Pipeline data processing method, system and device based on multi-source perception and medium

Abstract

This application relates to a pipeline data processing method, system, device, and medium based on multi-source sensing. The method includes: acquiring the static pose of the target installation interface, multi-source sensing data of the pipeline to be installed, and mechanical constraint parameters of the pipeline to be installed; extracting the pose, deformation, and installation environment data of the pipeline to be installed based on the multi-source sensing data; optimizing and solving for the interface docking compensation parameters of the pipeline to be installed based on the pose, deformation, and mechanical constraint parameters; calculating the target pose of the pipeline interface based on the static pose of the target installation interface and the interface docking compensation parameters; and generating pipeline installation motion trajectory control parameters based on the pose of the pipeline to be installed, the target pose of the pipeline interface, and the installation environment data. This method can ensure the sealing and structural stability of the pipeline connection.

Description

Technical Field

[0001] This application belongs to the field of pipeline data processing, and in particular relates to a pipeline data processing method, system, equipment and medium based on multi-source sensing. Background Technology

[0002] With the development of urban infrastructure construction and energy transmission networks, the construction scale of pipeline projects with complex working conditions, such as large-diameter water and gas transmission trunk pipelines, urban integrated pipe corridors, cross-river and tunnel crossings, continues to expand. As the core carrier of resource allocation and energy transmission, the accuracy, safety and stability of pipeline installation and construction are directly related to the operational safety of the entire life cycle of the project.

[0003] In pipeline installation projects, issues such as insufficient interface connection accuracy, excessive pipeline deformation, and structural damage during construction are the core causes of potential engineering quality problems such as pipeline interface leakage, weld cracking, and structural failure. Especially in special working conditions such as large-diameter heavy-load pipelines, dense pipe gallery clusters, and complex environment crossings, the status perception, deviation control, and trajectory control of the pipeline installation process face extremely high requirements. There is an urgent need in the industry for the application of digital, precise, and intelligent management and control technologies for the entire pipeline installation process.

[0004] Early pipeline installation relied mainly on manual measurement and experience-based construction. Static position data of the pipeline was obtained through traditional measuring equipment such as total stations and levels. The hoisting equipment and connection procedures were adjusted based on the on-site experience of the construction personnel. There was a lack of continuous perception of the dynamic deformation and real-time position of the pipeline during installation, and it was also impossible to quantitatively control the mechanical constraints of the interface. This not only resulted in low construction efficiency and difficulty in ensuring connection accuracy, but also made it impossible to identify the risk of excessive deformation during pipeline hoisting and connection. This could easily lead to problems such as pipeline structural damage and interface sealing failure, making it difficult to adapt to the construction needs of pipeline projects with complex working conditions. Summary of the Invention

[0005] Therefore, it is necessary to provide a pipeline data processing method, system, equipment, and medium based on multi-source sensing that can ensure the sealing and structural stability of pipeline connections and thus adapt to pipeline engineering under complex working conditions, in order to address the above-mentioned technical problems.

[0006] Firstly, this application provides a pipeline data processing method based on multi-source sensing, including:

[0007] Acquire static pose data of the target installation interface, multi-source sensing data of the pipeline to be installed, and mechanical constraint parameters of the pipeline interface to be installed;

[0008] Based on the multi-source sensing data of the pipeline to be installed, the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the real-time installation environment data of the pipeline to be installed are extracted.

[0009] Based on the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the mechanical constraint parameters of the interface of the pipeline to be installed, the docking compensation parameters of the interface of the pipeline to be installed are obtained by optimizing the solution using the docking compensation optimization algorithm.

[0010] Based on the static pose data of the target installation interface and the docking compensation parameters of the pipe interface to be installed, the target pose data of the pipe interface to be installed is calculated.

[0011] Based on the real-time pose data of the pipeline to be installed, the target pose data of the pipeline interface, and the real-time installation environment data of the pipeline, pipeline installation path planning and kinematic analysis are performed to generate pipeline installation motion trajectory control parameters.

[0012] Secondly, this application also provides a pipeline data processing system based on multi-source sensing, comprising:

[0013] The pipeline installation data monitoring module is used to acquire static pose data of the target installation interface, static structural data of the pipeline to be installed, multi-source sensing data of the pipeline to be installed, and mechanical constraint parameters of the interface of the pipeline to be installed.

[0014] The pipeline installation feature extraction module is used to extract real-time pose data, real-time deformation data, and real-time installation environment data of the pipeline to be installed based on the static structural data and multi-source sensing data of the pipeline to be installed.

[0015] The docking compensation optimization solution module is used to optimize and solve the docking compensation parameters of the pipeline interface based on the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the mechanical constraint parameters of the interface of the pipeline to be installed, combined with the docking compensation optimization algorithm.

