but comprehensively considers the reuse and length approximation of path edges across multiple optimal paths. This allows for the pursuit of an overall pipeline network scheme that minimizes the total length of path edges and maximizes path edge reuse from a global perspective spanning multiple starting points to multiple ending points. After each round of calculation, the path edge usage frequency is updated based on the number of overlaps among path edges in the current path. This allows "common path segments" that frequently appear between multiple master node pairs to be identified and given higher priority, guiding the calculation results of subsequent rounds towards "shared trunk roads and reduced branches," thereby reducing the total pipeline length and total pipeline investment. By selecting the optimal path from multiple angles and dimensions, the reliability and rigor of the optimal path results are guaranteed.

[0051] In one embodiment, step S104 includes the following steps S401 to S406: Step S401: Initialize the number of times each path edge is used to zero. Step S402: Based on all the nodes, the path edge length, and the length tolerance, the shortest path algorithm is used to calculate the shortest path between all the main nodes, and the number of times the path edge is used is updated by accumulating the number of times the path edge overlaps in the current calculation result. Step S403: Using the path edge length, the updated path edge usage count, and the length tolerance as the comprehensive weight, the minimum spanning tree algorithm is used to construct a minimum spanning tree for all the ordinary nodes to obtain a simplified path edge set. Step S404: Based on the simplified path edge set, recalculate the optimal path between all the main nodes; Step S405: For the main node corresponding to at least two child nodes, select the optimal child node corresponding to the main node from the at least two child nodes; Step S406: Based on all the master nodes and the simplified optimal child node set, prune redundant path edges that are not included in the simplified path edge set to obtain the core shortest path between all the master nodes.

[0052] In the application, step S401 initializes the usage count of each path edge to zero, providing an initial data benchmark for the usage count component in the comprehensive weight; step S402 performs the first calculation of the shortest path between all master nodes based on the classic shortest path algorithm, including the node composition and distance data value of each shortest path, and counts the number of overlaps of each path edge in all shortest paths, accumulating and updating the usage count of that path edge to obtain the initial dynamic weight of each path edge; step S403 uses the updated comprehensive weight to construct a minimum spanning tree for all ordinary nodes (excluding master nodes) using the minimum spanning tree algorithm, obtaining a simplified set of path edges after trade-offs; step S404, based on this simplified set... The simplified path edge set recalculates the optimal path between all master nodes, prioritizing the selection of the optimal path between master node pairs along the simplified path edge direction. It includes the node composition and distance data value of each optimal path. Step S405 simplifies the child nodes for each master node corresponding to at least two child nodes, selecting the optimal child node corresponding to the master node from multiple candidate child nodes. Step S406, based on all master nodes and the simplified optimal child node set, prunes redundant path edges not included in the simplified path edge set, and finally determines the core shortest path between all master nodes, including the node composition and distance data value of the core shortest path, and calculates the total distance of all optimal paths.

[0053] By refining the calculation of the optimal path for multiple points into six ordered steps—initialization, shortest path calculation, minimum spanning tree construction, recalculation of the optimal path for the main node, simplification of child nodes, and redundant edge pruning—the logic of multi-weight, multi-round calculation is clearly unfolded. Initial statistics on usage frequency are obtained by first performing basic shortest path calculations using path edge length and length tolerance. Then, minimum spanning tree construction is performed using a comprehensive weight that includes usage frequency. This ensures that the dynamic weight of "usage frequency" has a reasonable data source in the initial stage, avoiding the initialization problem where the comprehensive weight becomes invalid due to zero usage frequency. Finally, the redundant path edge pruning step filters out path edges that did not participate in the minimum spanning tree, ensuring that the final determined core shortest path only includes path edges that truly participate in the pipeline framework. The output structure is compact and easily used in subsequent path construction and visual display stages.

