CN120633978B

CN120633978B - Underground traffic construction pipeline migration optimization method and system

Info

Publication number: CN120633978B
Application number: CN202511115817.8A
Authority: CN
Inventors: 叶瑞; 王建峰; 向禹; 韩威威
Original assignee: Zhejiang Jiaohang Electronic Technology Co ltd
Current assignee: Zhejiang Jiaohang Electronic Technology Co ltd
Priority date: 2025-08-11
Filing date: 2025-08-11
Publication date: 2025-11-14
Anticipated expiration: 2045-08-11
Also published as: CN120633978A

Abstract

This application provides a method and system for optimizing the relocation of underground transportation pipelines. Specifically, this application acquires the spatial location, cross-sectional dimensions, joint locations, and maintenance records of existing cables, and constructs a spatial layout model based on the tunnel structure. Using non-contact detectors, it scans the tunnel sidewalls and floor, dynamically updating the model based on the identified obstacle locations, dimensional parameters, and structural boundaries to generate a tunnel distribution map. The distribution map is divided into a grid, and using cross-sectional dimensions to calculate safe distances as constraints, the grid connections are traversed to avoid high-risk areas marked with joint locations and determine the initial installation path. Subsequently, fault locations and maintenance frequencies are extracted, and the initial path is bound to the spatial location using a historical model to calculate path risks and output maintenance parameters. The path direction is adjusted to generate the target scheme and output a cable layout diagram. This application achieves precise optimization of cable paths, avoids construction collision risks, and reduces long-term operation and maintenance costs.

Description

Underground traffic construction pipeline migration optimization method and system

Technical Field

The application relates to the technical field of cable or wire installation engineering, in particular to a method and a system for optimizing the migration and modification of an underground traffic construction pipeline.

Background

When new pipelines are embedded in the operated underground comprehensive pipe rack system, the existing pipelines in the pipe rack are complex and compact in layout, the construction space is extremely limited, and a large number of hidden structures exist, including unrecorded metal embedded parts, concrete cavities, water seepage areas and other hidden risk points. The newly added pipeline needs to ensure that a strict safety distance is kept between the newly added pipeline and the existing facilities, collision accidents in the construction period are avoided, and the physical deformation requirement of heat expansion and cold contraction of equipment is met.

Currently, the mainstream solutions adopt a semi-automatic design method combining a building information model and a path optimizing algorithm. The scheme firstly integrates a piping lane structure drawing and pipeline completion data to construct a three-dimensional static model containing pipeline coordinates and a design interval threshold value. And finally, the feasibility of the generated path is manually checked, and then the construction scheme drawing is directly output to be delivered and implemented on site.

However, there are some key limitations to this technique. Firstly, because the construction drawing data is completely depended on, the dynamic change structures such as a newly added metal bracket or a hidden crack in the operation stage cannot be identified, and the model is seriously deviated from the actual working condition on site. Secondly, only a fixed geometric spacing is adopted as a hard constraint, so that the installation process faces the hidden danger of collision accidents.

Disclosure of Invention

The application provides an underground traffic construction pipeline migration optimization method and system, which are used for solving the problems of construction safety risk and out-of-control long-term maintenance cost in the prior art.

In a first aspect, the present application provides a method for optimizing the migration of an underground traffic construction pipeline, comprising:

acquiring the space position, the section size, the joint position and the maintenance record of the existing cable in the cable channel, and constructing a space layout model by combining the channel structure parameters;

scanning the side wall and the bottom plate of the channel by adopting a non-contact detector, identifying an obstacle and a hidden structure, and dynamically updating the space layout model based on the identified obstacle position, the size parameter and the structure boundary to obtain a channel distribution diagram;

Dividing an internal space in the channel distribution diagram into grids based on the space position, calculating a safety distance based on the section size, traversing the connection relation of the grids by a path calculator with the safety distance as constraint, marking a high risk area based on the joint position, avoiding grid nodes corresponding to the high risk area, and determining an initial installation path of a new cable;

Extracting fault positions and maintenance frequencies in the maintenance records, training a historical model based on a historical cable case library, binding the initial installation path with the space positions, inputting the historical model, calculating path risks by combining the fault positions and the maintenance frequencies, and outputting maintenance parameters corresponding to the initial installation path;

and according to the comparison result of the maintenance parameter and the preset cost threshold, the trend and node distribution of the initial installation path in the space position are adjusted, a target scheme is generated, and a corresponding cable layout diagram is output.

Optionally, extracting a fault location and a maintenance frequency in the maintenance record, training a history model based on a history cable case library, binding the initial installation path with the space location, inputting the history model, calculating a path risk in combination with the fault location and the maintenance frequency, and outputting maintenance parameters corresponding to the initial installation path, including:

extracting the coordinates of fault location points and the numerical values of maintenance frequency from the maintenance records, and training a historical prediction model based on all data sets of a historical cable case library;

coordinate point binding is carried out on the initial installation path and the space position, a binding path data set is generated, and the binding path data set, the fault position point coordinates and the maintenance frequency value are input into a history prediction model together;

And calculating a path risk value by combining the distribution density of the fault location point coordinates and the maintenance frequency through the history prediction model, converting the path risk value into a maintenance parameter value through a preset mapping function, and outputting the maintenance parameter value of the initial installation path.

Optionally, calculating, by using the history prediction model and combining the distribution density of the fault location point coordinates and the maintenance frequency, a path risk value, converting the path risk value into a maintenance parameter value by using a preset mapping function, and outputting a maintenance parameter value of an initial installation path, where the method includes:

Generating a spherical region with a fixed radius by taking the coordinates of each fault position point as a sphere center through the history prediction model, and calculating the ratio of the total number of fault points in the spherical region to the volume of the spherical region to be used as position distribution density data;

Dividing the initial installation path into continuous path segments, matching position distribution density data and maintenance weight values corresponding to each path segment, and calculating a path risk value according to a linear weighting formula based on the position distribution density data and the maintenance weight values;

And mapping the path risk value into a maintenance parameter value through a piecewise linear function, and outputting the maintenance parameter value according to the sequence of the path segment identifiers.

Optionally, scanning the side wall and the bottom plate of the channel by using a non-contact detector, identifying an obstacle and a hidden structure, dynamically updating the spatial layout model based on the identified obstacle position, the size parameter and the structural boundary to obtain a channel distribution diagram, including:

Scanning the side wall and the bottom plate surface of a channel by using a non-contact detector, generating scanning signal data, analyzing the scanning signal data, and identifying the barrier position points of the barrier and the structure boundary points of the hidden structure;

measuring three-dimensional coordinate information of the obstacle position points, calculating size parameter values of the obstacles, extracting outline data of the structure boundary points, and inputting the three-dimensional coordinate information, the size parameter values and the outline data into the space layout model;

And adjusting parameters of corresponding positions in the spatial layout model, updating channel internal structure data, and generating a channel distribution map comprising barrier distribution and structure boundaries.

