Intelligent pipe arrangement method and system for electromechanical pipe network

Abstract

The present invention discloses an intelligent pipe laying method and system for electromechanical pipe networks, which relates to the technical field of electromechanical pipe networks. The method comprises: obtaining pipe information of a target pipe laying area, wherein the pipe information includes pipe laying demand information of N pipe sections; collecting P regional constraint information of the target pipe laying area, wherein the regional constraint information is used to describe areas within the target pipe laying area where pipes cannot be laid; locating the pipe laying area based on the P regional constraint information to obtain a pipe laying area space; generating multiple pipe laying schemes based on the pipe laying demand information of the N pipe sections and the pipe laying area space; optimizing the multiple pipe laying schemes to generate a target pipe laying scheme. The present invention solves the technical problem in the prior art that the degree of fit between the electromechanical pipe network and the actual application area during intelligent pipe laying is not high, resulting in low pipe laying economy and practicality, thereby achieving the technical effect of improving pipe laying quality and accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of electromechanical pipe networks, and in particular to an intelligent pipe arrangement method and system for electromechanical pipe networks. Background Art

[0002] The routing of electromechanical pipes is primarily based on relevant design specifications and standards to ensure rationality. However, in actual routing, customer needs have evolved from previously standardized requirements, resulting in routing designs that are no longer adaptive to these needs. Existing technologies for intelligent routing of electromechanical pipes lack a high degree of alignment with the actual application area, resulting in technical issues such as low cost and practicality. Summary of the Invention

[0003] The present application provides an intelligent pipe laying method and system for electromechanical pipe networks, which is used to solve the technical problem in the prior art that the intelligent pipe laying of electromechanical pipe networks is not well aligned with the actual application area, resulting in low pipe laying economy and practicality.

[0004] In view of the above problems, the present application provides an intelligent pipe arrangement method and system for electromechanical pipe networks.

[0005] In a first aspect of the present application, a smart pipe arrangement method for an electromechanical pipe network is provided, the method comprising:

[0006] Obtaining pipeline information of a target pipe arrangement area, wherein the pipeline information includes pipe arrangement demand information of N pipe sections;

[0007] Collecting P pieces of regional constraint information of the target pipe arrangement area, where the regional constraint information is used to describe areas in the target pipe arrangement area where pipes cannot be laid;

[0008] Positioning the pipe arrangement area based on the P area constraint information to obtain the pipe arrangement area space;

[0009] Generate multiple pipeline layout plans based on the pipe layout demand information of N pipe sections and the pipe layout area space;

[0010] Optimize the multiple pipeline layout plans to generate a target pipeline layout plan.

[0011] A second aspect of the present application provides an intelligent pipe arrangement system for an electromechanical pipe network, the system comprising:

[0012] A pipeline information acquisition module is used to acquire pipeline information of a target pipe arrangement area, wherein the pipeline information includes pipe arrangement demand information of N pipe sections;

[0013] an area constraint information collection module, configured to collect P area constraint information of the target pipe arrangement area, wherein the area constraint information is used to describe areas in the target pipe arrangement area where pipes cannot be laid;

[0014] A layout area space acquisition module is used to locate the pipe arrangement area based on the P area constraint information to obtain the pipe arrangement area space;

[0015] A pipeline layout plan generating module is used to generate multiple pipeline layout plans based on the pipeline layout demand information of N pipe sections and the pipeline layout area space;

[0016] The target pipe arrangement scheme generating module is used to optimize the multiple pipe arrangement schemes and generate a target pipe arrangement scheme.

[0017] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0018] This application obtains pipeline information of the target pipe laying area, wherein the pipeline information includes pipe laying demand information of N pipe sections, and then collects P regional constraint information of the target pipe laying area. The regional constraint information is used to describe the area in the target pipe laying area where pipelines cannot be laid. Then, the pipe laying area is located based on the P regional constraint information, and the pipe laying area space is obtained. Based on the N pipe section pipe laying demand information and the pipe laying area space, multiple pipeline laying plans are generated. Then, the multiple pipeline laying plans are optimized to generate a target pipe laying plan. The technical effect of improving the degree of fit between the pipe laying plan and the actual situation of the area and improving the quality of pipe laying is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A flow chart of an intelligent pipe arrangement method for an electromechanical pipe network provided in an embodiment of the present application;

[0021] Figure 2 A schematic diagram of a process for obtaining P regional constraint information in the intelligent pipe arrangement method for electromechanical pipe networks provided in an embodiment of the present application;

[0022] Figure 3 A schematic diagram of a process for obtaining a set of multiple pipeline layout solutions to be selected in the intelligent pipe arrangement method for electromechanical pipe networks provided in an embodiment of the present application;

[0023] Figure 4A schematic structural diagram of an intelligent pipe arrangement system for electromechanical pipe networks provided in an embodiment of the present application.