[0054] In one embodiment, the formula for calculating the comprehensive weight is: in, This represents the combined weight of path x relative to path y. This represents the length of the path edge in path x. This represents the length of the path edge in path y. This indicates the number of times the path edge of path x is used. The path edge of path y is used the most times, and T represents the length tolerance. When the absolute value of the difference between the path edge length of path x and the path edge length of path y is not greater than the length tolerance, the comprehensive weight is equal to the difference between the number of times the path edge of path x is used and the number of times the path edge of path y is used. When the absolute value of the difference between the path edge length of path x and the path edge length of path y is greater than the length tolerance, the comprehensive weight is equal to the difference between the path edge length of path x and the path edge length of path y.

[0055] In application, the core of designing the comprehensive weighting function lies in formalizing the engineering experience of "prioritizing the reuse of path edges with higher usage frequency when length differences are not significant" into a computable rule. Specifically, the path edge length... This refers to the actual path length of the path edge between adjacent nodes, determined by the shortest path calculation logic between the two points in step S103; the number of times the path edge is used. This refers to the number of times the path edge between adjacent nodes appears in the optimal path between the primary node pairs. After clarifying the data of primary nodes, ordinary nodes, and path edges, the optimal path between primary nodes is calculated based on the minimum spanning tree, and the usage frequency of each path edge in the path is counted simultaneously. The length tolerance T refers to the allowable tolerance range of path edge length when calculating the optimal path between primary nodes based on the minimum spanning tree. Two or more path edges within the tolerance range are considered as equivalent edges with the same length.

[0056] By setting a piecewise functional formula for calculating the comprehensive weight, the algorithm can automatically switch weight criteria based on the magnitude of the length difference between two comparison paths: when the length difference is within the length tolerance range, the "difference in usage frequency" is used as the weight data to guide the algorithm to prioritize path edges shared by multiple master nodes, thereby maximizing the reuse rate of path edges; when the length difference exceeds the length tolerance range, the "length difference" is used as the weight data, and the algorithm reverts to optimizing for the minimum path edge length, avoiding a significant increase in the total pipeline length due to forcibly reusing excessively long path edges; by introducing a length tolerance T as a switching threshold, designers can flexibly adjust the preference for "length priority" and "reuse priority" according to specific engineering accuracy requirements, improving the adaptability of the comprehensive weight calculation formula under different design accuracy scenarios.

[0057] In one embodiment, the path priority determination and discard rules in step S104 include: When the value of the comprehensive weight is greater than zero, the larger the value of the comprehensive weight, the higher the priority of the corresponding path. For any two paths, if the overall weight of one path relative to the other path is greater than the overall weight of the other path relative to the first path, and both are greater than zero, the path with the larger overall weight value shall be selected first. Paths with zero edge length or zero edge usage count are discarded.

[0058] In application, a comprehensive weight value greater than zero means that one path being compared has a clear "priority" semantic relative to the other path. The larger the comprehensive weight value, the higher the priority of the path. Based on this, the algorithm sorts the candidate paths and selects the one with the highest priority. When there are two paths with comprehensive weights greater than zero, the path with the larger comprehensive weight value is selected as the optimal path. As for paths with zero edge length or zero edge usage, the former means that the two nodes overlap or the path is degenerate, and the latter means that the edge has never been selected by any master node pair as the optimal path throughout the multi-round calculation process. Neither should be included in the final pipeline scheme, so they are discarded by default in the algorithm.

[0059] By clearly defining the monotonic correspondence that "the larger the comprehensive weight data value, the higher the priority," the algorithm can directly sort candidate paths based on the weight data value without additional transformation or normalization processing, simplifying the implementation complexity of priority determination. By setting two types of discard rules, namely "path edge length is zero" and "path edge usage count is zero," degenerate paths and redundant path edges are automatically excluded from the final pipeline scheme, simplifying the structural complexity of the final output result and preventing redundant information from entering the subsequent drawing stage.

