Ship channel multi-path planning method, equipment and medium

Abstract

The invention relates to the field of ship three-dimensional design, and discloses a ship channel multi-path planning method and device and a medium, and the method comprises the steps: constructing a multi-path planning constraint condition; carrying out space grid division on the three-dimensional space of the ship by adopting an orthogonal grid method based on the constraint condition; performing channel path search in the divided space by adopting an improved A * algorithm to obtain feasible nodes; searching the feasible nodes by adopting a depth-first method to obtain an optimal path; according to the method, all feasible path search based on the optimal value is realized, a plurality of optimal paths are provided for designers for comprehensive evaluation and optimization, and the problems of low efficiency and quality caused by the fact that the designers need to manually plan channel paths due to the fact that a traditional single optimal path cannot be suitable for complex constraint conditions are solved.

Description

Technical Field

[0001] The present invention relates to the field of three-dimensional ship design, and in particular to a ship channel multi-path planning method, equipment and medium. Background Art

[0002] The layout and planning of ship pipelines, air ducts, cables and other channels is a complex project that comprehensively considers system functions, performance, safety, economy and maintainability. In the limited and complex space of ships, designers usually adopt refined zoning strategies to ensure that the layout of pipelines and channels is reasonable and avoid conflicts with the hull structure, equipment and other systems.

[0003] When planning the specific path of the channel, the designer follows the following principles: First, strictly avoid mutual interference between pipelines of different media, especially strictly prohibit crossing sensitive areas such as living rooms, control rooms, storage rooms, etc., to reduce the potential risk of pipeline failure and ensure personnel safety and normal operation of the ship; second, focus on the producibility requirements to ensure that all channels are arranged along the X, Y, and Z axes, the channel design meets the minimum straight pipe length and turning radius standards, and the support arrangement takes into account material utilization efficiency and installation convenience to ensure operability and product quality during the production process, so as to make the design scheme more feasible during the engineering implementation stage; third, reduce elbows and intersections, reduce fluid resistance and energy consumption, and at the same time ensure the maintainability and ease of operation of the channel, so as to achieve efficient, safe and economical operation of the ship system and meet multiple design requirements in complex spaces.

[0004] At present, in the design of ship piping, air ducts and electrical systems, 3D design software such as CATIA and NX provide designers with a virtual environment for planning paths in a three-dimensional space. At the same time, they have built-in path planning functions based on Dijkstra algorithm, A* algorithm, D algorithm, etc., which can find the shortest path from the starting point to the end point in a complex and restricted ship environment and avoid conflicts with other structures and systems.

[0005] However, the design of ship piping, air ducts and electrical systems is essentially a path optimization problem that includes multiple considerations, which not only needs to consider the shortest path, but also the system's functional performance, installation convenience, ease of maintenance and potential failure risks. For example, although some paths are theoretically the shortest, if they pass through sensitive areas or cause too many pipe elbows, it may increase fluid resistance, increase operating energy consumption, increase maintenance costs, and even threaten personnel safety and the safety of ship operations.

[0006] Therefore, in the actual design process, the path planning function based on a single optimal value is often not applicable. Designers need to combine professional knowledge and engineering experience to manually find the optimal path that meets multiple objectives. This process is not only time-consuming and labor-intensive, but also has low design efficiency and makes it difficult to quickly respond to design changes and optimization needs. Summary of the invention

[0007] The purpose of the present invention is to propose a ship channel multi-path planning method, device and medium to solve the technical problem that the existing ship channel path planning process has low design efficiency and is difficult to meet actual optimization needs.

[0008] Specifically, the present invention provides a ship channel multi-path planning method, comprising the following steps:

[0009] S1. Construct multi-path planning constraints;

[0010] S2: Based on the constraints, the three-dimensional space of the ship is divided into spatial grids using the orthogonal grid method;

[0011] S3: Use the improved A* algorithm to search for channel paths in the divided space to obtain feasible nodes;

[0012] S4: Use the depth-first method to search for feasible nodes and obtain the optimal path.

[0013] A storage medium stores instructions and data for implementing a multi-path planning method for a ship channel.

[0014] A ship channel multi-path planning device comprises: a processor and the storage medium; the processor loads and executes instructions and data in the storage medium to implement a ship channel multi-path planning method.

