A method and system for detecting a bridge maintenance space

Abstract

The application discloses a kind of bridge maintenance space detection method and system, it is related to building design technical field.The method comprises: identifying bridge component and bridge information of bridge component from the component of BIM model;Create the detection section of three-dimensional space for bridge component;All model components in detection section are successively converted into two-dimensional graphics under section view;With target graphics as reference, find the detection boundary of specified model component in the preset specified direction, obtain the region to be detected;In the region to be detected, the target graphics is analyzed using iterative path search algorithm, and the bridge maintenance space set is obtained;With bridge maintenance space set as analysis basis, the target graphics is executed using recursive algorithm Detection analysis, judge whether there is a continuous path that can be maintained, and according to the judgment result, corresponding operation is performed on the obstacle graphics, and the maintenance space compliance result is obtained;According to the maintenance space compliance result, the space detection report of bridge component is generated.

Description

Technical Field

[0001] This invention relates to the field of architectural design technology, and specifically to a method and system for detecting cable tray maintenance spaces. Background Technology

[0002] Cable trays are supporting devices used for laying cables in the field of architectural design. Maintenance space refers to the operating space that must be reserved around the cable tray to ensure the smooth implementation of subsequent cable maintenance work.

[0003] After completing the BIM (Building Information Modeling) model using software tools during the design phase, the maintenance space needs to be checked to ensure sufficient space can be reserved during construction. Current technology mainly relies on two methods to check the maintenance space. One is for designers to manually check based on experience during the design phase. The other is to use the sectional view function of BIM for manual measurement and verification.

[0004] All of the above methods suffer from low efficiency and low accuracy in the screening process. This is especially true in large and complex projects where the number of cable trays is enormous, making manual verification of each one extremely labor-intensive and time-consuming. Furthermore, the verification results are easily influenced by differences in personnel experience, leading to missed or incorrect assessments. Summary of the Invention

[0005] To address the problems of low efficiency and low accuracy in existing methods for detecting cable tray maintenance space, this invention aims to provide an automated, intelligent, and highly accurate detection method and system. The specific technical solution adopted is as follows: In a first aspect, embodiments of the present invention provide a method for detecting cable tray maintenance space, characterized in that the detection method includes: identifying cable tray components and cable tray information of the cable tray components from components of a BIM model; creating a three-dimensional detection profile for the cable tray components; sequentially converting all model components in the detection profile into two-dimensional graphics in the profile view; wherein, the two-dimensional graphics corresponding to the cable tray components are marked as target graphics; the remaining two-dimensional graphics are marked as obstacle graphics; using the target graphics as a reference, finding the detection boundary of a specified model component in a preset specified direction to obtain a region to be detected; within the region to be detected, performing maintenance space analysis on the target graphics using an iterative path search algorithm to obtain a set of cable tray maintenance spaces; using the set of cable tray maintenance spaces as the basis for analysis, performing detection analysis on the target graphics using a recursive algorithm to determine whether there is a continuous path that can be maintained, and performing corresponding operations on the obstacle graphics according to the determination result to obtain a compliance result of the maintenance space; and generating a space detection report for each cable tray component based on the compliance result of the maintenance space.

[0006] Optionally, the step of using the cable tray maintenance space set as the analysis basis and performing detection analysis on the target graphic using a recursive algorithm to determine whether there is a continuous path that can be maintained, and performing corresponding operations on the obstacle graphic according to the judgment result to obtain the maintenance space compliance result, includes: if there is a continuous path that can be maintained, the maintenance space compliance result of the cable tray component corresponding to the target graphic is compliant; if there is no continuous path that can be maintained, determine the obstacle graphic to be removed from the obstacle set, remove the determined obstacle, and obtain a new obstacle set; multiple obstacle graphics form an obstacle set; based on the new obstacle set, re-execute the detection analysis until the judgment result indicates that there is a continuous path that can be maintained or the number of obstacle graphics in the obstacle set is zero.

[0007] Optionally, determining the obstacle graphic to be removed from the obstacle set includes: acquiring the height and horizontal position information of all obstacle graphics and the target graphic in the cross-sectional view in the obstacle set; selecting the obstacle graphic with the smallest difference between the horizontal position information of the obstacle graphic and the horizontal position information of the target graphic as a candidate obstacle graphic; and finding the graphic among the candidate obstacle graphics whose top height information is less than the bottom height information of the target graphic or whose bottom height information is less than the top height information of the target graphic as the obstacle graphic to be removed.

[0008] Optionally, the step of performing corresponding operations on the obstacle graphics based on the judgment result to obtain the maintenance space compliance result includes: merging the lengths of the sequentially removed obstacle graphics to obtain the cumulative invalid maintenance length; dividing the cumulative invalid maintenance length by the total length of the bridge structure component to obtain a length ratio; if the length ratio is less than or equal to a preset threshold, the maintenance space compliance result of the bridge structure component is compliant; if the length ratio is greater than the preset threshold, the maintenance space compliance result of the bridge structure component is non-compliant.