[0024] Explanation of reference numerals: pipeline information acquisition module 11 , area constraint information acquisition module 12 , layout area space acquisition module 13 , pipeline layout plan generation module 14 , target pipe arrangement plan generation module 15 . DETAILED DESCRIPTION

[0025] The present application provides an intelligent pipe laying method and system for electromechanical pipe networks, aiming to solve the technical problem in the prior art that the intelligent pipe laying of electromechanical pipe networks is not well aligned with the actual application area, resulting in low pipe laying economy and practicality.

[0026] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0027] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0028] Example 1

[0029] like Figure 1 As shown, the present application provides an intelligent pipe arrangement method for an electromechanical pipe network, wherein the method comprises:

[0030] Step S100: Obtaining pipeline information of a target pipe arrangement area, wherein the pipeline information includes pipe arrangement demand information of N pipe sections;

[0031] In an embodiment of the present application, the target pipe laying area is any area that needs to be set up for pipe network laying, which can be a test building, a park, etc. Pipeline division is performed according to the pipe network design information of the target pipe laying area to obtain pipeline information. The pipeline information is used to describe the requirements for laying electromechanical pipelines in the target area. The pipeline information includes N pipe segment laying requirement information. The N pipe segment laying requirement information is used to describe the pipe specifications, lengths, laying purposes, etc. that need to be laid for each pipe segment in the target area. Obtaining the N pipe segment laying requirement information provides a basis for subsequent intelligent pipe laying.

[0032] Step S200: Collecting P pieces of regional constraint information of the target pipe arrangement area, where the regional constraint information is used to describe areas within the target pipe arrangement area where pipes cannot be laid;

[0033] Further, such as Figure 2 As shown, step S200 in this embodiment of the application further includes:

[0034] Detecting geological information of the target pipe-draining area to obtain multiple first warning areas;

[0035] Marking multiple building layout areas in the target drainage area to obtain multiple second warning areas;

[0036] Perform regional fusion on the multiple first warning areas and the multiple second warning areas to obtain P pieces of regional constraint information.

[0037] In one possible embodiment, regions within the target pipe laying area where pipes cannot be laid are collected to obtain the P region constraint information. The region constraint information is used to describe the regions within the target pipe laying area where pipes cannot be laid. Thus, based on the actual conditions of the target pipe laying area, regions where pipes can be laid are constrained, achieving the technical effects of improving pipe laying quality, performing dimensionality reduction analysis on the region in advance, and significantly increasing pipe laying efficiency.

[0038] In one embodiment, a radar detector can be used to determine the distribution of underground materials by utilizing the reflection of radar waves by the underground medium in the pipe drainage area, thereby obtaining multiple first warning areas. That is to say, after detecting the geological information of the target pipe drainage area, the area that is not suitable for pipe drainage is identified, and multiple first warning areas are generated, thereby achieving the goal of regional constraints on the target pipe drainage area from the perspective of geological analysis. Furthermore, multiple building layout areas in the target pipe drainage area are identified, and preferably, the locations of supporting equipment around the multiple building layout areas are matched and identified, and multiple second warning areas are obtained based on the identification results. Among them, the second warning area is a warning area obtained after constraining the target pipe drainage area from the perspective of existing buildings. The overlapping areas in the multiple first warning areas and the multiple second warning areas are fused to obtain the P regional constraint information. Based on the P regional constraint information, the target pipe drainage area can be restricted from two dimensions, thereby achieving the goal of regional dimensionality reduction.

[0039] Step S300: Positioning the pipe arrangement area based on the P area constraint information to obtain the pipe arrangement area space;

[0040] In one possible embodiment, the P area constraint information is removed from the target pipe arrangement area to obtain an area where pipe arrangement can be performed and generate the pipe arrangement area space. This achieves the technical effect of limiting the area for subsequent pipe arrangement and optimizing the accuracy of pipe arrangement.