[0015] The beneficial effects provided by the present invention are as follows: the path space of the potential path of the channel is preprocessed by setting constraints and dividing the space grid, the spatial scope of the feasible path search is narrowed, and the search of all feasible paths based on the optimal value is realized by improving the open list, closed construction method and feasible path generation method of the A* algorithm, providing designers with multiple optimal paths for comprehensive evaluation and optimization, solving the problem of low efficiency and quality caused by the traditional single optimal path being unable to apply to complex constraints and the need for designers to manually perform channel path planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic flow chart of the method of the present invention;

[0017] Figure 2 It is a working schematic diagram of the hardware device of the present invention. DETAILED DESCRIPTION

[0018] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0019] Before formally describing the present invention, the scheme of the present invention is first generally described for easy understanding.

[0020] Please refer to Figure 1 The present invention provides a method for multi-path planning of a ship channel, comprising the following steps:

[0021] S1. Construct multi-path planning constraints;

[0022] It should be noted that in multi-path planning, constraints are used to screen and optimize the intended search paths. These conditions not only ensure the safety, economy and feasibility of the design, but also take into account the convenience of production and maintenance. Safety specifications require that the channel avoid collisions with other pipelines, equipment or structures to ensure that it does not cross restricted areas; producibility constraints focus on the minimum straight pipe length and turning radius of the channel to ensure construction feasibility; maintainability conditions emphasize reserving enough space for later maintenance, which is achieved by controlling the spacing with adjacent components; support and fixation requirements require that the channel can be arranged with relevant supports to ensure the stability of the channel, which is met by setting the spacing of the surrounding structures; economy is to strive for the shortest path and maximize cost-effectiveness under the premise of meeting all the above conditions.

[0023] In the present invention, the multi-path planning constraints in step S1 include: channel planning area constraints, prohibited area constraints, channel path direction constraints, producibility constraints and support fixation constraints.

[0024] As an embodiment, the channel planning area constraint specifically refers to: setting the channel planning area: expressing the channel planning area in the form of a cube, setting the area start node recommend_A and the end node recommend_B, and the channel connection device interface must be completely contained in the cube.

[0025] The prohibited area constraint specifically refers to: expressing the channel prohibited area in the form of a cube, setting the area start node Prohibition_A and the end node Prohibition_B, and the prohibited area must be included in the channel planning area.

[0026] The channel path direction constraint specifically means that the channel path is along the X, Y, and Z axis directions of the three-dimensional space.

[0027] The productivity constraints specifically refer to: the minimum straight pipe length min_L of the channel and the turning radius turn_R.

[0028] The support fixed constraint specifically refers to: setting the minimum spacing min_D and maximum distance max_D of the channel model along the X, Y, and Z directions.

[0029] S2: Based on the constraints, the three-dimensional space of the ship is divided into spatial grids using the orthogonal grid method;

[0030] It should be noted that step S2 is specifically as follows: the continuous three-dimensional space environment is discretized into a series of cubic grids using the orthogonal grid method, and the position and attributes of each grid cell are expressed using a three-dimensional array grid[i,j,k]=value, where the array index [i,j,k] directly corresponds to the position coordinates of the grid cell in space, and the array value value is used to store the attributes corresponding to the grid.

[0031] As an embodiment, the specific division method of step S2 of the present invention is as follows:

[0032] S21. Grid size setting: Determine the grid size grid_Size based on the complexity of the environment and the accuracy requirements of path planning. It is generally expressed as a multiple of the pipeline diameter.

[0033] S22. Three-dimensional space division: Taking the starting node recommend_A as the coordinate origin, a series of cube units are generated based on the grid size to cover the entire channel planning area. The side length of each unit is equal and their sides are parallel to the coordinate axis.

[0034] S23. Grid information storage: Identify the space occupied by the existing model, and determine the attribute value of each unit according to the prohibited area range, support and fixation requirements, where the value in the model occupied space is 1, the value in the prohibited area is 2, the value within the minimum spacing is 3, the value outside the maximum spacing is 4, and the other values ​​are 0. A three-dimensional array is used for storage to provide input for multi-path search.

[0035] S3: Use the improved A* algorithm to search for channel paths in the divided space to obtain feasible nodes;

[0036] In the present invention, the open list, closed construction method and feasible path generation method of the A* algorithm are improved so that the improved algorithm can search for all paths that meet the optimal value conditions.