[0009] Optionally, the step of performing maintenance space analysis on the target graphic within the area to be detected using an iterative path search algorithm to obtain a set of cable tray maintenance spaces includes: using the bottom boundary of the area to be detected as a reference, searching for continuous vertical space in the vertical direction according to a vertical search standard to obtain a set of vertical maintenance spaces; wherein, the vertical search standard is not less than a preset minimum vertical maintenance width; for each vertical maintenance space in the set of vertical maintenance spaces, searching for continuous horizontal space in the horizontal direction according to a horizontal search standard to obtain a set of horizontal maintenance spaces; searching for continuous horizontal space according to a reach detection standard to obtain a set of reachable maintenance spaces; wherein, the horizontal search standard is not less than a preset minimum horizontal maintenance width; the reach detection standard is not less than a preset minimum reachable width and not greater than a preset reachable detection coverage length; for each horizontal maintenance space in the set of horizontal maintenance spaces, using the side of the horizontal maintenance space as a new bottom boundary, repeating the steps of vertical and horizontal searching until no new space can be found, to obtain the final set of cable tray maintenance spaces.

[0010] Optionally, the maintenance method further includes: ending the maintenance space analysis when the target graphic can be maintained within the vertical maintenance space set; ending the maintenance space analysis when the target graphic can be maintained within the horizontal maintenance space set or the reachable maintenance space set.

[0011] Optionally, the step of finding the detection boundary of a specified model component in a preset specified direction based on the target graphic to obtain the detection area includes: using the target graphic as a reference, performing ray projection or position querying upward and downward in the vertical direction respectively; determining the first obstacle graphic located above the target graphic and overlapping with the target graphic's projection in the vertical direction, and using the bottom height of the obstacle graphic as the top boundary line of the detection area; determining the first obstacle graphic located below the target graphic and overlapping with the target graphic's projection in the vertical direction, and using the top height of the obstacle graphic as the bottom boundary line of the detection area; and forming the detection area based on the top boundary line and the bottom boundary line.

[0012] Optionally, the step of sequentially converting all model components in the detection profile into two-dimensional graphics in the sectional view includes: obtaining the projected contour of each model component in the sectional view; determining the axially aligned boundary rectangle surrounding the projected contour based on the extreme coordinates of the projected contour, and using the axially aligned boundary rectangle as the two-dimensional graphics of the corresponding model component.

[0013] Optionally, creating a three-dimensional detection profile for the bridge structure component includes: constructing a corresponding profile frame with the geometric center of the bridge structure component as the origin and the orientation of the bridge structure component as the observation direction; determining the width and height of the profile frame according to preset rules, and setting the depth of the profile frame according to the length of the bridge structure component, thereby determining the profile frame as a three-dimensional detection profile.

[0014] In a second aspect, embodiments of the present invention provide a detection system for cable tray maintenance space, comprising: a processor and a memory; wherein the memory is used to store a computer program that can run on the processor; the processor is used to execute the program stored in the memory to implement the steps of the method for detecting cable tray maintenance space as mentioned in the first aspect.

[0015] This invention has the following beneficial effects: First, bridge structure components and their cable tray information are identified from the components of the BIM model; then, a three-dimensional detection profile is created for the bridge structure components; all model components in the detection profile are sequentially converted into two-dimensional graphics in the profile view; wherein, the two-dimensional graphics corresponding to the bridge structure components are marked as target graphics; the remaining two-dimensional graphics are marked as obstacle graphics; using the target graphics as a reference, the detection boundary of the specified model components is found in a preset specified direction to obtain the area to be detected; within the area to be detected, the target graphics are analyzed for maintenance space using an iterative path search algorithm to obtain a set of cable tray maintenance spaces; using the set of cable tray maintenance spaces as the basis for analysis, a recursive algorithm is used to perform detection analysis on the target graphics to determine whether there is a continuous path that can be maintained, and corresponding operations are performed on the obstacle graphics according to the judgment result to obtain the maintenance space compliance result; based on the maintenance space compliance result, a space detection report for each bridge structure component is generated.

[0016] Thus, this invention enables automated analysis and quantitative determination of cable tray maintenance space based on BIM models. By abstracting three-dimensional components into two-dimensional rectangles and constructing the area to be inspected, the computational complexity of spatial conflict detection is significantly reduced, improving inspection efficiency and accuracy. Through a combination of iterative search and recursive path detection, the invention accurately identifies the maintenance space around the cable tray and objectively judges the compliance of the maintenance space by combining obstacle removal strategies and length ratio rules, avoiding subjective errors and omissions caused by manual verification. Finally, it automatically generates space inspection reports for each cable tray, realizing batch, rapid, and standardized inspection of cable tray maintenance space, effectively improving the intelligence level of BIM-based integrated design and construction verification of MEP pipelines. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope of protection. For those skilled in the art, other related drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating a method for detecting cable tray maintenance space according to an embodiment of the present invention.

[0019] Figure 2 This is an algorithm flowchart corresponding to Embodiment 2, provided as one embodiment of the present invention.

[0020] Figure 3 This is a schematic diagram of a detection system for cable tray maintenance space provided in one embodiment of the present invention.

[0021] Figure 4 A schematic diagram of a detection system for cable tray maintenance space provided in another embodiment of the present invention. Detailed Implementation

[0022] The technical solution of the present invention will be clearly and completely described below with reference to specific embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0023] The main reason why existing technologies suffer from low screening efficiency and low accuracy is that: Currently, maintenance space verification relies heavily on the subjective experience and manual judgment of designers, lacking unified and quantifiable judgment standards. This leads to significant differences in verification results among different personnel, easily resulting in omissions and misjudgments. Secondly, in large and complex projects with numerous and densely distributed cable trays, manual inspection or manual sectioning and measurement is tedious, repetitive, and cannot achieve batch or automated processing, resulting in overall time-consuming, labor-intensive, and inefficient operations. Existing BIM sectioning and measurement tools only provide visual viewing and partial manual measurement, lacking automatic spatial analysis, path judgment, and compliance verification capabilities, making it difficult to quickly identify continuous maintenance spaces and the impact range of obstacles. Manual verification struggles to quantify the degree of obstacle impact and cannot objectively assess the restoration effect of maintenance space after obstacle removal, resulting in a lack of data support for maintenance space compliance judgments and insufficient reliability of results.

