A steel structure digital restoration device and method for digital twin construction

Abstract

A steel structure digital restoration device and method for digital twin construction, the device comprises a structure recognition module, the structure recognition module is configured to: the point cloud information of the acquired steel structure is executed in a virtual three-dimensional space according to its embedded space coordinate information based on the corresponding restoration operation of position, the total model field about the distribution of point cloud in space is acquired, and the restored point cloud information is in the form of a point model in the total model field;Based on the distribution of point cloud, the position with the best point model density is automatically selected, slicing is carried out to obtain the basic cross-section data of the structure;Based on the image in the basic cross-section data, the identification and judgment of the type of steel structure are executed, after correctly identifying the type of steel structure, the three-dimensional model fitting restoration of slicing is executed based on the identified type of steel structure.The present application can directly restore the three-dimensional pipeline model with high precision, and the engineering personnel can obtain the information of all steel structures in the whole factory by directly observing the three-dimensional steel structure model with sufficient rich details.

Description

[0001] The original basis of the divisional application is a patent application with the application number (202210308895.X), the application date of 2022.03.25, and the invention name of "a digital three-dimensional reverse modeling method and system". TECHNICAL FIELD

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

[0003] With the advancement of industrial progress, considering environmental protection, low carbon and other factors, the new construction projects of petroleum and chemical industry, power industry and other industries gradually slow down, and the maintenance and life extension of in-service plants become particularly important. How to use some digital technology to digitize and structure the stock assets to improve enterprise productivity, improve safety protection and reduce risks has become a concern. However, due to the complex information of oil, chemical and power process plants, the large number of pipelines, frequent maintenance and modification and other factors, the plants running for ten years or more produce a large amount of online and offline data, and the drawings, models and actual site conditions are often inconsistent. Technical personnel cannot accurately grasp the site conditions through data, which causes great difficulty in overhaul and technical transformation. Therefore, based on the actual situation of the plant area, digital twin construction of all process equipment pipelines and structures has become a key and difficult work for in-service plants.

[0004] Three-dimensional reverse modeling of the structure of the existing plant is a key work. The existing plant has been constructed for a long time, and the original engineering files and drawings may be missing. At the same time, during the long operation of the plant, small and large equipment and structure modifications are often made, resulting in inconsistencies between the existing plant structure and the original drawings. At present, with the rapid development of digital plant technology, the existing plant also needs to be transformed and upgraded to a digital and automated plant, which involves the three-dimensional reverse modeling of the existing structure in the plant. One of the main purposes of three-dimensional reverse modeling is to copy the specific structure in the existing plant into a three-dimensional model in a one-to-one manner of spatial position and structure shape.

[0005] In the prior art, the reverse modeling of the existing steel structure usually has high manual involvement, and the manual needs to filter out the point cloud model about the steel structure from a large amount of point cloud data, and then takes the point cloud model as a draft to construct a complete three-dimensional model about the steel structure in a manual re-modeling manner at the same position. In short, the prior art is to model the point cloud model in a copying manner on the basis of manual structure identification to finally obtain a three-dimensional model of the steel structure. This undoubtedly increases the labor cost of manual work, lengthens the cycle of reverse engineering, and causes time-consuming and laborious reverse engineering. At the same time, the obtained three-dimensional modeling is difficult to be used for subsequent actual work, because the current obtained three-dimensional modeling only has good restoration in structure and spatial position, but this can only provide an external reference for the engineer, and the specific parameters of the steel structure, the control logic of other components and the like are not exhibited, so the control parameters of the steel structure need to be manually bound while performing the three-dimensional reverse restoration of the steel structure, which further increases the workload.

[0006] The digital twin construction of the steel structure is one of the projects of the digital backup engineering of the in-service structure of the whole factory, and since the steel structure is complex and involves the mutual relationship with the pipeline, the scanning of the structure is not only concerned with the backup of the physical structure, but also the role and function of the attribute of the pipeline, which are also one of the targets of attribute backup.