Optionally, acquiring a spatial position, a section size, a joint position and a maintenance record of an existing cable in the cable channel, and constructing a spatial layout model by combining channel structure parameters, including:

Acquiring the space position of the existing cable in the cable channel, acquiring the section size of all the cables, recording the joint position information of the cable joint and the history maintenance record, and acquiring the channel structure parameters, wherein the channel structure parameters comprise the length range value, the width size value and the height data value of the channel;

combining the space position with channel structure parameter data, establishing a three-dimensional geometric framework of a channel, setting section size data of a cable in the three-dimensional geometric framework, marking all joint position information, and adding history maintenance record data to obtain a constructed space layout model.

Optionally, according to a comparison result of the maintenance parameter and a preset cost threshold, adjusting a trend and node distribution of the initial installation path in a space position, generating a target scheme, and outputting a corresponding cable arrangement diagram, including:

Comparing the magnitude relation between the maintained parameters and a preset cost threshold value, and adjusting the space trend curve of the initial installation path and the distribution density of the path nodes according to the comparison result;

Generating target path scheme data meeting a cost threshold based on the adjusted space trend curve and the path node distribution density;

analyzing the target path scheme data into a cable center line coordinate set and a pipe diameter parameter set, driving a drawing tool to draw a cable layout of a cable in a channel based on the cable center line coordinate set and the pipe diameter parameter set, and outputting the cable layout to a display device or a construction control terminal.

Optionally, dividing the internal space in the channel distribution diagram into grids based on the spatial position, calculating a safety distance based on the section size, traversing the connection relation of the grids by a path calculator with the safety distance as a constraint, marking a high risk area based on the joint position, avoiding grid nodes corresponding to the high risk area, and determining an initial installation path of a new cable, including:

dividing the internal space of the channel distribution diagram into equidistant grid cell sets according to the space position, and calculating a safe distance value between adjacent cables based on the section size data of the cables;

traversing connection relation data among all grid cells in the grid cell set by using the safety distance value as a movement constraint condition through a path calculator, and recording a feasible path point set meeting the safety distance value;

And marking grid nodes corresponding to the high-risk areas according to the joint positions, avoiding all grid nodes corresponding to the high-risk areas from the feasible path point set, calculating a continuous path point sequence of a new cable, and generating an initial installation path of the new cable.

In a second aspect, the present application provides an underground transportation construction pipeline relocation optimization system, comprising:

The acquisition module is used for acquiring the space position, the section size, the joint position and the maintenance record of the existing cable in the cable channel, and constructing a space layout model by combining the channel structure parameters;

The updating module is used for scanning the side wall and the bottom plate of the channel by adopting a non-contact detector, identifying an obstacle and a hidden structure, and dynamically updating the space layout model based on the identified obstacle position, the size parameter and the structure boundary to obtain a channel distribution diagram;

The calculation module is used for dividing the internal space in the channel distribution diagram into grids based on the space position, calculating the safety distance based on the section size, traversing the connection relation of the grids by using the safety distance as constraint through a path calculator, marking a high risk area based on the joint position, avoiding grid nodes corresponding to the high risk area and determining an initial installation path of a new cable;

The output module is used for extracting the fault position and the maintenance frequency in the maintenance record, training a historical model based on a historical cable case library, binding the initial installation path with the space position, inputting the historical model, calculating path risk by combining the fault position and the maintenance frequency, and outputting maintenance parameters corresponding to the initial installation path;

And the adjusting module is used for adjusting the trend and node distribution of the initial installation path in the space position according to the comparison result of the maintenance parameter and the preset cost threshold value, generating a target scheme and outputting a corresponding cable layout diagram.

In a third aspect, the application provides a computing device, which comprises a processing component and a storage component, wherein the storage component stores one or more computer instructions, and the one or more computer instructions are used for being called and executed by the processing component to realize the underground traffic construction pipeline migration optimization method according to the first aspect.

In a fourth aspect, the present application provides a computer storage medium storing a computer program which, when executed by a computer, implements a method for optimizing the migration of an underground traffic construction line according to the first aspect.

The method comprises the steps of integrating a channel structure and cable parameters through a space layout model, accurately establishing a three-dimensional space reference coordinate system, effectively identifying hidden structure boundaries and metal obstacle coordinates through non-contact detection and dynamic updating of the model, eliminating positioning deviation caused by drawing data lag, combining grid division with safety spacing constraint, ensuring that a path calculator traverses a physical avoidance existing facility and a safety spacing insufficient area, marking a high risk area based on joint positions and avoiding corresponding nodes, pertinently reducing interference risks of construction operation on key weak points, binding an initial path and the space positions through a history model, extracting maintenance recording parameters, converting failure frequency into path risk coefficients, outputting the path risk coefficients, realizing quantized pre-judgment of long-term maintenance cost, and finally dynamically adjusting path trend through comparing the maintenance parameters with cost threshold values, so as to generate a cable layout diagram which meets construction safety requirements and ensures full-period economy.

Further, the fault position point coordinates and the maintenance frequency values in the maintenance records are extracted to be used as data input, and a historical prediction model is trained based on the complete data set of the historical cable case library so as to eliminate sampling deviation; and finally, converting the risk value into a maintenance parameter value through a preset mapping function to be output, so that the parameter value accurately reflects the risk level of a high-risk fault aggregation area in a path section, and driving the path to actively avoid a high-frequency fault area, thereby remarkably reducing long-term maintenance cost and balancing resource allocation.

These and other aspects of the application will be more readily apparent from the following description of the embodiments.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 shows a flow chart of an underground traffic construction pipeline migration optimization method provided by the application;

FIG. 2 shows a scene diagram of an underground traffic construction pipeline migration optimization method provided by the application;

FIG. 3 shows a schematic structural diagram of an underground traffic construction pipeline migration optimization system provided by the application;

FIG. 4 illustrates a schematic diagram of a computing device provided by the present application.

Detailed Description

In order to enable those skilled in the art to better understand the present application, the following description will make clear and complete descriptions of the technical solutions according to the embodiments of the present application with reference to the accompanying drawings.

In some of the flows described in the specification and claims of the present application and in the foregoing figures, a plurality of operations occurring in a particular order are included, but it should be understood that the operations may be performed out of order or performed in parallel, with the order of operations such as 101, 102, etc., being merely used to distinguish between the various operations, the order of the operations themselves not representing any order of execution. In addition, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first" and "second" herein are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, and are not limited to the "first" and the "second" being different types.

Researchers find that the existing underground pipeline migration and modification technology mainly depends on construction period completion drawing data, cannot effectively identify dynamic change structures such as a newly added metal support, hidden cracks and the like in an operation stage, so that a space layout model is seriously deviated from the actual working conditions in the field, and meanwhile, the technologies only adopt fixed geometric spacing as hard constraint, cannot fully combine actual maintenance risks, and lead the installation process to face collision accident hidden dangers. Therefore, there is a need for an underground traffic construction pipeline migration optimization method capable of dynamically updating a model and intelligently optimizing a path.