[0024] The specific scheme of the detection method for cable tray maintenance space provided by the present invention will be described in detail below with reference to the accompanying drawings.

[0025] Please see Figure 1 The flowchart illustrates a method for detecting cable tray maintenance space according to an embodiment of the present invention, including: S101, Identify the bridge structure components and the bridge frame information of the bridge structure components from the components of the BIM model.

[0026] Specifically, cable tray information includes, but is not limited to: spatial location coordinates, geometric boundary range, laying direction, component length, cross-sectional dimensions, and elevation information.

[0027] In this step, the component categories in the BIM model mainly include electromechanical pipeline components, building structure components, and auxiliary components; among them, the target components to be inspected are various bridge structure components, and other components include but are not limited to: ventilation duct components, electrical conduit components, water supply and drainage pipe components, cable tray components, cable tray components, as well as building structure components such as beams, slabs, columns, and walls.

[0028] The process of identifying and acquiring information about target bridge components is as follows: traverse all components in the BIM model, automatically filter and identify all bridge components that need to be inspected for maintenance space based on predefined component categories, family names and family type parameters, and extract the above-mentioned bridge information to provide a data foundation for subsequent section creation and spatial analysis.

[0029] S102, Create a three-dimensional detection profile for the bridge structure component.

[0030] Specifically, for each bridge structure component to be inspected, a three-dimensional profile frame is constructed with the geometric center of the component as the origin and the laying direction of the component as the observation direction. The width and height of the profile frame are determined according to preset rules, which are set in combination with the cross-sectional dimensions of the bridge structure component and the minimum space margin required for maintenance operations. This ensures that the profile frame can completely cover the bridge structure component and the surrounding potential maintenance space. The depth of the profile frame matches the length of the bridge structure component, providing an accurate spatial reference for the subsequent conversion of the three-dimensional component into a two-dimensional graphic and the analysis of maintenance space.

[0031] S103, all model components in the detection profile are sequentially converted into two-dimensional graphics in the profile view; wherein, the two-dimensional graphics corresponding to the bridge structure components are marked as target graphics; the remaining two-dimensional graphics are marked as obstacle graphics.

[0032] Specifically, the process begins by collecting and capturing all model components within the aforementioned dynamic detection profile frame, ensuring no omissions. Then, for each collected model component, its projected contour within the detection profile is extracted. This projection contour of each component is then abstracted into one or more axially aligned boundary rectangles (AABBs). In other words, by capturing the extreme coordinates of the component's projection, the smallest rectangle capable of completely enclosing the component's projection contour is constructed, thus transforming the 3D component into a 2D graphic. The core purpose of this abstraction process is to simplify the complex 3D component contours into regular 2D rectangles, thereby transforming the originally complex 3D spatial conflict detection problem into a simple and easy-to-understand 2D rectangle relationship analysis. This significantly reduces the computational load of subsequent spatial analysis, improves detection efficiency, and lays the foundation for distinguishing target graphics from obstacle graphics and conducting maintenance spatial analysis.

[0033] It should be noted that in the above embodiments, the origin is taken as the geometric center of the bridge structure component, and the observation direction is the positive direction of the coordinate axis. The start and end points of the projection of each model component on the coordinate axis are first obtained. This step is intended to provide a data basis for the subsequent step S106.

[0034] S104, using the target graphic as a reference, find the detection boundary of the specified model component in a preset specified direction to obtain the area to be detected.

[0035] Specifically, using the target rectangle corresponding to the target graphic as a reference, ray projection or rectangle position queries are performed upwards and downwards in the vertical direction (Y-axis) of the two-dimensional profile to locate the boundary components that constrain the inspection space. These boundary components are building structural components such as floor slabs. Within the query range, the first boundary component located above the target rectangle and overlapping its projection is found, and the bottom height of its abstract rectangle is used as the top boundary line of the area to be inspected. Similarly, the first boundary component located below the target rectangle and overlapping its projection is found, and the top height of its abstract rectangle is used as the bottom boundary line. The top and bottom boundary lines together enclose a vertically defined area to be inspected, thereby further narrowing the analysis range of the subsequent inspection space within the global profile, reducing invalid calculations, and improving detection accuracy.

[0036] S105, within the area to be detected, the target graphic is analyzed for maintenance space using an iterative path search algorithm to obtain a set of cable tray maintenance spaces.

[0037] Specifically, within the area to be inspected determined in step S104, global indiscriminate spatial analysis is no longer performed. Instead, the focus is on the operable space around the target graphic (i.e., the two-dimensional rectangle corresponding to the bridge structure component). An iterative path search algorithm is used to gradually explore the effective space that can be used for maintenance, and finally a complete set of bridge structure maintenance spaces is formed. Further, the specific steps are as follows: a. Vertical space acquisition: Taking the bottom boundary of the area to be detected determined in step S104 as the starting point, according to the preset minimum width standard of vertical maintenance space, continuously check the unobstructed space upwards step by step, and select the vertical continuous space that meets the maintenance operation requirements and whose width is not less than the preset threshold. Include it in the vertical maintenance space set V_current. If the target graphic (the two-dimensional rectangle corresponding to the cable tray) can be completely in the vertical space and can meet the vertical activity requirements of the maintenance operation, then the area is directly determined to be a valid maintenance space, and there is no need to continue the subsequent horizontal search. The space analysis ends directly.