[0016] The target pose data calculation module is used to calculate the target pose data of the pipe interface to be installed based on the static pose data of the target installation interface and the docking compensation parameters of the pipe interface to be installed.

[0017] The pipeline installation path planning module is used to perform pipeline installation path planning and kinematic analysis based on the real-time pose data of the pipeline to be installed, the target pose data of the pipeline interface, and the real-time installation environment data of the pipeline to be installed, and to generate pipeline installation motion trajectory control parameters.

[0018] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method as described in any of the first aspects of this application.

[0019] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the first aspects of this application.

[0020] The aforementioned pipeline data processing method, system, equipment, and medium based on multi-source sensing, through the static pose data of the target installation interface, the multi-source sensing data of the pipeline to be installed, and the mechanical constraint parameters of the pipeline interface, accurately extracts the real-time pose data, real-time deformation data, and real-time installation environment data of the pipeline to be installed throughout the entire installation process. This enhances the ability to capture subtle state changes during the dynamic construction process of pipeline installation, improves the completeness, continuity, and accuracy of pipeline installation status data, and provides complete, continuous, and reliable data support for precise control throughout the pipeline installation process, ensuring the comprehensiveness and reliability of pipeline installation data processing. Furthermore, by constructing a multi-objective coupled optimization solution model through a docking compensation optimization solution mechanism, it can accurately quantify the impact of pose deviations and structural deformations during pipeline installation on pipeline interface docking, while meeting the mechanical safety requirements of the pipeline interface. Within the feasible region, the optimal compensation parameters for the pipe interface to be installed are obtained through optimization. This enables dynamic and precise compensation and adjustment of the pipe interface connection process, achieving coordinated control of pipe deformation and interface stress, reducing potential risks in pipe interface connection, and ensuring the accuracy and structural safety of the connection. By combining installation path planning and kinematic analysis that couples the real-time pipe status, target pose, and on-site environmental constraints, the target pose data of the pipe interface to be installed can be accurately calculated based on the static reference requirements and dynamic compensation needs of pipe installation. This allows for the construction of an installation motion path that perfectly matches the actual installation state of the pipe and the constraints of the on-site environment, generating pipe installation motion trajectory control parameters that adapt to the dynamic changes in pipe installation. This effectively avoids potential engineering quality hazards caused by excessive pipe deformation and improves the controllability and safety of pipe installation. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart illustrating a pipeline data processing method based on multi-source sensing, provided as an embodiment of this application. Figure 1 ;

[0023] Figure 2 A flowchart illustrating a pipeline data processing method based on multi-source sensing, provided as an embodiment of this application. Figure 2;

[0024] Figure 3 This is a schematic diagram of the structure of a pipeline data processing system based on multi-source sensing, provided as an embodiment of this application. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0026] In one exemplary embodiment of this application, such as Figure 1 As shown, a pipeline data processing method based on multi-source sensing is provided. This embodiment illustrates the application of this method to a pipeline data processing terminal. It is understood that this method can also be applied to a pipeline data processing server, and further to a pipeline data processing system including both a pipeline data processing terminal and a pipeline data processing server, and is implemented through the interaction between the pipeline data processing terminal and the pipeline data processing server. In this embodiment, the method includes the following steps:

[0027] Step S101: Obtain the static pose data of the target installation interface, the multi-source sensing data of the pipeline to be installed, and the mechanical constraint parameters of the pipeline interface to be installed.

[0028] Optionally, after obtaining authorization, the pipeline data processing terminal can establish communication connections with various sensing devices deployed at the pipeline installation site, pipeline engineering construction management and control platforms, pipeline engineering design platforms, and industry standard and specification databases to obtain static pose data of the target installation interface, multi-source sensing data of the pipeline to be installed, and mechanical constraint parameters of the interface of the pipeline to be installed.

[0029] For example, the various sensing and perception devices deployed at the pipeline installation site may include, but are not limited to, 3D laser scanning equipment, total stations, high-precision GNSS measuring equipment, laser trackers, articulated arm measuring machines, and industrial photogrammetry equipment.

[0030] Optionally, the pipeline data processing terminal can acquire static pose data of the target installation interface through various sensing devices deployed at the pipeline installation site and / or the pipeline engineering construction management platform. After acquiring the static pose data of the target installation interface, the pipeline data processing terminal can store the static pose data of the target installation interface in the local engineering database. At the same time, it can set associated information such as timestamp, unique interface identifier, measuring equipment identifier, measuring environment parameters, and project number for the static pose data of the target installation interface, which facilitates data retrieval, project traceability, and result verification in subsequent steps.

