Miniature pile construction design method in existing industrial building

Abstract

The invention discloses a micro pile construction design method in an existing industrial building, which comprises the following steps of: S1, scanning the current situation in the existing building by adopting a three-dimensional laser radar to form a building point cloud; s2, importing the building point cloud into the constructed BIM platform to generate a building point cloud model; s3, preliminarily selecting basic common equipment to form a common equipment point cloud database; and S4, different devices are selected in the BIM platform to carry out collision detection with the building point cloud model, and the best matching device and placement mode are selected. According to the method, equipment type selection and construction space verification can be completed in the design stage, and the accuracy and efficiency of construction scheme making are improved.

Description

Technical Field

[0001] This invention relates to the field of building construction, and specifically to a method for designing the construction of micropiles in existing industrial buildings. Background Technology

[0002] With the continuous advancement of urbanization and industrial restructuring, a large number of old industrial buildings require functional renovation or structural reinforcement to meet the needs of new equipment installation, load increases, or production line adjustments. In the renovation of such existing industrial buildings, it is often necessary to install micropiles inside the building.

[0003] In traditional construction methods, total stations and measuring tapes are commonly used to survey the interior of buildings. The results are typically presented as two-dimensional CAD drawings or base maps. Based on these drawings, designers need to manually assess the feasibility of equipment placement and the suitability of the construction space. However, due to the complex internal spatial structure of industrial buildings, especially the presence of numerous obstructive components such as pipes, cable trays, and beams, two-dimensional floor plans often fail to accurately reflect spatial hierarchy and height relationships. This leads to frequent adjustments or rework of design schemes during actual construction. Furthermore, existing industrial building drawings are often incomplete or inconsistent with the site conditions. The frequent adjustments to production equipment and dynamic changes in spatial status during renovation further increase the difficulty of surveying and design.

[0004] Meanwhile, the selection and layout of pile foundation equipment are particularly critical in confined spaces. If the selection is inappropriate, the equipment may be unable to be used for construction due to insufficient turning radius, limited boom reach, or failure to meet operating safety distance standards. If the equipment model or placement is adjusted temporarily during construction, it will not only cause delays in the construction period but may also affect the structural safety of existing buildings.

[0005] Therefore, to solve the above problems, a micropile construction design method for existing industrial buildings is needed, which can complete equipment selection and construction space verification during the design phase, thereby improving the accuracy and efficiency of construction plan formulation. Summary of the Invention

[0006] In view of this, the purpose of this invention is to overcome the deficiencies in the prior art and provide a micropile construction design method for existing industrial buildings, which can complete equipment selection and construction space verification in the design stage, thereby improving the accuracy and efficiency of construction plan formulation.

[0007] The present invention provides a method for designing the construction of micropiles in existing industrial buildings, comprising the following steps:

[0008] S1. Use 3D LiDAR to scan the existing interior of the building to form a building point cloud;

[0009] S2. Import the building point cloud into the constructed BIM platform to generate a building point cloud model;

[0010] S3. Initially select basic and commonly used equipment to form a point cloud database of commonly used equipment;

[0011] S4. In the BIM platform, select different devices and the building point cloud model to perform collision detection, and select the best matching device and placement method.

[0012] Furthermore, step S1 specifically includes:

[0013] Using mobile or handheld 3D LiDAR equipment, a comprehensive scan of the interior of existing industrial buildings is conducted to obtain high-density point cloud data within the building space. The scanning range includes structural columns, beams, walls, floors, hoisting tracks, ventilation ducts, water supply and drainage pipelines, and cable trays.

[0014] Furthermore, step S2 specifically includes:

[0015] Based on BIM technology, a basic coordinate system is established, which is consistent with the radar scanning coordinate system.

[0016] Define the categories of structure, pipeline, electrical, and equipment families for subsequent semantic recognition;

[0017] Import building point clouds using a point cloud plugin and generate corresponding 3D geometry in the BIM environment;

[0018] Three-dimensional geometry correction is performed by combining existing design data or survey data.

[0019] Furthermore, step S3 specifically includes:

[0020] Select the types of commonly used pile foundation construction equipment based on project requirements and construction technology;

[0021] Three-dimensional laser scanning is performed on different models of equipment to collect equipment information, including external dimensions, turning radius, arm length, operating space, and dimensions in the transportation state.

[0022] The point cloud of the equipment obtained by scanning is filtered, patch reconstructed and semantically annotated to generate equipment family files that can be used for BIM simulation.