[0060] In one embodiment, step S104, for the master node corresponding to at least two child nodes, selects the optimal child node corresponding to the master node from the at least two child nodes, including at least one of the following simplification strategies: The strategy of minimizing the sum of nearest distances is as follows: calculate the sum of the distances between each child node of the current master node and the nearest child node of each other master node, and determine the child node with the smallest sum of distances as the optimal child node corresponding to the current master node. Global distance sum minimum strategy: Calculate the total distance between each child node of the current master node and all child nodes of each other master node, and determine the child node with the smallest total distance value as the optimal child node corresponding to the current master node; Exhaustive optimization strategy: Enumerate all the combinations of the current master node's child nodes with all the child nodes of each other master node, calculate the total distance for each combination, and determine the child node corresponding to the combination with the smallest total distance as the optimal child node for the current master node.

[0061] In application, three simplification strategies allow designers to choose the appropriate strategy type when planning multi-point pipeline network routes to adapt to different design environments. Specifically, the minimum total nearest distance strategy and the minimum total global distance strategy are heuristic strategies with moderate computational cost, suitable for engineering scenarios with a large number of child nodes and master nodes, resulting in a large overall computational load. The exhaustive optimization strategy enumerates and compares all possible combinations of child nodes, achieving a strictly global optimal solution, but its computational cost increases exponentially with the number of child nodes, making it suitable for engineering scenarios with a small number of child nodes and requiring a strictly global optimal solution. When there are few nodes, the exhaustive optimization strategy can be prioritized; when there are many nodes leading to a large computational load, the minimum total nearest distance or minimum total global distance strategy is used to improve computational efficiency. All three strategies use "minimum total distance" as the criterion for determining the optimal child node, differing only in the granularity of the total distance calculation (nearest child node pair, all child node pairs, or all permutations).

[0062] By providing three optional sub-node simplification strategies—"minimum sum of nearest distances," "minimum sum of global distances," and "exhaustive search"—this method can flexibly select the appropriate strategy based on the node size and accuracy requirements of specific engineering scenarios, balancing computational efficiency and optimality. By providing both heuristic and exhaustive strategies and supporting manual specification, the algorithm does not force designers to accept a single simplification method. It can obtain a strictly optimal solution through exhaustive search when the sub-node size is small, and obtain an approximate optimal solution through heuristic search when the sub-node size is large, thus improving the usability of the algorithm in different engineering scenarios.

[0063] Step S105: Convert the multi-point optimal path into pipeline network path coordinate data in the target engineering drawing, and draw and display it in the target engineering drawing.

[0064] In the application, the path construction module and the visual display module work together to complete the function of this step: the path construction module converts the core shortest path data obtained in step S104 into pipeline network path coordinate data in the target engineering drawing coordinate system through de-normalization, and constructs the pipeline network entity based on the path coordinate data and pipeline network related attribute data (pipe diameter, material, pressure level, etc.); the visual display module further receives multiple path data transmitted by the path construction module and draws and displays the optimal path result of the pipeline network in the original two-dimensional system drawing.

[0065] By converting the optimal path from multiple points into pipeline network path coordinate data in the target engineering drawings and directly drawing and displaying it in the original drawings, the optimal path results calculated by the algorithm can be directly presented graphically in the CAD system commonly used by chemical engineers. This avoids the intermediate step of "calculation outside the algorithm and manual redrawing," improving the conversion efficiency from path planning schemes to engineering drawings. By combining path coordinate data with pipeline attribute data to construct pipeline network entities, the drawing and display results not only include the geometric information of pipeline direction but also carry the corresponding pipeline attribute information, so that the drawing results completely carry all the output content of path planning.

