Automatic wharf control method and system

Abstract

The invention relates to an automatic wharf control method and system, and the method builds communication connection with a database of a center line of a supporting tube composite structure, and achieves the real-time acquisition of a video stream and the acquisition of factory original data of the supporting tube composite structure. And selecting the structure three-dimensional data of the center line of the supporting pipe composite structure of the data database, and acquiring real-time monitoring on the steel tower of the wharf by using real-time video streaming. And performing vector analysis on the three-dimensional data of the structure by using a topological algorithm to obtain a data vector of the central line of the selected support tube combined structure, and bringing the data vector into an analysis script based on the data vector and the target bearing upper limit of the tube wall of the support tube to obtain a tube wall parameter of the central line of each support tube combined structure. The pipe wall parameter of the center line of each supporting pipe combined structure is compared with the factory original data of the supporting pipe combined structure, so that whether the steel tower of the wharf is in a safe working range or not can be determined in real time with high precision, and the steel tower can be determined to be in a metal fatigue credible range.

Description

Technical Field

[0001] This application relates to the field of computer technology, and particularly to a wharf automation control method and system. Background Art

[0002] During the process of lifting goods at the wharf, the structural strength of the steel tower is the guarantee for safely lifting goods. With the increasing level of automation and mechanization, more and more wharves adopt self-identification technical solutions to realize real-time monitoring of the structural strength of the steel tower. Due to the complex magnetic field environment and electric field environment at the wharf, most equipment R & D manufacturers are difficult to accurately and real-time monitor the structural strength of the steel tower at the wharf. Therefore, it is necessary to propose a wharf automation control method for the defect of low accuracy of the monitoring results of traditional wharf automatic monitoring technology. Summary of the Invention

[0003] Based on this, it is necessary to solve the current dilemma that the supporting pipe is heavy in weight while the supporting structural strength is small, and large-load professional transportation equipment is required, and to propose a wharf automation control method and system.

[0004] On the one hand, this application relates to a wharf automation control method, including:

[0005] Establish a communication connection with the database of the center line of the supporting pipe combined structure; the database of the center line of the supporting pipe combined structure is a data database;

[0006] Select the structural three-dimensional data of the center line of the supporting pipe combined structure in the data database; the structural three-dimensional data includes cloud point data and position data;

[0007] Use a topological algorithm to perform vector analysis on the structural three-dimensional data;

[0008] Obtain the data vector of the selected center line of the supporting pipe combined structure;

[0009] Return the structural three-dimensional data of the center line of the selected supporting pipe combined structure in the data database until all the structural three-dimensional data is selected;

[0010] Based on the data vector and the target bearing capacity upper limit of the supporting pipe wall, incorporate the data vector into the analysis script;

[0011] Obtain the wall parameters of each center line of the supporting pipe combined structure.

[0012] Further, based on the type of its own device, determine whether its own device type is a server device;

[0013] If its own device type is a server device, establish a communication connection with the database of the center line of the supporting pipe combined structure based on the loaded driver program;

[0014] If the type of its own device is a personal computer device, then based on configuring the ODBC data source, implement establishing a communication connection with the database of the center line of the support pipe combined structure;

[0015] If the type of its own device is a single-chip microcomputer device, then based on the API interface, implement establishing a communication connection with the database of the center line of the support pipe combined structure.

[0016] Furthermore, based on the data stream, use a data replication program to back up its own real-time data;

[0017] Based on the communication connection between its own device and the database of the center line of the support pipe combined structure, synchronize its own real-time data with the data in the material database.

[0018] Furthermore, use the point cloud three-dimensional environment to receive each cloud point data;

[0019] Select a cloud point data;

[0020] Based on the position data in the cloud point data, mark the selected three-dimensional point cloud in the point cloud three-dimensional environment;

[0021] Return the selected one cloud point data until all cloud point data has been selected.

[0022] Furthermore, based on the characteristic wavelength band of the cloud point data, determine whether the data source of the cloud point data is a structured light device;

[0023] If the data source of the cloud point data is a structured light device, then calculate the depth value of the object surface according to information such as the deformation of the structured light;

[0024] If the data source of the cloud point data is not a structured light device, then incorporate the point cloud three-dimensional environment into the RGB-D analysis program.

[0025] Furthermore, the topological algorithm includes one or more of the Poisson surface reconstruction algorithm and the Delaunay triangulation algorithm.

[0026] Furthermore, receive cloud point data whose data source is a structured light device;

[0027] Determine the API of the cloud point data whose data source is a structured light device;

[0028] Based on the determined API and the Poisson surface reconstruction algorithm, obtain the three-dimensional structure data for vector analysis.

