Accurate butt joint installation method and system for 220-meter basket arch bridge sections

Abstract

The invention relates to the technical field of bridge engineering, and discloses a precise butt joint installation method and system for 220-meter lifting-basket arch bridge segments, and the method comprises the steps: collecting the three-dimensional point cloud data of the 220-meter lifting-basket arch bridge segments, and constructing a three-dimensional segment model of the 220-meter lifting-basket arch bridge segments; analyzing the segment butt joint effect of the 220-meter lifting basket arch bridge segments, and identifying the butt joint demand precision of the lifting basket arch bridge segments; the section butt joint positions of the 220-meter lifting basket arch bridge sections are determined, and an intelligent monitoring network of the 220-meter lifting basket arch bridge sections is arranged; collecting butt joint angles and displacement parameters of the interface sections, and setting a butt joint error adjustment mechanism of the 220-meter basket arch bridge sections; identifying a potential bridge forming risk of the 220-meter lifting-basket arch bridge section, and constructing a butt joint behavior judgment model of the 220-meter lifting-basket arch bridge section; and in combination with a butt joint error adjustment mechanism, an intelligent monitoring network and a butt joint behavior judgment model, performing butt joint installation processing on the 220-meter lifting basket arch bridge sections. According to the method, the butt joint precision and the butt joint construction efficiency of the basket arch bridge sections can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge engineering, and in particular to a method and system for accurately docking and installing segments of a 220-meter basket-handled arch bridge. Background Art

[0002] The precise docking and installation of the segments of the 220-meter basket arch bridge refers to the process of accurately aligning and installing each arch rib segment during the construction of the basket arch bridge, which can improve the structural stability and safety of the basket arch bridge. With the rapid increase in my country's population, there is an urgent need to build more large-span bridges to alleviate the growing traffic pressure. As a new type of bridge structure, the basket arch bridge has the advantages of large spanning capacity and good structural stability. It has been increasingly used in actual projects. However, the construction process of the basket arch bridge is relatively complicated, especially the precise docking and installation of the segments, which is directly related to the overall quality and safety of the bridge.

[0003] The traditional method of butt-jointing and installing basket-handled arch bridge segments mainly uses the bracket method, which involves building a bracket under the bridge and then hoisting the arch rib segments onto the bracket for butt-jointing installation. Although this method is relatively simple to construct, the construction and removal of the bracket may take a lot of time, affecting the construction progress. Summary of the invention

[0004] In order to solve the above problems, the present invention provides a method and system for precise docking and installation of 220-meter basket-lift arch bridge segments, which can improve the docking accuracy and docking construction efficiency of the basket-lift arch bridge segments.

[0005] In a first aspect, the present invention provides a method for accurately docking and installing a 220-meter basket arch bridge segment, comprising:

[0006] Acquire a 220-meter basket handle arch bridge segment to be docked, collect three-dimensional point cloud data of the 220-meter basket handle arch bridge segment, and construct a three-dimensional segment model of the 220-meter basket handle arch bridge segment based on the three-dimensional point cloud data;

[0007] Based on the three-dimensional segment model, the segment docking effect of the 220-meter basket arch bridge segment is analyzed, and according to the segment docking result, the required docking accuracy of the 220-meter basket arch bridge segment is identified;

[0008] The segment types of the 220-meter basket handle arch bridge segments are collected, and according to the segment types, segment docking positions of the 220-meter basket handle arch bridge segments are determined, and based on the segment docking positions and the docking requirement accuracy, an intelligent monitoring network of the 220-meter basket handle arch bridge segments is set;

[0009] Identify the docking interface of the 220-meter basket arch bridge segment, and identify the interface segment of the docking interface, collect the docking angle and displacement parameters of the interface segment according to the intelligent monitoring network, and set the docking error adjustment mechanism of the 220-meter basket arch bridge segment based on the docking angle, the displacement parameters and the docking required accuracy;

[0010] Analyze the docking influencing factors of the 220-meter basket arch bridge segment, identify the potential bridge construction risk of the 220-meter basket arch bridge segment based on the docking influencing factors, and construct a docking behavior judgment model for the 220-meter basket arch bridge segment according to the potential bridge construction risk;

[0011] In combination with the docking error adjustment mechanism, the intelligent monitoring network and the docking behavior judgment model, the docking installation process of the 220-meter basket handle arch bridge segment is executed to obtain the docking installation result.

[0012] In a possible implementation of the first aspect, constructing a three-dimensional segment model of the 220-meter basket handle arch bridge segment based on the three-dimensional point cloud data includes:

[0013] Execute data splicing processing of the three-dimensional point cloud data to obtain spliced ​​point cloud data;

[0014] Extracting key features of the 220-meter basket arch bridge segment from the spliced ​​point cloud data;

[0015] Based on the key features, reconstruct the segmental surface of the 220-meter basket arch bridge segment;

[0016] According to the segment surface, a polygonal grid of the 220-meter basket arch bridge segment is generated;

[0017] Based on the polygonal grid, identifying structural elements of the 220-meter basket arch bridge segment;

[0018] The segment surface, the polygonal mesh and the structural element are combined to construct a three-dimensional segment model of the 220-meter basket handle arch bridge segment.

[0019] In a possible implementation of the first aspect, analyzing the segment docking effect of the 220-meter basket handle arch bridge segment based on the three-dimensional segment model includes:

[0020] identifying a classified segment model of the three-dimensional segment model;

[0021] Extracting the contact boundary of the classified segment model, and identifying the butt joint surface of the 220-meter basket arch bridge segment according to the contact boundary;

[0022] Calculating the geometric matching degree of the butt joint surface;

[0023] Based on the geometric matching degree, determining the docking position of the classification segment model;

[0024] In combination with the docking surface and the docking position, the segment docking effect of the 220-meter basket handle arch bridge segment is analyzed.

[0025] In a possible implementation of the first aspect, identifying the required docking accuracy of the 220-meter basket handle arch bridge segment according to the segment docking result includes:

[0026] According to the segment docking results, the docking segments of the 220-meter basket arch bridge segments are identified;

[0027] calculating the contact area between the docking segments;

[0028] Based on the contact area, identifying a dimensional fit of the docking segments;

[0029] Calculating the docking deviation degree of the docking segment according to the size fit;

[0030] identifying a butt joint surface of the butt joint segment and measuring the surface flatness of the butt joint surface;

[0031] Identify the segment joints of the 220-meter basket arch bridge segment;

[0032] Based on the segment joints, the load performance of the 220-meter basket arch bridge segment was analyzed;

[0033] According to the load performance, identifying the structural stability of the segment joint;

[0034] The docking requirement accuracy of the 220-meter basket arch bridge segment is identified by combining the docking deviation degree, the surface flatness and the structural stability.

