Steel structure digital restoration device and method for digital twinborn construction

Abstract

The invention discloses a steel structure digital restoration device and method for digital twin construction, and the device comprises a structure recognition module which is configured to carry out the restoration operation based on position correspondence in a virtual three-dimensional space according to the obtained point cloud information of a steel structure according to the embedded space coordinate information, acquiring a total model field about the distribution of the point cloud in the space, wherein the representation form of the restored point cloud information in the total model field is a point model; automatically selecting a position with the optimal point model density based on the distribution condition of the point cloud, and slicing to obtain basic section data of the structure; and performing identification judgment on the type of the steel structure based on the image in the basic section data, and after the type of the steel structure is correctly identified, performing three-dimensional model fitting reduction on the slice based on the identified type of the steel structure. According to the method, the three-dimensional pipeline model can be directly restored with high precision, and an engineer can obtain information of all steel structures in a whole factory by directly observing the three-dimensional steel structure model with sufficient and abundant details.

Description

[0001] The original basis of this divisional application is a patent application with application number (202210308895.X), application date 2022.03.25, and invention name “A digital three-dimensional reverse modeling method and system”. Technical Field

[0002] The present invention relates to the field of digital reverse modeling, and in particular to a steel structure digital restoration device and method for digital twin construction. Background Art

[0003] With the advancement of industrial progress, considering factors such as environmental protection and low carbon, new construction projects in industries such as petrochemicals and electric power have gradually slowed down, and the maintenance and life extension of in-service plants have become particularly important. How to use some digital technical means to digitize and structure existing assets to increase corporate production capacity, improve safety protection, and reduce risks has become a concern for everyone. However, due to factors such as the complex information, large number of pipelines, and frequent maintenance and renovation of process plants such as petroleum, chemical, and electric power, factories that have been in operation for more than ten years have generated a large amount of online and offline data, and there are many discrepancies between drawings, models, and actual on-site conditions. Technical personnel cannot accurately grasp the on-site situation through data, which causes great trouble for overhauls and technical transformation. Therefore, based on the actual situation of the plant, the construction of digital twins for all process equipment pipelines and structures has become a key and difficult task for in-service plants.

[0004] It is a key task to carry out 3D reverse modeling for the structure of existing factories. The construction time of existing factories is long, and the original engineering documents and drawings may be missing. At the same time, during the long operation of the factory, large and small equipment and structural modifications are often carried out, resulting in inconsistencies between the current factory structure and the original drawings. At present, with the vigorous development of digital factory technology, existing factories are also in urgent need of transformation and upgrading to digital and automated factories, which involves the 3D reverse modeling of existing structures in the factory. One of the main purposes of 3D reverse modeling is to copy the specific structure in the existing factory into a 3D model in a one-to-one manner in terms of spatial position and structural shape.

[0005] In the prior art, the reverse modeling of existing steel structures usually has a high degree of manual participation, and it is necessary to manually screen out the point cloud model of the steel structure from a large amount of point cloud data, and then use the point cloud model as a draft to manually remodel the same position to build a complete three-dimensional model of the steel structure. In short, the prior art is to copy the point cloud model on the basis of manual structural recognition to finally obtain the three-dimensional model of the steel structure. This undoubtedly increases the labor cost of the manual labor, prolongs the cycle of reverse engineering, and makes reverse engineering time-consuming and laborious. At the same time, the obtained three-dimensional modeling is difficult to use for subsequent practical work, because the currently obtained three-dimensional modeling only has a good restoration in structure and spatial position, but this can only provide an external reference for engineers, and the specific parameters of the steel structure, the control logic of other components, etc. are not displayed. Therefore, while performing the three-dimensional reverse restoration of the steel structure, it is also necessary to manually bind the control parameters of these steel structures, which further increases the workload.

[0006] Among them, the construction of digital twins of steel structures is one of the projects in the digital backup project of the entire factory's in-service structures. Due to the complexity of the steel structure and its relationship with the pipeline, its structural scanning is not only focused on the backup of its physical structure, but its role and function in the pipeline properties are also one of the targets that need to be backed up.

[0007] In addition, on the one hand, there are differences in understanding among those skilled in the art; on the other hand, the applicant studied a large number of documents and patents when making the present invention, but due to space limitations, not all details and contents are listed in detail. However, this does not mean that the present invention does not have the characteristics of these prior arts. On the contrary, the present invention already has all the characteristics of the prior art, and the applicant reserves the right to add relevant prior art to the background technology. Summary of the invention

[0008] In view of the shortcomings of the prior art, the present invention provides a digital three-dimensional reverse modeling system, which is used for the construction of digital twins of existing steel structures, including a point cloud acquisition unit, which collects point cloud information containing spatial coordinate information about any point on the existing steel structure and stores it in a point cloud repository, wherein a reverse restoration unit is also included, which is electrically connected to the point cloud repository to read the point cloud information collected by the point cloud acquisition unit and then restore it to a three-dimensional model of the steel structure in a virtual three-dimensional restoration manner. While performing the restoration of the three-dimensional model of the steel structure, process attributes are assigned to the steel structure and instruments based on P&ID logic to obtain a three-dimensional model that at least includes P&ID attribute data.