[0031] Indicatively, the pipeline data processing terminal can also retest and update the static pose data of the target installation interface based on the retest cycle, ensuring the long-term accuracy and effectiveness of the reference data.

[0032] For example, when construction disturbances and environmental changes occur during construction that may affect the pose of the target installation interface, the pipeline data processing terminal can trigger a retest operation of the static pose data of the target installation interface and update the static pose data of the target installation interface.

[0033] Optionally, the pipeline data processing terminal can acquire multi-source sensing data of pipeline installation through various sensing devices deployed at the pipeline installation site. This multi-source sensing data may include, but is not limited to, dynamic pipeline strain sensing data, dynamic lidar sensing data, dynamic inertial measurement sensing data, and dynamic environmental interference sensing data.

[0034] Optionally, the pipeline data processing terminal can obtain the basic engineering information of the pipeline to be installed through the pipeline engineering construction management and control platform, the pipeline engineering design platform, and the industry standard and specification database. The pipeline data processing terminal can obtain the mechanical constraint parameters of the interface of the pipeline to be installed by setting the basic engineering information of the pipeline to be installed. The basic engineering information of the pipeline to be installed may include, but is not limited to, the material type information, pipe diameter specification information, wall thickness parameters, design pressure rating, installation condition requirements information, connection method information, anti-corrosion treatment requirements information, and connection process specification information of the pipeline to be installed.

[0035] Step S102: Based on the multi-source sensing data of the pipeline to be installed, extract the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the real-time installation environment data of the pipeline to be installed.

[0036] For example, taking multi-source sensing data for pipeline installation, including dynamic pipeline strain sensing data, dynamic lidar sensing data, dynamic inertial measurement sensing data, and dynamic environmental interference sensing data, as an example, the pipeline data processing terminal can extract real-time deformation data of the pipeline to be installed based on the dynamic pipeline strain sensing data and the dynamic lidar sensing data. The pipeline data processing terminal can extract real-time pose data of the pipeline to be installed based on the dynamic inertial measurement sensing data. The pipeline data processing terminal can extract real-time installation environment data of the pipeline to be installed based on the dynamic environmental interference sensing data.

[0037] Furthermore, the real-time deformation data of the pipeline to be installed may include, but is not limited to, axial deformation data of the pipeline interface, circumferential deformation data of the pipeline interface, and axial deformation data of the pipeline hoisting end. The pipeline data processing terminal can extract the dynamic pipeline interface fitting plane model data and the dynamic pipeline interface adjacent hoisting circumferential plane model data corresponding to the LiDAR sampling time based on the dynamic LiDAR sensing data, and set the dynamic pipeline strain sensing data corresponding to the LiDAR sampling time of the dynamic LiDAR sensing data as the high-frequency update reference parameter of the dynamic LiDAR sensing data. The pipeline data processing terminal can calculate the dynamic interface plane normal vector of the pipeline interface plane corresponding to the LiDAR sampling time based on the dynamic pipeline interface fitting plane model data, and set the axial deformation data of the pipeline interface corresponding to the LiDAR sampling time based on the dynamic pipeline interface plane normal vector. The pipeline data processing terminal can calculate the dynamic eccentricity and dynamic major axis rotation angle of the pipeline interface plane based on the dynamic pipeline interface fitting plane model data, and set the circumferential deformation data of the pipeline interface corresponding to the LiDAR sampling time based on the dynamic eccentricity and dynamic major axis rotation angle. The pipeline data processing terminal can calculate the midpoint coordinates of the dynamic pipeline interface plane based on the fitted plane model data of the dynamic pipeline interface, and the midpoint coordinates of the dynamic lifting circumferential plane based on the adjacent lifting circumferential plane model data of the dynamic pipeline interface. Using the midpoint coordinates of the dynamic lifting circumferential plane as the starting point of the axial pointing vector and the midpoint coordinates of the dynamic pipeline interface plane as the ending point of the axial pointing vector, it constructs the axial pointing vector of the pipeline lifting end corresponding to the lidar sampling time. Based on the axial pointing vector of the pipeline lifting end, it sets the axial deformation data of the pipeline lifting end corresponding to the lidar sampling time. The pipeline data processing terminal can also update the axial deformation data of the pipeline interface, the circumferential deformation data of the pipeline interface, and the axial deformation data of the pipeline lifting end at each strain sampling time based on the dynamic pipeline strain sensing data within each strain sampling time corresponding to the dynamic lidar sensing data, combined with high-frequency updated reference parameters and the real-time deformation data of the pipeline to be installed corresponding to the lidar sampling time.