Aiming at the problems, the invention provides an underground traffic construction pipeline migration optimization method which is characterized in that a non-contact detector is utilized to dynamically update a space layout model, and a risk assessment optimization path plan is fused based on historical maintenance data. The method comprises the steps of firstly obtaining the space position, the section size, the joint position and the maintenance record of an existing cable, constructing an initial model by combining channel structure parameters, then scanning and identifying obstacles and hidden structures through a non-contact detector, dynamically updating the model to generate an accurate channel distribution map, gridding the inner space, traversing a grid path by taking a safety distance as a constraint, avoiding a high risk area marked by the joint position to determine an initial installation path, further extracting fault positions and maintenance frequencies of the maintenance record, training a historical model to calculate path risks, outputting maintenance parameters, and finally dynamically adjusting path trend according to the maintenance parameters and a cost threshold to generate and output an optimized cable layout. The method ensures that the model is in actual agreement with the site through dynamic scanning and identification of a newly added dynamic change structure in the operation stage, solves the problem of model deviation, and simultaneously obviously reduces hidden danger of collision accidents through risk assessment and safety interval optimization path planning, thereby realizing intelligent and high-reliability pipeline migration optimization.

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to fall within the scope of the application.

Fig. 1 is a flowchart of an embodiment of the present application for providing an optimizing method for underground traffic construction pipeline migration, as shown in fig. 1, the method includes:

101. acquiring the space position, the section size, the joint position and the maintenance record of the existing cable in the cable channel, and constructing a space layout model by combining the channel structure parameters;

Optionally, the step 101 may specifically include the following steps:

1011. acquiring the space position of the existing cable in the cable channel, acquiring the section size of all the cables, recording the joint position information of the cable joint and the history maintenance record, and acquiring the channel structure parameters, wherein the channel structure parameters comprise the length range value, the width size value and the height data value of the channel;

1012. Combining the space position with channel structure parameter data, establishing a three-dimensional geometric framework of a channel, setting section size data of a cable in the three-dimensional geometric framework, marking all joint position information, and adding history maintenance record data to obtain a constructed space layout model.

In the above steps, the spatial position refers to specific position coordinate data of the cable in the channel, including three-dimensional coordinate point values, the section size refers to external dimension data of the cable cross section, such as diameter values of round cables, the joint position information refers to specific position coordinate data of cable connection points, the maintenance record refers to historical data of past maintenance and inspection of the cable, such as maintenance date and description content, the channel structure parameter includes a channel length range value representing a channel length interval range value, a width dimension value representing a channel width value and a height data value representing a channel height value, and the spatial layout model is a geometric model frame in three-dimensional space and is used for visualizing the channel, the cable and related information.

In the embodiment of the application, basic data in a cable channel is acquired through step 1011, namely, spatial position coordinate data of all existing cables are acquired by using a laser scanner, a measuring tool is used for recording the section size value of the cables, three-dimensional coordinates of joint positions are read by positioning equipment, a database is called to extract historical maintenance record text, and channel structure parameters are analyzed from construction drawings. For example, for a certain 10-meter long channel, the space position coordinate of the cable is measured to be X0.5 meter/Y1 meter/Z0.8 meter, the section diameter is 5cm, the connector is positioned at X8 meter/Y0.6 meter/Z1 meter, maintenance record is "no abnormality in 2023 annual inspection", and the channel parameters are in the length range of 10-15 meters/width 1 meter/height 2 meters.

Next, a spatial layout model is constructed by step 1012, which is to create a rectangular box frame using three-dimensional modeling software input channel parameters based on the data of step 1011, map cable spatial position coordinates to the frame to generate anchor points, generate corresponding geometry from the cross-sectional dimension data, add a marker symbol at joint position coordinates, and correlate the maintenance record text to the corresponding positions. For example, a basic frame with the length of 12 meters (the value in the range of 10-15 meters) and the width of 1 meter and the height of 2 meters is firstly established for the data, a cylinder with the diameter of 5 cm is arranged at the position of 0.5/1/0.8 of coordinates to represent a cable, a red sphere marking joint is added at the position of 8/0.6/1 of coordinates, a '2023 repair no abnormality' label is displayed on the side surface of the model, and finally a complete three-dimensional model is output.

In practical application, in the upgrading engineering of an underground pipeline of a certain power grid, the project group adopts the following method to construct a three-dimensional space layout model of a cable channel. The staff goes deep into the passageway at first, utilizes precision measurement instrument to obtain the space position coordinate and the central point interval data of all 6 existing cables in the passageway accurately, simultaneously the detail measurement records the cross-section size of every cable, and the cable cross-section size of important passageway branch road is 0.5 meters 0.3 meters, 0.4 meters 0.25 meters two kinds of specifications respectively. By consulting the archive system, three-dimensional coordinates of cable connectors distributed at key positions at the channel 12 and historical maintenance information are completely acquired, wherein the three-dimensional coordinates comprise records of replacement of the connector No. 3 in 2022. The measurement team then obtains the key parameters of the channel structure, the total length of the channel body portion being 47.5 meters, the width being 2.5 meters, the height of the shaft connection being 2.2 meters. The technical staff inputs the basic data into a three-dimensional modeling system, and generates a channel frame model with the ratio of 1:1 according to the actually measured channel space parameters. In the digital model, each cable is accurately modeled according to the measured section size, and all joint information is clearly marked at a specific coordinate point. The technician also correlates the historical maintenance events at 35 to corresponding cable model nodes, forming a visual spatial layout model containing spatial structure, facility attributes, and maintenance status. The model realizes the visual presentation of the channel condition and provides an accurate basis for the establishment of a subsequent construction scheme.

In the overall scheme of the step 101, through collecting the spatial position and the section size of the existing cable in the cable channel and combining the cable joint position information and the history maintenance record, channel structure parameters such as a length range value, a width size value, a height data value and the like of the channel are obtained, the information is integrated, a three-dimensional geometric framework of the channel is built, the cable section size data is arranged in the framework, all joint positions are marked, the history maintenance record data is added, and finally, a spatial layout model comprising the channel structure, the cable layout and key information is built, so that accurate visualization and management of the cable channel are realized.

102. Scanning the side wall and the bottom plate of the channel by adopting a non-contact detector, identifying an obstacle and a hidden structure, and dynamically updating the space layout model based on the identified obstacle position, the size parameter and the structure boundary to obtain a channel distribution diagram;

Optionally, the step 102 may specifically include the following steps;

1021. scanning the side wall and the bottom plate surface of a channel by using a non-contact detector, generating scanning signal data, analyzing the scanning signal data, and identifying the barrier position points of the barrier and the structure boundary points of the hidden structure;

1022. Measuring three-dimensional coordinate information of the obstacle position points, calculating size parameter values of the obstacles, extracting outline data of the structure boundary points, and inputting the three-dimensional coordinate information, the size parameter values and the outline data into the space layout model;

1023. And adjusting parameters of corresponding positions in the spatial layout model, updating channel internal structure data, and generating a channel distribution map comprising barrier distribution and structure boundaries.