[0041] Step S400: generating multiple pipeline layout plans based on the pipe layout demand information of N pipe sections and the pipe layout area space;

[0042] In one possible embodiment, multiple sample pipe segment routing requirements, multiple sample pipe layout area spaces, and multiple sample pipe layout plan sets are obtained as training data. A network layer constructed based on a convolutional neural network is supervised and trained until convergence, thereby obtaining a plan identification network layer. Furthermore, the N pipe segment routing requirements and the pipe layout area spaces are transmitted to the plan identification network layer for intelligent plan identification, thereby obtaining multiple pipe layout plans. By utilizing the plan identification network layer for intelligent identification, the technical effect of improving pipe layout efficiency is achieved, paving the way for intelligent pipe routing.

[0043] Step S500: Optimizing the plurality of pipeline layout plans to generate a target pipeline layout plan.

[0044] Further, such as Figure 3 As shown, step S500 in this embodiment of the application further includes:

[0045] Collect the design specification requirements of the pipe arrangement demand information of N pipe sections and generate the first pipe arrangement constraint information;

[0046] Perform tolerance interval analysis based on the pipe arrangement demand information of N pipe sections to generate N tolerance intervals;

[0047] Adjusting the plurality of pipeline layout plans multiple times according to the N tolerance intervals to generate a plurality of adjusted pipeline layout plan sets;

[0048] The plurality of adjusted pipeline layout scheme sets are screened using the first row of pipe constraint information to obtain a plurality of candidate pipeline layout scheme sets.

[0049] Furthermore, step S500 in the embodiment of the present application further includes:

[0050] Using the pipe quality identification network layer to perform fitness identification on the multiple candidate pipe layout scheme sets to obtain multiple scheme fitness sets;

[0051] Traversing the plurality of scheme fitness sets and selecting the optimal candidate pipeline layout schemes for the plurality of stages corresponding to the maximum fitness values;

[0052] Taking the optimal candidate pipeline layout schemes in the multiple stages as the optimization direction, the multiple candidate pipeline layout scheme sets are optimized and adjusted to obtain multiple optimized pipeline layout scheme sets.

[0053] Furthermore, step S500 in the embodiment of the present application further includes:

[0054] Generate multiple optimization coefficients by respectively calculating the ratio of the fitness of the multiple optimal solutions of the multiple optimal candidate pipeline layout solutions to the sum of the fitness of the multiple optimal solutions of the previous multiple stages;

[0055] Multiplying the plurality of optimization coefficients by a preset optimization step size to obtain a plurality of free optimization step sizes;

[0056] Based on the multiple free optimization step sizes, taking the multiple optimal candidate pipeline layout schemes as the optimization direction, optimizing and adjusting the multiple candidate pipeline layout scheme sets, thereby obtaining multiple optimized pipeline layout scheme sets;

[0057] The maximum fitness of the scheme among the plurality of optimized pipeline layout schemes is selected as the target pipeline layout scheme.

[0058] Furthermore, step S500 in the embodiment of the present application further includes:

[0059] Obtain multiple sample pipeline layout plans and multiple plan fitnesses as training sample data;

[0060] The network layer constructed based on the feedforward neural network is trained by dividing the training sample data into n groups, and the parameters of the network layer are updated according to the training results of the previous group during the training process until the output reaches convergence, thereby generating the pipe quality recognition network layer.

[0061] In one possible embodiment, after obtaining the plurality of pipeline layout plans, the plurality of pipeline layout plans are adjusted and optimized to obtain the target pipeline layout plan that best meets the actual conditions of the target pipeline layout area. The target pipeline layout plan is used for pipeline layout in the target pipeline layout area.

[0062] Preferably, the design specification requirements that need to be met when laying each pipe section in the N pipe section piping demand information are collected separately, such as the spacing between adjacent pipes is 30 cm, and multiple design specification requirements are summarized to generate the first pipe arrangement constraint information. The first pipe arrangement constraint information is used to restrict the piping of different pipe sections in the target pipe arrangement area. Then, based on the piping design information corresponding to the N pipe section piping area information, the range that can be adjusted when laying different pipe sections is determined, thereby obtaining the N tolerance intervals. Based on the N tolerance intervals, multiple pipeline layout schemes are adjusted multiple times within the N tolerance intervals, and the amplitude of each adjustment may be inconsistent, thereby obtaining multiple sets of adjusted pipeline layout schemes. Then, the first pipe arrangement constraint information is used to perform an overall analysis of the multiple sets of adjusted pipeline layout schemes, and the schemes that do not meet the pipeline layout requirements are eliminated, thereby obtaining the multiple sets of candidate pipeline layout schemes.