[0009] The advantage is that the recognition and modeling of steel structures in the prior art are improved by automation. Based on the steps of automatic steel structure recognition, continuity monitoring and missing structure restoration given in this solution, a three-dimensional reverse restoration model can be automatically generated based on point cloud information without the need for manual modeling. In comparison, the efficiency of three-dimensional reverse modeling is greatly improved, and the labor cost is significantly reduced. After obtaining the steel structure, it is segmented according to the specific location and structure of the steel structure, saved as unit component data, or corrected and modified. Due to the automatically generated three-dimensional model of the steel structure, the subsequent manual participation process becomes relatively simple, which can effectively reduce manual labor.

[0010] In addition, the P&ID logic can be used to assist in the construction of relevant structural attributes and data topology in the three-dimensional restoration process of steel structures, so that the speed of related three-dimensional pipeline restoration construction is substantially accelerated when there are limited component matches. At the same time, the pipeline logic can be directly superimposed on the three-dimensional model based on the structural attributes assigned by the P&ID. When the engineering personnel obtain the reverse three-dimensional model generated by the system or method, they can not only intuitively and accurately observe the three-dimensional spatial model image of the relevant structure to perform maintenance point selection, pipeline analysis, planning of new facility installation points, etc., but also directly observe the pipeline logic displayed in the form of several model-associated control points from the model. These pipeline logics On the one hand, the editor shows the pipeline properties (such as valve model, parameters, instrument model, parameters, etc.) to the engineering personnel, so that they can not only better complete the above tasks, but also access the control unit for the control points associated with each model, so that the engineering personnel can directly control the control link corresponding to the model in the entity by clicking the relevant control point model marked with pipeline logic on the reverse restored three-dimensional model, such as controlling the on and off of valves, so that the factory control is transformed from the existing scattered control and on-site control to the central control realized by the terminal system, which can effectively integrate the original old equipment in the factory, realize the unification of the production control of the entire factory, and significantly improve the efficiency and effect of factory control.

[0011] Through the automatic identification of pipeline structure and automatic assignment of control parameters, this solution actually obtains a three-dimensional reverse model with complete control logic parameters, accurate structure, and intuitive and clear view structure. The P&ID graphics originally displayed in two-dimensional form are transformed into three-dimensional views combined with three-dimensional spatial structures, so that engineers can directly use the three-dimensional reverse model to perform control-related work on factory-related equipment, such as parameter query, monitoring, control and other operations. Compared with the nested two-dimensional P&ID graphics, the three-dimensional model can provide engineers with multiple accurate structural positions at different levels of control sites at the same time in a more intuitive and comprehensive display form, so that the control efficiency is further improved. At the same time, in the process of executing three-dimensional reverse modeling, the structural parameters in P&ID can be reversely used to accelerate the construction of three-dimensional reverse modeling. Based on the correspondence between some or all of the feature models in the three-dimensional construction and the P&ID diagram, the remaining unfinished parts in the three-dimensional construction process can be assisted by the corresponding parameters provided by P&ID to complete the three-dimensional modeling. The above-mentioned feature models are some special shapes set manually to characterize some structures, such as the I-shaped shape of steel structures and the disc shape of valve structures. After these feature models are identified or preferentially identified, it is known that the component exists at the location, but the specific structural parameters of the component may still remain unknown or partially unknown. Through the connection relationship between the component and the other components, the parts with the same connection relationship in the P&ID image are compared and queried to confirm the correspondence between the P&ID diagram and the three-dimensional model, and the structural parameters in the P&ID diagram are used to restore the above-mentioned unknown three-dimensional structure. At this time, it is not necessary to perform the steps of point cloud shape recognition and three-dimensional restoration. The above process actually realizes the organic combination of P&ID images and three-dimensional structure restoration. The three-dimensional inverse model provides a more intuitive visual display upgrade for P&ID images with weak structures, and the P&ID with complete parameters provides an auxiliary acceleration process for the construction of the three-dimensional inverse model.

[0012] Preferably, the point cloud acquisition unit is configured as a three-dimensional scanner, which scans the spatial position information of any and / or all visible points on the existing steel structure and forms point cloud information before the reverse restoration unit performs the step of reconstructing the three-dimensional model of the steel structure.

[0013] Preferably, the reverse restoration unit includes a denoising module, which is electrically connected to the point cloud repository to obtain the original point cloud information scanned only by the point cloud acquisition unit and perform filtering denoising on the information. The filtering denoising is performed in combination of at least two methods: custom point cloud density recognition and manual box selection denoising.