[0035] In a possible implementation of the first aspect, determining the segment docking position of the 220-meter basket handle arch bridge segment according to the segment type includes:

[0036] According to the segment type, identifying the segment docking point of the 220-meter basket arch bridge segment;

[0037] Analyze the stress conditions of the segment joints;

[0038] According to the stress conditions, the arch bridge bearing capacity corresponding to the 220-meter basket arch bridge segment is analyzed;

[0039] Based on the bearing capacity of the arch bridge, identify the butt joint construction process of the 220-meter basket arch bridge segment;

[0040] According to the docking construction process, the docking construction characteristics of the 220-meter basket arch bridge segment are analyzed;

[0041] Based on the docking construction characteristics, identifying the factors affecting the convenient construction and the error tolerance of the 220-meter basket arch bridge segment;

[0042] In combination with the bearing capacity, the factors affecting the convenient construction and the error tolerance, the segment docking positions of the 220-meter basket arch bridge segments are determined.

[0043] In a possible implementation of the first aspect, the intelligent monitoring network of the 220-meter basket handle arch bridge segment is set based on the segment docking position and the docking required accuracy, including:

[0044] Based on the segment docking position, a parameter sensing device of the 220-meter basket arch bridge segment is configured;

[0045] According to the parameter sensing device, the docking construction data of the 220-meter basket arch bridge segment is collected;

[0046] Based on the docking requirement accuracy, extracting key data types of the docking construction data;

[0047] Identify key parameter categories of the key data types, and define abnormality judgment baselines for the key parameter categories;

[0048] Based on the abnormality judgment baseline, a docking abnormality feedback mechanism for the 220-meter basket arch bridge segment is set;

[0049] In combination with the parameter sensing device, the abnormality judgment baseline and the docking abnormality feedback mechanism, an intelligent monitoring network for the 220-meter basket arch bridge segment is set up.

[0050] In a possible implementation of the first aspect, the docking error adjustment mechanism of the 220-meter basket handle arch bridge segment is set based on the docking angle, the displacement parameter, and the docking required accuracy, including:

[0051] Based on the required docking accuracy, identifying the normal motion trajectory of the docking angle and the displacement parameter;

[0052] According to the normal motion trajectory, the docking error trend of the 220-meter basket arch bridge segment is analyzed;

[0053] Based on the docking error trend, the docking behavior characteristics of the 220-meter basket arch bridge segment are extracted;

[0054] According to the docking behavior characteristics, the bridge completion effect of the 220-meter basket arch bridge segment is identified;

[0055] Constructing a performance analysis model of the bridge-building effect;

[0056] Based on the performance analysis model, a docking effect verification system for the 220-meter basket arch bridge segment is set up;

[0057] According to the docking effect verification system, a docking error adjustment mechanism for the 220-meter basket arch bridge segment is set up.

[0058] In a possible implementation of the first aspect, identifying the potential bridge completion risk of the 220-meter basket handle arch bridge segment based on the docking influencing factors includes:

[0059] Identifying the factor types of the docking influencing factors, and calculating the correlation coefficients between the factor types;

[0060] According to the factor type, the classification data corresponding to the 220-meter basket arch bridge segment is collected, and the data feature type of the classification data is extracted;

[0061] Analyzing a data development pattern of the classified data based on the data feature type;

[0062] According to the correlation coefficient and the data development pattern, the risk occurrence type of the 220-meter basket arch bridge segment is identified;

[0063] Analyze the risk results corresponding to the risk occurrence type;

[0064] Identify the probability distribution of the docking influencing factors, and analyze the risk probability of the 220-meter basket arch bridge segment based on the probability distribution;

[0065] Based on the risk occurrence type, risk consequence and risk occurrence probability, the potential bridge completion risk of the 220-meter basket arch bridge segment is identified.

[0066] In a possible implementation of the first aspect, constructing a docking behavior judgment model for the 220-meter basket arch bridge segment according to the potential bridge completion risk includes:

[0067] Identify the risk level of the potential bridge completion risk, and based on the risk level, identify the key docking influencing factors of the 220-meter basket arch bridge segment;

[0068] Based on the key docking influencing factors, the dimension reduction docking behavior characteristics of the 220-meter basket arch bridge segment are extracted;

[0069] Identifying the key segment parts corresponding to the dimensionality reduction docking behavior characteristics;

[0070] According to the key segment position, a target point behavior detection mechanism for the 220-meter basket arch bridge segment is set;

[0071] Based on the dimension reduction docking behavior characteristics and the key docking influencing factors, defining the detection indicator type of the target point behavior detection mechanism;

[0072] In combination with the target point behavior detection mechanism and the detection index type, a docking behavior judgment model for the 220-meter basket arch bridge segment is constructed.

[0073] In a second aspect, the present invention provides a 220-meter basket arch bridge segment precise docking and installation system, characterized in that the system comprises:

[0074] A three-dimensional model building module is used to obtain a 220-meter basket handle arch bridge segment to be docked, collect three-dimensional point cloud data of the 220-meter basket handle arch bridge segment, and build a three-dimensional segment model of the 220-meter basket handle arch bridge segment based on the three-dimensional point cloud data;

[0075] A required accuracy identification module is used to analyze the segment docking effect of the 220-meter basket handle arch bridge segment based on the three-dimensional segment model, and identify the required docking accuracy of the 220-meter basket handle arch bridge segment according to the segment docking result;

[0076] An intelligent monitoring module is used to collect the segment type of the 220-meter basket arch bridge segment, determine the segment docking position of the 220-meter basket arch bridge segment according to the segment type, and set the intelligent monitoring network of the 220-meter basket arch bridge segment based on the segment docking position and the docking requirement accuracy;

[0077] A docking error adjustment module is used to identify the docking interface of the 220-meter basket arch bridge segment and the interface segment of the docking interface, collect the docking angle and displacement parameters of the interface segment according to the intelligent monitoring network, and set the docking error adjustment mechanism of the 220-meter basket arch bridge segment based on the docking angle, the displacement parameters and the docking required accuracy;

[0078] A docking behavior judgment module is used to analyze the docking influencing factors of the 220-meter basket handle arch bridge segment, identify the potential bridge completion risk of the 220-meter basket handle arch bridge segment based on the docking influencing factors, and construct a docking behavior judgment model for the 220-meter basket handle arch bridge segment according to the potential bridge completion risk;

[0079] The docking installation module is used to combine the docking error adjustment mechanism, the intelligent monitoring network and the docking behavior judgment model to perform the docking installation processing of the 220-meter basket arch bridge segment and obtain the docking installation result.