[0007] In addition, on the one hand, there are differences in the understanding of those skilled in the art, and on the other hand, a large number of literatures and patents have been studied by the applicant when making the present application, but all the details and contents have not been listed in detail due to the limitation of the page, which is by no means that the present application does not have the characteristics of the prior art, on the contrary, the present application has all the characteristics of the prior art, and the applicant reserves the right to add relevant prior art in the background art. SUMMARY

[0008] In view of the deficiencies of the prior art, the present application provides a digital three-dimensional reverse modeling system for the digital twin construction of the existing steel structure, which comprises a point cloud acquisition unit, the point cloud acquisition unit collects point cloud information containing spatial coordinate information about any point on the existing steel structure, and stores it in a point cloud storage, which further comprises a reverse restoration unit electrically connected to the point cloud storage to read the point cloud information collected by the point cloud acquisition unit and restore it to a three-dimensional model of the steel structure in a virtual three-dimensional restoration manner, and at the same time of performing the three-dimensional model restoration of the steel structure, based on the P&ID logic, the process attribute of the steel structure and the instrument is valued to obtain a three-dimensional model including at least P&ID attribute data.

[0009] The advantage is that the identification and modeling of the existing steel structure are improved automatically. Based on the automatic steel structure identification, continuous monitoring and missing structure restoration steps in the present scheme, a three-dimensional reverse restoration model can be automatically generated based on point cloud information without manual modeling process. Compared with the prior art, the efficiency of three-dimensional reverse modeling is greatly improved, and the labor cost is significantly reduced. After obtaining the steel structure, the steel structure is segmented according to the specific position and structure, and saved as unit element data, or corrected and modified. Due to the automatic generation of the steel structure three-dimensional model, the subsequent manual process becomes relatively simple, and the manual labor is effectively reduced.

[0010] In addition, the construction of related structure attributes and data topology in the steel structure three-dimensional restoration process can be assisted based on P&ID logic, so that the related three-dimensional pipeline restoration construction speed is substantially accelerated under the condition of a limited number of element matches, and the pipeline logic can be directly established on the three-dimensional model based on the structure attributes given by P&ID, so that when the reverse three-dimensional model generated by the system or the method is obtained, the engineer can not only intuitively and accurately observe the three-dimensional space model image of the related structure to perform maintenance point selection, pipeline analysis, new facility installation point planning and other work, but also can directly observe the pipeline logic displayed in the form of several model associated control points from the model. These pipeline logics show the pipeline attributes (such as valve model, parameter, instrument model, parameter, etc.) to the engineer, so that he can better complete the above tasks, and can access the control unit for each model associated control point, so that the engineer can directly control the control link corresponding to the model in the entity by selecting the related control point model marked by the pipeline logic on the three-dimensional model of the reverse restoration, such as controlling the on-off operation of the valve, so that the factory control is changed from the original scattered control and on-site control to the central control realized by the terminal system, the original old equipment in the factory can be effectively integrated, the production control of the whole factory is unified, and the factory control efficiency and effect are significantly improved.

[0011] By automatic identification of the pipeline structure and automatic assignment of the control parameters, the scheme actually obtains a three-dimensional reverse model with complete control logic parameters, accurate structure and intuitive and clear view structure. The two-dimensional P&ID graph is transformed into a three-dimensional view combined with the three-dimensional spatial structure, so that the engineering personnel can directly use the three-dimensional reverse model to perform control-related work on the related equipment of the factory, such as parameter inquiry, monitoring, control and other operations. Compared with the nested two-dimensional P&ID graph, the three-dimensional model can provide multiple structure position accurate different level control points for the engineering personnel at the same time, so that the control efficiency is further improved. At the same time, in the process of performing three-dimensional reverse modeling, the structure parameters in the P&ID can be used reversely to accelerate the construction of three-dimensional reverse modeling. Based on the correspondence between part or all of the feature models in the three-dimensional construction and the P&ID graph, the remaining incomplete part in the three-dimensional construction process can be completed by using the corresponding parameters provided by the P&ID to assist the three-dimensional modeling. The above feature models are some artificially set special shapes used to represent some structures, such as the I-shaped appearance of steel structure and the disc appearance of valve structure. After these feature models are identified or preferentially identified, it is known that the component exists at this position, but the specific structure parameters of the component can still remain unknown or partially unknown. By the connection relationship of the component and the remaining components, the part with the same connection relationship in the P&ID image is compared and queried to confirm the correspondence between the P&ID graph and the three-dimensional model, and the structure parameters in the P&ID graph are used to restore the above unknown three-dimensional structure. At this time, it is not necessary to perform the steps of point cloud shape identification and three-dimensional restoration. The above process actually realizes the mutual organic combination of P&ID image and three-dimensional structure restoration. The three-dimensional reverse model provides more intuitive visual display upgrade for the P&ID image with weak structure, and the P&ID with complete parameters provides an auxiliary acceleration process for the construction of the three-dimensional reverse model.