[0038] b. Obtaining Horizontal and Reaching Spaces: For each vertical maintenance space V_i obtained in step a, conduct a spatial search to its left and right sides (horizontally), selecting continuous spaces with a width not less than the minimum width for horizontal maintenance, forming a horizontal maintenance space set H_current1; simultaneously, search for spaces that meet the minimum width for reaching operations and whose coverage does not exceed the preset reaching detection length, forming a reaching maintenance space set H_current2. Together, these two sets constitute the horizontal and reaching maintenance space system. If the target graphic can achieve a complete maintenance operation within either set, the spatial analysis ends directly.

[0039] c. Iterative path extension search: For each lateral maintenance space H1_i obtained in step b, take its side as the new starting boundary, and repeat the operations of steps a and b. That is, based on this, search for vertical continuous space upwards and lateral and reachable spaces to both sides, and continue to iterate until no new effective maintenance space can be found.

[0040] This iterative search method can comprehensively capture all available maintenance spaces around the target graphic, avoiding the omission of potential effective maintenance areas. At the same time, by setting a minimum width standard, it ensures that all the excavated spaces can meet the actual maintenance operation requirements. Finally, all effective maintenance spaces are integrated to form a complete set of cable tray maintenance spaces, providing accurate data support for subsequent compliance judgments.

[0041] S106. Using the cable tray maintenance space set as the analysis basis, a recursive algorithm is used to perform detection and analysis on the target graphic to determine whether there is a continuous path that can be maintained, and corresponding operations are performed on the obstacle graphic according to the judgment result to obtain the compliance result of the maintenance space.

[0042] Specifically, the spatial analysis in step S105 is first performed on the target graphic to determine if there is a continuous path for the cable tray to be inspected. If a continuous path for inspection exists, the cable tray is directly determined to be compliant; if no continuous path for inspection exists, the "obstacle removal-re-inspection" loop is executed. The steps of this loop are as follows: a. Identify and remove: Among all obstacle graphics, select the obstacle that is vertically lower than the target graphic and horizontally closest to the target graphic, and remove it from the set of obstacles detected in this test; b. Re-analysis: Based on the new set of obstacles, re-execute the spatial analysis in step S105; c. Loop condition: Repeat steps a and b until there is a continuous path that can repair the target graphic, or all obstacles in the obstacle set are removed.

[0043] After the above cycle is completed, a compliance quantification judgment is performed. The judgment method and basis are as follows: for all temporarily removed obstacles, the length is calculated by merging the projection values ​​of their start and end points to solve the overlap statistics problem, and the cumulative invalid maintenance length L_blocked is obtained; the ratio L_blocked / TotalLength (where TotalLength is the total length of the cable tray) is calculated. If L_blocked / TotalLength ≤ 5% (i.e. 1 / 20), the cable tray is judged to be compliant; otherwise, it is judged to be non-compliant.

[0044] To further explain the aforementioned start and end point projection values, these values ​​are the starting and ending coordinates of the obstacle projected onto a coordinate axis with the geometric center of the bridge structure component as the origin and the observation direction as the positive direction. The starting and ending coordinates are used to describe the current component's occlusion effect on the bridge structure and its range of influence.

[0045] It should be noted that by combining the continuous path judgment S105 with the compliance quantification judgment S106, this invention achieves two significant beneficial effects: First, for long, straight, extended components such as cable trays, it proposes an innovative judgment principle of "allowing local non-compliance, but quantifying whether the total obstruction length exceeds 5%." This avoids directly judging the overall maintenance space as non-compliant based on a small amount of local obstruction, making the test results more consistent with engineering realities and the judgment criteria more scientific and reasonable. Second, the core algorithm, which combines iterative composite path search with recursive obstacle removal, can gradually simulate obstacle avoidance scenarios and accurately identify maintainable continuous paths. Simultaneously, by merging lengths to eliminate overlapping statistical errors, it achieves an objective quantitative judgment of maintenance space compliance, significantly improving the accuracy and reliability of the test and avoiding subjective biases, omissions, and misjudgments caused by manual verification.

[0046] S107, Based on the compliance results of the maintenance space, generate a space inspection report for each bridge structure component.

[0047] Specifically, the system can generate a "compliant" or "non-compliant" inspection report for each bridge structure component, ensuring that the maintenance space status of each component is clearly verifiable. Simultaneously, the report records key inspection data, including but not limited to the cumulative invalid maintenance length L_blocked, total length of the cable tray, length ratio, and compliance judgment threshold, enabling traceability and verification of inspection results. For bridge structures judged as "non-compliant," their specific location can be accurately located in the 3D view of the BIM model, and the component and any obstacles affecting its compliance will be highlighted, visually presenting the reasons for non-compliance and the scope of impact. This facilitates designers in quickly identifying problems, making targeted adjustments to component layouts, or optimizing obstacle avoidance schemes, thus improving design optimization efficiency. For bridge structures judged as "compliant," the core parameters of their maintenance space are recorded simultaneously, providing a reference for subsequent maintenance work and ensuring the orderly conduct of maintenance work.