[0080] Compared with the prior art, the technical principle and beneficial effects of the above solution are:

[0081] The embodiment of the present invention constructs a three-dimensional segment model of the 220-meter basket arch bridge segment based on the three-dimensional point cloud data, and can use the structural analysis results of the basket arch bridge segment to evaluate the performance of the segment under different load conditions; further, the embodiment of the present invention analyzes the segment docking effect of the 220-meter basket arch bridge segment based on the three-dimensional segment model to identify the docking requirement accuracy of the 220-meter basket arch bridge segment, and can simulate the docking installation of the basket arch bridge segment in advance to ensure that the segment can be accurately docked, reduce on-site adjustment work, and improve docking efficiency; secondly, the embodiment of the present invention sets up an intelligent monitoring network of the 220-meter basket arch bridge segment based on the segment docking position and the docking requirement accuracy, so as to monitor the structural response and docking parameter changes during the construction process in real time, and provide real-time data support for construction; thirdly, the embodiment of the present invention sets up a docking error adjustment mechanism for the 220-meter basket arch bridge segment based on the docking angle, the displacement parameter and the docking requirement accuracy, so as to allow The construction team can make timely adjustments when deviations are found to improve docking accuracy, and can also reduce manual intervention, speed up construction progress, and improve construction efficiency; further, the embodiment of the present invention can accurately judge and analyze docking behavior by constructing a docking behavior judgment model of the 220-meter basket arch bridge segment according to the potential bridge risk, helping construction personnel to better grasp the various parameters and changes in the docking process, thereby improving the docking accuracy and ensuring the accurate installation of the arch bridge segment; finally, the embodiment of the present invention performs the docking installation processing of the 220-meter basket arch bridge segment by combining the docking error adjustment mechanism, the intelligent monitoring network and the docking behavior judgment model, and obtains the docking installation result, which can monitor and adjust the error in the docking process in real time, ensure the docking accuracy of the arch bridge segment, and discover potential safety hazards in advance, take corresponding measures to prevent them, thereby enhancing the safety of the construction process, and also helping to reduce the possibility of material waste, rework and accidents, and reduce construction costs and risks. Therefore, the 220-meter basket arch bridge segment precise docking installation method proposed by the present invention can improve the docking accuracy and docking construction efficiency of the basket arch bridge segment. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0083] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0084] Figure 1 A schematic diagram of a process for the precise docking and installation of a 220-meter basket arch bridge segment provided in one embodiment of the present invention;

[0085] Figure 2 A schematic diagram of a module of a 220-meter basket arch bridge segment precision docking and installation system provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0086] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0087] The embodiment of the present invention provides a 220-meter basket arch bridge segment precise docking installation method, and the execution subject of the 220-meter basket arch bridge segment precise docking installation method includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present invention. In other words, the 220-meter basket arch bridge segment precise docking installation method can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content distribution networks (Content De l ivery Network, CDN), and big data and artificial intelligence platforms.

[0088] See also Figure 1 The figure is a flow chart of a method for accurately docking and installing a 220-meter basket arch bridge segment provided by an embodiment of the present invention. Figure 1 The precise docking and installation method of the 220-meter basket arch bridge segments described in the specification includes:

[0089] S1. Obtain a 220-meter basket handle arch bridge segment to be docked, collect three-dimensional point cloud data of the 220-meter basket handle arch bridge segment, and construct a three-dimensional segment model of the 220-meter basket handle arch bridge segment based on the three-dimensional point cloud data.

[0090] The embodiment of the present invention can clarify the actual object of the arch bridge segment docking and installation by obtaining the 220-meter basket arch bridge segment to be docked. The 220-meter basket arch bridge segment refers to the various components of the basket arch bridge with a main bridge span of 200 meters, such as arch rib segments, main beam segments, etc.

[0091] Furthermore, the embodiment of the present invention can reconstruct a surface model of the basket handle arch bridge segment by collecting three-dimensional point cloud data of the 220-meter basket handle arch bridge segment to simulate the bridge-building effect of the basket handle arch bridge segment docking and installation. The three-dimensional point cloud data refers to a data set composed of spatial points of the entire 220-meter-long basket handle arch bridge segment.

[0092] Optionally, the three-dimensional point cloud data collection of the 220-meter basket handle arch bridge segment can be achieved using three-dimensional laser scanning technology.

[0093] The embodiment of the present invention constructs a three-dimensional segment model of the 220-meter basket handle arch bridge segment based on the three-dimensional point cloud data, and can use the structural analysis results of the basket handle arch bridge segment to evaluate the performance of the segment under different load conditions. The three-dimensional segment model refers to a three-dimensional digital representation of the basket handle arch bridge segment.

[0094] As an embodiment of the present invention, constructing a three-dimensional segment model of the 220-meter basket handle arch bridge segment based on the three-dimensional point cloud data includes: performing data stitching processing of the three-dimensional point cloud data to obtain stitching point cloud data; extracting key features of the 220-meter basket handle arch bridge segment from the stitching point cloud data; reconstructing the segment surface of the 220-meter basket handle arch bridge segment based on the key features; generating a polygonal grid of the 220-meter basket handle arch bridge segment based on the segment surface; identifying structural elements of the 220-meter basket handle arch bridge segment based on the polygonal grid; and constructing a three-dimensional segment model of the 220-meter basket handle arch bridge segment by combining the segment surface, the polygonal grid and the structural elements.

[0095] Among them, the data stitching processing refers to the process of merging the point cloud data obtained from multiple scanning positions into a complete data set, the stitching point cloud data refers to the complete point cloud data obtained after data stitching processing, the key features refer to the feature points in the point cloud data that can represent the main structure and shape of the basket arch bridge segment, such as edges, corners, intersections and planes, etc., the segment surface refers to the surface shape of the basket arch bridge segment reconstructed according to the point cloud data, the polygonal grid refers to a grid composed of multiple polygons, such as a triangle, and the structural element refers to the main structural components in the basket arch bridge segment, such as arch ribs, beams, bridge decks, etc.

[0096] Optionally, the data stitching processing of the three-dimensional point cloud data can be obtained through point cloud processing software, such as CloudCompare software; the reconstruction of the segment surface of the 220-meter basket handle arch bridge segment based on the key features can be achieved using Poisson reconstruction; the identification of structural elements of the 220-meter basket handle arch bridge segment based on the polygonal grid can be obtained through structural recognition technology, such as geometric analysis technology; the construction of the three-dimensional segment model of the 220-meter basket handle arch bridge segment combining the segment surface, the polygonal grid and the structural elements can be achieved using three-dimensional modeling software, such as AutoCAD software.

[0097] S2. Based on the three-dimensional segment model, the segment docking effect of the 220-meter basket handle arch bridge segment is analyzed, and according to the segment docking result, the required docking accuracy of the 220-meter basket handle arch bridge segment is identified.

[0098] The embodiment of the present invention analyzes the segment docking effect of the 220-meter basket handle arch bridge segment based on the three-dimensional segment model, and can simulate the docking installation of the basket handle arch bridge segment in advance to ensure that the segments can be accurately docked and reduce on-site adjustment work. The segment docking effect refers to the overall performance and performance after the various segments of the basket handle arch bridge segment are accurately connected together.

[0099] As an embodiment of the present invention, the segment docking effect of the 220-meter basket handle arch bridge segment is analyzed based on the three-dimensional segment model, including: identifying the classification segment model of the three-dimensional segment model; extracting the contact boundary of the classification segment model, and identifying the docking surface of the 220-meter basket handle arch bridge segment according to the contact boundary; calculating the geometric matching degree of the docking surface; determining the docking position of the classification segment model based on the geometric matching degree; and analyzing the segment docking effect of the 220-meter basket handle arch bridge segment in combination with the docking surface and the docking position.

[0100] Among them, the classified segment model refers to the three-dimensional digital model of different positions of the basket handle arch bridge segment, the contact boundary refers to the edge used for connection or docking in the model, the docking surface refers to the contact surface used for connection between two segments, the geometric matching degree refers to the degree of matching between two docking surfaces in geometric shape, size and position, and the docking position refers to the specific position where the two segment models are docked in space.