[0029] Furthermore, receive the point cloud three-dimensional environment in the RGB-D analysis program;

[0030] Determine the connection function of the point cloud three-dimensional environment in the RGB-D analysis program;

[0031] Based on the connection function and the Delaunay triangulation algorithm, three-dimensional data of the structure is obtained for vector analysis.

[0032] Furthermore, based on the elastic modulus reduction algorithm, the target force range of the three-dimensional data of the center line of the support pipe combined structure is obtained;

[0033] Using the generalized yield function and the target force range, the upper limit of the target bearing capacity of the support pipe wall is determined.

[0034] The data vector and the upper limit of the target bearing capacity of the support pipe wall are incorporated into the finite element analysis algorithm;

[0035] Based on the load increase script of the finite element analysis algorithm, the geometric structure shape of the support pipe wall is determined.

[0036] On the other hand, the present application also provides a dock automation control system, including a processing component and a computing component, where the dock automation control method described in any one of the foregoing is executed by the processing component, and data calculation is executed by the computing component.

[0037] The present application relates to a dock automation control method and system. By establishing a communication connection with the database of the center line of the support pipe combined structure, real-time video stream acquisition and acquisition of the original data of the support pipe combined structure at the factory site are realized. The three-dimensional data of the center line of the support pipe combined structure in the selected data database can be used to perform real-time monitoring of the steel tower of the dock by using the real-time video stream acquisition. Using the topology algorithm to perform vector analysis on the three-dimensional data of the structure, a data vector of the selected center line of the support pipe combined structure is obtained. Based on the data vector and the upper limit of the target bearing capacity of the support pipe wall, the data vector is incorporated into the analysis script to obtain the wall parameters of each center line of the support pipe combined structure. Comparing the wall parameters of each center line of the support pipe combined structure with the original data of the support pipe combined structure at the factory site can accurately determine in real time whether the steel tower of the dock is within the safe working range, and can also determine the credible range of the steel tower in metal fatigue. Description of the Drawings

[0038] Figure 1 It is a schematic flowchart of a dock automation control method provided by an embodiment of the present application.

[0039] Figure 2 It is a schematic system structure diagram of a dock automation control system provided by an embodiment of the present application.

[0040] Description of the Drawings: 100. Processing component; 200. Computing component. Detailed Embodiments

[0041] In order to make the objectives, technical solutions, and advantages of the present application clearer and more understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0042] The present application provides a method for automatic control of a dock.

[0043] As Figure 1 shown, in an embodiment of the present application, a method for automatic control of a dock includes:

[0044] S100, establish a communication connection with the database of the center line of the support pipe combined structure.

[0045] Specifically, the database of the center line of the support pipe combined structure is a data database.

[0046] Based on the type of its own device, determine whether its own device type is a server device. If its own device type is a server device, establish a communication connection with the database of the center line of the support pipe combined structure based on loading the driver program. If its own device type is a personal computer device, establish a communication connection with the database of the center line of the support pipe combined structure based on configuring the ODBC data source. If its own device type is a single-chip microcomputer device, establish a communication connection with the database of the center line of the support pipe combined structure based on the API interface.

[0047] More specifically, use JDBC (Java Database Connectivity), load the driver program, and load the database driver to be used through the Class.forName() method, such as Class.forName("com.mysql.cj.jdbc.Driver").

[0048] Establish a connection, use the DriverManager.getConnection() method, and pass in the URL, username, and password of the database to establish a connection. For example, to connect to a local MySQL database, it can be written as Connection connec = DriverManager.getConnection("jdbc:mysql: / / localhost:3306 / mydatabase", "username", "password").

[0049] Execute an SQL query, create a Statement or PreparedStatement object to execute the SQL query, and process the result set.

[0050] Use ODBC, Open Database Connectivity, to configure the ODBC data source, load the ODBC driver, and establish a connection.

[0051] It is understandable that based on the data stream, a data replication program is used to back up its own real-time data. Based on the communication connection of the database with the combined structure center line of its own device and the support pipe, the real-time data of itself is synchronized with the data of the material database.

[0052] Create a database link. Utilize the link function provided by the database system itself, such as the Database Link in the Oracle database, to create a link from one database to another in a database.

[0053] Access the remote database. Through the created link, queries and operations on the remote database can be executed in the local database to achieve data sharing and communication.

[0054] ETL tool: ETL is the abbreviation of Extract, Transform, and Load, mainly used for data integration and data warehouse construction. Through the ETL tool, data in one database can be extracted, after necessary transformation, loaded into another database to achieve data synchronization and sharing. At the same time, data can be cleaned and processed during the data transformation process to improve data quality.