[0038] Step S103: Based on the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the mechanical constraint parameters of the interface of the pipeline to be installed, the docking compensation parameters of the interface of the pipeline to be installed are obtained by optimizing the solution using the docking compensation optimization algorithm.

[0039] Specifically, the pipeline data processing terminal can construct a feasible solution domain for docking compensation optimization based on the mechanical constraint parameters of the interface of the pipeline to be installed. Within this feasible solution domain, the pipeline data processing terminal can optimize and solve for the docking compensation parameters of the interface of the pipeline to be installed, based on the real-time pose data and real-time deformation data of the pipeline to be installed, and the docking compensation optimization algorithm.

[0040] Step S104: Calculate the target pose data of the pipe interface to be installed based on the static pose data of the target installation interface and the docking compensation parameters of the pipe interface to be installed.

[0041] For example, the docking compensation parameters for the pipe interface to be installed may include docking compensation parameters for the position of the pipe interface to be installed and docking compensation parameters for the attitude of the pipe interface to be installed. The static pose data of the target installation interface may include target installation interface position data and target installation interface attitude data. The target pose data of the pipe interface to be installed may include target position data and target attitude data of the pipe interface to be installed. The pipe data processing terminal can calculate the target position data of the pipe interface to be installed based on the target installation interface position data and the docking compensation parameters for the position of the pipe interface to be installed. The pipe data processing terminal can calculate the target attitude data of the pipe interface to be installed based on the target installation interface attitude data and the docking compensation parameters for the attitude of the pipe interface to be installed.

[0042] Step S105: Based on the real-time pose data of the pipeline to be installed, the target pose data of the pipeline interface to be installed, and the real-time installation environment data of the pipeline to be installed, perform pipeline installation path planning and kinematic analysis to generate pipeline installation motion trajectory control parameters.

[0043] To illustrate, the pipeline data processing terminal can send pipeline installation motion trajectory control parameters to the pipeline hoisting and installation equipment, and the pipeline hoisting and installation equipment can then perform operations such as pipeline hoisting, moving, and docking based on these parameters.

[0044] Optionally, the pipeline data processing terminal can construct a three-dimensional spatial environment map of the pipeline installation site based on real-time installation environment data of the pipeline to be installed. The terminal can mark obstacle boundaries and work space boundaries on this map. It can set the spatial pose corresponding to the real-time pose data of the pipeline to be installed as the starting point for path planning and the spatial pose corresponding to the target pose data of the pipeline interface as the ending point. Within the constructed three-dimensional spatial environment map, a global path planning operation is performed to generate a globally collision-free optimal path from the starting point to the ending point. Based on this globally collision-free optimal path, and combining the kinematic model of the pipeline hoisting and installation equipment with the structural dynamics characteristics of the pipeline to be installed, the terminal can perform kinematic analysis. This analysis and calculation of the motion states of each moving device of the pipeline hoisting and installation equipment and the motion state of the pipeline to be installed under the globally collision-free optimal path generates pipeline installation motion trajectory control parameters.

[0045] The aforementioned pipeline data processing method based on multi-source sensing accurately extracts real-time pose data, real-time deformation data, and real-time installation environment data of the pipeline during the entire installation process by utilizing the static pose data of the target installation interface, the multi-source sensing data of the pipeline to be installed, and the mechanical constraint parameters of the pipeline interface. This enhances the ability to capture subtle state changes during the dynamic construction process of pipeline installation, improves the completeness, continuity, and accuracy of pipeline installation status data, and provides complete, continuous, and reliable data support for precise control of the entire pipeline installation process, ensuring the comprehensiveness and reliability of pipeline installation data processing. Furthermore, by constructing a multi-objective coupled optimization solution model through a docking compensation optimization solution mechanism, the method can accurately quantify the impact of pose deviations and structural deformations during pipeline installation on pipeline interface docking, ensuring feasibility while meeting the mechanical safety requirements of the pipeline interface. Within the domain, the optimal compensation parameters for the pipe interface to be installed are obtained through optimization, enabling dynamic and precise compensation and adjustment during the pipe interface connection process. This allows for coordinated control of pipe deformation and interface stress, reducing potential risks associated with pipe interface connection and ensuring the accuracy and structural safety of the connection. By combining installation path planning and kinematic analysis that couples the real-time pipe status, target pose, and on-site environmental constraints, the target pose data of the pipe interface to be installed can be accurately calculated based on the static reference requirements and dynamic compensation needs of pipe installation. This constructs an installation motion path that perfectly matches the actual installation state of the pipe and the constraints of the on-site environment, generating pipe installation motion trajectory control parameters that adapt to the dynamic changes in pipe installation. This effectively avoids potential engineering quality hazards caused by excessive pipe deformation and improves the controllability and safety of pipe installation.