[0012] Preferably, the point cloud acquisition unit is configured as a three-dimensional scanner which performs scanning of 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 reconstruction step of the steel structure three-dimensional model.

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

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

[0015] Preferably, when a plurality of orthogonal line segments are found in the basic cross-section, and one of the line segments is perpendicular to the other two parallel and coplanar line segments, the structure exhibited by the basic cross-section is determined as an H steel structure, and the fitting reduction of the H steel three-dimensional model is performed on the basic cross-section.

[0016] Preferably, when a plurality of orthogonal line segments are found in the basic cross-section, and the intersection points of the two mutually orthogonal line segments are both endpoints of the two line segments, it is determined whether the lengths of the two line segments are equal, if equal, it is identified as an angle steel structure, if not equal, it is identified as a channel steel structure, and the structure identification module performs the corresponding steel structure three-dimensional model fitting reduction at the basic cross-section position according to different identification results.

[0017] Preferably, the reverse reduction unit further comprises a continuity monitoring module, which is electrically connected to the structure identification module and performs structure continuity monitoring while the structure identification module identifies the steel structure to perform three-dimensional model reduction, wherein the continuity monitoring module obtains the intersection positions of a plurality of cross-sections and the structure, obtains the maximum value two 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 value of d is greater than the distance from the starting point of the structure to the center point, it is determined that the two segments of steel structure corresponding to the two center lines do not belong to the same steel structure, if the value of d is less than the distance from the starting point of the structure to the center point, it is determined that the two center lines belong to the same steel structure.

[0018] Preferably, the reverse reduction unit further comprises 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 reduction, wherein the instrument judgment module finds the point cloud structure that meets the parameters based on the pre-stored instrument parameters of P&ID near the position where the pipe diameter changes suddenly, when the matching search result is found, the three-dimensional model reduction of the instrument structure in this part is performed and the instrument type parameters pre-stored in P&ID are assigned to this part.

[0019] The present application provides a digital three-dimensional reverse modeling method, comprising the following steps, comprising 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 to a three-dimensional model of the steel structure in a virtual three-dimensional restoration manner, and at the same time of performing the restoration of the three-dimensional model of the steel structure, based on P&ID logic, the process attributes of the steel structure and the instrument are assigned to obtain a three-dimensional model including at least P&ID attribute data.

[0022] Preferably, the instrument judgment is performed at the same time of performing the three-dimensional model restoration, wherein the point cloud structure meeting the parameters is found based on the P&ID pre-stored instrument parameters near the position where the pipe diameter suddenly changes, when the matching search result is found, the three-dimensional model restoration of the instrument structure is performed and the assignment is performed based on the P&ID pre-stored instrument type parameters. BRIEF DESCRIPTION OF DRAWINGS

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

[0024] Figure 2 is a H-shaped steel structure identification schematic diagram;

[0025] Figure 3 is a channel steel structure identification schematic diagram;

[0026] Figure 4 is an angle steel structure identification schematic diagram;

[0027] Figure 5 is a H-shaped steel intermediate point identification schematic diagram;

[0028] Figure 6 is a channel steel intermediate point identification schematic diagram;

[0029] Figure 7 is a structure continuity identification schematic diagram;

[0030] Figure 8 is a point cloud repair identification schematic diagram;

[0031] Figure 9 is an instrument identification schematic diagram;

[0032] LIST OF REFERENCE NUMERALS

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

[0034] The present application will be described in detail below with reference to the accompanying drawings. Figure 1 The present application will be described in detail below with reference to the accompanying drawings.