[0037] Step S3 is as follows:

[0038] S31, using f(n)=g(n)+h(n) as the evaluation function of the search algorithm, where n represents the current node, f(n) is the estimated total cost from the starting node through node n to the target node, g(n) is the actual cost from the starting node to the current node n, and h(n) is the heuristic estimated cost, expressed as the diagonal distance from the current node n to the target node;

[0039] S32. During the execution of the algorithm, an open list open_list storing nodes to be explored and a closed list close_list of nodes that have been explored are maintained.

[0040] Step S32 is specifically as follows:

[0041] S321, add the starting point to the open list open_list, and calculate its f(n), where the starting node g(n) is 0, and h(n) is the diagonal distance from the starting node to the target node;

[0042] S322, select the node n with the smallest f(n) from the open list. If the open list is empty, there are no more paths to the end point, and the algorithm ends;

[0043] S323, remove the node n from the open list open_list, and add it to the closed list close_list;

[0044] S324, if node n is the end point, a path from the start point to the end point has been found; otherwise, according to the forbidden area setting, the channel path direction, the support and fixation requirements, all the neighboring nodes of node n that meet the conditions are obtained based on the three-dimensional array grid storing the grid information, and the g(m), h(m) and f(m) values ​​of each neighboring node m that meets the constraint conditions are calculated and then the following processing is performed:

[0045] When the adjacent node m is already in the closed list close_list, check whether the g values ​​of the two are equal. If they are equal, add the current node n as another parent node of the adjacent node m, otherwise ignore the adjacent node;

[0046] When the adjacent node m is already in the open list open_list, check the two g values. If the g value in the open list is greater, update its parent node and g; if they are equal, add the current node as another parent node; otherwise ignore it;

[0047] When the adjacent node m is not in the open list open_list, add it to the open list;

[0048] S325. Repeat steps S322 to S324 until all nodes are traversed.

[0049] S4: Use the depth-first method to search for feasible nodes and obtain the optimal path.

[0050] Step S4 is as follows:

[0051] Based on the channel producibility conditions, a depth-first algorithm is used to construct multiple paths that meet the optimal values ​​and evaluation conditions based on the searched nodes for designers to conduct comprehensive evaluation.

[0052] It should be noted that depth-first search (BFS) is a commonly used path search algorithm. It is implemented using a recursive function. The specific method is as follows:

[0053] a) Take the end point as the current search node and construct the optimal path from the starting point to the current search node through the "path backtracking" method;

[0054] b) Path backtracking: Get all parent nodes f_nodes of the current search node cur_node. If the parent node is empty, the algorithm ends; otherwise, traverse all parent nodes f_nodes, take each parent node f_node as the current search node, and construct the path road from the starting point to each parent node f_node by recursively calling the "path backtracking" method. Take road+cur_node as the path from the starting point to the current node, calculate whether the path meets the producibility condition, and return the path if it does, otherwise discard the current path.

[0055] It should be noted that the above path backtracking is a typical recursive function, which continuously calls itself to construct the path with new nodes as input parameters during execution.

[0056] See also Figure 2 , Figure 2 It is a schematic diagram of the working of the hardware device of an embodiment of the present invention, and the hardware device specifically includes: a ship channel multi-path planning device 401, a processor 402 and a storage medium 403.

[0057] A ship channel multi-path planning device 401: The ship channel multi-path planning device 401 implements the ship channel multi-path planning method.

[0058] Processor 402: The processor 402 loads and executes the instructions and data in the storage medium 403 to implement the multi-path planning method for a ship channel.

[0059] Storage medium 403: The storage medium 403 stores instructions and data; the storage medium 403 is used to implement the multi-path planning method for a ship channel.

[0060] The key points of the present invention are:

[0061] 1. In the setting of constraint conditions, the channel planning area setting adopts the minimization principle, and the prohibited area setting adopts the maximization principle, thereby narrowing the path search space.

[0062] 2. In the spatial grid division, the grid size directly affects the accuracy and efficiency of the subsequent path search. It is generally expressed in multiples of the pipeline diameter. The volume of the divided cube should be smaller than the volume of the smallest component in the space.

[0063] 3. In the optimal path evaluation, users can further filter the search path by customizing rules (such as the number of path turns and intersections) according to design requirements, thereby narrowing the user's screening range.