[0046] In an optional embodiment of this application, the multi-source sensing data for pipeline installation may include dynamic pipeline strain sensing data, dynamic lidar sensing data, dynamic inertial measurement sensing data, and dynamic environmental interference sensing data. Please refer to... Figure 1 and Figure 2 Step S102, based on the multi-source sensing data of the pipeline to be installed, extract the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the real-time installation environment data of the pipeline to be installed, which may include:

[0047] Specifically, the pipeline data processing terminal can extract real-time deformation data of the pipeline to be installed based on dynamic pipeline strain sensing data and dynamic lidar sensing data.

[0048] Step S207: Based on the dynamic inertial measurement sensing data, extract the real-time pose data of the pipeline to be installed.

[0049] Step S208: Based on the dynamic environmental interference sensing data, extract the real-time installation environment data of the pipeline to be installed.

[0050] In an optional embodiment of this application, the real-time deformation data of the pipeline to be installed may include axial deformation data of the pipeline interface, circumferential deformation data of the pipeline interface, and axial deformation data of the pipeline hoisting end. Please refer to... Figure 2 Based on dynamic pipeline strain sensing data and dynamic lidar sensing data, real-time deformation data of the pipeline to be installed is extracted, which may include:

[0051] Step S202: Based on the dynamic lidar sensing data, extract the dynamic pipe interface fitting plane model data and the dynamic pipe interface adjacent hoisting circumferential cutting plane model data, and set the dynamic pipe strain sensing data corresponding to the lidar sampling time of the dynamic lidar sensing data as the high-frequency update benchmark parameter of the dynamic lidar sensing data.

[0052] Step S203: Calculate the dynamic interface plane normal vector of the pipe interface plane based on the dynamic pipe interface fitting plane model data, and set the axial deformation data of the pipe interface based on the dynamic pipe interface plane normal vector.

[0053] Step S204: Calculate the dynamic eccentricity and dynamic major axis rotation angle of the pipe interface plane based on the dynamic pipe interface fitting plane model data, and set the circumferential deformation data of the pipe interface based on the dynamic eccentricity and dynamic major axis rotation angle.

[0054] Step S205: Calculate the midpoint coordinates of the dynamic pipe interface plane based on the fitted plane model data of the dynamic pipe interface. Calculate the midpoint coordinates of the dynamic hoisting circumferential cutting plane based on the adjacent hoisting circumferential cutting plane model data of the dynamic pipe interface. Using the midpoint coordinates of the dynamic hoisting circumferential cutting plane as the starting point of the axial pointing vector and the midpoint coordinates of the dynamic pipe interface plane as the ending point of the axial pointing vector, construct the axial pointing vector at the end of the pipe hoisting. Then, set the axial deformation data at the end of the pipe hoisting based on the axial pointing vector at the end of the pipe hoisting.

[0055] Step S206: Based on the dynamic pipeline strain sensing data at each strain sampling time within the laser radar sampling interval corresponding to the dynamic laser radar sensing data, and combined with the high-frequency updated reference parameters and the real-time deformation data of the pipeline to be installed at the laser radar sampling time, update the axial deformation data of the pipeline interface, the circumferential deformation data of the pipeline interface, and the axial deformation data of the pipeline hoisting end at each strain sampling time.

[0056] In an optional embodiment of this application, the dynamic pipeline strain sensing data may include axial strain sensing data of the pipeline interface fitting plane, circumferential strain sensing data of the pipeline interface fitting plane, axial strain sensing data of the adjacent hoisting circumferential cutting plane, and circumferential strain sensing data of the adjacent hoisting circumferential cutting plane. The high-frequency updated reference parameters may include axial strain reference parameters of the pipeline interface fitting plane, circumferential strain reference parameters of the pipeline interface fitting plane, axial strain reference parameters of the adjacent hoisting circumferential cutting plane, and circumferential strain reference parameters of the adjacent hoisting circumferential cutting plane. Based on the dynamic pipeline strain sensing data at each strain sampling time within the laser radar sampling interval corresponding to the dynamic laser radar sensing data, combined with the high-frequency updated reference parameters and the real-time deformation data of the pipeline to be installed corresponding to the laser radar sampling time, the axial deformation data of the pipeline interface, the circumferential deformation data of the pipeline interface, and the axial deformation data of the pipeline hoisting end at each strain sampling time are calculated, which may include:

[0057] Specifically, the pipeline data processing terminal can calculate the axial strain increment of the pipeline interface fitting plane at each strain sampling time based on the difference between the axial strain sensing data of the pipeline interface fitting plane at each strain sampling time and the axial strain reference parameter of the pipeline interface fitting plane. It can also calculate the circumferential strain increment of the pipeline interface fitting plane at each strain sampling time based on the difference between the circumferential strain sensing data of the pipeline interface fitting plane at each strain sampling time and the circumferential strain reference parameter of the pipeline interface fitting plane.