[0101] Optionally, the contact boundary extraction of the classified segment model can be implemented using a feature matching algorithm, such as a scale-invariant feature transformation algorithm. Combined with the docking surface and the docking position, the segment docking effect analysis of the 220-meter basket handle arch bridge segment can be obtained through a finite element analysis method.

[0102] In an optional embodiment of the present invention, the geometric matching degree of the butt joint surface is calculated using the following formula:

[0103]

[0104] Among them, A represents the geometric matching degree of the butt joint surface, S e′ Indicates the eth ′ Gap value of group contact segment, Z e′ Indicates the eth ′ Dislocation value of the contact segment, L e′ Indicates the eth ′ The angle deviation value of the group contact segment, m represents the number of groups corresponding to the contact segment in the docking surface, e ′ Indicates the group sequence number corresponding to the contact segment.

[0105] Furthermore, the embodiment of the present invention can reduce the adjustment and repair work in on-site construction, improve the docking efficiency, and ensure the construction quality and service life of the basket handle arch bridge by identifying the docking requirement accuracy of the 220-meter basket handle arch bridge segment according to the segment docking result. The docking requirement accuracy refers to the accuracy requirements for the docking between each segment when the basket handle arch bridge segment is docked and installed, such as material requirements, size requirements, etc.

[0106] As an embodiment of the present invention, the method of identifying the required docking accuracy of the 220-meter basket handle arch bridge segment according to the segment docking result includes: identifying the docking segment of the 220-meter basket handle arch bridge segment according to the segment docking result; calculating the contact area between the docking segments; identifying the size fit of the docking segment based on the contact area; calculating the docking deviation of the docking segment according to the size fit; identifying the docking surface of the docking segment and measuring the surface flatness of the docking surface; identifying the segment docking part of the 220-meter basket handle arch bridge segment; based on the segment docking part, analyzing the load performance of the 220-meter basket handle arch bridge segment; identifying the structural stability of the segment docking part according to the load performance; and identifying the required docking accuracy of the 220-meter basket handle arch bridge segment in combination with the docking deviation, the surface flatness and the structural stability.

[0107] Among them, the docking segment refers to the various arch bridge segments that need to be precisely docked during the construction of the basket arch bridge, the contact area refers to the area of ​​the two docking segments on the contact surface, the size fit refers to the degree of matching between the docking segments in size, including length, width, height, etc., the docking deviation degree refers to the deviation between the actual docking position and the design position, the docking surface refers to the surface in contact between the two segments, the surface flatness refers to an indicator to measure the smoothness and uniformity of the surface of the docking segments, the segment docking position refers to the specific position where the segments are docked, the load performance refers to the performance of the basket arch bridge when bearing the design load, including static and dynamic loads, and the structural stability refers to the overall stability of the basket arch bridge after docking.

[0108] Optionally, the calculation of the contact area between the butted segments can be determined by the geometric shape and size of the segments, the surface flatness measurement of the butt joint surface can be achieved by using a surface roughness meter, and the load performance analysis of the 220-meter basket handle arch bridge segment based on the segment butt joint can be determined by on-site load testing.

[0109] In an optional embodiment of the present invention, based on the contact area, the size fit of the docking segment is identified using the following formula:

[0110]

[0111] Where M represents the size fit of the docking segment, w j represents the weight of the jth size parameter in the docking segment, B j represents the reference value of the jth size parameter, C j represents the actual measured value of the jth size parameter, max(B j ,C j ) represents the maximum value of the reference value and the actual measurement value of the j-th dimensional parameter, n represents the number of dimensional parameters in the docking segment, and j represents the index number of the dimensional parameter.

[0112] S3. Collect the segment types of the 220-meter basket handle arch bridge segment, determine the segment docking position of the 220-meter basket handle arch bridge segment according to the segment type, and set up an intelligent monitoring network for the 220-meter basket handle arch bridge segment based on the segment docking position and the docking requirement accuracy.

[0113] The embodiment of the present invention can identify the docking position of each arch bridge docking segment by collecting the segment types of the 220-meter basket arch bridge segments. The segment type refers to the various parts that constitute the 220-meter basket arch bridge, such as the arch foot segment, the arch rib segment, etc.

[0114] Optionally, the segment type collection of the 220-meter basket handle arch bridge segment can be determined by the type of the arch bridge.

[0115] Furthermore, the embodiment of the present invention determines the segment docking position of the 220-meter basket arch bridge segment according to the segment type, and can set an intelligent monitoring system at the segment docking position to monitor the segment docking parameters in real time. The segment docking position refers to the specific bridge-forming position of two or more prefabricated segments.

[0116] As an embodiment of the present invention, determining the segment docking position of the 220-meter basket arch bridge segment according to the segment type includes: identifying the segment docking point of the 220-meter basket arch bridge segment according to the segment type; analyzing the stress condition of the segment docking point; analyzing the bearing capacity of the arch bridge corresponding to the 220-meter basket arch bridge segment according to the stress condition; identifying the docking construction process of the 220-meter basket arch bridge segment based on the arch bridge bearing capacity; analyzing the docking construction characteristics of the 220-meter basket arch bridge segment according to the docking construction process; identifying the convenient construction influencing factors and error tolerance of the 220-meter basket arch bridge segment based on the docking construction characteristics; determining the segment docking position of the 220-meter basket arch bridge segment in combination with the bearing capacity, the convenient construction influencing factors and the error tolerance.

[0117] Among them, the segment docking point refers to the point or area where the arch bridge segments are connected to each other, the stress condition refers to the distribution and size of the force borne by the docking point under different loads, the arch bridge bearing capacity refers to the ability of the arch bridge to withstand the maximum force without being damaged under a specific load, the docking construction process refers to the method and technique used to achieve precise docking between arch bridge segments during the construction process, the docking construction characteristics refer to the characteristics of the docking construction process, such as construction speed, construction safety, segment docking accuracy requirements, etc., the factors affecting construction convenience refer to the factors that may affect the smooth progress of the construction process, and the error tolerance refers to the range of deviations in the size or position of the arch bridge segments allowed during the construction process.

[0118] Optionally, the stress analysis of the segment docking point can be implemented using structural analysis software, such as Ansys software; based on the stress conditions, the arch bridge bearing capacity analysis corresponding to the 220-meter basket handle arch bridge segment can be determined by material strength, structural geometry and connection method; based on the docking construction characteristics, the identification of factors affecting the convenient construction of the 220-meter basket handle arch bridge segment can be implemented using principal component analysis; based on the docking construction characteristics, the error tolerance analysis of the 220-meter basket handle arch bridge segment can be obtained through the construction specifications and quality control of the basket handle arch bridge.

[0119] The embodiment of the present invention sets up an intelligent monitoring network for the 220-meter basket handle arch bridge segment based on the segment docking position and the docking requirement accuracy, so as to monitor the structural response and docking parameter changes during the construction process in real time and provide real-time data support for the construction. The intelligent monitoring network refers to a system that uses advanced information technology and sensor equipment to monitor and manage the docking construction of the basket handle arch bridge segment in real time.