[0064] The beneficial effects of the present invention are as follows: the present invention proposes a multi-path channel planning method and output system, pre-processes the path space of the potential path of the channel by setting constraints and dividing the space grid, narrows the spatial scope of the feasible path search, and realizes the search of all feasible paths based on the optimal value by improving the open list, closed construction method and feasible path generation method of the A* algorithm, provides designers with multiple optimal paths for comprehensive evaluation and optimization, and solves the problem of low efficiency and quality caused by the traditional single optimal path being unable to apply to complex constraints and the need for designers to manually perform channel path planning.

[0065] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A ship channel multi-path planning method, characterized in that: The method comprises the following steps: S1. Construct multi-path planning constraints; S2: Based on the constraints, the three-dimensional space of the ship is divided into spatial grids using the orthogonal grid method; S3: Use the improved A* algorithm to search for channel paths in the divided space to obtain feasible nodes; S4: Use the depth-first method to search for feasible nodes and obtain the optimal path.

2. A ship channel multi-path planning method as claimed in claim 1, characterized in that: The multi-path planning constraints in step S1 include: channel planning area constraints, prohibited area constraints, channel path direction constraints, producibility constraints and support fixation constraints.

3. A ship channel multi-path planning method as claimed in claim 1, characterized in that: Step S2 is specifically as follows: the continuous three-dimensional space environment is discretized into a series of cubic grids using the orthogonal grid method, and the position and attributes of each grid cell are expressed using a three-dimensional array grid[i,j,k]=value, where the array index [i,j,k] directly corresponds to the position coordinates of the grid cell in space, and the array value value is used to store the attributes corresponding to the grid.

4. A ship channel multi-path planning method as claimed in claim 1, characterized in that: Step S3 is as follows: S31, using f(n)=g(n)+h(n) as the evaluation function of the search algorithm, where n represents the current node, f(n) is the estimated total cost from the starting node through node n to the target node, g(n) is the actual cost from the starting node to the current node n, and h(n) is the heuristic estimated cost, expressed as the diagonal distance from the current node n to the target node; S32. During the execution of the algorithm, an open list open_list storing nodes to be explored and a closed list close_list of nodes that have been explored are maintained.

5. A ship channel multi-path planning method as claimed in claim 4, characterized in that: Step S32 is specifically as follows: S321, add the starting point to the open list open_list, and calculate its f(n), where the starting node g(n) is 0, and h(n) is the diagonal distance from the starting node to the target node; S322, select the node n with the smallest f(n) from the open list. If the open list is empty, there are no more paths to the end point, and the algorithm ends; S323, remove the node n from the open list open_list, and add it to the closed list close_list; S324, if node n is the end point, a path from the start point to the end point has been found; otherwise, according to the forbidden area setting, the channel path direction, the support and fixation requirements, all the neighboring nodes of node n that meet the conditions are obtained based on the three-dimensional array grid storing the grid information, and the g(m), h(m) and f(m) values ​​of each neighboring node m that meets the constraint conditions are calculated and then the following processing is performed: When the adjacent node m is already in the closed list close_list, check whether the g values ​​of the two are equal. If they are equal, add the current node n as another parent node of the adjacent node m, otherwise ignore the adjacent node; When the adjacent node m is already in the open list open_list, check the two g values. If the g value in the open list is greater, update its parent node and g; If they are equal, add the current node as another parent node; Otherwise ignore it; When the adjacent node m is not in the open list open_list, add it to the open list; S325. Repeat steps S322 to S324 until all nodes are traversed.

6. A ship channel multi-path planning method as claimed in claim 1, characterized in that: Step S4 is as follows: obtain all parent nodes f_nodes of the current search node cur_node in the feasible nodes. If the parent node is empty, the algorithm ends; otherwise, traverse all parent nodes f_nodes, take each parent node f_node as the current search node, construct a path road from the starting point to each parent node f_node through the path construction algorithm, take road+cur_node as the path from the starting point to the current node, calculate whether the path meets the producibility condition, and return the path if it does, otherwise discard the current path.

7. A storage medium, characterized in that: The storage medium stores instructions and data for implementing a ship channel multi-path planning method as described in any one of claims 1 to 6.

8. A ship channel multi-path planning device, characterized in that: include: Processor and storage medium; the processor loads and executes instructions and data in the storage medium to implement a ship channel multi-path planning method as described in any one of claims 1 to 6.

Images