In the above steps, the non-contact detector refers to a device such as a laser radar instrument which can scan without touching the surface of a channel, the side walls and the bottom plate of the channel refer to the signal waveform or image data output by the detector during scanning, the obstacle refers to an obstacle in the channel such as a pipeline or a device body, the hidden structure refers to hidden accessory structures such as a pit or a hole, the obstacle position point refers to position coordinate point data of the obstacle, the structure boundary point refers to contour coordinate point data of the hidden structure, the three-dimensional coordinate information refers to X-axis value, Y-axis value and Z-axis value of the position point, the size parameter value refers to the length value, the width value and the height value of the obstacle, the contour data refers to contour point integrated data of the hidden structure, and the channel distribution map refers to the updated three-dimensional visual model map contains the obstacle and the structure boundary information.

In the embodiment of the present application, first, a non-contact detector such as a laser radar is used to scan the surface of the side wall and the bottom plate of the channel to obtain the original data, after the laser beam emitted by the detector is reflected, the scanning signal data such as point-cloud waveform information is generated, then the data are processed by using a signal analysis algorithm in a computer system to identify the position point and the structure boundary point of the obstacle, so as to form the intermediate data of the identification position and the boundary for the subsequent step, for example, in an actual 10-meter long channel, after scanning, the rock obstacle position point is identified by the algorithm analysis, the coordinates are 5 meters in the length direction, 1 meter in the width direction and 0.5 meter in the height direction, and meanwhile, the structure boundary point set of a concave hidden structure is identified, the starting point is 7 meters in the length direction, 0.8 meters in the width direction and 0.2 meters in the height direction, the end point is 7.5 meters in the length direction, 0.8 meters in the width direction and 0.4 meters in the height direction, and these point data are directly stored as the input basis of the next step.

Then, three-dimensional coordinate information record values of the barrier position points are directly extracted based on the position point and boundary point data in step 1022, such as a length direction of 5 meters, a width direction of 1 meter and a height direction of 0.5 meter, then a geometric calculation algorithm is used to calculate the size parameter values of the barrier based on the multi-position point data, for example, the length value width value height value is obtained by subtracting after finding out the minimum value point and the maximum value point in all relevant points, the specific calculation process is as follows, assuming that a plurality of scanning points comprise a point 1 coordinate of 4.8 meters in length direction, a point 0.9 meter in width direction and a point 2 coordinate of 5.2 meters in length direction, a point 1.1 meter in width direction and a point 0.6 meter in height direction, the maximum point of 5.2 meters in length direction is reduced by 4.8 meters to be used as a length value, the maximum point of 1.1 meter in width direction is reduced by 0.9 meter to be used as a width value, the maximum point of 0.6 meter in height direction is reduced by 0.4 meters to be used as a width value, a three-dimensional profile data of a coordinate of 0.2 meter is obtained by updating a three-dimensional profile data, and a three-dimensional profile data is simultaneously prepared, and a three-dimensional profile data is obtained by updating a coordinate profile data set.

Finally, dynamically updating the space layout model based on the three-dimensional coordinate information size parameter values and the contour data by step 1023, adding an obstacle object at a corresponding position by using computer modeling software, setting a size numerical simulation new element, adjusting an internal structure to generate a channel distribution diagram based on the contour data adding hidden structure region, for example, placing a cube with the length of 0.4 meter and the width of 0.2 meter and the height of 0.2 meter at the position of a coordinate point of 1 meter and the width of 0.5 meter, applying a surface deformation algorithm on the position point set of a concave position representing the obstacle, generating a shape region, outputting a three-dimensional view diagram file containing the new element as a final channel distribution diagram, and continuously updating the model from the identification data to the calculated size in the whole flow to ensure seamless connection.

In practical application, in a city utility tunnel updating engineering field, technicians execute the following non-contact detection flow to perfect a channel model. The operation group evenly distributes 23 detection points along a 130 m long channel, and the ground penetrating radar equipment is utilized to continuously scan the concrete side wall and the basalt bottom plate at intervals of 0.3 m. After the instrument receives the electromagnetic wave reflection signal, an abnormal signal area with the burial depth of 0.5 meter is identified at a position 35.6 meters away from the starting point, and the system judges that the system is a cast iron tubular barrier with the diameter of about 0.45 meter. Meanwhile, the scanning data reveals that irregular structure boundaries with the extension length of 5.2 meters exist on the west side of the channel, and the irregular structure boundaries are confirmed to be waste civil air defense engineering entrances through comparison with construction drawings. The measurement team then builds a total station to accurately map the obstacle, obtains the spatial coordinates of the central points of the obstacle to be X= 35.612, Y= 2.304 and Z= -1.258 (unit meters), and marks the axial length of the obstacle to be 2.1 meters. For the boundary outline of the hidden structure, three-dimensional coordinates of 143 feature points are extracted through a point cloud capturing technology. These include 3 obstacle pose parameters and hidden structure profile data are transmitted to the modeling platform through the data interface. The model system automatically fuses the new acquired data, accurately marks the tubular barrier existing in the No. 7 detection area and the boundary range thereof in the original space layout model, and synchronously optimizes the three-dimensional contour line at the southwest corner of the channel. After the data iteration is completed, the system generates a channel distribution diagram containing a newly added barrier layer and a structural boundary thermodynamic diagram, and space characteristic elements of 7 types of different attributes in the channel are clearly displayed on the diagram, so that the visual management precision of the underground space environment is remarkably improved.

In the overall scheme of the step 102, the side wall and the bottom plate of the cable channel are comprehensively scanned through the non-contact detector, scanning signal data are obtained, obstacle position points and hidden structure boundary points are analyzed and identified, three-dimensional coordinate information of the obstacle is precisely measured, size parameters of the obstacle are calculated, meanwhile, structure boundary contour data are extracted, the information is dynamically input into a space layout model to adjust corresponding position parameters, internal structure data of the channel are synchronously updated, a channel distribution map containing accurate obstacle distribution conditions and structure boundary features is finally generated, and dynamic optimization and visual upgrading of the space model are achieved.

103. Dividing an internal space in the channel distribution diagram into grids based on the space position, calculating a safety distance based on the section size, traversing the connection relation of the grids by a path calculator with the safety distance as constraint, marking a high risk area based on the joint position, avoiding grid nodes corresponding to the high risk area, and determining an initial installation path of a new cable;

optionally, the step 103 may specifically include the following steps:

1031. Dividing the internal space of the channel distribution diagram into equidistant grid cell sets according to the space position, and calculating a safe distance value between adjacent cables based on the section size data of the cables;

1032. Traversing connection relation data among all grid cells in the grid cell set by using the safety distance value as a movement constraint condition through a path calculator, and recording a feasible path point set meeting the safety distance value;

1033. and marking grid nodes corresponding to the high-risk areas according to the joint positions, avoiding all grid nodes corresponding to the high-risk areas from the feasible path point set, calculating a continuous path point sequence of a new cable, and generating an initial installation path of the new cable.