[0055] Data replication tool: A tool used to replicate data in a database in real time or regularly, such as MySQL's replication, Oracle's Data Guard, SQL Server's Replication, etc. It can achieve real-time data synchronization to ensure data consistency, and can also be used for database backup to improve data security and reliability.

[0056] S200, select the three-dimensional structure data of the center line of the support pipe combination structure of the material database.

[0057] Specifically, the three-dimensional structure data includes cloud point data and position data.

[0058] Utilize the point trace three-dimensional environment to receive each cloud point data. Select one cloud point data. Based on the position data in the cloud point data, mark the selected three-dimensional point cloud in the point trace three-dimensional environment. Return the selected one cloud point data until all cloud point data is selected.

[0059] The data acquisition device includes a structured light device and an RGB-D camera.

[0060] Structured light devices project structured light onto the surface of an object and calculate the depth value of the object surface based on information such as the deformation of the structured light, and then generate a point cloud. Commonly, technologies such as Apple's Face ID project hundreds of thousands of tiny light points onto the human face and analyze the reflection of the light points to construct a three-dimensional point cloud model of the human face.

[0061] It can be understood that based on the characteristic wavelength band of the point cloud data, it is determined whether the data source of the point cloud data is a structured light device. If the data source of the point cloud data is a structured light device, the depth value of the object surface is calculated based on information such as the deformation of the structured light. If the data source of the point cloud data is not a structured light device, the three-dimensional point trace environment is incorporated into the RGB-D analysis program.

[0062] Specifically, an RGB-D camera combines a color camera and a depth sensor, and can simultaneously obtain the color information and depth information of an object to generate a point cloud containing color attributes. It is commonly used in fields such as robot vision and augmented reality to help robots or virtual scenes better understand the surrounding environment.

[0063] S300, uses a topological algorithm to perform vector analysis on the three-dimensional structure data.

[0064] Specifically, the topological algorithm includes one or more of the Poisson surface reconstruction algorithm and the Delaunay triangulation algorithm.

[0065] Receive point cloud data whose data source is a structured light device. Determine the API of the point cloud data whose data source is a structured light device. Based on the determined API and the Poisson surface reconstruction algorithm, obtain the three-dimensional structure data for vector analysis.

[0066] Poisson surface reconstruction algorithm: suitable for objects with closed surfaces, and can generate a closed surface model on a given set of sample points. It is based on the definition of an implicit function and determines the position and shape of the surface by solving the Poisson equation, thereby generating a high-quality point cloud.

[0067] Receive the three-dimensional point trace environment in the RGB-D analysis program. Determine the connection function of the three-dimensional point trace environment in the RGB-D analysis program. Based on the connection function and the Delaunay triangulation algorithm, obtain the three-dimensional structure data for vector analysis.

[0068] Delaunay triangulation algorithm: For a scattered set of points, a Delaunay triangulation network can be constructed to generate a point cloud. The algorithm divides the point set into several non-overlapping triangles such that no other points are contained within the circumcircle of each triangle, thereby enabling the meshing of the point cloud for subsequent analysis and applications.

[0069] Finite Element Analysis (FEA for short) is an important numerical calculation method that decomposes a complex structure or object into a finite number of small elements, which are called finite elements. Each element has a simple shape and mechanical properties. By mathematically modeling and calculating these elements, the behavior of the entire object can be approximately solved. For example, when analyzing a complex mechanical part, it can be divided into numerous elements in the shapes of triangles, quadrilaterals, or hexahedrons, etc.

[0070] Based on basic mechanical principles such as elasticity, plasticity, and fluid mechanics, combined with mathematical methods such as the variational principle and the weighted residual method, a finite element equation system is established, and then an approximate solution to the problem is obtained by solving this equation system.

[0071] The analysis steps of finite element analysis include preprocessing, defining the solution model according to the actual problem, including determining the geometric region of the problem, selecting the element type, defining the material properties, geometric properties, connectivity, basis functions, and boundary conditions and loads of the elements. Assembly and solution, assembling the elements into the total matrix equation of the entire discrete domain. This process includes the assembly of the element stiffness matrix and the formation of the global stiffness matrix, as well as introducing boundary conditions and applying loads. Postprocessing, analyzing and evaluating the obtained solution according to relevant criteria, enabling users to easily extract information and understand the calculation results, such as drawing stress nephograms, deformation diagrams, etc., to intuitively display the stress distribution, displacement changes, etc. of the structure.