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

[0036] It is used for reverse modeling of existing pipelines in in-service factories and forming a complete twin model. This scheme is based on three-dimensional laser scanning technology, using abstract shape, intelligent judgment, and matching resource library (level library) to automatically identify and create object-oriented three-dimensional models. At the same time, combined with intelligent P&ID, the three-dimensional pipeline is automatically logically combed 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 the coordinates of any or all points on the steel structure in the existing factory in space. In this embodiment, the steel structure is all component types that make up the steel support structure, which is usually used to constitute various steel support structures in the factory. The steel support structure is a component for supporting other factory structures, such as steel supports for supporting high-position pipelines, support structures for supporting large reaction kettles and storage tanks, or structures such as tracks and side plates. Preferably, the point cloud acquisition unit 100 selects a laser scanning method to acquire 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 based on the time of the laser beam emitted by it irradiating on the scanning target point and then returning to the laser receiver on the scanning device. By setting different angle laser emission positions at the same time, the phase difference can be calculated. The laser scanner can select, for example, HandySCAN 3D series laser scanning devices provided by CREAFORM, or HOLON 771 laser scanning devices provided by Hualang Three-Dimensional.

[0038] In some embodiments, the staff responsible for scanning hand-held point cloud acquisition unit 100 in the factory for mobile scanning to obtain a large amount of point cloud information about the existing steel structure, and save or upload these information into the point cloud storage.

[0039] The system further comprises a reverse restoration unit 200, which is configured to restore the three-dimensional model of the steel structure by using the point cloud information stored in the point cloud repository. The reverse restoration unit 200 is electrically connected to the point cloud repository to obtain the point cloud information and use the point cloud information to perform the next operation. The reverse restoration unit 200 comprises a denoising module 210, which is electrically connected to the point cloud repository to obtain the point cloud information first, and outputs the point cloud information to the downstream module after performing the filtering denoising operation. The filtering denoising can be selected in multiple ways, such as selecting binning denoising, voxel filtering, bilateral filtering, Gaussian filtering, etc. In the embodiment, the filtering denoising is performed by combining the self-defined point cloud density recognition denoising and the manual frame selection denoising. The two methods include automatic denoising and manual assisted denoising, which can achieve the denoising effect meeting the expectation of the personnel in a relatively fast denoising execution period, and provide a good basis for the subsequent processing of the point cloud information, thereby improving the quality and efficiency of the subsequent processing.

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

[0041] The reverse restoration unit 200 further comprises a structure recognition module 220, which is electrically connected to the denoising module 210 to obtain the denoised point cloud information, and performs a restoration operation based on the position in the virtual three-dimensional space according to the spatial coordinate information embedded in the point cloud information, to obtain a total model field about the distribution of the point cloud in the space, wherein the restored point cloud information in the total model field is in the form of a point model, or simply referred to as a point. In the total model field, based on the distribution of the point cloud, the position with the best point model density is automatically selected, and the structure is sliced to obtain basic cross-section data. The basic cross-section data is a cross-section figure formed by a plurality of point models restored from the point cloud information in a two-dimensional plane. For example, after a cylindrical structure is scanned to form a point cloud, the points in the virtual three-dimensional space form a shape surrounding a cylinder, and the slice is performed to form a circle surrounded by a plurality of point models in a two-dimensional plane.

[0042] After obtaining the basic cross-section data, the structure recognition module 220 performs the identification and judgment of the type of the steel structure based on the image in the basic cross-section data, and after correctly identifying the type of the steel structure, performs the three-dimensional model fitting restoration of the slice part based on the identified type.

[0043] Common steel structures are channel steel, angle steel and I-beam. The identification method of each steel structure is introduced below.

[0044] As shown in Figure 2 , the identification method for H steel, i.e. the I-beam, is provided. The starting and ending points of several orthogonal line segments are found in the basic cross-section data, and the spatial coordinate information of the related points is obtained, wherein the selected orthogonal line segment can be a straight line segment that can include the most point model based on the least square method. If there are at least three groups of starting and ending points, i.e. 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 straight line where EF is located is perpendicular to the line segments where AB and CD are located respectively, and the AB vector and the CD vector are parallel and coplanar vectors, it is judged that the cross-section where the point model of A, B, C, and D is located is an H steel cross-section.