In the above steps, the grid unit set refers to an equal-size area block set into which the internal space of the channel is divided, the safety distance value refers to the minimum safety distance value required to be kept between cables, the path calculator refers to an algorithm tool used for path searching in a computer system, the connection relation data refers to the relation information of interconnection between grid units, the feasible path point set refers to all grid position point sets meeting the safety distance condition, the high risk area refers to a dangerous area near the cable joint position, the grid node refers to the center point or the joint position of the grid unit, the continuous path point sequence refers to a series of communicated grid point position sequences, the initial installation path refers to the first route path of the new cable planning wiring, the section size data refers to the diameter value parameter of the cable cross section, and the joint position refers to the specific coordinate position of the cable joint.

In the embodiment of the application, firstly, the space inside the channel is uniformly divided into equidistant grid cell sets based on space position data in step 1031, and then the safety distance value is calculated based on cable section size data. The method comprises the steps of inputting three-dimensional space data of a channel distribution diagram, generating grid units with consistent sizes by using a grid division algorithm, for example, dividing a 10-meter long channel into 100 units by adopting a 1-meter by 1-meter grid, taking the central point of each unit as a node position, and then calculating a safety distance value, wherein the safety distance value is defined by a formula of safety distance value=safety coefficient×cable section diameter, the safety coefficient is fixed to be 1.5 by an industry standard, and the cable section diameter is an actual measurement value. For example, when the cable diameter is 0.1 meter, the calculation process is that the safety spacing value=1.5x0.1=0.15 meter, the value constrains the node spacing of the subsequent path to be more than or equal to 0.15 meter, and all grid cell sets and the safety spacing value are output to the next flow.

Next, step 1032 uses the safe distance value of 0.15m as the movement constraint condition, and the path calculator traverses the connection relation among the grid cells to screen the feasible path point set. The method comprises the specific processes of inputting the positions and connection relations of grid nodes in step 1031, traversing the grid nodes by using a path search algorithm in a computer, and checking whether the distance between adjacent nodes is more than or equal to 0.15 meter or not by using the algorithm, wherein the nodes meeting the conditions are reserved. For example, node a coordinates (1.0 m ) are spaced from adjacent node B (1.0 m, 1.2 m) by |1.2-1.0|=0.2 m >0.15m, node B is retained, whereas node C (1.0 m, 1.1 m) is rejected if the spacing is 0.1m <0.15 m. The final set of output feasible path points is passed to step 1033.

Finally, the high risk zone grid nodes are marked based on joint locations, generating an initial installation path avoiding these nodes in the set of feasible path points, via step 1033. The method specifically comprises the steps of inputting joint position coordinates (8.0 m and 0.6 m) in the step 101, setting a circular area with the radius of 0.5m as a high risk area by taking the point as the center, marking grid nodes in the coverage area, deleting high risk nodes from a feasible path point set, calculating a continuous point set of a communication path sequence such as a starting point (0 m and 0.5 m) and a final point (10 m and 0.5 m) by using a path planning algorithm, skipping the high risk nodes, and finally outputting an initial installation path such as a coordinate sequence text file for construction reference.

In practice, in a city underground cable optimization project, engineers perform the following path planning operations to determine the installation plan of new cables. They first divide the channel interior space into equidistant sets of grid cells based on the spatial position data in the channel profile, ensuring that each grid cell covers the entire area uniformly. And then, calculating the safety distance value which is required to be maintained between adjacent cables by using the section size parameters of the existing cables, and taking the safety distance value as a critical path constraint condition. The team inputs the data into a path calculator, and the system automatically traverses the connection relation among all grid units, screens out all feasible path point sets meeting the requirements of the safety distance, and forms a potential path library. Meanwhile, according to the known cable joint position information, grid nodes corresponding to the high-risk areas are accurately marked, and the risk nodes are actively avoided in the path selection process. Through algorithm processing, the path calculator generates a continuous path point sequence which successfully avoids all high-risk areas and strictly follows safety interval constraint, so that the initial installation path of a new cable is determined, and the planning reliability and implementation safety are improved.

In the overall scheme of step 103, the internal space is divided into equidistant grid cells according to the channel distribution diagram, the safety distance value between adjacent cables is calculated by combining the cable section size, the safety distance value is used as a movement constraint condition, the path calculator traverses the connection relation data of each cell in the grid cell set, a feasible path point set conforming to the safety distance is screened out, grid nodes corresponding to the high risk area are marked according to the joint position, all the high risk grid nodes are removed from the feasible path point set, and an initial installation path is automatically generated by calculating the continuous path point sequence of the new cable.

104. Extracting fault positions and maintenance frequencies in the maintenance records, training a historical model based on a historical cable case library, binding the initial installation path with the space positions, inputting the historical model, calculating path risks by combining the fault positions and the maintenance frequencies, and outputting maintenance parameters corresponding to the initial installation path;

optionally, the step 104 may specifically include the following steps:

1041. extracting the coordinates of fault location points and the numerical values of maintenance frequency from the maintenance records, and training a historical prediction model based on all data sets of a historical cable case library;

1042. Coordinate point binding is carried out on the initial installation path and the space position, a binding path data set is generated, and the binding path data set, the fault position point coordinates and the maintenance frequency value are input into a history prediction model together;

1043. and calculating a path risk value by combining the distribution density of the fault location point coordinates and the maintenance frequency through the history prediction model, converting the path risk value into a maintenance parameter value through a preset mapping function, and outputting the maintenance parameter value of the initial installation path.

The step 1043 may specifically include generating a spherical region with a fixed radius by using each fault location point coordinate as a sphere center through the history prediction model, calculating a ratio of a total number of fault points in the spherical region to a volume of the spherical region as location distribution density data, dividing the initial installation path into continuous path segments, matching location distribution density data and maintenance weight values corresponding to each path segment, calculating a path risk value according to a linear weighting formula based on the location distribution density data and the maintenance weight values, mapping the path risk value into a maintenance parameter value through a piecewise linear function, and sequentially outputting the maintenance parameter value according to a path segment identifier.