[0014] Preferably, the reverse restoration unit also includes a structure recognition module, which is electrically connected to the denoising module to obtain the point cloud information after denoising processing, and then performs a position-corresponding restoration operation on the point cloud information in the virtual three-dimensional space according to its embedded spatial coordinate information to obtain the total model field of the point cloud distribution in space, and based on the point cloud distribution, select the position with the best point model density, slice it, obtain the basic cross-sectional data of the structure, perform recognition and judgment of the steel structure type based on the image in the basic cross-sectional data, and after correctly identifying the steel structure type, perform three-dimensional model fitting restoration of the sliced ​​part based on the identified type.

[0015] Preferably, when several orthogonal line segments are found in the basic section, and one of the line segments perpendicularly bisects the other two parallel and coplanar line segments, the structure displayed by the basic section is determined to be an H-steel structure, and the fitting restoration of the H-steel three-dimensional model is performed on the basic section.

[0016] Preferably, when several orthogonal line segments are found in the basic section and the intersection of two mutually orthogonal line segments is also one of the endpoints of the two line segments, it is determined whether the lengths of the two line segments are equal. If they are equal, it is identified as an angle steel structure; if they are not equal, it is identified as a channel steel structure. The structural recognition module performs corresponding steel structure three-dimensional model fitting and restoration at the basic section position according to different recognition results.

[0017] Preferably, the reverse restoration unit also includes a continuity monitoring module, which is electrically connected to the structure identification module and performs structural continuity monitoring while the structure identification module identifies the steel structure to perform three-dimensional model restoration, wherein the continuity monitoring module obtains the intersection positions of multiple sections and the structure, obtains the two maximum points, and then obtains the center line of the structure. When the center lines of two different spatial positions are obtained, the distance between the two center lines is calculated as d. If the d value is greater than the distance from the starting point to the center point of the structure, it is determined that the two sections of steel structures corresponding to the two center lines do not belong to the same steel structure. If the d value is less than the distance from the starting point to the center point of the structure, it is determined that the two center lines belong to the same steel structure.

[0018] Preferably, the reverse restoration unit also includes an instrument judgment module, which is electrically connected to the structure identification module and performs instrument judgment while the structure identification module performs three-dimensional model restoration, wherein the instrument judgment module searches for a point cloud structure that meets the parameters based on the instrument parameters pre-stored in the P&ID near the location where the pipe diameter changes suddenly, and when a matching result is generated, performs three-dimensional model restoration on this part of the instrument structure and assigns a value to this part based on the instrument type parameters pre-stored in the P&ID.

[0019] The present invention provides a digital three-dimensional reverse modeling method, comprising the following steps: a point cloud acquisition unit,

[0020] S1: The acquisition unit collects point cloud information containing spatial coordinate information about any point on the existing steel structure;

[0021] S2: After reading the point cloud information, it is restored into a three-dimensional model of the steel structure in a virtual three-dimensional restoration manner. While restoring the three-dimensional model of the steel structure, process attributes are assigned to the steel structure and instruments based on P&ID logic to obtain a three-dimensional model that at least includes P&ID attribute data.

[0022] Preferably, instrument judgment is performed while executing three-dimensional model restoration, wherein a point cloud structure that meets the parameters is searched based on the instrument parameters pre-stored in P&ID near the location where the pipe diameter suddenly changes. When a matching result is generated, three-dimensional model restoration of this part of the instrument structure is performed and assignment is performed on this part based on the instrument type parameters pre-stored in P&ID. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a structural schematic diagram of the system provided by the present invention;

[0024] Figure 2 It is a schematic diagram for identifying H-shaped steel structures;

[0025] Figure 3 It is a schematic diagram for identifying the channel steel structure;

[0026] Figure 4 It is a schematic diagram of angle steel structure identification;

[0027] Figure 5 This is a schematic diagram of the identification of the middle point of the H-beam;

[0028] Figure 6 This is a schematic diagram for identifying the middle point of the channel steel;

[0029] Figure 7 It is a schematic diagram of structural continuity identification;

[0030] Figure 8 It is a schematic diagram of point cloud repair recognition;

[0031] Fig. 9 It is a schematic diagram of instrument identification;

[0032] Reference numerals list

[0033] 100: point cloud acquisition unit; 200: reverse restoration unit; 210: denoising module; 220: structure recognition module; 230: continuity monitoring module; 240: missing recovery module; 250: instrument judgment module. DETAILED DESCRIPTION

[0034] The following is combined with Figure 1 Provide detailed explanation.

[0035] like Figure 1 As shown, the present invention provides a digital three-dimensional reverse modeling system, which is used for digital restoration of steel structures in existing factories.