[0066] The pipeline path drawing method based on multi-weighted multi-source to multi-endpoints provided in this invention takes multiple starting points, multiple ending points, and locations to be traversed as input. It identifies channel areas and obstacle areas and constructs a topology structure composed of main nodes, ordinary nodes, and path edges. It calculates the path edge length between adjacent nodes through optimal path calculation at two points. Through multi-round iterative calculation based on comprehensive weights and simplification of child nodes, it obtains the global core shortest path. Finally, it completes the result display through coordinate transformation and engineering drawing. This method can apply intelligent algorithms to pipeline network design, simplify the pipeline network path planning process in multi-source to multi-endpoint scenarios, improve the design efficiency of pipeline network transportation path planning for designers, significantly optimize the design scheme of pipeline network path planning in the chemical industry, and reduce the total design cost of pipeline network for chemical projects. It is especially suitable for the pipeline general layout design of large-scale chemical projects such as coal chemical, petrochemical, and fine chemical industries.

[0067] This invention also provides a multi-weighted multi-source to multi-endpoint pipeline path drawing system for executing the steps in the above method embodiments. The multi-weighted multi-source to multi-endpoint pipeline path drawing system can be a virtual appliance in a terminal device, run by the terminal device's processor, or it can be the terminal device itself.

[0068] like Figure 2 As shown, Figure 2 This diagram illustrates the structure of a multi-weighted, multi-source to multi-endpoint pipeline path drawing system provided in an embodiment of the present invention. The system comprises seven modules: an initial input module, a data acquisition module, a node construction module, a two-point optimal path calculation module, a multi-point optimal path calculation module, a path construction module, and a visual display module. These seven modules are sequentially connected and communicate with each other according to the data flow direction. The initial input module is used to obtain at least two starting points, at least two ending points, and the locations to be traversed from the target engineering drawings. The data acquisition module is communicatively connected to the starting input module and is used to identify in the target engineering drawings the passage areas that allow priority passage for pipelines and the obstacle areas that prohibit pipeline passage. The node construction module, which is communicatively connected to the data acquisition module, is used to construct the endpoints and branch intersections of the channel area as ordinary nodes, and to construct the starting point, the ending point and the location to be traversed as master nodes. The two-point optimal path calculation module is communicatively connected to the node construction module. It is used to calculate the two-point optimal path between each two adjacent nodes under the constraints of prioritizing the channel area and avoiding the obstacle area, and use the length of the two-point optimal path as the path edge length of the corresponding path edge. The multi-point optimal path calculation module is communicatively connected to the two-point optimal path calculation module. It is used to perform multi-round calculations on the multi-point optimal path between all the main nodes based on the main node, the ordinary node, and the path edge, using a comprehensive weight composed of the path edge length, the number of times the path edge is used, and the length tolerance. The number of times the path edge is used is updated according to the number of times each path edge overlaps in the calculation results of each round. The path construction module is communicatively connected to the multi-point optimal path calculation module and is used to convert the multi-point optimal path into pipeline network path coordinate data in the target engineering drawing. The visual display module is communicatively connected to the path construction module and is used to draw and display the pipeline network path corresponding to the pipeline network path coordinate data in the target engineering drawing.

[0069] In the application, the seven modules are sequentially connected according to the overall data flow of "input acquisition, data recognition, node construction, two-point path calculation, multi-point path selection, path construction, and visual display." The output of the previous module serves as the input data for the next module, forming a complete "end-to-end" path planning link. Specifically, the initial input module transmits the identified start point, end point, and location to be traversed to the data acquisition module; the data acquisition module further transmits the identified channel area and obstacle area to the node construction module; after constructing the main node and ordinary nodes, the node construction module transmits the node topology data to the two-point optimal path calculation module; after calculating the path edge length between adjacent nodes, the two-point optimal path calculation module transmits the path edge data to the multi-point optimal path calculation module; after completing multiple rounds of iterative calculations, the multi-point optimal path calculation module transmits the core shortest path data to the path construction module; after completing coordinate transformation and pipeline network entity modeling, the path coordinate data is transmitted to the visual display module; and finally, the visual display module completes the drawing and display on the engineering drawings. Each module in the system can be a software program module, or it can be implemented through different logic circuits integrated in a processor, or it can be implemented through multiple distributed processors.