[0058] Specifically, the pipeline data processing terminal can calculate the axial strain increment of the adjacent hoisting circumferential plane at each strain sampling time based on the difference between the axial strain sensing data of the adjacent hoisting circumferential plane at each strain sampling time and the axial strain reference parameter of the adjacent hoisting circumferential plane. It can also calculate the circumferential strain increment of the adjacent hoisting circumferential plane at each strain sampling time based on the difference between the circumferential strain sensing data of the adjacent hoisting circumferential plane at each strain sampling time and the circumferential strain reference parameter of the adjacent hoisting circumferential plane.

[0059] Specifically, the pipeline data processing terminal can calculate the dynamic interface plane normal vector increment corresponding to the dynamic interface plane normal vector based on the axial strain increment of the fitting plane of the pipeline interface and the circumferential strain increment of the fitting plane of the pipeline interface. Based on the dynamic interface plane normal vector increment at each strain sampling time and the pipeline interface axial deformation data at the lidar sampling time, the pipeline interface axial deformation data at each strain sampling time can be calculated.

[0060] Specifically, the pipeline data processing terminal can calculate the dynamic eccentricity increment corresponding to the dynamic eccentricity and the dynamic major axis rotation angle increment corresponding to the dynamic major axis rotation angle based on the circumferential strain increment of the fitting plane at the pipeline interface. Based on the dynamic eccentricity increment, the dynamic major axis rotation angle increment, the dynamic eccentricity corresponding to the lidar sampling time, and the dynamic major axis rotation angle corresponding to the lidar sampling time, the pipeline interface circumferential deformation data at each strain sampling time can be calculated.

[0061] Specifically, the pipeline data processing terminal can calculate the axial pointing vector increment of the pipeline hoisting end corresponding to the axial pointing vector of the pipeline hoisting end based on the axial strain increment of the adjacent hoisting circumferential plane and the circumferential strain increment of the adjacent hoisting circumferential plane. Based on the axial pointing vector increment of the pipeline hoisting end at each strain sampling time and the axial pointing vector of the pipeline hoisting end corresponding to the lidar sampling time, it can calculate the axial deformation data of the pipeline hoisting end at each strain sampling time.

[0062] In an optional embodiment of this application, the docking compensation parameters of the pipe interface are obtained by optimizing the solution based on the real-time pose data of the pipe to be installed, the real-time deformation data of the pipe to be installed, and the mechanical constraint parameters of the pipe interface, combined with the docking compensation optimization algorithm. This optimization may include:

[0063] Specifically, the pipeline data processing terminal can construct a feasible solution domain for docking compensation optimization based on the mechanical constraint parameters of the interface of the pipeline to be installed.

[0064] Specifically, the pipeline data processing terminal can optimize and solve for the interface docking compensation parameters of the pipeline to be installed in the feasible solution domain of docking compensation optimization, based on the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the docking compensation optimization algorithm.

[0065] Optionally, the expression for the optimization loss function of the docking compensation optimization algorithm can be:

[0066]

[0067] In the formula, This is the vector of docking compensation parameters corresponding to the docking compensation parameters of the pipe interface to be installed. To optimize the loss function, , and These are the deformation weighting coefficient, pose weighting coefficient, and stress weighting coefficient, respectively. This is a vector function for deformation compensation based on the docking compensation parameter vector. for The real-time deformation vector corresponding to the real-time deformation data of the pipeline to be installed at any given moment. It is the second norm. This refers to the real-time pose vector corresponding to the real-time pose data of the pipeline to be installed. This is a function for calculating the equivalent stress at pipe interfaces based on the docking compensation parameter vector. The maximum allowable stress value, It is a function for maximizing the value.

[0068] Optionally, the docking compensation parameters for the pipe interfaces to be installed may include position docking compensation parameters and attitude docking compensation parameters for the pipe interfaces to be installed. The docking compensation parameter vector corresponding to the docking compensation parameters may include a position docking compensation parameter vector and an attitude docking compensation parameter vector. The expression for the docking compensation parameter vector can be:

[0069]

[0070] In the formula, For the docking compensation parameter vector, and These are the position docking compensation parameter vector and the attitude docking compensation parameter vector, respectively.

[0071] In an optional embodiment of this application, the mechanical constraint parameters of the pipe interface to be installed may include pipe interface tensile strain constraint parameters, pipe interface compressive strain constraint parameters, and pipe interface connection stiffness parameters.