[0036] It is used to reverse model existing pipelines in in-service plants and form a complete twin model. Based on 3D laser scanning technology, this solution uses abstract shapes, intelligent judgment, and matching resource libraries (grade libraries) to automatically identify and create object-oriented 3D models. At the same time, combined with intelligent P&ID, the 3D pipelines are automatically logically sorted and divided, and process attributes are given.

[0037] The device includes a point cloud acquisition unit 100, which is used to collect point cloud information of coordinate information of any or all points in space on the steel structure in the existing factory. In this embodiment, the steel structure is all types of components that constitute the steel support structure, which is usually used to constitute various steel support structures in the factory. The steel support structure is a component used to support other factory structures, such as steel supports for supporting high-level pipelines, supporting structures for large reactors and storage tanks, or structures such as rails and side panels. Preferably, the point cloud acquisition unit 100 selects a laser scanning method to obtain point cloud information about the steel structure. In this case, the point cloud acquisition unit 100 is selected as a laser scanning device. The laser scanner can calculate the spatial position coordinate information of the irradiated point by setting the laser emission positions emitted at different angles at the same time based on the time when the laser spot beam emitted by it is irradiated to the scanning target point and then returns to the laser receiver on the scanning device. The laser scanner can select a device such as the HandySCAN 3D series laser scanning device provided by CREAFORM, or the HOLON 771 laser scanning device provided by Hualang 3D.

[0038] In some embodiments, the staff responsible for scanning holds the point cloud acquisition unit 100 to perform mobile scanning in the factory to obtain a large amount of point cloud information about the existing steel structure, and saves or uploads this information to a point cloud storage library.

[0039] The system also includes a reverse restoration unit 200, which is used to restore the three-dimensional model of the steel structure using a large amount of point cloud information stored in the point cloud repository. The reverse restoration unit 200 is electrically connected to the point cloud repository to obtain point cloud information, and uses the point cloud information to perform the next step. The reverse restoration unit 200 includes a denoising module 210, which is electrically connected to the above-mentioned point cloud repository to first obtain point cloud information, and performs filtering and denoising operations on the point cloud information and then outputs it to the data downstream module. There are many ways to select filtering and denoising, such as binning denoising, voxel filtering, bilateral filtering, Gaussian filtering, etc. In this embodiment, a combination of custom point cloud density recognition denoising and manual frame selection denoising is selected for filtering and denoising. The two methods include the functions of automatic denoising and manual assisted denoising, and can achieve denoising effects that meet the expectations of personnel within a relatively fast denoising execution cycle, providing a good foundation for the subsequent processing of point cloud information, and can improve the quality and efficiency of subsequent processing.

[0040] In this embodiment, the processing unit can adapt to point cloud data of various formats obtained by scanning various types of scanning units. In addition to adapting to common general point cloud data formats such as .PTS and .E57, it can also read the point cloud formats (.FLS, .ZFS) and native point cloud project files (.IMP, .ISPROJ) generated by the mainstream three-dimensional scanning equipment on the market.

[0041] The reverse restoration unit 200 also includes a structure recognition module 220, which is electrically connected to the denoising module 210 to obtain a large amount of point cloud information after denoising, and performs a position-corresponding restoration operation on the point cloud information in the virtual three-dimensional space according to its embedded spatial coordinate information, to obtain a total model field about the distribution of the point cloud in space, wherein the restored point cloud information is expressed as a point model, or simply referred to as a point, in the total model field. In the total model field, based on the distribution of the point cloud, the position with the best point model density is automatically selected, sliced, and the basic cross-sectional data of the structure is obtained. The basic cross-sectional data is a cross-sectional figure formed by the point models restored from several determined point cloud information in a two-dimensional plane. For example, after a physical object with a cylindrical structure is scanned to form a point cloud, its points form a cylindrical shape in the virtual three-dimensional space, and when it is sliced, a circle formed by several point models is formed on the two-dimensional plane.

[0042] After acquiring the basic cross-sectional data, the structure recognition module 220 performs recognition and judgment of the steel structure type based on the image in the basic cross-sectional data. After correctly identifying the steel structure type, it performs fitting and restoration of the three-dimensional model of the sliced ​​part based on the identified type.

[0043] Common steel structures include channel steel, angle steel, and I-beam. The following introduces the identification methods of each steel structure.

[0044] like Figure 2 As shown, a recognition method for H steel is provided, and H steel is the above-mentioned I-beam. The starting and ending points of several orthogonal line segments are found in the basic section data, and the spatial coordinate information of the relevant points is obtained, wherein the selected orthogonal line segment can be a straight line segment that can encompass the most point models based on the least squares method. If there are at least three groups of starting and ending points, namely A(x1,y1,z1), B(x2,y2,z2), C(x3,y3,z3), D(x4,y4,z4), E(x5,y5,z5), F(x6,y6,z6), wherein AB forms a line segment, CD forms a line segment, and EF forms a line segment, the spatial expressions of the AB / CD / EF line segments are calculated respectively, and the following judgment is performed: if the line where EF is located perpendicularly bisects the line segments where AB and CD are located, and the AB vector and the CD vector are parallel and coplanar vectors, then the section where the A, B, C, and D point models are located is judged to be an H steel section.