[0070] By encapsulating the various functional stages of the multi-source to multi-endpoint pipeline path drawing method into seven independent functional modules, a clear one-to-one correspondence is formed between the system structure and the method steps, facilitating system implementation, maintenance, and functional expansion. By clarifying the communication connections and data flow between modules, the entire data transmission path from input to output is clearly traceable, facilitating system debugging and fault location during engineering implementation. By placing the node construction module after the data acquisition module and before the two-point optimal path calculation module, the node topology data required for the two-point optimal path calculation is complete before the path calculation begins, avoiding calculation anomalies caused by data timing misalignment.

[0071] In one embodiment, the multi-point optimal path calculation module is specifically used for: Initialize the number of times each path edge is used to zero for all of the aforementioned path edges; Based on all the nodes, the path edge length, and the length tolerance, the shortest path algorithm is used to calculate the shortest path between all the main nodes, and the number of times the path edge is used is updated by accumulating the number of times the path edge overlaps in the current calculation result. Using the path edge length, the updated number of times the path edge is used, and the length tolerance as the comprehensive weight, the minimum spanning tree algorithm is used to construct a minimum spanning tree for all the ordinary nodes, resulting in a simplified set of path edges. Based on the simplified set of path edges, the optimal path between all the main nodes is recalculated; For a master node that corresponds to at least two child nodes, select the optimal child node corresponding to the master node from the at least two child nodes; Based on all the master nodes and the simplified optimal child node set, redundant path edges not included in the simplified path edge set are pruned to obtain the core shortest path between all the master nodes.

[0072] In application, the multi-point optimal path calculation module, as the core module with the largest computational load in the entire system, undertakes the execution tasks of all sub-steps from S401 to S406 mentioned above. Internally, it executes the sub-steps in the order of "initialization of usage count, basic calculation of shortest path, construction of minimum spanning tree with comprehensive weight, recalculation of optimal path of main node, simplification of child node, and pruning of redundant path edges", and maintains the synchronous update and consistency of three types of weight data: path edge length, path edge usage count, and length tolerance during the execution process.

[0073] By encapsulating all sub-steps of multi-round comprehensive weight calculation within a single multi-point optimal path calculation module, the system only needs to concern itself with the input and output of the multi-point optimal path calculation module at the data interaction level, without needing to pay attention to the internal multi-round iteration details, thus simplifying the communication burden between system modules. By integrating post-processing steps such as sub-node simplification and redundant path edge pruning into the multi-point optimal path calculation module, the data output to the subsequent path construction module is directly the final core shortest path, avoiding the appearance of semi-finished intermediate data between the output of the multi-point optimal path calculation module and the input of the path construction module. By maintaining the synchronous update of the three types of weight data within the multi-point optimal path calculation module, the comprehensive weight can reflect the latest path edge reuse situation in each round of calculation, ensuring the consistency of multi-round iterative calculation results.

[0074] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for drawing multi-source to multi-endpoint pipeline paths based on multi-weighting, characterized in that, include: Obtain at least two starting points, at least two ending points, and the locations to be traversed from the target project drawings; In the target engineering drawings, identify the passage areas that allow priority passage for pipelines and the obstacle areas that prohibit pipeline passage, construct the endpoints and branch intersections of the passage areas as ordinary nodes, and construct the starting point, the ending point and the location to be traversed as master nodes; Under the constraint of prioritizing the passage area and avoiding the obstacle area, the optimal path between each pair of adjacent nodes is calculated, and the length of the optimal path between the two points is used as the path edge length of the corresponding path edge. Based on the master node, the ordinary node, and the path edge, a comprehensive weight consisting of the path edge length, the number of times the path edge is used, and the length tolerance is used to perform multiple rounds of calculation on the optimal multi-point path between all the master nodes, and the number of times the path edge is used is updated according to the number of times each path edge overlaps in the calculation results of each round. The optimal path at multiple points is converted into pipeline network path coordinate data in the target engineering drawing, and then drawn and displayed in the target engineering drawing.