[0023] Equipment point cloud models are generated using equipment family files, and the point cloud models and their technical parameters for each type of equipment are stored in a database. The technical parameters include dimensions, weight, working height, turning radius, and power source type. The database supports categorized retrieval and parameterized access, and can be filtered by equipment purpose, size, and construction capability.

[0024] Furthermore, a device point cloud model is generated using the device family file, specifically including:

[0025] Extract the 3D geometric component information from the family file, obtain the device's bounding box, rotation radius, and arm span, and export it as an intermediate 3D format;

[0026] Triangulation is performed on the device's geometric surface to generate a continuous surface; the sampling interval is set, and point sets are generated according to rules; the spatial coordinates and normal information of each point are recorded, and the output is a standard point cloud data format.

[0027] Furthermore, step S4 specifically includes:

[0028] Import the 3D model generated from the building point cloud and the equipment point cloud model into the BIM platform simultaneously;

[0029] Call the collision detection module built into the BIM software or in the form of a plug-in, and set the collision detection parameters, including the collision tolerance and the detection range; wherein, the detection range needs to cover the equipment operating radius and the transportation path;

[0030] The collision detection module identifies the geometric interference areas between the equipment and the building structure, pipelines, and equipment, and outputs a collision report.

[0031] If the collision volume in the collision report is less than the preset threshold and the equipment can complete the construction task, then the current equipment is determined to be a candidate equipment; otherwise, the current equipment is discarded.

[0032] For each candidate device, a spatial adaptability index is calculated, which includes accessibility, maneuver space, stability, and safety distance.

[0033] By combining the working area size, equipment transportation route, construction phase arrangement and safety regulations, the best equipment model and placement location are automatically selected using a weighted scoring method or multi-objective optimization algorithm.

[0034] The final selection results are presented in a 3D visualization format, showing the equipment placement, operating range, and safety distance.

[0035] The beneficial effects of this invention are as follows: This invention discloses a micropile construction design method for existing industrial buildings. It acquires internal spatial data of the building through three-dimensional lidar scanning to generate a building point cloud model; imports the point cloud data into a BIM platform to construct a digital model of the building space; selects commonly used micropile construction equipment from the equipment family library to generate an equipment point cloud database; and performs collision detection between the building model and the equipment model through the BIM platform to analyze the spatial adaptability of different equipment. Finally, it selects the optimal matching equipment and placement method, enabling rapid design and efficient decision-making for micropile construction in narrow spaces, thereby improving the accuracy and efficiency of construction plan formulation. Attached Figure Description

[0036] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0037] Figure 1 This is a schematic diagram of the micropile construction design method of the present invention. Detailed Implementation

[0038] The present invention will be further described below with reference to the accompanying drawings, as shown in the figures:

[0039] This embodiment discloses a method for designing the construction of micropiles within existing industrial buildings, including the following steps:

[0040] S1. Use 3D LiDAR to scan the existing interior of the building to form a building point cloud;

[0041] S2. Import the building point cloud into the constructed BIM platform to generate a building point cloud model;

[0042] S3. Initially select basic and commonly used equipment to form a point cloud database of commonly used equipment;

[0043] S4. In the BIM platform, select different devices and the building point cloud model to perform collision detection, and select the best matching device and placement method.

[0044] This invention proposes a construction design method for micropiles in existing industrial buildings based on three-dimensional digital modeling technology. It can quickly acquire internal spatial data of buildings using three-dimensional lidar and combine it with a BIM platform to realize visual matching analysis of equipment and building space. This allows for the completion of equipment selection and construction space verification during the design phase, thereby improving the accuracy and efficiency of construction plan formulation.

[0045] In this embodiment, in step S1, a mobile or handheld 3D LiDAR device with high precision and high resolution is selected to perform a comprehensive scan of the interior space of the existing industrial building. During the scanning process, the operator lays out the scanning path point by point along the main passages, work areas, and densely packed component areas inside the building to ensure coverage without blind spots.

[0046] The device's built-in positioning and attitude correction system performs real-time stitching and error correction on multi-site scan data to obtain high-density point cloud data of the building's interior space. The scanning range includes structural columns, beams, walls, floors, hoisting tracks, ventilation ducts, water supply and drainage pipelines, and cable trays. This point cloud data accurately reflects the building's internal geometry and component distribution, providing a precise spatial information foundation for subsequent obstacle identification in the micropillar deployment area, construction equipment path planning, and construction feasibility analysis.

[0047] In this embodiment, in step S2, the basic coordinate system of the building information model is first established based on BIM technology and is aligned with the coordinate system of the point cloud obtained by the 3D LiDAR scan to achieve consistency in spatial location and data alignment.