[0045] As shown in Figure 3 and 4 , the identification method for channel steel and angle steel is provided: the starting points and ending points of several orthogonal line segments are found in the basic cross-section data, and the spatial coordinate information of the related points is obtained. The way of finding the line segment is as described above. If there are at least two groups of starting point and ending point combinations, and the coordinates of the starting points are the same, the following determination is further performed: the length of the line segment from the starting point to one of the ending points is calculated, the length of the line segment from the starting point to the other ending point is calculated, and the numerical values of the two line segment lengths are compared. When the numerical values are not equal, it is determined that the basic cross-section is a channel steel cross-section, and when the numerical values are equal, it is determined that the basic cross-section is an angle steel cross-section. For example, the found starting and ending points are A(x1, y1, z1), B(x2, y2, z2), C(x3, y3, z3), wherein point A is a common starting point, and points B and C are two coordinate different ending points. The point distance based on the coordinates of the above points is calculated, i.e. the numerical value of the above line segment length, which is denoted as AB and AC. When AB≠AC, it is determined that the cross-section is a channel steel cross-section, and when AB=AC, it is determined that the cross-section is an angle steel cross-section.

[0046] While the structure is identified and the three-dimensional model fitting and reduction are performed, the structure continuity monitoring is performed on the process of fitting and reduction of the steel structure. The continuity monitoring is performed by the continuity monitoring module 230 provided in the reverse reduction unit 200, which is electrically connected to the structure identification module 220 and monitors the structure continuity while the structure identification module 220 identifies and fits the three-dimensional simulation of the steel structure in different slice orders. Specifically, as shown in Figures 5 to 7As shown, the continuity monitoring module 230 obtains the intersection positions of the plurality of cross sections and the structure, calculates the connecting distances of each intersection, takes the maximum value of the connecting distances, and this maximum value has two, that is, as shown in the figure Figure 5 and Figure 6 The two lines intersected as shown are the lines with the maximum connecting distance, which can be called maximum lines, and 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, as shown in Figure 7 , only one maximum line can be found, and the midpoint of the line is the center point of the steel structure. Based on the plurality of cross sections, a plurality of center points are obtained, and the plurality of center points are connected to form a center line. When two center lines at different spatial positions are obtained, continuity judgment is performed. Specifically, the distance between the two center lines is calculated as d. If the value of d is greater than half the length of the maximum line, it is determined that the two steel structures corresponding to the two center lines do not belong to the same steel structure. If the value of d 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 fitting is performed, the two steel structures determined not to belong to the same steel structure are fitted in a virtual space, and the two steel structures determined to belong to the same steel structure are made to coincide by translation.

[0047] While the structure is identified and the three-dimensional model fitting and restoration are performed, the structure point cloud data loss recovery is performed on the process of fitting and restoring the steel structure. The loss recovery is performed by the loss recovery module 240 arranged in the reverse restoration unit 200, which is electrically connected to the structure identification module 220 and recovers the structure point cloud data loss while the structure identification module 220 identifies and fits the steel structure three-dimensional simulation according to different slice orders. This module mainly aims at the situation that the collection angle is insufficient and part of the point cloud information is missing when the existing steel structure is scanned in the early stage. In this case, the structure identification module 220 may not be able to accurately determine the type of the steel structure. Therefore, when restoring the structure data, the structure characteristics need to be found. For example, for an I-beam structure, as shown in Figure 8 , the point cloud information of the structure points ABDEF is obtained during the early scanning, but due to limited scanning angle and other reasons, the point cloud information of the structure point C is not obtained, resulting in an error in identifying the cross section of this part by the structure identification module 220. At this time, based on the generated error information, the loss recovery module 240 takes over the pipe identification and restoration of this part, which identifies this part as an H steel section by judging the cross section point cloud characteristics of the model, EF is perpendicular to AB, and the FD vector is collinear with the AB vector, and performs three-dimensional model fitting and restoration of this part.