[0045] like Figure 3 and 4 As shown, a recognition method for channel steel and angle steel is provided: the starting point and the ending point of several orthogonal line segments are found in the basic section data, and the spatial coordinate information of the relevant points is obtained. The method for finding the line segment is as described above. If there are at least two sets of starting point and ending point combinations, and the coordinates of the starting points are the same, the following judgment is further performed, the length of the line segment from the starting point to one of the ending points is calculated, and the length of the line segment from the starting point to the other ending point is calculated, and the two line segment length values ​​are compared. When they are not equal, the basic section is determined to be a channel steel section, and when they are equal, the basic section is determined to be an angle steel section. For example, the starting and ending points found are A (x1, y1, z1), B (x2, y2, z2), and C (x3, y3, z3), respectively, where point A is a common starting point, and B and C are two ending points with different coordinates. The point distances are calculated based on the coordinates of the above points, that is, the length values ​​of the above line segments, which are recorded as AB and AC. When AB≠AC, the section is determined to be a channel steel section, and when AB=AC, the section is determined to be an angle steel section.

[0046] While the structure is identified and the three-dimensional model is fitted and restored, the structural continuity monitoring is performed on the process of fitting and restoring the steel structure. The continuity monitoring is performed by the continuity monitoring module 230 set in the reverse restoration unit 200, which is electrically connected to the structure identification module 220, and monitors the structural continuity while the structure identification module 220 identifies and fits the three-dimensional simulation of the steel structure according to different slice sequences. Specifically, Figures 5 to 7As shown, the continuity monitoring module 230 obtains the intersection positions of multiple cross sections and structures, calculates the line distances of each intersection, and takes the maximum value of the line distances. There are two maximum values, namely Figure 5 and Figure 6 The two intersecting lines shown are the lines with the largest connection distance, which can be called the maximum line. The intersection of the two maximum lines is the center point of the steel structure. This calculation method is the same for I-beams and channel steels. For angle steels, such as Figure 7 As shown, it can only find one maximum line, and the midpoint of the line is the center point of the steel structure. Multiple center points are obtained based on multiple sections, and the multiple center points are connected to form a center line. When the center lines of two different spatial positions are obtained, a continuity judgment is performed. Specifically, the distance between the two center lines is calculated as d. If the d value is greater than half the length of the maximum line, it is determined that the two sections of steel structures corresponding to the two center lines do not belong to the same steel structure. If the d value is less than half the length of the maximum line, it is determined that the two center lines belong to the same steel structure. When performing fitting, the two sections of steel structures that are determined not to belong to the same steel structure are misaligned in the virtual space, and the two sections of steel structures that are determined to belong to the same steel structure are translated to make the center lines of the two sections of steel structures coincide.

[0047] While the structure is identified and the three-dimensional model is fitted and restored, the missing structure point cloud data is recovered during the steel structure fitting and restoration process. Missing recovery is performed by a missing recovery module 240 provided in the reverse restoration unit 200, which is electrically connected to the structure identification module 220, and while the structure identification module 220 identifies and fits the three-dimensional simulation of the steel structure according to different slicing sequences, the missing structure point cloud data is recovered. This module is mainly aimed at the situation where the acquisition angle is insufficient and some point cloud information is missing when performing three-dimensional scanning on the existing steel structure in the early stage. In this case, the structure identification module 220 may not be able to accurately determine the type of steel structure. Therefore, when recovering the structural data, it is necessary to find the structural features. For example, for an I-beam structure, such as Figure 8 As shown, during the initial scanning, the point cloud information of the structural points ABDEF was obtained, but due to the limited scanning angle and other reasons, the point cloud information of the structural point C was not obtained, resulting in an error in the structural recognition module 220 when identifying the section of the slice. At this time, based on the generated error information, the missing recovery module 240 takes over the identification and restoration of the pipeline of this part. It tracks and identifies the part as an H steel section by judging the point cloud features of the model section, EF is perpendicular to AB, and the FD vector is collinear with the AB vector, and performs the three-dimensional model fitting restoration of this part.