In the above step, the grid cell set is a set of equal-size regions divided in the channel interior space; the safe distance value is the minimum safe distance value that must be maintained between cables; the path calculator is a tool in the computer system for searching paths; the connection relation data are information sets connected between grid points, the feasible path point sets are all grid point position sets meeting the safety distance requirement, the high risk area is a potential dangerous area around a cable connector, the grid nodes are central point positions of grid units, the continuous path point sequence is a position sequence of continuous points in the cable path, the initial installation path is a first route planned by a new cable, the section size data are diameter values of a cable cross section, the connector positions are specific coordinate positions of cable connection points, the fault positions are coordinate positions where past faults occur, the maintenance frequency is a number of times of maintenance of each fault point, the historical cable case library is a data set storing historical fault cases, the historical model is a prediction tool trained based on the historical cases, the protection parameters are time interval values required by cable maintenance, the path risk is a risk size value on the cable path, the binding path data set is a data set combining the path point sequence with the coordinate positions, the path risk value is a risk value obtained through calculation, the maintenance parameter value is a specific maintenance value after mapping the risk, the position distribution density data is a specific coordinate value of the fault near the fault point and the area volume, the maintenance weight value is a maintenance step weight value, the value is a step-by step weight value is a step-by step weight value, the step-by step weight is a step of a tool is a step-by step of a tool is a step of a is a linear tool is a step of a is a step of a step of a is has a has a unique value has a value has a was has a.has a.

In the embodiment of the application, firstly, data and a training model are extracted through a step 1041, a computer system reads a maintenance record file, three-dimensional coordinates of a fault position are analyzed from a text record (8.0,0.6,0.5), a corresponding maintenance frequency value 3 is extracted, then a history cable case library is called to load all history data sets, then a history prediction model is trained by using a random forest algorithm, the history fault coordinates and maintenance frequency data are input to automatically learn characteristic association, and finally a trained model file and a fault point coordinate list are output. For example, actually reading the fault point coordinates (8.0,0.6,0.5) and the maintenance times 3, calling a historical database training model containing 100 records, finally generating a model file and storing a coordinate list for the next step.

Secondly, finishing data binding and model input through step 1042, obtaining an initial installation path point sequence such as [ (0.0,0.5,0.2), (5.0,1.0,0.3) ], verifying and binding each path point coordinate with the space position data of step 101 by using a space matching algorithm to generate a data set, merging and packaging the data set and a fault position point coordinate list, and finally inputting a historical prediction model together with a maintenance frequency value. For example, the path point (0.0,0.5,0.2) is bound as an identifier P001, and is merged with the fault point (8.0,0.6,0.5) and then input into the model, and the maintenance frequency value 3 is synchronously submitted.

Finally, by performing risk calculation and parameter output in step 1043, the model generates a spherical region with radius of 0.5m with each fault point such as (8.0,0.6,0.5) as the center, calculates the volume v=4/3× 3.1416 × (0.5) 3=0.523m3, calculates the number of fault points in the region such as 5 to calculate the density d=5/0.523≡9.56 times/m 3, divides the installation path into segments such as P001 (0 m-5 m) to match the density value, calculates the maintenance weight w=3×0.1=0.3, calculates the risk value (α=0.2, β=0.3) using the formula r=α×d+β×w to obtain r=0.2×9.56+0.3×0.3=2.002, and outputs the maintenance parameter value 40 by mapping r+.2 through the segmentation rule, and finally generates the result file P001:40. The complete calculation example is that the density of 5 fault points is 9.56 times/m 3 in the area volume of the fault point (8.0,0.6,0.5) 0.823 m3, the density and the weight of the P001 segment are matched, R=2.002 is calculated because the mapping output is not less than 2 and is not less than 40.

In practical applications, in a project of modifying a certain grid facility, an engineering team performs the following path risk assessment procedure. A technician firstly extracts three-dimensional coordinates of 17 historical fault points and corresponding maintenance frequency data from the cable maintenance file, and trains a prediction model by utilizing a historical database containing more than 200 cable fault cases. The initial installation path of the new cable is then point-to-point bound to the channel space coordinate system to form a dataset containing 83 path nodes. The binding dataset is input into a predictive model together with the fault location coordinates and the maintenance frequency parameters. In the model processing process, the system automatically generates a spherical analysis area with the radius of 0.8 meter by taking each fault point as a center, and calculates the fault point density in the area, for example, the No. 3 area contains 1.2 fault points per cubic meter. Meanwhile, the initial path is divided into 12 continuous sections, and corresponding fault density values and maintenance frequency weight coefficients are matched for each section. And (3) calculating the risk value of each path segment by using a linear weighting algorithm, wherein the density weight is 0.6, the maintenance frequency weight is 0.4. After the mapping of the piecewise functions, the risk values are converted into maintenance parameter sets containing maintenance cycle grades such as grade A which need 3 months for detection and risk identification such as red high-risk segments. And finally outputting an evaluation report containing maintenance parameter values of each path segment, and providing a quantitative basis for subsequent construction decisions.

In the overall scheme of step 104, the coordinate point of the initial installation path and the space position are bound to generate a bound path data set by extracting the coordinates of fault location points and the maintenance frequency value in the maintenance record and combining with the historical cable case library training historical prediction model, the bound data, the fault coordinates and the maintenance frequency are input into the historical prediction model together, the model takes each coordinate of fault location point as a sphere center to generate a spherical area with a fixed radius, the number of fault location points in the area is calculated as the position distribution density, then the initial path is divided into continuous path segments, the position distribution density and the maintenance weight value corresponding to each segment are dynamically matched, the path risk value is calculated through a linear weighting formula, finally the piecewise linear function is utilized to map the risk value into the maintenance parameter value, and the maintenance parameter value of each segment is output according to the sequence of the path segments, so that the operation and maintenance risk level of the new cable installation path is quantitatively estimated.

105. And according to the comparison result of the maintenance parameter and the preset cost threshold, the trend and node distribution of the initial installation path in the space position are adjusted, a target scheme is generated, and a corresponding cable layout diagram is output.

Optionally, the step 105 may specifically include the following steps:

1051. Comparing the magnitude relation between the maintained parameters and a preset cost threshold value, and adjusting the space trend curve of the initial installation path and the distribution density of the path nodes according to the comparison result;

1052. generating target path scheme data meeting a cost threshold based on the adjusted space trend curve and the path node distribution density;

1053. analyzing the target path scheme data into a cable center line coordinate set and a pipe diameter parameter set, driving a drawing tool to draw a cable layout of a cable in a channel based on the cable center line coordinate set and the pipe diameter parameter set, and outputting the cable layout to a display device or a construction control terminal.

In the above steps, the maintenance parameter is a quantized value of a cable maintenance requirement, such as 40, the preset cost threshold is a preset budget control value, such as 50, the space trend curve is a continuous curve shape of the path in the three-dimensional space, the node distribution density is a node number value of 1.2 points/meter on the path per unit length, the target path scheme is an optimized path planning data set, the cable center line coordinate set is a three-dimensional coordinate sequence of the path center point, the pipe diameter parameter set is a cable pipe dimension parameter set, the drawing tool is a software tool for automatically generating drawings, the cable layout is a construction drawing file containing the cable path, the display device is a display screen or projection device, and the construction control terminal is a site construction control device.