[0048] Instruments are judged during the process of fitting and restoring the steel structure based on the structure recognition and the three-dimensional model fitting and restoring. The instrument judgment is performed by the instrument judgment module 250 arranged in the reverse restoration unit 200, which is electrically connected to the structure recognition module 220 and judges the instruments while the structure recognition module 220 recognizes and fits the three-dimensional simulation of the steel structure in different slice orders. The module is mainly aimed at the instrument configuration structure on the pipeline. Generally, a change or mutation in the pipe diameter will occur at the position where the instrument is arranged. Therefore, while the reverse simulation and restoration of the pipeline are performed by the reverse restoration module, the instrument judgment module 250 synchronously performs the recognition and reverse restoration of the pipeline instrument based on the pipe diameter mutation and the point cloud characteristics near the mutation point position. As shown in Figure 9 the distance between the known coordinate point of the section and the center line or center point can be further calculated based on the calculation of the point cloud model around the pipeline slice. In the case where the pipeline is a cylinder by default, the distance represents the radius of the pipeline. When the reverse restoration is performed for different slices, the radius calculated by some or several slices may be greater than that of other slices. In this case, the instrument judgment module 250 further searches for a point cloud set in the form of a cylinder near the segment, assuming that the instrument radius is D and the height is H. If at least one cylinder with a radius of D and a height of H is found in the nearby position, it can be considered that an instrument exists at this position.

[0049] Preferably, the point cloud with a radius mutation does not only appear in one slice, but also appears in a relatively long pipeline where the radius is greater than that of the remaining part. In the above case, during the process of performing the reverse restoration of the pipeline, the instrument judgment module 250 takes the first slice position where the radius starts to mutate in time sequence as the starting position of the pipe diameter mutation, takes the previous slice position where the radius is recorded with a larger radius attribute as the ending position of the pipe diameter mutation, takes the starting position and the ending position of the pipe diameter mutation as the markers for dividing the pipe segment, and identifies the pipe segment with a larger pipe diameter, and performs the task of finding the cylindrical instrument structure at the pipe segment position and nearby. For example, on the same pipeline center line, two radii are present, denoted as r2 and r1, and r2>r1, r2=r3, and r4=r1, where the position of r2 corresponds to the starting position of the pipe diameter mutation, and the position of r3 corresponds to the ending position of the pipe diameter mutation. It can be considered that a pipe exists in the interval position from r2 to r3. The instrument judgment module 250 then searches for a cylinder near the midpoint position of r2 to r3, and when a cylinder with a radius of D and a height of H is found, it is considered that an instrument exists at this position. The instrument judgment module 250 simulates and restores the instrument pipe at this position, judges the type and parameters of the instrument based on the intelligent P&ID, and then assigns values.

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

[0051] S11: Selecting equipment numbers based on the reduction work plan;

[0052] S12: Indexing to the corresponding P&ID segment according to the equipment numbers;

[0053] S13: Performing reconstruction of the three-dimensional steel structure model based on P&ID logical relationship;

[0054] S14: Attaching P&ID attributes to the restored three-dimensional pipeline model, matching the corresponding level element library.

[0055] "Selecting equipment numbers based on the reduction work plan" refers to dividing the project into phased tasks for the steel structure between two devices in the project of reducing an existing structure point cloud according to a pre-set plan, and project personnel select two devices with known equipment numbers for subsequent point cloud model reverse construction work based on the plan, wherein the equipment number is an attribute value corresponding to the device in the P&ID, which is basically used to indicate the identity of the device in the P&ID.

[0056] "Indexing to the corresponding P&ID segment according to the equipment numbers" refers to finding all P&ID data between the two equipment numbers in the P&ID data based on the equipment numbers. The P&ID is a pre-set data set or relational database at least recording P&ID logical relationship and P&ID attributes, wherein the P&ID logical relationship refers to the relationship record recording the superior-inferior relationship, connection relationship, etc. of the steel structure and branch, the steel structure and connecting piece, the steel structure and device, and the P&ID attributes refer to the pre-input attribute information of the steel structure, device, valve, etc. components, such as the size of the device, the wall thickness of the steel structure, etc. The data in the P&ID is generally pre-input by artificial or P&ID data that already exists before the reverse construction process of the present scheme is performed.

[0057] "Performing reconstruction of the three-dimensional steel structure model based on P&ID logical relationship" refers to, after obtaining the P&ID data between the two assigned devices, performing topological relationship retrieval and point cloud model assignment in the P&ID data in the order of device-steel structure-branch steel structure-connecting piece-valve instrument when performing point cloud data reverse construction pipeline restoration model, so that each component model (at least including steel structure, branch steel structure, connecting piece, valve instrument, etc.) between the two devices can be automatically assigned.