[0120] As an embodiment of the present invention, the intelligent monitoring network of the 220-meter basket handle arch bridge segment is set up based on the segment docking position and the docking requirement accuracy, including: configuring a parameter sensing device of the 220-meter basket handle arch bridge segment based on the segment docking position; collecting docking construction data of the 220-meter basket handle arch bridge segment according to the parameter sensing device; extracting key data types of the docking construction data based on the docking requirement accuracy; identifying key parameter categories of the key data types, and defining an abnormality judgment baseline for the key parameter category; setting a docking abnormality feedback mechanism for the 220-meter basket handle arch bridge segment based on the abnormality judgment baseline; and setting up an intelligent monitoring network for the 220-meter basket handle arch bridge segment in combination with the parameter sensing device, the abnormality judgment baseline and the docking abnormality feedback mechanism.

[0121] Among them, the parameter sensing device refers to various sensors installed on the bridge segments, such as strain sensors, displacement sensors, acceleration sensors, etc.; the docking construction data refers to all relevant data collected by the parameter sensing device during the docking process of the bridge segments; the key data type refers to data attributes that have a significant impact on the precise docking and installation of the 220-meter basket arch bridge segments, such as displacement data; the key parameter category refers to key parameters that affect the precise docking and installation of the 220-meter basket arch bridge segments, such as the stress parameters of the main arch segments; the abnormal judgment baseline refers to a reference value used to judge whether the construction parameters are within the normal range; the docking abnormal feedback mechanism refers to a system that can promptly issue alarms and feedback to the construction team when an abnormal situation is detected.

[0122] Optionally, based on the segment docking position, the parameter sensing device configuration of the 220-meter basket handle arch bridge segment can be implemented by using a sensor, such as a strain sensor, the key parameter category identification of the key data type can be determined by calculation through a correlation degree formula, the abnormal judgment baseline definition of the key parameter category can be implemented using historical data of the docking construction of the basket handle arch bridge segment, and based on the abnormal judgment baseline, the docking abnormality feedback mechanism setting of the 220-meter basket handle arch bridge segment can be obtained by developing a mobile application and a notification system.

[0123] S4. Identify the docking interface of the 220-meter basket handle arch bridge segment, and identify the interface segment of the docking interface. According to the intelligent monitoring network, collect the docking angle and displacement parameters of the interface segment. Based on the docking angle, the displacement parameters and the required docking accuracy, set the docking error adjustment mechanism of the 220-meter basket handle arch bridge segment.

[0124] The embodiment of the present invention can determine the areas that need special attention in the docking construction of the basket handle arch bridge segments by identifying the docking interfaces of the 220-meter basket handle arch bridge segments and identifying the interface segments of the docking interfaces, thereby ensuring the construction quality and accuracy of these areas. The docking interfaces refer to the areas where the arch bridge segments are interconnected, and the interface segments constitute the various parts of the docking interfaces, such as arch ribs, beams, etc.

[0125] Optionally, the docking interface and interface segment identification of the 220-meter basket handle arch bridge segment can be achieved using a total station.

[0126] Furthermore, the embodiment of the present invention can ensure that the docking process meets the design requirements and the required docking accuracy by collecting the docking angle and displacement parameters of the interface segment according to the intelligent monitoring network, so as to avoid error accumulation and ensure construction quality. The docking angle refers to the relative angle between the two segments during the docking process, and the displacement parameter refers to the displacement of the basket arch bridge segment during the docking process, including vertical displacement and horizontal displacement.

[0127] Optionally, according to the intelligent monitoring network, the acquisition of the docking angle of the interface segment can be achieved by using an angle sensor, and according to the intelligent monitoring network, the acquisition of the displacement parameter of the interface segment can be determined by a displacement sensor.

[0128] The embodiment of the present invention sets a docking error adjustment mechanism for the 220-meter basket-handled arch bridge segment based on the docking angle, the displacement parameter and the required docking accuracy, which allows the construction team to make timely adjustments when deviations are found to improve docking accuracy. It can also reduce manual intervention, speed up construction progress and improve construction efficiency. The docking error adjustment mechanism refers to a technology that automatically adjusts construction parameters according to real-time monitoring data during the docking construction of the basket-handled arch bridge segment to reduce docking errors.

[0129] As an embodiment of the present invention, the docking error adjustment mechanism of the 220-meter basket-lift arch bridge segment is set based on the docking angle, the displacement parameter and the required docking accuracy, including: identifying the normal movement trajectory of the docking angle and the displacement parameter based on the required docking accuracy; analyzing the docking error trend of the 220-meter basket-lift arch bridge segment according to the normal movement trajectory; extracting the docking behavior characteristics of the 220-meter basket-lift arch bridge segment based on the docking error trend; identifying the bridge-building effect of the 220-meter basket-lift arch bridge segment according to the docking behavior characteristics; constructing a performance analysis model of the bridge-building effect; setting a docking effect verification system for the 220-meter basket-lift arch bridge segment based on the performance analysis model; and setting the docking error adjustment mechanism of the 220-meter basket-lift arch bridge segment according to the docking effect verification system.

[0130] Among them, the normal motion trajectory refers to the trajectory that the docking angle and displacement parameters should follow under ideal conditions without errors, the docking error trend refers to the overall direction or pattern after the docking angle and displacement parameters deviate from the normal motion trajectory, the docking behavior characteristics refer to indicators that reflect the characteristics of the docking process of the basket-handled arch bridge segments, the bridge completion effect refers to the overall performance and appearance of the basket-handled arch bridge segments after the docking is completed, the performance analysis model refers to a model used to simulate and predict the performance results of the bridge under various load conditions, and the docking effect verification system refers to a mechanism used to evaluate and verify whether the overall effect after the bridge segments are docked meets the design and safety requirements.

[0131] Optionally, the identification of normal motion trajectory of the docking angle and the displacement parameters based on the required docking accuracy can be achieved using simulation software, and the docking error trend analysis of the 220-meter basket handle arch bridge segment based on the normal motion trajectory can be obtained through a trend analysis model, such as a polynomial regression model, and the construction of a performance analysis model for the bridge completion effect can be achieved using a fuzzy comprehensive evaluation method; based on the performance analysis model, the docking effect verification system setting of the 220-meter basket handle arch bridge segment can be determined by the difference between the actual output and the expected output.

[0132] S5. Analyze the factors affecting the docking of the 220-meter basket-handled arch bridge segment, identify the potential bridge construction risks of the 220-meter basket-handled arch bridge segment based on the docking factors, and construct a docking behavior judgment model for the 220-meter basket-handled arch bridge segment according to the potential bridge construction risks.

[0133] By analyzing the influencing factors of the docking of the 220-meter basket handle arch bridge segments, the embodiment of the present invention can identify the key factors that have a significant impact on the construction quality and construction efficiency of the docking of the basket handle arch bridge segments. The docking influencing factors refer to variables that may affect the docking process and the final docking quality, such as material properties, environmental conditions, etc.

[0134] Optionally, the analysis of factors affecting the docking of the 220-meter basket handle arch bridge segment can be achieved by analyzing historical construction data using a machine learning model, such as a support vector machine model.