[0072] It can be used for structural strength analysis, fatigue analysis, modal analysis, etc. of mechanical parts, helping to optimize part design and improve the performance and reliability of mechanical products. For example, in the strength analysis of a steel tower, potential weak parts can be discovered in advance through finite element analysis for strengthening design.

[0073] Common software includes ANSYS, a widely used finite element analysis software that provides multiple modules, including structural analysis, fluid analysis, electromagnetic field analysis, etc., with powerful functions and a good user interface.

[0074] ABAQUS is suitable for analysis in multiple fields such as structure, heat, electromagnetics, and fluid, and has advantages especially in solving nonlinear problems. Nastran, a classic finite element analysis software, is mainly used for structural analysis, dynamics analysis, thermal analysis, etc. MSC Patran, a commonly used pre- and post-processing software, is compatible with multiple finite element analysis software and can be used for model establishment, load setting, and result post-processing. COMSOL Multiphysics, a multi-physics finite element analysis software, can be used for analysis in multiple fields such as structure, heat, fluid, and electromagnetics.

[0075] S400, obtain the data vector of the center line of the selected support tube combination structure.

[0076] S500, return the structural three-dimensional data of the center line of the support pipe combination structure in the selected data database until all the structural three-dimensional data are selected.

[0077] S600, incorporate the data vector into the analysis script based on the data vector and the target bearing capacity upper limit of the support pipe wall.

[0078] Specifically, based on the elastic modulus reduction algorithm, obtain the target stress range of the structural three-dimensional data of the center line of the support pipe combination structure. Use the generalized yield function and the target stress range to determine the target bearing capacity upper limit of the support pipe wall.

[0079] The elastic modulus reduction method is based on the elastic modulus reduction method and the reference body method, and combines the elastic finite element method for iterative analysis. The unit bearing ratio expressed by the generalized yield function is used as the control parameter for elastic modulus adjustment. According to the uniformity of the unit bearing ratio, determine the threshold value of modulus adjustment - the reference bearing ratio. Use the principle of energy conservation in the conversion of unit strain energy to establish the unit elastic modulus adjustment strategy. Simulate the elastoplastic damage process of the structure by reducing the elastic modulus of high-stress elements, construct a series of kinematically admissible displacement fields, and then use the upper limit load calculation method of the reference body to solve the upper limit of the structural ultimate bearing capacity.

[0080] It can be understood that the data vector and the target bearing capacity upper limit of the support pipe wall are incorporated into the finite element analysis algorithm. Based on the load increase script of the finite element analysis algorithm, determine the geometric structure shape of the support pipe wall.

[0081] Use finite element software to establish a numerical model of the structure, input information such as the mechanical property parameters and boundary conditions of the material, and then apply loads for calculation. By continuously increasing the load, observe the stress and strain changes of the structure until the structure reaches the failure state, so as to determine the bearing capacity upper limit of the structure. Finite element analysis can consider factors such as complex geometric shapes, material nonlinearity, and boundary conditions, but has high requirements for the accuracy of the model and the selection of parameters.

[0082] S700, obtain the wall parameters of the center line of each support pipe combination structure.

[0083] Specifically, the target structural strength of the steel tower will exist in the original factory data of the support pipe combination structure. This data can be used as a safety threshold for measuring the support pipe combination structure with the same thickness, material and other parameters. When it is determined that the steel tower is within the credible range of metal fatigue, the steel tower can be replaced in advance.

[0084] This embodiment relates to a method for automatic control of a wharf. By establishing a communication connection with the database of the center line of the support pipe combined structure, real-time video stream acquisition and acquisition of the original data of the support pipe combined structure at the factory are realized. Selecting the three-dimensional structure data of the center line of the support pipe combined structure in the data database, the steel tower of the wharf can be monitored in real time by using the real-time video stream acquisition. Using a topology algorithm to perform vector analysis on the three-dimensional structure data, obtaining the data vector of the selected center line of the support pipe combined structure, and based on the data vector and the target bearing capacity upper limit of the support pipe wall, incorporating the data vector into the analysis script to obtain the wall parameters of each center line of the support pipe combined structure. Comparing the wall parameters of each center line of the support pipe combined structure with the original data of the support pipe combined structure at the factory can determine in real time and with high precision whether the steel tower of the wharf is within the safe working range, and can also determine the credible range of the steel tower in metal fatigue.

[0085] As Figure 2 shown, in an embodiment of the present application, a wharf automatic control system is further provided, including a processing component 100 and a computing component 200. The processing component 100 executes the wharf automatic control method described in any one of the foregoing, and the computing component 200 executes data calculation.