[0048] While identifying the structure and performing three-dimensional model fitting and restoration, instrument judgment is performed on the process of fitting and restoration of the steel structure. The instrument judgment is performed by the instrument judgment module 250 set in the reverse restoration unit 200, which is electrically connected to the structure recognition module 220, and judges the instrument while the structure recognition module 220 recognizes and fits the three-dimensional simulation of the steel structure according to different slicing orders. This module is mainly aimed at configuration structures such as instruments on pipelines. Generally speaking, changes or mutations in the pipe diameter will occur at the locations where instruments are set. Therefore, while the reverse restoration module performs reverse simulation restoration of the pipeline, the instrument judgment module 250 synchronously performs identification and reverse restoration of the pipeline instrument based on the pipe diameter mutation and the point cloud features near the mutation point. Fig. 9 As shown, specifically, based on the calculation of the point cloud model around the pipe slice, the distance from a known coordinate point of the cross section to the center line or center point can be further calculated on the basis of the calculated center point or center line of the pipe. In the case where the pipe is cylindrical by default, the distance represents the radius of the pipe. When performing reverse restoration on different slices, the radius calculated for one or several slices may be greater than the radius of other slices. In this case, the instrument judgment module 250 further searches for a point cloud set with a cylindrical structure near the section, assuming that the instrument radius is D and the height is H. If at least one cylinder with a radius that meets D and a height that meets H is found in a nearby position, it can be considered that there is an instrument at that location.

[0049] Preferably, the point cloud of the sudden change in radius often does not appear in only one slice, but in a fairly long section of the pipeline, the radius will appear larger than the rest. In the above case, in the process of performing the reverse restoration of the pipeline, the instrument judgment module 250 uses the first slice position where the radius starts to suddenly change in the sequence as the starting position of the sudden change in the diameter, and uses the slice position recorded with a larger radius attribute before the sudden change in the sequence as the ending position of the sudden change in the diameter, and uses the starting position and the ending position of the sudden change in the diameter as the mark of dividing the pipe segment to identify the pipe segment with a larger diameter, and performs the task of finding a cylindrical instrument structure at the position of the pipe segment and its vicinity. For example, on the same pipeline centerline, two radii appear, denoted as r2 and r1. If r2>r1 and r2=r3, r4=r1, where the position of r2 corresponds to the starting position of the sudden change in the diameter, and the position of r3 corresponds to the ending position of the sudden change in the diameter, it can be regarded as that there is a pipe fitting in the interval between r2 and r3. The instrument judgment module 250 then searches for a cylinder near the midpoint between r2 and r3, and when a cylinder with a radius of D and a height of H is found, it is considered that there is an instrument there. The instrument judgment module 250 simulates and restores the instrument pipe fitting there, and at the same time, determines the instrument type and parameters here based on the intelligent P&ID, and then assigns values.

[0050] Preferably, when the reverse reduction unit 200 performs reverse reduction of the steel structure, the following steps are adopted:

[0051] S11: Selecting a device number based on the restoration work plan;

[0052] S12: Index to the corresponding P&ID segment according to the equipment number;

[0053] S13: Reconstruct the 3D steel structure model based on P&ID logical relationships;

[0054] S14: Attach P&ID attributes to the restored 3D piping model and match the corresponding grade component library.

[0055] "Selecting equipment numbers based on the restoration work plan" means that in a project for point cloud restoration of an existing structure, the project is divided into phased tasks for steel structures that can be between two devices according to a pre-set plan. Based on the plan, the engineering staff selects two devices with known equipment numbers to carry out the subsequent point cloud model reverse construction work. Among them, the equipment number is an attribute value corresponding to the equipment in P&ID, which is basically used to identify the identity of the equipment in P&ID.

[0056] "Indexing to the corresponding P&ID segment based on the equipment number" means searching for all P&ID data between the two equipment numbers in the P&ID data based on the equipment number. P&ID is a pre-set data set or relational database that records at least P&ID logical relationships and P&ID attributes, wherein P&ID logical relationships refer to relationship records that record the superior-subordinate relationships, connection relationships, etc. between steel structures and branches, steel structures and connectors, and steel structures and equipment, and P&ID attributes refer to pre-entered attribute information of steel structures, equipment, valves and other components, such as the size of the equipment, the wall thickness of the steel structure, and other information. The data in P&ID is generally manually pre-entered data, or P&ID data that already exists before the reverse construction process of this solution is executed.

[0057] "Reconstructing the three-dimensional steel structure model based on the P&ID logical relationship" means that after obtaining the P&ID data between the two assigned devices, when executing the reverse construction of the pipeline restoration model based on the point cloud data, the topological relationship is retrieved and the point cloud model is assigned in the order of equipment-steel structure-branch steel structure-connectors-valves and instruments in the P&ID data segment, so that the component models between the two devices (at least including steel structure, branch steel structure, connectors, valves and instruments, etc.) can be automatically assigned.

[0058] "Attaching P&ID attributes to the restored 3D piping model and matching the corresponding grade component library" means that each P&ID attribute stored in the P&ID is assigned to the corresponding component model during the assignment process, wherein some P&ID attribute assignments are used to build the corresponding component object model. The above-mentioned part of the P&ID attributes are at least attributes related to the structural dimensions, such as size, thickness, etc. These parameters can be intuitively reflected in the model and can assist in the construction of the model, realizing the reverse model construction of the two-way mutual verification of the point cloud and P&ID attributes.