[0135] Furthermore, the embodiment of the present invention can identify the potential bridge construction risks of the 220-meter basket-handled arch bridge segment based on the docking influencing factors, so as to discover possible risks in advance and take corresponding preventive measures to reduce the possibility of risks. The potential bridge construction risks refer to the situation in which during the docking process of the basket-handled arch bridge segment, due to the influence of various factors, the bridge may have safety hazards after completion.

[0136] As an embodiment of the present invention, the identifying of the potential bridge construction risk of the 220-meter basket handle arch bridge segment based on the docking influencing factors includes: identifying the factor type of the docking influencing factors, and calculating the correlation coefficient between the factor types; according to the factor type, collecting the classified data corresponding to the 220-meter basket handle arch bridge segment, and extracting the data feature type of the classified data; based on the data feature type, analyzing the data development pattern of the classified data; according to the correlation coefficient and the data development pattern, identifying the risk occurrence type of the 220-meter basket handle arch bridge segment; analyzing the risk results corresponding to the risk occurrence type; identifying the probability distribution of the docking influencing factors, and based on the probability distribution, analyzing the risk occurrence probability of the 220-meter basket handle arch bridge segment; combining the risk occurrence type, the risk result and the risk occurrence probability, identifying the potential bridge construction risk of the 220-meter basket handle arch bridge segment.

[0137] Among them, the factor type refers to the classification of docking influencing factors, such as construction process factors, material factors, environmental factors, etc., the correlation coefficient refers to the strength value of measuring the relationship between different factor types, the classified data refers to the data related to the 220-meter basket arch bridge segment collected according to the factor type, such as construction records, material inspection reports, environmental monitoring data, etc., the data feature type refers to the manifestation of classified data in different aspects, such as numerical features, time-demand features, etc. The data development pattern refers to the changing rules and trends of classified data over time or other variables, such as quality problems caused by a specific material combination, the risk occurrence type refers to the type of risk that may occur identified based on the correlation coefficient and the data development pattern, such as structural failure risk, construction safety risk, etc., the risk result refers to the possible consequences after the risk occurs, such as damage to the bridge structure, the probability distribution refers to the distribution of the possibility of occurrence of docking influencing factors, and the risk occurrence probability refers to the possibility of risk occurring in the 220-meter basket arch bridge segment.

[0138] Optionally, based on the data feature type, the data development pattern analysis of the classified data can be determined by time series analysis, the probability distribution identification of the docking influencing factors can be achieved by probability analysis, and based on the probability distribution, the risk occurrence probability analysis of the 220-meter basket arch bridge segment can be obtained through a risk assessment model.

[0139] In an optional embodiment of the present invention, the correlation coefficient between the factor types is calculated using the following formula:

[0140]

[0141] Among them, G represents the correlation coefficient between factor types, e represents the index number of factor pairs in factor types, n′ represents the number of factor pairs in factor types, S e represents the weight of the e-th factor pair, F e represents the relationship score of the e-th factor pair, g represents the factor index in the factor type, m represents the total number of factors in the factor type, and E g Indicates the actual weight value of the g-th factor type.

[0142] Furthermore, the embodiment of the present invention constructs a docking behavior judgment model of the 220-meter basket-handled arch bridge segment according to the potential bridge construction risks, which can accurately judge and analyze the docking behavior, help construction personnel to better understand the various parameters and changes in the docking process, thereby improving the docking accuracy and ensuring the precise installation of the arch bridge segment. The docking behavior judgment model refers to a model tool for evaluating and judging the docking behavior of the 220-meter basket-handled arch bridge segment.

[0143] As an embodiment of the present invention, the docking behavior judgment model of the 220-meter basket-handled arch bridge segment is constructed according to the potential bridge construction risk, including: identifying the risk level of the potential bridge construction risk, and identifying the key docking influencing factors of the 220-meter basket-handled arch bridge segment according to the risk level; extracting the reduced-dimensionality docking behavior characteristics of the 220-meter basket-handled arch bridge segment based on the key docking influencing factors; identifying the key segment parts corresponding to the reduced-dimensionality docking behavior characteristics; setting the target point behavior detection mechanism of the 220-meter basket-handled arch bridge segment according to the key segment parts; defining the detection index type of the target point behavior detection mechanism based on the reduced-dimensionality docking behavior characteristics and the key docking influencing factors; and constructing the docking behavior judgment model of the 220-meter basket-handled arch bridge segment in combination with the target point behavior detection mechanism and the detection index type.

[0144] Among them, the risk level refers to the level for dividing the severity of potential bridge construction risks, the key docking influencing factors refer to the factors that have an important influence on the docking process of the 220-meter basket arch bridge segments, the dimensionality reduction docking behavior characteristics refer to the key behavior characteristics in the docking process of the 220-meter basket arch bridge segments, the key segment parts refer to the key influencing parts of the arch bridge segments for segment docking, such as arch ribs, the target point behavior detection mechanism refers to a method and system for detecting and monitoring the behavior of specific target points, and the detection indicator type refers to the specific indicator type used to measure and evaluate the target point behavior detection results, such as displacement, stress distribution, etc.

[0145] Optionally, the risk level identification of the potential bridge completion risk can be determined by a qualitative evaluation method, the dimensionality reduction docking behavior feature extraction of the 220-meter basket-handled arch bridge segment based on the key docking influencing factors can be achieved by using data dimensionality reduction technology, such as principal component analysis technology, and the target point behavior detection mechanism setting of the 220-meter basket-handled arch bridge segment according to the key segment position can be obtained by a multi-target tracking algorithm, such as the DeepSORT algorithm.

[0146] S6. In combination with the docking error adjustment mechanism, the intelligent monitoring network and the docking behavior judgment model, the docking installation process of the 220-meter basket arch bridge segment is executed to obtain a docking installation result.

[0147] The embodiment of the present invention combines the docking error adjustment mechanism, the intelligent monitoring network and the docking behavior judgment model to perform the docking installation processing of the 220-meter basket arch bridge segment to obtain the docking installation result. The error in the docking process can be monitored and adjusted in real time to ensure the docking accuracy of the arch bridge segment, and potential safety hazards can be discovered in advance and corresponding measures can be taken to prevent them, thereby enhancing the safety of the construction process. It also helps to reduce the possibility of material waste, rework and accidents, and reduce construction costs and risks. The docking installation process refers to the operation process of connecting and installing the various segments of the 220-meter basket arch bridge, such as adjusting the position and angle of the segments. The docking installation result refers to the overall state and performance of the 220-meter basket arch bridge segment after the docking installation process, including the connection quality between the segments, the stability of the overall structure, etc.