[0063] Preferably, the pipe quality identification network layer is used to perform fitness identification on the multiple sets of candidate pipeline layout schemes to obtain multiple scheme fitness sets. The pipe quality identification network layer is used to perform intelligent identification of the pipeline layout schemes to be selected. The scheme fitness is used to describe the degree of adaptability of the pipeline layout scheme to be selected and the target pipe area. The multiple scheme fitness sets are traversed to select the multiple stage optimal candidate pipeline layout schemes corresponding to the maximum fitness. With the multiple stage optimal candidate pipeline layout schemes as the optimization direction, the multiple sets of candidate pipeline layout schemes are optimized and adjusted, so that the candidate pipeline layout schemes in the corresponding candidate pipeline layout scheme set can be adjusted as a whole towards the direction of the stage optimal candidate pipeline, thereby obtaining multiple optimized pipeline layout scheme sets.

[0064] In one possible embodiment, the ratio of the fitness of the multiple optimal solutions for the multiple optimal candidate pipeline layout solutions for each stage to the sum of the fitness of the multiple optimal solutions for the previous stages is used to generate multiple optimization coefficients. The optimization coefficient reflects the quality of the optimal candidate pipeline layout solutions for different stages. The larger the optimization coefficient, the better the quality of the optimal candidate pipeline layout solution for the corresponding stage. Furthermore, the multiple optimization coefficients are multiplied by the preset optimization step size to obtain multiple free optimization step sizes. The preset optimization step size is the amplitude for adjusting the solution set by those skilled in the art. By multiplying the multiple optimization coefficients by the multiple free optimization step sizes, an optimization amplitude that conforms to the actual situation of the set of multiple candidate pipeline layout solutions is obtained. This achieves the technical effect of making refined solution adjustments and improving the accuracy and optimization efficiency of the optimized solution.

[0065] In one possible embodiment, the maximum fitness value of the scheme in the set of multiple optimized pipe layout schemes is selected as the target pipe layout scheme. Preferably, multiple sample pipe layout schemes and multiple scheme fitness values ​​are obtained as training sample data, and then the network layer constructed based on the feedforward neural network is trained by dividing the training sample data into n groups. During the training process, the network layer parameters are updated according to the training results of the previous group until the output reaches convergence, thereby generating the pipe layout quality identification network layer. The pipe layout quality identification network layer is used to intelligently identify the quality of the pipe layout scheme.

[0066] In summary, the embodiments of the present application have at least the following technical effects:

[0067] This application obtains pipeline information of the target pipe laying area, wherein the pipeline information includes N pipe section pipe laying demand information as the basis for subsequent pipe laying scheme optimization, then collects P regional constraint information of the target pipe laying area, the regional constraint information is used to describe the area in the target pipe laying area where pipelines cannot be laid, locates the pipe laying area based on the P regional constraint information, obtains the pipe laying area space, and achieves the goal of optimizing and screening the pipe laying area and improving the accuracy of pipe laying. Then, based on the N pipe section pipe laying demand information and the pipe laying area space, multiple pipe laying schemes are generated, and the multiple pipe laying schemes are optimized to generate a target pipe laying scheme. The technical effect of improving the quality and accuracy of pipe laying is achieved.

[0068] Example 2

[0069] Based on the same inventive concept as the intelligent pipe arrangement method for electromechanical pipe network in the above embodiment, Figure 4 As shown, the present application provides an intelligent pipe arrangement system for electromechanical pipe networks. The system and method embodiments in the present application are based on the same inventive concept. The system includes:

[0070] The pipeline information acquisition module 11 is used to obtain pipeline information of the target pipe arrangement area, wherein the pipeline information includes pipe arrangement demand information of N pipe sections;

[0071] An area constraint information collection module 12 is used to collect P area constraint information of the target pipe arrangement area, where the area constraint information is used to describe areas in the target pipe arrangement area where pipes cannot be laid;

[0072] A layout area space obtaining module 13 is configured to locate the pipe arrangement area based on the P area constraint information to obtain the pipe arrangement area space;

[0073] A pipeline layout plan generating module 14 is configured to generate multiple pipeline layout plans based on the pipeline layout demand information of the N pipe sections and the pipeline layout area space;

[0074] The target pipe arrangement scheme generating module 15 is used to optimize the multiple pipe arrangement schemes and generate a target pipe arrangement scheme.