[0059] Combining P&ID logic and the pre-stored component library of the control node to assist the three-dimensional restoration modeling of the steel structure of the existing factory, for the control node, not only can the restored three-dimensional model be obtained, but also the attribute information about the control node in the P&ID can be generated. In this way, the control logic of the P&ID attribute can be directly superimposed on the three-dimensional pipeline model restored with high precision. By directly observing the three-dimensional steel structure model with sufficient details, the engineering personnel can obtain the direction, attributes, location, use and other information of all the steel structures in the entire factory, and based on the additional control logic, by directly clicking on the control node model, it can directly connect to the control loop of the control node entity, which is convenient for the engineering personnel to observe the impact of evaluation and control, and at the same time gives them the ability to control any equipment in the factory directly from the control center. The originally scattered and complex steel structure control in the old factory can be concentrated on the logic control system of the additional steel structure and additional control items based on the restored three-dimensional model, realizing the centralization of management control, which can greatly improve the production efficiency of the old factory. At the same time, some pre-stored parameters in P&ID can realize data visualization in the process of assisting the reverse construction of the 3D model. For example, the steel structure size, length, width, plate thickness and other parameters pre-stored in P&ID are often not obvious and non-intuitive when only provided in a list. However, when these parameters are executed based on the 3D reverse restoration project indexed to P&ID to generate a 3D model of the existing structure, the attribute data in P&ID can be used to supplement the shape of the reverse 3D model restored by the point cloud. This supplement is not only the attribute that the point cloud data can "see", but also the attribute that the point cloud data cannot "see", such as plate thickness and some back structures. The point cloud restored model provides guidance for indexing P&ID, and P&ID provides auxiliary acceleration for the reverse model construction of the point cloud, and can obtain a more accurate and comprehensive reverse construction model at the same time. The numerical attributes in P&ID can be intuitively converted into visual attributes.The above scheme not only realizes the point-to-point mapping of the control logic parameters in the P&ID while constructing the reverse 3D model of the existing steel structure, but also organically combines the P&ID image that was originally relatively abstract and basically does not contain spatial position information and structural information into a three-dimensional, intuitive, easy-to-observe, and structurally accurate three-dimensional reverse composite model. On the one hand, some of the retained model structure-related parameters in the P&ID can provide the effect of missing item correction for the three-dimensional reverse modeling link. On the other hand, the obtained three-dimensional modeling of the steel structure can be directly used in the pipeline control management of the factory, and can achieve all the effects of P&ID control. At the same time, based on the advantages of three-dimensional modeling, it can also obtain effects higher than P&ID control. First, the original two-dimensional P&ID control logic is upgraded to three-dimensional, so that some complex control logic that originally needed to be displayed in a hierarchical manner can be directly displayed in three-dimensional space. It can display the parameters in multiple levels quickly and intuitively, so that engineers can quickly and intuitively control the parameters in multiple levels. Secondly, it can display the structural parameters in the control logic more intuitively, so that engineers can directly confirm the structural relationship and size parameters between the components in the three-dimensional structure, especially the extrusion and contact between the components, which provides a very intuitive criterion for the factory's safe production and structural optimization. Finally, it can also provide P&ID control with a pre-simulated visual feedback function based on simulation technology. Based on pre-set rules, the control link selected by the engineer and the adjusted control parameters are used as trigger parameters. It can output an intuitive result view to the engineer in the form of simulated superimposed animation in the three-dimensional pipeline model, which can assist the engineer in knowing whether the control can achieve the expected effect, whether there are any unexpected situations, etc., and effectively improve the efficiency and safety of the control.

[0060] It should be noted that the above-mentioned specific embodiments are exemplary, and those skilled in the art can come up with various solutions inspired by the disclosure of the present invention, and these solutions also belong to the disclosure scope of the present invention and fall within the protection scope of the present invention. Those skilled in the art should understand that the present invention specification and its drawings are illustrative and do not constitute a limitation on the claims. The scope of protection of the present invention is defined by the claims and their equivalents. The present invention specification contains multiple inventive concepts, such as "preferably" and "according to a preferred embodiment", which means that the corresponding paragraph discloses an independent concept, and the applicant reserves the right to file a divisional application based on each inventive concept.

Claims

1. A digital restoration device for a steel structure used for digital twin construction, comprising a structure recognition module (220), characterized in that: The structure recognition module (220) is configured to: The point cloud information of the steel structure is restored based on position correspondence in the virtual three-dimensional space according to the embedded spatial coordinate information thereof, so as to obtain a total model field of the point cloud distribution in the space, wherein the restored point cloud information is expressed as a point model in the total model field; Automatically select the location with the best point model density based on the distribution of the point cloud and slice it to obtain the basic cross-sectional data of the structure; The steel structure type is identified and judged based on the image in the basic cross-section data. After the steel structure type is correctly identified, the three-dimensional model fitting and restoration of the slice is performed based on the identified steel structure type.