In the embodiment of the present application, first, through the step 1051 of performing parameter comparison and path adjustment, the computer system reads the maintenance parameter file to obtain the value 40, and simultaneously obtains the preset cost threshold value 50 for comparison operation. The path adjustment algorithm is automatically triggered when the maintenance parameter value 40 is greater than the preset cost threshold 30. The algorithm first modifies the spatial strike curve of the original installation path, using a curve optimization tool to reduce the path curvature, for example, changing a 90 turn to a 45 gentle turn. Meanwhile, the distribution density of the path nodes is regulated, the node density value is increased through a density calculation function and is regulated from the original density of 1 points/m to 1.2 points/m, so that the path trend is flatter and the nodes are denser, and finally, the regulated space trend curve file and the node density parameter file are generated. For example, when the maintenance parameter 45 is greater than the preset cost threshold 40, the system calculates a new bend radius of 2m to reduce the turn angle and increases the node density from 1.1 points/m to 1.5 points/m to accommodate the new path shape.

Next, a target path plan is generated in step 1052, and the computer system invokes the path generation algorithm to recalculate the sequence of path points based on the spatial trend curve file and the new node density parameter values output in step 1051. The algorithm firstly draws a basic path track according to the shape of the new curved curve, and then uniformly sets path points on the track according to the node density value of 1.2 points/m to generate a continuous coordinate sequence so as to form a target path scheme data file. When the maintenance parameter 40 does not exceed the cost threshold 50, the original path is directly output as the target solution. For example, path points are set at node density of 1.2 points/m according to the track of the gentle curve, 12 node coordinate sequences are generated in 10m channels to complete path planning, and finally, the scheme data file is output to the next step.

Finally, a layout is generated and output in step 1053, and after the system reads the target path scheme data file, the parsing module converts the path point sequence into a cable centerline coordinate set such as the coordinate sequence [ (0 m,0 m) → (1 m,1 m) ], and calculates a pipe diameter parameter set such as a pipe diameter 0.1 m data set from the section size data. And then driving a CAD drawing tool in a computer, drawing a continuous path line segment in a three-dimensional space according to the coordinate set, and adding a pipeline model with corresponding thickness according to the pipe diameter parameter to complete a cable layout. And finally, outputting the graphic file to a display screen or a construction equipment terminal. For example, blue line segments from coordinate points (0 m, 0m, 0 m) to (1 m, 1m, 1 m) are drawn in software, pipeline thickness is set according to the diameter of 0.1 m, and a vector drawing capable of being enlarged and reduced is generated and sent to a flat-panel device for construction.

In practical application, in the underground cable laying optimization engineering of a certain city, an engineering team performs path optimization according to the analysis result of the maintenance parameters. When the system detects that the value of the maintenance parameter at the 3 rd section in the initial path exceeds a preset cost threshold value, a technician immediately adjusts the space layout, namely, changing the trend of the cable which passes through the high-risk area in an original straight line into a smooth curve which is offset by 2.3 meters along the western side wall surface, and simultaneously, increasing the node density from 1.2 nodes per meter to 1.8 nodes per meter so as to optimize the bending radius. And (5) newly adding two transition nodes to shorten the span aiming at the 5 th section, and finally forming a target path scheme containing 126 three-dimensional coordinate points. The space coordinate data and the 0.28 meter pipe diameter parameter are synchronously input into a modeling system, a three-dimensional cable layout chart is automatically generated, a 15-degree turning trend of a main cable at 7.5 meters is clearly displayed by a red solid line in the chart, a blue ring-shaped mark accurately marks a pipe diameter change point position, and meanwhile, a yellow high-brightness mark is adopted to annotate a high-voltage joint risk area. Through system verification, the scheme is used for successfully avoiding three high-risk structures, and meanwhile, the overall maintenance cost index is strictly controlled within a preset threshold range, and finally, drawing data are transmitted to a construction terminal to guide accurate operation on site.

In the overall scheme of step 105, the space trend curve and the path node distribution density of the initial installation path are dynamically adjusted by comparing the magnitude relation between the maintenance parameter value and the preset cost threshold value, the target path scheme data meeting the cost constraint condition is generated, the scheme is resolved into an accurate cable center line coordinate set and a pipe diameter parameter set, a drawing tool is driven to automatically generate a three-dimensional space layout of the cable in the channel, and the final scheme is output to a construction control terminal or display device, so that quantized cost management and control of the cable installation path and construction visualization cooperation are realized.

The following is one specific embodiment for steps 101 to 105:

as shown in FIG. 2, in the project of the pipeline reconstruction matched with the subway tunnel in a certain city, the concrete flow of the construction team for carrying out the cable migration optimization is as follows, the engineering team firstly goes deep into the existing cable channel with the length of 127 meters, three-dimensional coordinates of nine operation cables are precisely collected through a total station, the three-dimensional coordinates comprise 35.12 meters of X-axis position, 1.78 meters of Y-axis height and minus 2.15 meters of Z-axis depth, and meanwhile, the cross section sizes of the main cable with the width of 0.4 meters and the height of 0.25 meters are recorded. The team retrieves seventeen joint coordinate locations distributed within the channel and an archive containing seventy-three repair records. And constructing a spatial layout system of the fused cable entity model on the three-dimensional modeling platform by combining the basalt structural features of the actually measured channel parameters, namely 127 meters in length, 2.8 meters in width and 2.5 meters in height. Then, the sidewall structure is scanned at intervals of 0.2m by using a pulse geological radar, a concrete obstacle with a burial depth of 0.6m is identified at a position 42.3 m away from a south-side entrance, the length of the obstacle is 1.2m and the width of the obstacle is 0.8m, an unmeasured cavity boundary with a north section extending 3.5 m is found, and a channel distribution map is updated and a newly increased risk area is marked by the system.

Based on the digital model, the technician divides the channel space into a grid cell array of 0.5 meter square, and calculates the minimum safe spacing of 0.35 meters from the cable cross section. After three high risk joint areas are avoided, the path planning algorithm generates an initial installation path of the through channel, wherein the path comprises eighty-nine discrete coordinate points. The system calls a database training prediction model covering the cable fault cases in the ten years, performs space association analysis on the initial path coordinates and thirty-five historical fault points, constructs a spherical analysis domain with the radius of 0.7 meter by taking each fault point as the center, calculates space fault density data, for example, 0.4 fault points are distributed in a third analysis area per cubic meter, and performs double-factor weighted calculation by combining with a maintenance frequency weight coefficient to obtain a path risk value. When the maintenance index of the fifth path section reaches 0.83 and exceeds the preset safety threshold value of 0.75, the engineering group dynamically adjusts the path space topology, namely, the original straight path is transformed into a curve path with the radius of 4.5 meters, the curve is offset by 2.1 meters, and three path nodes are newly added, so that the maintenance index of the section is reduced to 0.68.