[0058] "attaching P&ID attributes to the restored three-dimensional pipeline model, matching the corresponding hierarchical component library" refers to assigning each P&ID attribute pre-stored in the P&ID to the corresponding component model in the assignment process, wherein part of the P&ID attribute assignment is used to build the corresponding component object model. The above-mentioned part of the P&ID attribute is at least the attribute related to the structure size, such as size, thickness and the like, which can be directly reflected on the model and can assist in the construction of the model, realizing the reverse model construction of the point cloud and the P&ID attribute bidirectional mutual inspection.

[0059] In combination with P&ID logic and pre-stored element library of control nodes, three-dimensional reverse modeling of steel structure of existing factory is assisted, for control nodes, not only three-dimensional model of reverse modeling can be obtained, but also attribute information of the control node in P&ID can be generated. Thus, P&ID attribute control logic can be superimposed directly on the basis of high-precision reverse three-dimensional pipeline model, engineers can obtain the trend, attribute, position, purpose and other information of all steel structures in the entire factory by directly observing the three-dimensional steel structure model with sufficient details, and based on additional control logic, by directly clicking the control node model, the control loop of the control node physical object can be directly connected, which not only facilitates engineers to observe, evaluate and control the impact, but also enables them to directly control any equipment in the factory from the control center. The originally scattered and complex steel structure control in the old factory can be centralized to the logic control system of additional steel structure and additional control items based on the restored three-dimensional model, which realizes the centralization of management and control and 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 reverse construction of three-dimensional model, for example, the pre-stored steel structure size, length, width, thickness and other parameters in P&ID are often insignificant and non-intuitive when provided in a list, but when these parameters are executed to generate a three-dimensional model of the existing structure based on the index to P&ID, the attribute data in P&ID can be used to supplement the shape of the reverse three-dimensional model of point cloud, and such supplement not only has the attributes that point cloud data can "see", but also has the attributes that point cloud data "cannot see", such as plate thickness and some back structure, the point cloud recovery model provides guidance for the index P&ID, and the P&ID assists the reverse model construction of point cloud, at the same time, a more accurate and comprehensive reverse construction model can be obtained, and the numerical attribute in P&ID can be directly converted into visual attribute.The above scheme realizes the reverse three-dimensional model of the existing steel structure while automatically mapping the control logic parameters in the P&ID point by point, and actually combines the P&ID image which is relatively abstract and basically does not contain spatial position information and structure information into a three-dimensional, intuitive, easy-to-observe, and structure-accurate three-dimensional reverse composite model. On the one hand, the part of the remaining type structure related parameters in the P&ID can provide the effect of missing item correction for the three-dimensional reverse modeling link, and 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 the full effect of P&ID control, and can also obtain higher effect than P&ID control based on the advantages of three-dimensional modeling. First, the two-dimensional P&ID control logic is upgraded to three dimensions, so that part of the complex control logic that needs to be displayed by levels can be directly displayed in three-dimensional space, which facilitates engineers to quickly and intuitively control parameters in multiple levels. Secondly, the structure parameters in the control logic are more intuitively displayed, so that engineers can directly confirm the structure relationship and size parameters between components in the three-dimensional structure, especially can intuitively view the extrusion and contact between components, which provides a very intuitive criterion for the safety production and structure optimization of the factory. Finally, the simulation technology can be used to provide visual feedback function for P&ID control based on pre-simulation. Based on the pre-set rules, the control link and adjustment control parameters selected by the engineer are used as trigger parameters to output intuitive result view to the engineer in the form of simulation superimposed animation in the three-dimensional pipeline model, which can help engineers to know whether the control can achieve the expected effect, whether there are unexpected situations, etc., effectively improving the efficiency and safety of control.

[0060] It should be noted that the above specific embodiments are exemplary, and those skilled in the art can think of various solutions under the inspiration of the disclosure of the present application, and these solutions also belong to the disclosed range of the present application and fall within the protection scope of the present application. Those skilled in the art should understand that the specification and drawings of the present application are illustrative and do not constitute a limitation on the claims. The protection scope of the present application is defined by the claims and their equivalents. The specification of the present application contains multiple inventive concepts, such as "preferably", "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 according to each inventive concept.