[0048] Furthermore, the detailed algorithm implementation processes for the S105 iterative path search algorithm, the S106 recursive algorithm obstacle removal, and the S107 compliance quantification judgment in this embodiment are as follows: Before executing step S105, the input profile boundaries are sectionLeft (representing the left boundary), sectionRight (representing the right boundary), sectionTop (representing the upper boundary), and sectionBottom (representing the lower boundary). The target rectangle / target graphic targetRect's attribute parameters include Left (representing the left boundary), Right (representing the right boundary), Top (representing the upper boundary), and Bottom (representing the lower boundary). The obstacle rectangle set obstacles is a collection of all two-dimensional rectangles corresponding to obstacles that may affect maintenance. The minimum vertical maintenance space width V_min is the minimum space width required to meet maintenance needs in the vertical direction. The minimum horizontal maintenance space width H_min is the minimum space width required to meet maintenance needs in the horizontal direction. The minimum reach width R_min is the minimum space width required to meet reach operation needs. The reach detection coverage length R_len is the maximum distance range that can be covered by the reach operation.

[0049] Input the above parameters into S105 to sequentially complete the vertical spatial search, horizontal spatial search, and iterative path search. In the vertical spatial search algorithm: first, based on the filtering conditions of: bottom boundary (Bottom) ≤ top boundary (top) of the current detection boundary (the area to be detected), top boundary (Top) ≥ bottom boundary (bottom) of the current detection boundary, left boundary (Left) ≤ right boundary (right) of the current detection boundary, and right boundary (Right) ≥ left boundary (left) of the current detection boundary, obstacles that intersect with the current detection boundary are selected from the obstacle set (obstacles). Then, the boundary set (xBoundaries) is initialized (this set contains the left and right boundaries of the current detection boundary). The relevant obstacles selected above are traversed, and the values ​​of their Left and Right values ​​between left and right are added to xBoundaries. After deduplication, they are sorted in ascending order to complete the process of collecting X boundaries. Next, scan adjacent boundaries: take two adjacent boundaries in the set as the left and right boundaries, calculate the difference between them as the current interval width. If the width is less than V_min, skip the interval; if it is not less than V_min, proceed to the next step. Then, determine the top boundary of the vertical space: if there are no obstacles in the current interval, take the top of the current detected boundary as the top boundary of the vertical space; if there are obstacles, sort the obstacles in ascending order of Bottom, and take the Bottom of the first obstacle as the top boundary of the vertical space. Next, construct the vertical space: take the selected left and right boundaries as the left and right ranges, the bottom of the current detected boundary as the bottom boundary, and the top boundary determined above as the top boundary, construct a vertical continuous free space, and store it in the verticalSpaces set. Finally, complete the inspection judgment: traverse verticalSpaces and check whether the target rectangle can be inspected in any vertical space. If it can be inspected, the inspection is feasible and the algorithm ends; if not, proceed to the horizontal space search. In this step, the inspection judgment meets criteria (1) and criteria (2). Standard (1) is to check whether there is an overlapping area (boundary overlap) between the target rectangle and the space, that is, the target rectangle intersects with the space in both the horizontal direction (Left / Right) and the vertical direction (Top / Bottom). Standard (2) is to determine whether the target rectangle is completely contained in the space in the vertical direction, that is, the top of the target rectangle does not exceed the top of the space, and the bottom of the target rectangle is not lower than the bottom of the space.

[0050] The specific algorithm process of horizontal space search is as follows: traverse each vertical space in verticalSpaces, and perform horizontal search to the left and right sides respectively. Taking the left search as an example: take the Left of the current vertical space as the bottom of the detection boundary, Bottom as the left side of the detection boundary, Top as the right side of the detection boundary, and sectionLeft as the top of the detection boundary. According to the logic of filtering relevant obstacles, collecting boundaries, determining the space width, and constructing horizontal spaces, horizontally continuous free spaces are searched, so as to obtain the horizontal space set horizontalSpaces and the reach space set reachSpaces. Taking the right search as an example: take the Right of the current vertical space as the bottom of the detection boundary, and the remaining boundaries are set symmetrically. Check whether the target rectangle can be overhauled in any horizontal space according to the above-mentioned overhaul judgment criteria (1) and (2), or check whether the target rectangle is covered by a reach space according to criteria (3) and (4). If yes, the overhaul is feasible and the algorithm ends. Criterion (3) is checking whether there is an overlapping area between the target rectangle and the space according to criterion (1). Criterion (4) is determining whether the target rectangle is also completely contained by the space in the horizontal direction, that is, the Left of the target rectangle is not lower than the Left of the space, and the Right of the target rectangle does not exceed the Right of the space.

[0051] The implementation details of the iterative path search algorithm are as follows: traverse each space in horizontalSpaces and reachSpaces, take the top of the space as the new bottom of the detection boundary, repeat the vertical space search and horizontal space search, and recursively mine accessible overhaul paths until no new space can be expanded or an accessible overhaul path is found.

[0052] When no accessible overhaul path is found after executing the S105 iterative path search algorithm, the S106 recursive algorithm obstacle removal process starts to be executed. The specific algorithm details are as follows: Identify the nearest obstacle: within the section boundary range, screen out obstacles that are lower than the target rectangle in the vertical direction (Top <targetRect.Bottom), calculate the horizontal distance between each obstacle and the target rectangle (min (| obstacle.Left - targetRect.Right|, | obstacle.Right -targetRect.Left|)), and select the obstacle with the closest horizontal distance as the object to be removed. Temporarily remove the obstacle, record its information (for subsequent length calculation), and re-execute the search process of S105 based on the updated obstacle set. Repeat the above operations until an accessible overhaul path is found or all obstacles are removed.