2. The method for drawing multi-source to multi-endpoint pipeline paths based on multi-weighting as described in claim 1, characterized in that, The acquisition of at least two starting points, at least two ending points, and the locations to be traversed in the target engineering drawings includes: Obtain at least one pathfinding task as input, each pathfinding task including the location of the starting point and the location of the ending point, and at least one of the attribute data of the location to be traversed and the corresponding pipeline; The entity coordinates in the target engineering drawing are identified, and the starting point, ending point, and traversed location in the pathfinding task are associated with the corresponding entity coordinates.

3. The method for drawing multi-source to multi-endpoint pipeline paths based on multi-weighting as described in claim 1, characterized in that, For each of the aforementioned master nodes, the corresponding child nodes are constructed as follows: When the coordinate data of at least two connection exits of the entity corresponding to the main node are known, the at least two connection exits are respectively constructed as child nodes of the main node; When the coordinate data of the connection exit of the entity corresponding to the main node is unknown, the center coordinates of the entity corresponding to the main node are used as the starting position, and the optimal connection point position is automatically found as the child node of the main node.

4. The method for drawing multi-source to multi-endpoint pipeline paths based on multi-weighting as described in claim 1, characterized in that, The calculation of the optimal path between each pair of adjacent nodes includes: For each pair of adjacent nodes, one is taken as the starting point and the other as the target point. Accessibility of the path is explored in eight directions around the starting point. The estimated total cost to reach the target point is used as a weight to gradually determine the feasible path from the starting point to the target point. The overall cost of at least one of the obtained feasible paths is compared, and the feasible path with the minimum overall cost is determined as the optimal path between the two points. The optimal path between the two points is denormalized and converted into the corresponding coordinate data in the target engineering drawing.

5. The method for drawing multi-source to multi-endpoint pipeline paths based on multi-weighting as described in claim 1, characterized in that, The process of performing multiple rounds of calculations on the optimal multi-point path between all the master nodes, and updating the path edge usage count based on the overlap count of each path edge in each round of calculation results, includes: Initialize the number of times each path edge is used to zero for all of the aforementioned path edges; Based on all the nodes, the path edge length, and the length tolerance, the shortest path algorithm is used to calculate the shortest path between all the main nodes, and the number of times the path edge is used is updated by accumulating the number of times the path edge overlaps in the current calculation result. Using the path edge length, the updated number of times the path edge is used, and the length tolerance as the comprehensive weight, the minimum spanning tree algorithm is used to construct a minimum spanning tree for all the ordinary nodes, resulting in a simplified set of path edges. Based on the simplified set of path edges, the optimal path between all the main nodes is recalculated; For a master node that corresponds to at least two child nodes, select the optimal child node corresponding to the master node from the at least two child nodes; Based on all the master nodes and the simplified optimal child node set, redundant path edges not included in the simplified path edge set are pruned to obtain the core shortest path between all the master nodes.

6. The method for drawing multi-source to multi-endpoint pipeline paths based on multi-weighting as described in claim 5, characterized in that, The formula for calculating the overall weight is as follows: in, This represents the combined weight of path x relative to path y. This represents the length of the path edge of path x. This represents the length of the path edge in path y. This indicates the number of times the path edge of path x is used. The path edge of path y is used the most times, and T represents the length tolerance. When the absolute value of the difference between the path edge length of path x and the path edge length of path y is not greater than the length tolerance, the comprehensive weight is equal to the difference between the number of times the path edge of path x is used and the number of times the path edge of path y is used. When the absolute value of the difference between the path edge length of path x and the path edge length of path y is greater than the length tolerance, the comprehensive weight is equal to the difference between the path edge length of path x and the path edge length of path y.