[0075] Furthermore, the method is used to perform the following steps:

[0076] Detecting geological information of the target drainage area to obtain multiple first warning areas;

[0077] Marking multiple building layout areas in the target pipe drainage area to obtain multiple second warning areas;

[0078] Perform regional fusion on the multiple first warning areas and the multiple second warning areas to obtain P pieces of regional constraint information.

[0079] Furthermore, the method is used to perform the following steps:

[0080] Collect the design specification requirements of the pipe arrangement demand information of N pipe sections and generate the first pipe arrangement constraint information;

[0081] Perform tolerance interval analysis based on the pipe arrangement demand information of N pipe sections to generate N tolerance intervals;

[0082] Adjusting the plurality of pipeline layout plans multiple times according to the N tolerance intervals to generate a plurality of adjusted pipeline layout plan sets;

[0083] The plurality of adjusted pipeline layout scheme sets are screened using the first row of pipe constraint information to obtain a plurality of candidate pipeline layout scheme sets.

[0084] Furthermore, the method is used to perform the following steps:

[0085] Using the pipe quality identification network layer to perform fitness identification on the multiple candidate pipe layout scheme sets to obtain multiple scheme fitness sets;

[0086] Traversing the plurality of scheme fitness sets and selecting the optimal candidate pipeline layout schemes for the plurality of stages corresponding to the maximum fitness values;

[0087] Taking the optimal candidate pipeline layout schemes in the multiple stages as the optimization direction, the multiple candidate pipeline layout scheme sets are optimized and adjusted to obtain multiple optimized pipeline layout scheme sets.

[0088] Furthermore, the method is used to perform the following steps:

[0089] Generate multiple optimization coefficients by respectively calculating the ratio of the fitness of the multiple optimal solutions of the multiple optimal candidate pipeline layout solutions to the sum of the fitness of the multiple optimal solutions of the previous multiple stages;

[0090] Multiplying the plurality of optimization coefficients by a preset optimization step size to obtain a plurality of free optimization step sizes;

[0091] Based on the multiple free optimization step sizes, taking the multiple optimal candidate pipeline layout schemes as the optimization direction, optimizing and adjusting the multiple candidate pipeline layout scheme sets, thereby obtaining multiple optimized pipeline layout scheme sets;

[0092] The maximum fitness of the scheme among the plurality of optimized pipeline layout schemes is selected as the target pipeline layout scheme.

[0093] Furthermore, the method is used to perform the following steps:

[0094] Obtain multiple sample pipeline layout plans and multiple plan fitnesses as training sample data;

[0095] The network layer constructed based on the feedforward neural network is trained by dividing the training sample data into n groups, and the parameters of the network layer are updated according to the training results of the previous group during the training process until the output reaches convergence, thereby generating the pipe quality recognition network layer.

[0096] It should be noted that the above-mentioned order of the embodiments of the present application is for descriptive purposes only and does not represent the superiority or inferiority of the embodiments. The above description is of specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0097] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

[0098] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. An intelligent pipe arrangement method for electromechanical pipe networks, characterized in that: The method comprises: Obtaining pipeline information of a target pipe arrangement area, wherein the pipeline information includes pipe arrangement demand information of N pipe sections; Collecting P pieces of regional constraint information of the target pipe arrangement area, where the regional constraint information is used to describe areas in the target pipe arrangement area where pipes cannot be laid; Positioning the pipe arrangement area based on the P area constraint information to obtain the pipe arrangement area space; Generate multiple pipeline layout plans based on the pipe layout demand information of N pipe sections and the pipe layout area space; Optimizing the multiple pipeline layout plans to generate a target pipeline layout plan; The method further comprises: Collect the design specification requirements of the pipe arrangement demand information of N pipe sections and generate the first pipe arrangement constraint information; Perform tolerance interval analysis based on the pipe arrangement demand information of N pipe sections to generate N tolerance intervals; Adjusting the plurality of pipeline layout plans multiple times according to the N tolerance intervals to generate a plurality of adjusted pipeline layout plan sets; Filtering the plurality of adjusted pipeline layout scheme sets using the first pipe row constraint information to obtain a plurality of candidate pipeline layout scheme sets; Using the pipe quality identification network layer to perform fitness identification on the multiple candidate pipe layout scheme sets to obtain multiple scheme fitness sets; Traversing the plurality of scheme fitness sets and selecting the optimal candidate pipeline layout schemes for the plurality of stages corresponding to the maximum fitness values; Taking the optimal candidate pipeline layout schemes of the multiple stages as the optimization direction, optimizing and adjusting the multiple candidate pipeline layout scheme sets, thereby obtaining multiple optimized pipeline layout scheme sets; Generate multiple optimization coefficients by respectively calculating the ratio of the fitness of the multiple optimal solutions of the multiple optimal candidate pipeline layout solutions to the sum of the fitness of the multiple optimal solutions of the previous multiple stages; Multiplying the plurality of optimization coefficients by a preset optimization step size to obtain a plurality of free optimization step sizes; Based on the multiple free optimization step sizes, taking the multiple optimal candidate pipeline layout schemes as the optimization direction, optimizing and adjusting the multiple candidate pipeline layout scheme sets, thereby obtaining multiple optimized pipeline layout scheme sets; The maximum fitness of the scheme among the plurality of optimized pipeline layout schemes is selected as the target pipeline layout scheme.