[0053] Finally, compliance quantification is completed according to step S107. The specific algorithm is as follows: Calculate the projected length of all temporarily removed obstacles along the cable tray direction, merge overlapping parts (to avoid duplicate counting), and obtain the cumulative invalid maintenance length L_blocked. Calculate the ratio of L_blocked to the total length of the cable tray (TotalLength). If the ratio is ≤5%, it is considered compliant; otherwise, it is considered non-compliant.

[0054] Example 2:

[0055] This embodiment was developed on the Autodesk Revit 2020 platform, based on the .NET Framework 4.7.2.

[0056] S1: Input parameters for the interface: minimum width of the vertical inspection space (Min_Vertical_Width), minimum width of the horizontal inspection space (Min_Horizontal_Width), hand detection coverage length (Hand_Detect_Length), and minimum hand width (Hand_Min_Width). Then, select the detection area, collect all elements using PickElementsByRectangle, and filter the cable tray components using Category.Name. Use CableTray.Location to obtain the cable tray's LocationCurve, thereby obtaining the cable tray's Direction, Geometric Center OriginPoint, and TotalLength.

[0057] S2: The geometric center of the cable tray, OriginPoint, is used as the origin of the section frame. The coordinate system orientation of the section frame is set according to the cable tray's orientation vector, Direction. Typically, BasisX represents the "width" direction of the section view, BasisY represents the "height" direction, and BasisZ represents the viewing direction (perpendicular to the section line). This defines a section frame. The section frame range is calculated as follows: Width W = 2 * Margin1 (Margin1 is a preset safety value, such as 1m).

[0058] Height H = 2 * Margin2 (Margin2 is a preset safety value, such as 10m).

[0059] Depth D = TotalLength (Cable tray length).

[0060] S3: Use FilteredElementColloector to obtain all components within the section. Traverse these components, performing the following steps to obtain their BoundingBoxXYZ in world coordinates: 1) Use GeometryElement to obtain the complete geometry of the element; 2) Iterate through all Solids in GeometryElement and use BooleanOperationsUtils.ExecuBooleanOperation() to clip the portion within the section frame; 3) Use Solid.Edges to get the faces of the clipped solid, then use Edge.AsCurve() to convert the faces into curved edges, and then use Curve.Tessellate() to collect the points on the curved edges; 4) Construct a bounding box (BoundingBoxXYZ) in the world coordinate system based on the points obtained in the above steps.

[0061] Finally, the BoundingBoxXYZ coordinates in the world coordinate system are projected onto the view section, the axially aligned boundary rectangle (AABB) is calculated, and stored in a rectangle list. <rectangle2d>Rectangle2D_all, and find out Rectangle2D_obstacles whose type is obstacle.

[0062] S4: Find Rectangle2D_target representing the target rectangle from Rectangle2D_all. Then: Search upward: Traverse all Rectangle2D_floor which are rectangles of the floor category, find the rectangle satisfying the condition (Rectangle2D_floor.Bottom>Rectangle2D_target.Top and their projections on the X axis overlap) among which the value of Rectangle2D_floor.Bottom is the smallest, and record its Bottom as Y_top.

[0063] Search downward: Find the rectangle satisfying the condition (Rectangle2D_floor.Top<Rectangle2D_target.Bottom and their projections on the X axis overlap) among which the value of Rectangle2D_floor.Top is the largest, and record its Top as Y_bottom, where Y_top and Y_bottom together define a region to be detected.

[0064] S5: In the region to be detected defined in S4, perform the following steps.

[0065] a. Acquisition of vertical space: Starting from the bottom boundary, search upward for vertically continuous spaces with a width not less than Min_Vertical_Width to obtain a vertical maintenance space set V_current. Intersect each vertical maintenance space V_i in the vertical maintenance space set V_current with the target rectangle, if there is an intersection, maintenance is available, and the process ends directly.

[0066] b. Acquisition of horizontal space: For each vertical maintenance space V_i in the current vertical maintenance space set V_current, search horizontally on both sides for horizontally continuous spaces that are not less than the minimum width of horizontal maintenance space, not less than the minimum reach width and not greater than the reach detection coverage length, to obtain horizontal maintenance space set H_current1 and reach maintenance space set H_current2. Intersect each horizontal maintenance space H1_i in the horizontal maintenance space set H_current1 with the target rectangle, if there is an intersection, maintenance is available, and the process ends directly. Perform space occupancy analysis on the target rectangle upward based on the top, if the target rectangle is covered by any space in the reach maintenance space set H_current2, maintenance is available, and the process ends directly.

[0067] c. Iterative path search: for each transverse maintenance space H1_i in the current transverse maintenance space set H_current1, take the side surface of H1_i as the bottom boundary, continue to perform steps a and b until no new space can be found.

[0068] S6: Perform the space analysis of S5 on the target rectangle, and determine whether there is a continuous path for maintenance of the target rectangle. If yes, the cable bridge is determined as "compliant"; if no, execute the "obstacle removal-re-detection" cycle: a. Identification and removal: among all obstacle rectangles, find Rectangle2D_obstacles[i] where Rectangle2D_obstacles[i].Top<Rectangle2D_target.Bottom or Rectangle2D_obstacles[i].Bottom<Rectangle2D_target.Top and the horizontal distance from the target rectangle is the smallest, and remove it from the obstacle set for the current detection.

[0069] b. Re-analysis: based on the new obstacle set, re-perform the space analysis of S5.

[0070] c. Cycle condition: repeat steps a and b until there is a continuous path for maintenance of the target rectangle, or all obstacles are removed.