[0072] In an optional embodiment of this application, the docking compensation parameters for the pipe interface to be installed may include the position docking compensation parameters and the attitude docking compensation parameters for the pipe interface to be installed. The static pose data of the target installation interface may include the position data and attitude data of the target installation interface. The target pose data of the pipe interface to be installed may include the target position data and the target attitude data of the pipe interface to be installed. The target pose data of the pipe interface to be installed is calculated based on the static pose data and the docking compensation parameters, and may include:

[0073] Specifically, the pipeline data processing terminal can calculate the target location data of the pipeline interface to be installed based on the target installation interface location data and the interface location compensation parameters of the pipeline to be installed.

[0074] Specifically, the pipeline data processing terminal can calculate the target attitude data of the pipeline interface to be installed based on the target installation interface attitude data and the attitude docking compensation parameters of the pipeline interface to be installed.

[0075] In one exemplary embodiment of this application, such as Figure 2 As shown, a pipeline data processing method based on multi-source sensing is provided, including:

[0076] Step S201: Obtain the static pose data of the target installation interface, the multi-source sensing data of the pipeline to be installed, and the mechanical constraint parameters of the pipeline interface to be installed.

[0077] Step S202: Based on the dynamic lidar sensing data, extract the dynamic pipe interface fitting plane model data and the dynamic pipe interface adjacent hoisting circumferential cutting plane model data, and set the dynamic pipe strain sensing data corresponding to the lidar sampling time of the dynamic lidar sensing data as the high-frequency update benchmark parameter of the dynamic lidar sensing data.

[0078] Step S203: Calculate the dynamic interface plane normal vector of the pipe interface plane based on the dynamic pipe interface fitting plane model data, and set the axial deformation data of the pipe interface based on the dynamic pipe interface plane normal vector.

[0079] Step S204: Calculate the dynamic eccentricity and dynamic major axis rotation angle of the pipe interface plane based on the dynamic pipe interface fitting plane model data, and set the circumferential deformation data of the pipe interface based on the dynamic eccentricity and dynamic major axis rotation angle.

[0080] Step S205: Calculate the midpoint coordinates of the dynamic pipe interface plane based on the fitted plane model data of the dynamic pipe interface. Calculate the midpoint coordinates of the dynamic hoisting circumferential cutting plane based on the adjacent hoisting circumferential cutting plane model data of the dynamic pipe interface. Using the midpoint coordinates of the dynamic hoisting circumferential cutting plane as the starting point of the axial pointing vector and the midpoint coordinates of the dynamic pipe interface plane as the ending point of the axial pointing vector, construct the axial pointing vector at the end of the pipe hoisting. Then, set the axial deformation data at the end of the pipe hoisting based on the axial pointing vector at the end of the pipe hoisting.

[0081] Step S206: Based on the dynamic pipeline strain sensing data at each strain sampling time within the laser radar sampling interval corresponding to the dynamic laser radar sensing data, and combined with the high-frequency updated reference parameters and the real-time deformation data of the pipeline to be installed at the laser radar sampling time, update the axial deformation data of the pipeline interface, the circumferential deformation data of the pipeline interface, and the axial deformation data of the pipeline hoisting end at each strain sampling time.

[0082] Step S207: Based on the dynamic inertial measurement sensing data, extract the real-time pose data of the pipeline to be installed.

[0083] Step S208: Based on the dynamic environmental interference sensing data, extract the real-time installation environment data of the pipeline to be installed.

[0084] Step S209: Based on the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the mechanical constraint parameters of the interface of the pipeline to be installed, the docking compensation parameters of the interface of the pipeline to be installed are obtained by optimizing the solution using the docking compensation optimization algorithm.

[0085] Step S210: Calculate the target pose data of the pipe interface to be installed based on the static pose data of the target installation interface and the docking compensation parameters of the pipe interface to be installed.

[0086] Step S211: Based on the real-time pose data of the pipeline to be installed, the target pose data of the pipeline interface to be installed, and the real-time installation environment data of the pipeline to be installed, perform pipeline installation path planning and kinematic analysis to generate pipeline installation motion trajectory control parameters.

[0087] The aforementioned pipeline data processing method based on multi-source sensing utilizes static pose data of the target installation interface, multi-source sensing data of the pipeline to be installed, and mechanical constraint parameters of the pipeline interface. It integrates dynamic lidar sensing data and dynamic pipeline strain sensing data to accurately extract and frequently update real-time pipeline deformation data. Combining the pipeline's real-time pose, real-time deformation, and interface mechanical constraint parameters, a docking compensation optimization algorithm is used to obtain interface docking compensation parameters and accurately calculate the target pose data of the pipeline interface. Finally, based on the pipeline's real-time state, target pose, and installation environment data, installation path planning and kinematic analysis are completed, generating pipeline installation trajectory control parameters. This enables precise dynamic control of the pose, deformation, and construction trajectory throughout the entire pipeline installation process, effectively mitigating engineering risks caused by uneven force distribution and improper control of squeezing force during pipeline hoisting and docking. It comprehensively adapts to the needs of pipeline installation under complex working conditions, ensuring the construction quality and long-term operational safety of pipelines under various complex conditions.