2. The method according to claim 1, wherein The method further comprises: Detecting geological information of the target drainage area to obtain multiple first warning areas; Marking multiple building layout areas in the target pipe drainage area to obtain multiple second warning areas; Perform regional fusion on the multiple first warning areas and the multiple second warning areas to obtain P pieces of regional constraint information.

3. The method according to claim 1, wherein The method further comprises: Obtain multiple sample pipeline layout plans and multiple plan fitnesses as training sample data; The network layer constructed based on the feedforward neural network is trained by dividing the training sample data into n groups, and the parameters of the network layer are updated according to the training results of the previous group during the training process until the output reaches convergence, thereby generating the pipe quality recognition network layer.

4. Intelligent pipe arrangement system for electromechanical pipe network, characterized by: The system comprises: A pipeline information acquisition module is used to acquire pipeline information of a target pipe arrangement area, wherein the pipeline information includes pipe arrangement demand information of N pipe sections; an area constraint information collection module, configured to collect P area constraint information of the target pipe arrangement area, wherein the area constraint information is used to describe areas in the target pipe arrangement area where pipes cannot be laid; A layout area space acquisition module is used to locate the pipe arrangement area based on the P area constraint information to obtain the pipe arrangement area space; A pipeline layout plan generating module is used to generate multiple pipeline layout plans based on the pipeline layout demand information of N pipe sections and the pipeline layout area space; A target pipe arrangement scheme generating module is used to optimize the multiple pipe arrangement schemes and generate a target pipe arrangement scheme; The system is used to perform the following steps: Collect the design specification requirements of the pipe arrangement demand information of N pipe sections and generate the first pipe arrangement constraint information; Perform tolerance interval analysis based on the pipe arrangement demand information of N pipe sections to generate N tolerance intervals; Adjusting the plurality of pipeline layout plans multiple times according to the N tolerance intervals to generate a plurality of adjusted pipeline layout plan sets; Filtering the plurality of adjusted pipeline layout scheme sets using the first pipe row constraint information to obtain a plurality of candidate pipeline layout scheme sets; Using the pipe quality identification network layer to perform fitness identification on the multiple candidate pipe layout scheme sets to obtain multiple scheme fitness sets; Traversing the plurality of scheme fitness sets and selecting the optimal candidate pipeline layout schemes for the plurality of stages corresponding to the maximum fitness values; Taking the optimal candidate pipeline layout schemes of the multiple stages as the optimization direction, optimizing and adjusting the multiple candidate pipeline layout scheme sets, thereby obtaining multiple optimized pipeline layout scheme sets; Generate multiple optimization coefficients by respectively calculating the ratio of the fitness of the multiple optimal solutions of the multiple optimal candidate pipeline layout solutions to the sum of the fitness of the multiple optimal solutions of the previous multiple stages; Multiplying the plurality of optimization coefficients by a preset optimization step size to obtain a plurality of free optimization step sizes; Based on the multiple free optimization step sizes, taking the multiple optimal candidate pipeline layout schemes as the optimization direction, optimizing and adjusting the multiple candidate pipeline layout scheme sets, thereby obtaining multiple optimized pipeline layout scheme sets; The maximum fitness of the scheme among the plurality of optimized pipeline layout schemes is selected as the target pipeline layout scheme.

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