[0071] Quantitative compliance determination: For each obstacle, obtain the projection values of the start point and end point on the observation direction vector Direction with OriginPoint as the base point. For all temporarily removed obstacles, perform combined length calculation according to their projection values of the start and end points (to solve the overlapping problem), so as to obtain the cumulative invalid maintenance length L_blocked. Calculate L_blocked / TotalLength, where TotalLength is the total length of the cable bridge.

[0072] Final determination: if L_blocked / TotalLength≤5% (i.e., 1 / 20), the cable bridge is determined as "compliant"; otherwise, it is determined as "non-compliant".

[0073] S7: Write the detection results (ID, name, status) of each cable bridge into custom parameters, and display components with insufficient maintenance space on the software interface.

[0074] The algorithm flow chart corresponding to the second embodiment above is shown in Figure 2 .

[0075] Embodiment 3:

[0076] Based on the cable tray maintenance space detection method provided in the above embodiments, and based on the same technical concept, the present invention also provides a cable tray maintenance space detection system. Figure 3 This is a schematic diagram of a detection system for cable tray maintenance space provided in one embodiment of the present invention, as shown below. Figure 3 As shown. The cable tray maintenance space detection system 200 includes: an identification module 201, used to identify cable tray components and cable tray information of the cable tray components from the components of the BIM model; a creation module 202, used to create a three-dimensional detection profile for the cable tray components; a conversion module 203, used to convert all model components in the detection profile into two-dimensional graphics under the profile view in sequence; a detection module 204, used to find the detection boundary of a specified model component in a preset specified direction based on the target graphic to obtain the area to be detected; an analysis module 205, used to perform maintenance space analysis on the target graphic in the area to be detected using an iterative path search algorithm to obtain a set of cable tray maintenance spaces; a recursive module 206, used to perform detection analysis on the target graphic using a recursive algorithm based on the set of cable tray maintenance spaces to determine whether there is a continuous path that can be maintained, and to perform corresponding operations on the obstacle graphics according to the judgment result to obtain the maintenance space compliance result; and a generation module 207, used to generate a space detection report for each cable tray component based on the maintenance space compliance result.

[0077] The cable tray maintenance space detection system provided in this invention embodiment is based on the same technical concept as the detection method. Through modular design, it integrates functions such as identification, profile creation, 2D conversion, path detection, and compliance judgment. The modules work together to achieve fully automated processing from cable tray component identification and space analysis to compliance judgment. This not only eliminates the subjectivity and inefficiency of manual verification, but also accurately matches the actual needs of the project through iterative path search, recursive obstacle removal, and quantitative judgment, effectively improving the accuracy and reliability of detection. At the same time, it relies on the BIM model to achieve visualized positioning and traceability, providing efficient and standardized technical support for the design, construction, and maintenance of cable tray maintenance spaces, fully demonstrating the innovative advantages of iterative path search and quantitative compliance judgment.

[0078] Example 4:

[0079] Corresponding to the cable tray maintenance space detection method provided in the above embodiments, based on the same technical concept, this embodiment of the invention also provides a cable tray maintenance space detection system, which is used to perform the above-described cable tray maintenance space detection method. Figure 4 A schematic diagram of a detection system for cable tray maintenance space provided in another embodiment of the present invention is shown below. Figure 4 As shown. The detection system for the cable tray maintenance space can vary considerably depending on its configuration or performance. It may include one or more processors 301 and memory 302. The memory 302 stores computer programs that can run on the processor 301. The processor 301 executes the programs stored in the memory 302 to achieve the above. Figure 1 The various steps in the Chinese method embodiment. The memory 302 can be temporary or persistent storage. The application stored in the memory 302 may include one or more modules (not shown in the figures), each module may include a series of computer-executable instructions for a detection system of the cable tray maintenance space.

[0080] Furthermore, the processor 301 can be configured to communicate with the memory 302 and execute a series of computer-executable instructions stored in the memory 302 on the detection system of the cable tray maintenance space. The detection system of the cable tray maintenance space may also include one or more power supplies 303, one or more wired or wireless network interfaces 304, one or more input / output interfaces 305, and one or more keyboards 306. Specifically, in this embodiment, the detection system of the cable tray maintenance space includes a processor, a communication interface, a memory, and a communication bus; wherein, the processor, the communication interface, and the memory communicate with each other through the bus; the memory is used to store computer programs; the processor is used to execute the programs stored in the memory to achieve the above... Figure 1 The various steps in the method embodiments are the same as those in the above method embodiments, and have the same beneficial effects. To avoid repetition, the embodiments of the present invention will not be described again here.

[0081] This cable tray maintenance space inspection system enables batch, automated inspection of a large number of cable trays, significantly improving design review efficiency. Through geometric calculations and preset rules, it achieves objective judgment, avoiding the subjectivity and oversights of manual inspection and ensuring accurate and reliable results. It can identify spatial conflicts in the design phase, effectively reducing changes and rework during construction and lowering project costs. Developed based on the Revit 2020 API, the system seamlessly integrates into existing BIM workflows and supports rule configuration to adapt to different project standards and specifications, demonstrating excellent integration and versatility. It should be noted that the detection system for cable tray maintenance space provided in this embodiment of the invention and the detection method for cable tray maintenance space provided in this embodiment of the invention are based on the same application concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned detection method for cable tray maintenance space, and has the same or similar beneficial effects. Repeated parts will not be described again.