7. The method for drawing multi-source to multi-endpoint pipeline paths based on multi-weighting as described in claim 6, characterized in that, Also includes: When the value of the comprehensive weight is greater than zero, the larger the value of the comprehensive weight, the higher the priority of the corresponding path. For any two paths, if the overall weight of one path relative to the other path is greater than the overall weight of the other path relative to the first path, and both are greater than zero, the path with the larger overall weight value shall be selected first. Paths with zero edge length or zero edge usage count are discarded.

8. The method for drawing multi-source to multi-endpoint pipeline paths based on multi-weighting as described in claim 5, characterized in that, The step of selecting the optimal child node corresponding to the master node from the at least two child nodes includes: Calculate the sum of distances between each child node of the current master node and the nearest child node of each other master node, and determine the child node with the smallest sum of distances as the optimal child node corresponding to the current master node; And / or, calculate the total distance between each child node of the current master node and all child nodes of every other master node, and determine the child node with the smallest total distance value as the optimal child node corresponding to the current master node; And / or, enumerate all the combinations of the current master node's child nodes with all the child nodes of each other master node, calculate the total distance for each combination, and determine the child node corresponding to the combination with the smallest total distance as the optimal child node for the current master node.

9. A multi-weighted, multi-source to multi-endpoint pipeline path drawing system, characterized in that, include: The initial input module is used to obtain at least two starting points, at least two ending points, and the locations to be traversed from the target engineering drawings. The data acquisition module is communicatively connected to the starting input module and is used to identify in the target engineering drawings the passage areas that allow priority passage for pipelines and the obstacle areas that prohibit pipeline passage. The node construction module, which is communicatively connected to the data acquisition module, is used to construct the endpoints and branch intersections of the channel area as ordinary nodes, and to construct the starting point, the ending point and the location to be traversed as master nodes. The two-point optimal path calculation module is communicatively connected to the node construction module. It is used to calculate the two-point optimal path between each two adjacent nodes under the constraints of prioritizing the channel area and avoiding the obstacle area, and use the length of the two-point optimal path as the path edge length of the corresponding path edge. The multi-point optimal path calculation module is communicatively connected to the two-point optimal path calculation module. It is used to perform multi-round calculations on the multi-point optimal path between all the main nodes based on the main node, the ordinary node, and the path edge, using a comprehensive weight composed of the path edge length, the number of times the path edge is used, and the length tolerance. The number of times the path edge is used is updated according to the number of times each path edge overlaps in the calculation results of each round. The path construction module is communicatively connected to the multi-point optimal path calculation module and is used to convert the multi-point optimal path into pipeline network path coordinate data in the target engineering drawing. The visual display module is communicatively connected to the path construction module and is used to draw and display the pipeline network path corresponding to the pipeline network path coordinate data in the target engineering drawing.

10. The multi-weighted, multi-source to multi-endpoint pipeline path drawing system as described in claim 9, characterized in that, The multi-point optimal path calculation module is specifically used for: Initialize the number of times each path edge is used to zero for all of the aforementioned path edges; Based on all the nodes, the path edge length, and the length tolerance, the shortest path algorithm is used to calculate the shortest path between all the main nodes, and the number of times the path edge is used is updated by accumulating the number of times the path edge overlaps in the current calculation result. Using the path edge length, the updated number of times the path edge is used, and the length tolerance as the comprehensive weight, the minimum spanning tree algorithm is used to construct a minimum spanning tree for all the ordinary nodes, resulting in a simplified set of path edges. Based on the simplified set of path edges, the optimal path between all the main nodes is recalculated; For a master node that corresponds to at least two child nodes, select the optimal child node corresponding to the master node from the at least two child nodes; Based on all the master nodes and the simplified optimal child node set, redundant path edges not included in the simplified path edge set are pruned to obtain the core shortest path between all the master nodes.

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