[0086] Specifically, the processing component 100 is communicatively connected to the computing component 200.

[0087] The technical features of the above embodiments can be combined arbitrarily, and there is no limitation on the execution order of each method step. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0088] The above embodiments only represent several implementation manners of the present application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several deformations and improvements can be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A terminal automation control method, characterized in that: include: Establishing a communication connection with a database of the center line of the support tube assembly structure; the database of the center line of the support tube assembly structure is a data database; Selecting the structural three-dimensional data of the center line of the support pipe combination structure in the data database; the structural three-dimensional data includes cloud point data and position data; Use topological algorithms to perform vector analysis on the three-dimensional structural data; Obtaining a data vector of the center line of the selected support tube assembly structure; Returning the structural three-dimensional data of the center line of the support tube combination structure in the selected data database until all the structural three-dimensional data are selected; Based on the data vector and the target upper limit of the load-bearing capacity of the supporting pipe wall, the data vector is incorporated into the analysis script; Obtain the pipe wall parameters of the center line of each support pipe combination structure.

2. The terminal automation control method according to claim 1, characterized in that: The step of establishing a communication connection with a database of the centerline of the support tube assembly structure includes: Based on the type of the device itself, determine whether the device itself is a server device; If the device type is a server device, a communication connection with a database of the center line of the support pipe assembly structure is established based on the loading driver; If the device type is a personal computer device, a communication connection with the database of the center line of the support pipe assembly structure is established based on the configuration of the ODBC data source; If the device type is a single-chip microcomputer device, a communication connection with the database of the center line of the support pipe combination structure is established based on the API interface.

3. The terminal automation control method according to claim 2, characterized in that: After establishing the communication connection with the database of the center line of the support tube assembly structure, the support tube wall analysis method further includes: Based on data stream, use data replication program to back up its own real-time data; Based on the communication connection between the own equipment and the database of the center line of the support pipe combination structure, the own real-time data is synchronized with the data in the material database.

4. The terminal automation control method according to claim 3, characterized in that: The three-dimensional structural data of the center line of the support pipe combination structure in the selected data database includes: Utilize the point trace three-dimensional environment to receive each cloud point data; Select a cloud point data; Based on the position data in the cloud point data, the selected 3D point cloud is annotated in the point trace 3D environment; Return to selecting a cloud point data until all cloud point data are selected.

5. The terminal automation control method according to claim 4, characterized in that: The three-dimensional structural data of the center line of the support pipe combination structure in the selected data database also includes: Based on the characteristic bands of the cloud point data, determine whether the data source of the cloud point data is a structured light device; If the cloud point data comes from a structured light device, the depth value of the object surface is calculated based on information such as the deformation of the structured light; If the data source of the cloud point data is not a structured light device, the three-dimensional environment of the point traces is included in the RGB-D analysis program.

6. The terminal automation control method according to claim 5, characterized in that: The method of performing vector analysis on the three-dimensional structural data using a topological algorithm includes: The topology algorithm includes one or more of a Poisson surface reconstruction algorithm and a Delaunay triangulation algorithm.

7. The terminal automation control method according to claim 6, characterized in that: The method of performing vector analysis on the three-dimensional structural data using a topological algorithm includes: The receiving data source is the cloud point data of the structured light device; Determine the data source as the API of cloud point data of structured light equipment; Based on the determined API and Poisson surface reconstruction algorithm, the three-dimensional data of the structure is obtained for vector analysis.

8. The terminal automation control method according to claim 6, characterized in that: The method of performing vector analysis on the three-dimensional structural data using a topological algorithm includes: Receive a point trace three-dimensional environment in an RGB-D analysis program; Determine the connection function of the three-dimensional environment of the point trace in the RGB-D analysis program; Based on the connection function and Delaunay triangulation algorithm, the three-dimensional data of the structure is obtained for vector analysis.

9. The terminal automation control method according to claim 1, characterized in that: The target bearing limit of the support pipe wall based on the data vector is incorporated into the analysis script, including: Based on the elastic modulus reduction algorithm, the target force range of the three-dimensional structural data of the center line of the support tube assembly structure is obtained; The target upper limit of the bearing capacity of the support pipe wall is determined by using the generalized yield function and the target bearing range; Incorporating the data vector and the target upper limit of the load-bearing capacity of the supporting tube wall into the finite element analysis algorithm; The load increase script based on the finite element analysis algorithm determines the geometric structure shape of the support tube wall.

10. A terminal automation control system, characterized in that: include: A processing component, through which the terminal automation control method according to any one of claims 1 to 9 is executed; A computing component, through which data computing is performed.

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