2. The steel structure digital restoration device for digital twin construction according to claim 1 is characterized in that: The device also includes a continuity monitoring module (230) connected to the structure recognition module (220) for monitoring the continuity of the structure while the structure recognition module (220) recognizes and fits the three-dimensional simulation of the steel structure according to different slice sequences.

3. The steel structure digital restoration device for digital twin construction according to claim 2 is characterized in that: The continuity monitoring module (230) obtains the intersection positions of multiple cross sections and the structure, calculates the connection distance of each intersection, takes two maximum lines of the connection distance, and the intersection point of the two maximum lines is the center point of the steel structure; When the center lines of two different spatial positions are obtained, a continuity check is performed.

4. The steel structure digital restoration device for digital twin construction according to claim 3 is characterized in that: The continuity monitoring module (230) performs continuity judgment in the following manner: Calculate the distance between the two center lines as d, If the d value is greater than the distance from the starting point to the center point of the structure, it is determined that the two sections of steel structures corresponding to the two center lines do not belong to the same steel structure; If the d value is less than the distance from the starting point to the center point of the structure, it is determined that the two center lines belong to the same steel structure.

5. The digital restoration device for steel structure used for digital twin construction according to any one of claims 1 to 4, characterized in that: The device also includes a missing recovery module (240) connected to the structure recognition module (220) for recovering missing structure point cloud data while the structure recognition module (220) recognizes and fits the three-dimensional simulation of the steel structure according to different slice sequences.

6. The steel structure digital restoration device for digital twin construction according to claim 5 is characterized in that: In the event that an error occurs when the structure recognition module (220) recognizes a slice section, the missing recovery module (240) determines the cross-sectional point cloud features of the point model based on the generated error information, tracks and recognizes the steel structure type of the slice section, and performs three-dimensional model fitting and restoration of the slice.

7. The digital restoration device for steel structure used for digital twin construction according to any one of claims 1 to 6, characterized in that: It also includes an instrument determination module (250) connected to the structure identification module (220), While the structure recognition module (220) recognizes the steel structure and performs three-dimensional model fitting and restoration, the instrument judgment module (250) performs instrument judgment on the process of steel structure fitting and restoration; Wherein, while the structure recognition module (220) recognizes and fits the three-dimensional simulation of the steel structure according to different slice sequences, the instrument judgment module (250) judges the instrument; and / or The instrument judgment module (250) synchronously performs identification and reverse restoration of pipeline instruments based on the sudden change in pipe diameter and point cloud features near the sudden change point.

8. The steel structure digital restoration device for digital twin construction according to claim 7, characterized in that: In the process of executing pipeline reverse restoration, the instrument judgment module (250) uses the first slice position where the radius begins to suddenly change in the time sequence as the starting position of the pipe diameter sudden change, uses the slice position recorded with a larger radius attribute before the radius suddenly changes back to the original smaller radius in the time sequence as the ending position of the pipe diameter sudden change, uses the starting position and the ending position of the pipe diameter sudden change as marks for dividing pipe sections to identify the pipe section with a larger pipe diameter, and performs the task of searching for a cylindrical instrument structure at the pipe section position and its vicinity; When it is determined that an instrument exists, the instrument determination module (250) simulates and restores the instrument pipe fittings at the location where the instrument exists, determines the instrument type and parameters based on the intelligent P&ID, and then assigns values.

9. A steel structure digital restoration method for digital twin construction, characterized in that: The method comprises: performing a position-corresponding restoration operation on the acquired point cloud information of the steel structure in a virtual three-dimensional space according to the embedded spatial coordinate information thereof, obtaining a total model field of the point cloud distribution in space, wherein the restored point cloud information is expressed as a point model in the total model field; Automatically select the location with the best point model density based on the distribution of the point cloud and slice it to obtain the basic cross-sectional data of the structure; The steel structure type is identified and judged based on the image in the basic cross-section data. After the steel structure type is correctly identified, the three-dimensional model fitting and restoration of the slice is performed based on the identified steel structure type.

10. The steel structure digital restoration method for digital twin construction according to claim 9, characterized in that: The method further comprises: Obtain the intersection positions of multiple sections and structures, calculate the line distance of each intersection, take the two lines with the largest line distance, and the intersection point of the two largest lines is the center point of the steel structure; When the center lines of two different spatial positions are obtained, the distance between the two center lines is calculated as d; If the d value is greater than the distance from the starting point to the center point of the structure, it is determined that the two sections of steel structures corresponding to the two center lines do not belong to the same steel structure; If the d value is less than the distance from the starting point to the center point of the structure, it is determined that the two center lines belong to the same steel structure.

Images