Claims

1. A steel structure digital restoration device for digital twin construction, comprising a structure recognition module (220), characterized in that, The structure recognition module (220) is configured to: obtain a large amount of point cloud information after denoising from the denoising module (210); wherein the point cloud information is point cloud information of coordinate information of any or all points on the steel structure in the existing factory in space; perform a restoration operation based on position correspondence in a virtual three-dimensional space according to the embedded spatial coordinate information of the obtained point cloud information of the steel structure, obtain a total model field about the distribution of the point cloud in space, and the restored point cloud information is in the form of a point model in the total model field; automatically select a position with the best point model density based on the distribution of the point cloud, slice to obtain basic cross-sectional data of the structure; perform recognition and judgment of the type of the steel structure based on the image in the basic cross-sectional data, and perform three-dimensional model fitting and restoration of the slice based on the recognized type of the steel structure after correctly recognizing the type of the steel structure.

2. The steel structure digital restoration device for digital twin construction according to claim 1, characterized in that, The device further comprises a continuity monitoring module (230) connected to the structure recognition module (220), which is used to monitor 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 orders.

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

4. The steel structure digital restoration device for digital twin construction according to claim 3, 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 value of d is greater than the distance from the starting point of the structure to the center point, it is determined that the two segments of the steel structure corresponding to the two center lines do not belong to the same steel structure; if the value of d is less than the distance from the starting point of the structure to the center point, it is determined that the two center lines belong to the same steel structure.

5. The steel structure digital restoration device for digital twin construction according to any one of claims 1-4, characterized in that, The device further comprises a missing recovery module (240) connected to the structure recognition module (220), which is used to recover the missing of the 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 orders.

6. The steel structure digital restoration device for digital twin construction according to claim 5, characterized in that, In the case that the structure recognition module (220) makes an error when recognizing the slice cross section, the missing recovery module (240) judges the cross-sectional point cloud features of the point model based on the generated error information, traces the type of the steel structure of the recognized slice cross section, and performs three-dimensional model fitting and restoration of the slice.

7. The steel structure digital restoration device for digital twin construction according to any one of claims 1-4, characterized in that, Further comprising an instrument judgment module (250) connected to the structure recognition module (220), The instrument judgment module (250) performs instrument judgment on the process of fitting and restoration of the steel structure while the structure recognition module (220) recognizes and performs three-dimensional model fitting and restoration based on the recognition of the steel structure; wherein the instrument judgment module (250) judges the instrument while the structure recognition module (220) recognizes and fits the three-dimensional simulation of the steel structure according to different slice orders; and / or The instrument judgment module (250) synchronously performs identification and reverse restoration of the pipeline instrument based on the sudden change of the pipe diameter and the 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 performing pipeline reverse restoration, the instrument judgment module (250) identifies the first slice position where the radius starts to change as the starting position of the pipe diameter change, identifies the slice position where the radius changes back to the smaller radius before the larger radius attribute is recorded as the ending position of the pipe diameter change, identifies the pipe diameter larger pipe section by taking the starting position and the ending position of the pipe diameter change as the markers for dividing the pipe section, and performs the task of finding the cylindrical instrument structure in the pipe section and its vicinity; In the case of judging the presence of an instrument, the instrument judgment module (250) simulates the restoration of the instrument pipe at the position where the instrument exists, and then judges the type and parameters of the instrument at this position based on the intelligent P&ID, and then assigns values.

9. A steel structure digital restoration method for digital twin construction, characterized by, The method comprises: obtaining a large amount of point cloud information after denoising from the denoising module (210), wherein the point cloud information is the point cloud information of the coordinates of any or all points on the steel structure in the existing factory in space; The point cloud information of the steel structure obtained is subjected to a restoration operation based on the corresponding position in the virtual three-dimensional space according to the space coordinate information embedded therein, to obtain a total model field about the distribution of the point cloud in space, and the point cloud information after restoration is in the form of a point model in the total model field; Based on the distribution of the point cloud, the position with the best point model density is automatically selected, and slicing is performed to obtain the basic cross-sectional data of the structure; Based on the image in the basic cross-sectional data, the type of the steel structure is identified and judged, and after the type of the steel structure is correctly identified, the three-dimensional model fitting restoration of the slice is performed based on the identified type of the steel structure.

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

Images