The final solution forms a three-dimensional routing path containing one hundred twelve precise coordinate nodes, exhibiting a 22 degree smooth bend feature at 56.7 meters. The system outputs a design drawing fused with pipe diameter parameters, the diameter of a main cable is set to be 0.32 m, a red pipeline in a visual interface marks the trend of the main cable, seven pipe diameter change points are marked by blue light rings, and three high-risk joint areas are displayed as yellow early warning frames. Through field actual measurement verification, the scheme avoids all survey barriers and risk areas, meanwhile, the full-path maintenance parameter value is strictly controlled within the cost threshold range, and the design scheme is transmitted to a tunnel construction equipment terminal through a high-speed network to guide the mechanical arm to finish millimeter-level precision cable laying operation.

Fig. 3 is a schematic structural diagram of an optimizing system for underground traffic construction pipeline migration according to an embodiment of the present application, as shown in fig. 3, the system includes:

The obtaining module 31 is configured to obtain a spatial position, a cross-sectional size, a joint position and a maintenance record of an existing cable in the cable channel, and construct a spatial layout model by combining channel structure parameters;

The updating module 32 is configured to scan the side wall and the bottom plate of the channel with a non-contact detector, identify the obstacle and the hidden structure, and dynamically update the spatial layout model based on the identified obstacle position, the size parameter and the structural boundary to obtain a channel distribution diagram;

a calculation module 33, configured to divide an internal space in the channel distribution diagram into grids based on the spatial position, calculate a safety distance based on the cross-sectional dimension, traverse a connection relationship of the grids by using the safety distance as a constraint through a path calculator, mark a high risk area based on the joint position, avoid grid nodes corresponding to the high risk area, and determine an initial installation path of a new cable;

The output module 34 is configured to extract a fault location and a maintenance frequency in the maintenance record, train a history model based on a history cable case library, bind the initial installation path with the spatial location, input the history model, calculate a path risk in combination with the fault location and the maintenance frequency, and output maintenance parameters corresponding to the initial installation path;

and the adjusting module 35 is configured to adjust the trend and node distribution of the initial installation path in the spatial position according to the comparison result of the maintenance parameter and the preset cost threshold, generate a target scheme, and output a corresponding cable layout diagram.

The underground traffic construction pipeline migration optimization system described in fig. 3 may execute the underground traffic construction pipeline migration optimization method described in the embodiment shown in fig. 1, and its implementation principle and technical effects are not described again. The specific manner in which the various modules and units of the underground transportation construction line migration and optimization system of the above embodiments perform operations has been described in detail in connection with the embodiments of the method, and will not be described in detail herein.

In one possible design, an underground traffic construction line migration optimization system of the embodiment shown in FIG. 3 may be implemented as a computing device, as shown in FIG. 4, which may include a storage component 41 and a processing component 42;

The storage component 41 stores one or more computer instructions for execution by the processing component 42.

The processing component 42 is used in the underground transportation construction line migration optimization method of the embodiment described above with reference to fig. 1.

Wherein the processing component 42 may include one or more processors to execute computer instructions to perform all or part of the steps of the methods described above. Of course, the processing component may also be implemented as one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic elements for executing the methods described above.

The storage component 41 is configured to store various types of data to support operations at the terminal. The memory component may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.

Of course, the computing device may necessarily include other components as well, such as input/output interfaces, display components, communication components, and the like.

The input/output interface provides an interface between the processing component and a peripheral interface module, which may be an output device, an input device, etc.

The communication component is configured to facilitate wired or wireless communication between the computing device and other devices, and the like.

The computing device may be a physical device or an elastic computing host provided by the cloud computing platform, and at this time, the computing device may be a cloud server, and the processing component, the storage component, and the like may be a base server resource rented or purchased from the cloud computing platform.

The embodiment of the application also provides a computer storage medium which stores a computer program, and the computer program can realize the underground traffic construction pipeline migration optimization method of the embodiment shown in the figure 1 when being executed by a computer.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.

The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.

It should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present application, and not for limiting the same, and although the present application has been described in detail with reference to the above-mentioned embodiments, it should be understood by those skilled in the art that the technical solution described in the above-mentioned embodiments may be modified or some technical features may be equivalently replaced, and these modifications or substitutions do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solution of the embodiments of the present application.

Claims

1. The underground traffic construction pipeline migration optimization method is characterized by comprising the following steps of:

The binding the initial installation path with the space position, inputting the history model, and calculating path risk by combining the fault position and the maintenance frequency, wherein the method comprises the following steps:

Dividing the initial installation path into continuous path segments, matching the position distribution density data and maintenance weight values corresponding to each path segment, and calculating a path risk value according to a linear weighting formula based on the position distribution density data and the maintenance weight values, wherein the maintenance weight values are weight factors of influence risks of the maintenance frequency;

And according to the comparison result of the maintenance parameter and the preset cost threshold, the trend and the node distribution of the initial installation path are adjusted, a target scheme is generated, and a corresponding cable layout diagram is output.

2. The method of claim 1, wherein extracting the fault location and the repair frequency in the maintenance record, training a historical model based on a historical cable case library, binding the initial installation path with the spatial location, inputting the historical model, calculating a path risk in combination with the fault location and the repair frequency, and outputting maintenance parameters corresponding to the initial installation path, comprising:

3. The method according to claim 2, wherein converting the path risk value into a maintenance parameter value by a preset mapping function, outputting a maintenance parameter value of an initial installation path, comprises:

4. The method of claim 1, wherein scanning the channel sidewalls and floor with a non-contact detector, identifying obstacles and hidden structures, dynamically updating the spatial layout model based on the identified obstacle locations, dimensional parameters, and structural boundaries, and obtaining a channel profile, comprising:

5. The method of claim 1, wherein obtaining spatial locations, cross-sectional dimensions, joint locations, and maintenance records of existing cables within the cable channel, and constructing a spatial layout model in combination with channel structure parameters, comprises:

6. The method of claim 1, wherein adjusting the trend and node distribution of the initial installation path according to the comparison result of the maintenance parameter and a preset cost threshold value, generating a target scheme, and outputting a corresponding cable arrangement diagram, comprises:

7. The method of claim 1, wherein dividing the interior space in the channel profile into grids based on the spatial locations, calculating a safety pitch based on the cross-sectional dimensions, traversing connection relationships of the grids by a path calculator with the safety pitch as a constraint, marking high risk areas based on the joint locations, avoiding grid nodes corresponding to the high risk areas, and determining an initial installation path of a new cable, comprising:

8. An underground traffic construction line migration optimization system for executing the method for optimizing the migration of an underground traffic construction line according to any one of claims 1 to 7, comprising:

and the adjusting module is used for adjusting the trend and node distribution of the initial installation path according to the comparison result of the maintenance parameter and the preset cost threshold value, generating a target scheme and outputting a corresponding cable layout diagram.

9. A computing device comprising a processing component and a storage component, the storage component storing one or more computer instructions for execution by the processing component to implement a method of optimizing migration of an underground traffic construction pipeline according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that a computer program is stored, which, when being executed by a computer, implements a method for optimizing the migration of an underground traffic construction line according to any one of claims 1 to 7.