[0048] Subsequently, classification standards for structural components, pipeline systems, electrical facilities, and equipment families are predefined in the BIM platform to provide a basis for semantic recognition and object attribute association of subsequent point cloud data.

[0049] Next, using a professional point cloud processing plugin, the building point cloud data obtained in step S1 is imported into the BIM environment, automatically identifying the main geometric features and generating the corresponding three-dimensional geometric model.

[0050] After the model is generated, the dimensions, positions and elevations of key structural components are compared and corrected by combining existing architectural design data, as-built survey data or construction drawings, so as to ensure that the point cloud model is consistent with the accuracy of the actual building space.

[0051] Through the above processing, a high-precision, semantic building point cloud model can be formed within the BIM platform, providing a reliable data foundation for the virtual simulation and collision detection of subsequent equipment layout and micropile construction schemes.

[0052] In this embodiment, in step S3, firstly, based on the engineering requirements, site limitations, and construction process requirements of micropile construction, the types of commonly used pile foundation construction equipment suitable for internal operations of existing industrial buildings are selected, such as small drilling rigs, crawler cranes, mud pumps, air compressors, and grouting equipment.

[0053] For each type of equipment, a 3D laser scanner is used to perform a full-range scan of the equipment's appearance to obtain its high-precision point cloud data, and key parameter information of the equipment is collected simultaneously, including its external dimensions, turning radius, arm length, operating space, and dimensions in the transportation state.

[0054] Subsequently, the original equipment point cloud data obtained from the scan is processed by noise filtering, point cloud sparsification, patch reconstruction, and semantic annotation to form a 3D geometric model with complete topological structure and attribute information. Based on the processed model, BIM software is used to generate corresponding equipment family files, and the main technical parameters of the equipment, including dimensions, weight, working height, turning radius, and power source type, are embedded in the family files, enabling the model to have parametric adjustment and simulation functions.

[0055] Finally, the point cloud models and their technical parameter files of various equipment are uniformly stored in the equipment point cloud database. This database has classification retrieval and parameterized calling functions, and can quickly filter according to equipment purpose, size, operation capacity or power type. It provides standardized data support for spatial matching analysis, equipment selection optimization and collision detection in subsequent steps, thereby achieving efficient, accurate and visualized equipment selection and construction layout.

[0056] Furthermore, the specific steps for generating a device point cloud model using device family files are as follows:

[0057] First, the interface of the selected equipment family file in the BIM platform is called to extract the three-dimensional geometric component information in the family file, including the equipment shape, component boundaries and structural outline. At the same time, the key parameters such as the equipment's bounding box, rotation radius and arm span are obtained and exported as a common three-dimensional intermediate format file, such as obj or stl, for subsequent processing.

[0058] Subsequently, the exported equipment geometric model is surface-meshed. A triangulation algorithm is used to divide the continuous curved surface into a high-density triangular mesh to maintain the accurate geometric features of the equipment's shape. Based on this, a predetermined sampling interval, such as 5-10 mm, is set, and discrete point sets are generated uniformly on the curved surface according to rules. At the same time, the spatial coordinates and normal information of each point are recorded to ensure that the geometric and directional characteristics of the point cloud can accurately reflect the surface morphology of the equipment.

[0059] Finally, the generated discrete point set is output as a standardized point cloud data format, such as pts or las, forming a device point cloud model that can be directly used for collision detection and spatial adaptability analysis on the BIM platform.

[0060] This method enables the parameterized geometric information in the equipment family file to be effectively converted into discrete 3D data that can be matched with the building point cloud model, thereby realizing digital, visualized, and simulated pre-construction equipment layout analysis.

[0061] In this embodiment, in step S4, the 3D point cloud model of the building generated in step S2 and the point cloud models of various equipment generated in step S3 are first imported into the BIM platform to realize a unified digital environment for building space and construction equipment.

[0062] In the BIM platform, the collision detection module, either built into the software or extended via a plugin, is used to perform spatial interference analysis on the imported model. During the collision detection process, parameters such as collision tolerance and detection range are set, where the collision tolerance is ≤ The testing scope must cover the equipment's operating radius and the estimated transportation route to ensure the comprehensiveness and safety of the construction layout.

[0063] The collision detection module identifies the geometric interference areas between the equipment and the building structure, pipelines, and existing equipment, and generates a detailed collision report. The report includes the collision location coordinates, collision volume, collision object, and collision level.

[0064] The collision result is determined based on a preset threshold: if the collision volume is less than the threshold and the equipment can complete the construction task, the equipment is identified as a candidate; otherwise, unsuitable equipment is discarded. The threshold can be set according to actual working conditions; for example, the threshold value can be set to... .