[0148] It can be seen that the embodiment of the present invention constructs a three-dimensional segment model of the 220-meter basket arch bridge segment based on the three-dimensional point cloud data, and can use the structural analysis results of the basket arch bridge segment to evaluate the performance of the segment under different load conditions; further, the embodiment of the present invention analyzes the segment docking effect of the 220-meter basket arch bridge segment based on the three-dimensional segment model to identify the docking requirement accuracy of the 220-meter basket arch bridge segment, and can simulate the docking installation of the basket arch bridge segment in advance to ensure that the segment can be accurately docked, reduce on-site adjustment work, and improve docking efficiency; secondly, the embodiment of the present invention sets the intelligent monitoring network of the 220-meter basket arch bridge segment based on the segment docking position and the docking requirement accuracy, which can monitor the structural response and docking parameter changes during the construction process in real time, and provide real-time data support for construction; thirdly, the embodiment of the present invention sets the docking error adjustment mechanism of the 220-meter basket arch bridge segment based on the docking angle, the displacement parameter and the docking requirement accuracy, The construction team can be allowed to make timely adjustments when deviations are found, thereby improving docking accuracy, and can also reduce manual intervention, speed up construction progress, and improve construction efficiency. Furthermore, the embodiment of the present invention can accurately judge and analyze docking behavior by constructing a docking behavior judgment model for the 220-meter basket arch bridge segment according to the potential bridge risk, thereby helping construction personnel to better grasp the various parameters and changes in the docking process, thereby improving the docking accuracy and ensuring the accurate installation of the arch bridge segment. Finally, the embodiment of the present invention performs the docking installation processing of the 220-meter basket arch bridge segment by combining the docking error adjustment mechanism, the intelligent monitoring network, and the docking behavior judgment model to obtain the docking installation result, which can monitor and adjust the error in the docking process in real time, ensure the docking accuracy of the arch bridge segment, and discover potential safety hazards in advance, and take corresponding measures to prevent them, thereby enhancing the safety of the construction process, and also helping to reduce the possibility of material waste, rework, and accidents, and reduce construction costs and risks. Therefore, the 220-meter basket arch bridge segment precise docking installation method proposed by the present invention can improve the docking accuracy and docking construction efficiency of the basket arch bridge segment.

[0149] like Figure 2 As shown, it is a system functional module diagram of the precise docking and installation of the 220-meter basket arch bridge segments of the present invention.

[0150] The 220-meter basket arch bridge segment precise docking installation system 200 of the present invention can be installed in an electronic device. According to the functions to be implemented, the 220-meter basket arch bridge segment precise docking installation system can include a three-dimensional model building module 201, a required accuracy identification module 202, an intelligent monitoring module 203, a docking error adjustment module 204, a docking behavior judgment module 205, and a docking installation module 206. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0151] In the embodiment of the present invention, the functions of each module / unit are as follows:

[0152] A three-dimensional model building module is used to obtain a 220-meter basket handle arch bridge segment to be docked, collect three-dimensional point cloud data of the 220-meter basket handle arch bridge segment, and build a three-dimensional segment model of the 220-meter basket handle arch bridge segment based on the three-dimensional point cloud data;

[0153] A required accuracy identification module is used to analyze the segment docking effect of the 220-meter basket handle arch bridge segment based on the three-dimensional segment model, and identify the required docking accuracy of the 220-meter basket handle arch bridge segment according to the segment docking result;

[0154] An intelligent monitoring module is used to collect the segment type of the 220-meter basket arch bridge segment, determine the segment docking position of the 220-meter basket arch bridge segment according to the segment type, and set the intelligent monitoring network of the 220-meter basket arch bridge segment based on the segment docking position and the docking requirement accuracy;

[0155] A docking error adjustment module is used to identify the docking interface of the 220-meter basket arch bridge segment and the interface segment of the docking interface, collect the docking angle and displacement parameters of the interface segment according to the intelligent monitoring network, and set the docking error adjustment mechanism of the 220-meter basket arch bridge segment based on the docking angle, the displacement parameters and the docking required accuracy;

[0156] A docking behavior judgment module is used to analyze the docking influencing factors of the 220-meter basket handle arch bridge segment, identify the potential bridge completion risk of the 220-meter basket handle arch bridge segment based on the docking influencing factors, and construct a docking behavior judgment model for the 220-meter basket handle arch bridge segment according to the potential bridge completion risk;

[0157] The docking installation module is used to combine the docking error adjustment mechanism, the intelligent monitoring network and the docking behavior judgment model to perform the docking installation processing of the 220-meter basket arch bridge segment and obtain the docking installation result.

[0158] In detail, the modules in the 220-meter basket arch bridge segment precise docking installation system 200 described in the embodiment of the present invention are used in the same manner as described above. Figure 1 The same technical means are used as the method for precise docking and installation of the 220-meter basket arch bridge segments described in the specification and can produce the same technical effects, so I will not go into details here.

[0159] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0160] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for precise docking and installation of 220-meter basket arch bridge segments, characterized in that: The method comprises: Acquire a 220-meter basket handle arch bridge segment to be docked, collect three-dimensional point cloud data of the 220-meter basket handle arch bridge segment, and construct a three-dimensional segment model of the 220-meter basket handle arch bridge segment based on the three-dimensional point cloud data; Based on the three-dimensional segment model, the segment docking effect of the 220-meter basket arch bridge segment is analyzed, and according to the segment docking result, the required docking accuracy of the 220-meter basket arch bridge segment is identified; The segment types of the 220-meter basket handle arch bridge segments are collected, and according to the segment types, segment docking positions of the 220-meter basket handle arch bridge segments are determined, and based on the segment docking positions and the docking requirement accuracy, an intelligent monitoring network of the 220-meter basket handle arch bridge segments is set; Identify the docking interface of the 220-meter basket arch bridge segment, and identify the interface segment of the docking interface, collect the docking angle and displacement parameters of the interface segment according to the intelligent monitoring network, and set the docking error adjustment mechanism of the 220-meter basket arch bridge segment based on the docking angle, the displacement parameters and the docking required accuracy; Analyze the docking influencing factors of the 220-meter basket arch bridge segment, identify the potential bridge construction risk of the 220-meter basket arch bridge segment based on the docking influencing factors, and construct a docking behavior judgment model for the 220-meter basket arch bridge segment according to the potential bridge construction risk; In combination with the docking error adjustment mechanism, the intelligent monitoring network and the docking behavior judgment model, the docking installation process of the 220-meter basket handle arch bridge segment is executed to obtain the docking installation result.

2. The method according to claim 1, characterized in that The three-dimensional segment model of the 220-meter basket arch bridge segment is constructed based on the three-dimensional point cloud data, including: Execute data splicing processing of the three-dimensional point cloud data to obtain spliced ​​point cloud data; Extracting key features of the 220-meter basket arch bridge segment from the spliced ​​point cloud data; Based on the key features, reconstruct the segmental surface of the 220-meter basket arch bridge segment; According to the segment surface, a polygonal grid of the 220-meter basket arch bridge segment is generated; Based on the polygonal grid, identifying structural elements of the 220-meter basket arch bridge segment; The segment surface, the polygonal mesh and the structural element are combined to construct a three-dimensional segment model of the 220-meter basket handle arch bridge segment.