[0082] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0083] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for detecting the maintenance space of a cable tray, characterized in that, The detection method includes: Identify bridge structure components and their cable tray information from the components of the BIM model; Create a three-dimensional inspection profile for the bridge structure component; All model components in the detection profile are sequentially converted into two-dimensional graphics in the profile view; wherein, the two-dimensional graphics corresponding to the bridge structure components are marked as target graphics; the remaining two-dimensional graphics are marked as obstacle graphics; Using the target graphic as a reference, the detection boundary of the specified model component is found in a preset specified direction to obtain the area to be detected; Within the area to be detected, an iterative path search algorithm is used to perform maintenance space analysis on the target graphic to obtain a set of cable tray maintenance spaces, including: Using the bottom boundary of the area to be detected as a reference, a vertical continuous space is searched in the vertical direction according to the vertical search standard to obtain a set of vertical maintenance spaces; wherein, the vertical search standard is not less than the preset minimum width for vertical maintenance; For each vertical maintenance space in the set of vertical maintenance spaces, a set of horizontal maintenance spaces is obtained by searching the horizontal continuous space according to the horizontal search criterion; a set of reachable maintenance spaces is obtained by searching the horizontal continuous space according to the reachable detection criterion; wherein, the horizontal search criterion is not less than the preset minimum horizontal maintenance width; the reachable detection criterion is not less than the preset minimum reachable width and not greater than the preset reachable detection coverage length; For each horizontal maintenance space in the set of horizontal maintenance spaces, the side of the horizontal maintenance space is used as the new bottom boundary. The steps of vertical search and horizontal search are repeated until no new space can be found, thus obtaining the final set of cable tray maintenance spaces. The maintenance space is an operating space that must be reserved around the cable tray to ensure that subsequent cable maintenance work can be carried out smoothly. Based on the set of cable tray maintenance spaces, a recursive algorithm is used to perform detection and analysis on the target graphic to determine whether there is a continuous path that can be maintained. Based on the determination result, corresponding operations are performed on the obstacle graphic to obtain the compliance result of the maintenance space, including: If there is a continuous path that can be inspected, the inspection space compliance result of the bridge structure component corresponding to the target graphic is compliant. In the absence of a continuous path that can be repaired, the obstacle graphics to be removed are determined from the obstacle set, and the determined obstacles are removed to obtain a new obstacle set; multiple obstacle graphics constitute an obstacle set; Based on the new obstacle set, re-execute the detection analysis until the judgment result indicates that there is a repairable continuous path or the number of obstacle patterns in the obstacle set is zero; The lengths of the obstacles that are removed in sequence are merged to obtain the cumulative invalid maintenance length; Divide the cumulative invalid maintenance length by the total length of the bridge structure components to obtain the length ratio; If the length ratio is less than or equal to a preset threshold, the compliance result of the maintenance space of the bridge structure component is compliant. If the length ratio is greater than a preset threshold, the compliance result of the maintenance space of the bridge structure component is non-compliant. Based on the compliance results of the maintenance space, a space inspection report is generated for each bridge structure component.

2. The detection method according to claim 1, characterized in that, The process of determining the obstacle graphic to be removed from the obstacle set includes: Within the obstacle set, obtain the height and horizontal position information of all obstacle and target graphics in the cross-sectional view; The obstacle graphic with the smallest difference between its horizontal position information and the target graphic's horizontal position information is selected as the candidate obstacle graphic. Among the candidate obstacle graphics, the graphic whose top height is less than the bottom height of the target graphic, or whose bottom height is less than the top height of the target graphic, is the obstacle graphic to be removed.

3. The detection method according to claim 1, characterized in that, The detection method further includes: If the target graphic can be inspected within the set of vertical maintenance spaces, the maintenance space analysis ends. If the target graphic can be inspected within the set of lateral maintenance spaces or the set of reachable maintenance spaces, the maintenance space analysis ends.

4. The detection method according to claim 1, characterized in that, The step of finding the detection boundary of a specified model component in a preset specified direction, based on the target graphic, to obtain the region to be detected includes: Using the target graphic as a reference, ray projection or position query is performed upward and downward in the vertical direction, respectively; Identify the first obstacle graphic located above the target graphic and overlapping the target graphic in the vertical direction, and use the bottom height of the obstacle graphic as the top boundary line of the area to be detected; Identify the first obstacle graphic located below the target graphic and overlapping the target graphic in the vertical direction, and use the top height of the obstacle graphic as the bottom boundary line of the area to be detected; The detection area is formed based on the top and bottom boundary lines.

5. The detection method according to claim 1, characterized in that, The step of sequentially converting all model components in the detection profile into two-dimensional graphics in the profile view includes: Obtain the projected outline of each model component in the sectional view; Based on the extreme coordinates of the projected contour, an axially aligned boundary rectangle is determined to surround the projected contour, and this axially aligned boundary rectangle is used as the two-dimensional graphic of the corresponding model component.

6. The detection method according to claim 1, characterized in that, The process of creating a three-dimensional inspection profile for the bridge structure component includes: With the geometric center of the bridge structure component as the origin and the orientation of the bridge structure component as the observation direction, a corresponding cross-sectional frame is constructed. The width and height of the profile frame are determined according to preset rules, and the depth of the profile frame is set according to the length of the bridge structure component, so that the profile frame is determined as a three-dimensional detection profile.

7. A detection system for cable tray maintenance space, characterized in that, include: Processor and memory; wherein the memory is used to store computer programs that can run on the processor; A processor is used to execute a program stored in memory to implement the steps of a method for detecting cable tray maintenance space as described in any one of claims 1-6.

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