[0065] For each candidate device, a spatial adaptability index is further calculated. The index comprehensively considers factors such as accessibility, operating maneuvering space, device stability, and safety distance to quantify the device's suitability for construction in a specific space.

[0066] Subsequently, by combining the working area size, equipment transportation route, construction phase arrangement and relevant safety regulations, the candidate equipment and its layout scheme are automatically screened using a weighted scoring method or multi-objective optimization algorithm to obtain the best matching equipment model and its placement position.

[0067] Finally, the optimization results are presented in a three-dimensional visualization, which intuitively displays the placement, operating range and safety distance of the equipment in the construction space, providing accurate and operable digital basis for construction scheme decision-making, and realizing efficient design and optimization of micropile construction schemes in existing industrial buildings.

[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method of micro-pile construction design within an existing industrial building, characterized by: It comprises the following steps: S1. Scanning the existing building interior with a three-dimensional laser radar to form a building point cloud; S2. Importing the building point cloud into a BIM platform to generate a building point cloud model; S3. Preliminarily selecting basic commonly used equipment to form a commonly used equipment point cloud database; S4. Selecting different equipment in the BIM platform to perform collision detection with the building point cloud model to select the best matching equipment and placement method.

2. A method of micropile construction design in an existing industrial building according to claim 1, characterized in that: The step S1 specifically comprises: Using a mobile or handheld three-dimensional laser radar device to perform all-around scanning on the interior of an existing industrial building to obtain high-density point cloud data in the building space; wherein the scanning range includes structural columns, beams, walls, floors, hoisting tracks, ventilation pipelines, water supply and drainage pipelines, and cable bridges.

3. The method of micro-pile construction design in an existing industrial building according to claim 1, characterized in that: The step S2 specifically comprises: Based on BIM technology, establishing a basic coordinate system consistent with the radar scanning coordinate system; Defining structure, pipeline, electrical, and equipment family categories for subsequent semantic recognition; Importing the building point cloud through a point cloud plug-in and generating corresponding three-dimensional geometric bodies in the BIM environment; Combining existing design data or surveying data to correct the three-dimensional geometric bodies.

4. The method of micro pile construction design in an existing industrial building according to claim 1, characterized in that: The step S3 specifically comprises: Selecting commonly used pile foundation construction equipment types according to engineering requirements and construction processes; Performing three-dimensional laser scanning on different types of equipment and collecting equipment information; the equipment information includes external dimensions, turning radius, arm length, operating space, and transportation state dimensions; Filtering, facet reconstruction, and semantic labeling processing the scanned equipment point cloud to generate equipment family files that can be used for BIM simulation; Generating equipment point cloud models using the equipment family files and storing the point cloud models and their technical parameters of each type of equipment in a database; the technical parameters include dimensions, weight, operating height, turning radius, and power source type; the database supports classified retrieval and parameterized calling, and can be filtered according to equipment purpose, volume, and construction capacity.

5. A method of micropile construction design within an existing industrial building according to claim 4, characterized in that: Generating equipment point cloud models using the equipment family files specifically comprises: Extracting three-dimensional geometric component information from the family files to obtain equipment shape bounding boxes, turning radii, and arm spans, and exporting them as intermediate three-dimensional formats; Performing triangular meshing on the equipment geometric facets to generate continuous surfaces; setting a sampling interval to generate a point set in a regular distribution; recording the spatial coordinates and normal information of each point and outputting them as standard point cloud data formats.

6. The method of micro pile construction design in an existing industrial building according to claim 1, wherein: The step S4 specifically comprises: Importing the three-dimensional model generated from the building point cloud and the equipment point cloud model into the BIM platform; Calling the built-in or plug-in form collision detection module of the BIM software, setting collision detection parameters, including collision tolerance and detection range; wherein the detection range needs to cover the equipment operating radius and the transportation path; Using the collision detection module to identify the geometric interference area between the equipment and the building structure, pipelines, and equipment, and output a collision report; If the collision volume in the collision report is less than a preset threshold and the equipment can complete the construction task, then the current equipment is determined as a candidate equipment, otherwise, the current equipment is discarded; For each candidate equipment, a space adaptation index is calculated, which includes accessibility, operation swing space, stability, and safety clearance; By combining the dimensions of the construction surface, the transportation route of the equipment, the construction stage arrangement, and the safety regulations, the best equipment model and placement position are automatically selected by using a weighted scoring method or a multi-objective optimization algorithm; The final preferred result is displayed in a three-dimensional visualization form, including the equipment placement position, the operation range, and the safety clearance.

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