3. The method according to claim 1, characterized in that The segment docking effect of the 220-meter basket arch bridge segment is analyzed based on the three-dimensional segment model, including: identifying a classified segment model of the three-dimensional segment model; Extracting the contact boundary of the classified segment model, and identifying the butt joint surface of the 220-meter basket arch bridge segment according to the contact boundary; Calculating the geometric matching degree of the butt joint surface; Based on the geometric matching degree, determining the docking position of the classification segment model; In combination with the docking surface and the docking position, the segment docking effect of the 220-meter basket handle arch bridge segment is analyzed.

4. The method according to claim 1, characterized in that: The step of identifying the required docking accuracy of the 220-meter basket arch bridge segment according to the segment docking result includes: According to the segment docking results, the docking segments of the 220-meter basket arch bridge segments are identified; calculating the contact area between the docking segments; Based on the contact area, identifying a dimensional fit of the docking segments; Calculating the docking deviation degree of the docking segment according to the size fit; identifying a butt joint surface of the butt joint segment and measuring the surface flatness of the butt joint surface; Identify the segment joints of the 220-meter basket arch bridge segment; Based on the segment joints, the load performance of the 220-meter basket arch bridge segment was analyzed; According to the load performance, identifying the structural stability of the segment joint; The docking requirement accuracy of the 220-meter basket arch bridge segment is identified by combining the docking deviation degree, the surface flatness and the structural stability.

5. The method according to claim 1, characterized in that Determining the segment docking position of the 220-meter basket arch bridge segment according to the segment type includes: According to the segment type, identifying the segment docking point of the 220-meter basket arch bridge segment; Analyze the stress conditions of the segment joints; According to the stress conditions, the arch bridge bearing capacity corresponding to the 220-meter basket arch bridge segment is analyzed; Based on the bearing capacity of the arch bridge, identify the butt joint construction process of the 220-meter basket arch bridge segment; According to the butt joint construction process, the butt joint construction characteristics of the 220-meter basket arch bridge segment are analyzed; Based on the docking construction characteristics, identifying the factors affecting the convenient construction and the error tolerance of the 220-meter basket arch bridge segment; In combination with the bearing capacity, the factors affecting the convenient construction and the error tolerance, the segment docking positions of the 220-meter basket arch bridge segments are determined.

6. The method according to claim 1, characterized in that The intelligent monitoring network of the 220-meter basket arch bridge segment is set based on the segment docking position and the docking required accuracy, including: Based on the segment docking position, a parameter sensing device of the 220-meter basket arch bridge segment is configured; According to the parameter sensing device, the docking construction data of the 220-meter basket arch bridge segment is collected; Based on the docking requirement accuracy, extracting key data types of the docking construction data; Identify key parameter categories of the key data types, and define abnormality judgment baselines for the key parameter categories; Based on the abnormality judgment baseline, a docking abnormality feedback mechanism for the 220-meter basket arch bridge segment is set; In combination with the parameter sensing device, the abnormality judgment baseline and the docking abnormality feedback mechanism, an intelligent monitoring network for the 220-meter basket arch bridge segment is set up.

7. The method according to claim 1, characterized in that The docking error adjustment mechanism of the 220-meter basket arch bridge segment is set based on the docking angle, the displacement parameter and the docking required accuracy, including: Based on the required docking accuracy, identifying the normal motion trajectory of the docking angle and the displacement parameter; According to the normal motion trajectory, the docking error trend of the 220-meter basket arch bridge segment is analyzed; Based on the docking error trend, the docking behavior characteristics of the 220-meter basket arch bridge segment are extracted; According to the docking behavior characteristics, the bridge completion effect of the 220-meter basket arch bridge segment is identified; Constructing a performance analysis model of the bridge-building effect; Based on the performance analysis model, a docking effect verification system for the 220-meter basket arch bridge segment is set up; According to the docking effect verification system, a docking error adjustment mechanism for the 220-meter basket arch bridge segment is set up.

8. The method according to claim 1, characterized in that Based on the docking influencing factors, the potential bridge completion risks of the 220-meter basket arch bridge segment are identified, including: Identifying the factor types of the docking influencing factors, and calculating the correlation coefficients between the factor types; According to the factor type, the classification data corresponding to the 220-meter basket arch bridge segment is collected, and the data feature type of the classification data is extracted; Analyzing a data development pattern of the classified data based on the data feature type; According to the correlation coefficient and the data development pattern, the risk occurrence type of the 220-meter basket arch bridge segment is identified; Analyze the risk results corresponding to the risk occurrence type; Identify the probability distribution of the docking influencing factors, and analyze the risk probability of the 220-meter basket arch bridge segment based on the probability distribution; Based on the risk occurrence type, risk consequence and risk occurrence probability, the potential bridge completion risk of the 220-meter basket arch bridge segment is identified.

9. The method according to claim 1, characterized in that: According to the potential bridge completion risk, a docking behavior judgment model of the 220-meter basket arch bridge segment is constructed, including: Identify the risk level of the potential bridge completion risk, and based on the risk level, identify the key docking influencing factors of the 220-meter basket arch bridge segment; Based on the key docking influencing factors, the dimension reduction docking behavior characteristics of the 220-meter basket arch bridge segment are extracted; Identifying the key segment parts corresponding to the dimensionality reduction docking behavior characteristics; According to the key segment position, a target point behavior detection mechanism for the 220-meter basket arch bridge segment is set; Based on the dimension reduction docking behavior characteristics and the key docking influencing factors, defining the detection indicator type of the target point behavior detection mechanism; In combination with the target point behavior detection mechanism and the detection index type, a docking behavior judgment model for the 220-meter basket arch bridge segment is constructed. 10.220m basket arch bridge segment precise docking installation system, characterized by: The system comprises: A three-dimensional model building module is used to obtain a 220-meter basket handle arch bridge segment to be docked, collect three-dimensional point cloud data of the 220-meter basket handle arch bridge segment, and build a three-dimensional segment model of the 220-meter basket handle arch bridge segment based on the three-dimensional point cloud data; A required accuracy identification module is used to analyze the segment docking effect of the 220-meter basket handle arch bridge segment based on the three-dimensional segment model, and identify the required docking accuracy of the 220-meter basket handle arch bridge segment according to the segment docking result; An intelligent monitoring module is used to collect the segment type of the 220-meter basket arch bridge segment, determine the segment docking position of the 220-meter basket arch bridge segment according to the segment type, and set the intelligent monitoring network of the 220-meter basket arch bridge segment based on the segment docking position and the docking requirement accuracy; A docking error adjustment module is used to identify the docking interface of the 220-meter basket arch bridge segment and the interface segment of the docking interface, collect the docking angle and displacement parameters of the interface segment according to the intelligent monitoring network, and set the docking error adjustment mechanism of the 220-meter basket arch bridge segment based on the docking angle, the displacement parameters and the docking required accuracy; A docking behavior judgment module is used to analyze the docking influencing factors of the 220-meter basket handle arch bridge segment, identify the potential bridge completion risk of the 220-meter basket handle arch bridge segment based on the docking influencing factors, and construct a docking behavior judgment model for the 220-meter basket handle arch bridge segment according to the potential bridge completion risk; The docking installation module is used to combine the docking error adjustment mechanism, the intelligent monitoring network and the docking behavior judgment model to perform the docking installation processing of the 220-meter basket arch bridge segment and obtain the docking installation result.

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