[0088] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0089] Based on the same inventive concept, this application also provides a multi-source sensing-based pipeline data processing system for implementing the multi-source sensing-based pipeline data processing method described above. The solution provided by this system is similar to the implementation scheme described in the above method. Therefore, the specific limitations of one or more embodiments of the multi-source sensing-based pipeline data processing system provided below can be found in the limitations of the multi-source sensing-based pipeline data processing method described above, and will not be repeated here.

[0090] In one exemplary embodiment, such as Figure 3 As shown, a pipeline data processing system 300 based on multi-source sensing is provided, including:

[0091] The pipeline installation data monitoring module 301 can be used to acquire static pose data of the target installation interface, static structural data of the pipeline to be installed, multi-source sensing data of the pipeline to be installed, and mechanical constraint parameters of the interface of the pipeline to be installed.

[0092] The pipeline installation feature extraction module 302 can be used to extract real-time pose data, real-time deformation data, and real-time installation environment data of the pipeline to be installed based on the static structural data and multi-source sensing data of the pipeline to be installed.

[0093] The docking compensation optimization solution module 303 can be used to optimize and solve the docking compensation parameters of the pipe interface based on the real-time pose data of the pipe to be installed, the real-time deformation data of the pipe to be installed, and the mechanical constraint parameters of the pipe interface, combined with the docking compensation optimization algorithm.

[0094] The target pose data calculation module 304 can be used to calculate the target pose data of the pipe interface to be installed based on the static pose data of the target installation interface and the docking compensation parameters of the pipe interface to be installed.

[0095] The pipeline installation path planning module 305 can be used to perform pipeline installation path planning and kinematic analysis based on the real-time pose data of the pipeline to be installed, the target pose data of the interface of the pipeline to be installed, and the real-time installation environment data of the pipeline to be installed, and generate pipeline installation motion trajectory control parameters.

[0096] In an optional embodiment of this application, the pipeline installation feature extraction module 302 can also be used for:

[0097] Based on dynamic pipeline strain sensing data and dynamic lidar sensing data, real-time deformation data of the pipeline to be installed is extracted.

[0098] Based on dynamic inertial measurement sensing data, the real-time pose data of the pipeline to be installed is extracted.

[0099] Based on dynamic environmental interference sensing data, real-time installation environment data of the pipeline to be installed is extracted.

[0100] In an optional embodiment of this application, the pipeline installation feature extraction module 302 can also be used for:

[0101] Based on the dynamic lidar sensing data, the dynamic pipeline interface fitting plane model data and the dynamic pipeline interface adjacent hoisting circumferential cutting plane model data are extracted, and the dynamic pipeline strain sensing data corresponding to the lidar sampling time of the dynamic lidar sensing data are set as the high-frequency update benchmark parameters of the dynamic lidar sensing data.

[0102] The dynamic interface plane normal vector of the pipe interface is calculated based on the fitted plane model data of the dynamic pipe interface, and the axial deformation data of the pipe interface is obtained based on the dynamic pipe interface plane normal vector.

[0103] The dynamic eccentricity and dynamic major axis rotation angle of the pipe interface plane are calculated based on the fitted plane model data of the dynamic pipe interface, and the circumferential deformation data of the pipe interface is obtained based on the dynamic eccentricity and dynamic major axis rotation angle.

[0104] The coordinates of the midpoint of the dynamic pipe interface plane are calculated based on the fitted plane model data of the dynamic pipe interface. The coordinates of the midpoint of the dynamic lifting circumferential cutting plane are calculated based on the adjacent lifting circumferential cutting plane model data of the dynamic pipe interface. The coordinates of the midpoint of the dynamic lifting circumferential cutting plane are used as the starting point of the axial pointing vector and the coordinates of the midpoint of the dynamic pipe interface plane are used as the ending point of the axial pointing vector to construct the axial pointing vector of the pipe lifting end. The axial deformation data of the pipe lifting end is then set based on the axial pointing vector of the pipe lifting end.

[0105] Based on the dynamic pipeline strain sensing data at each strain sampling time within the LiDAR sampling interval corresponding to the dynamic LiDAR sensing data, combined with the high-frequency updated benchmark parameters and the real-time deformation data of the pipeline to be installed at the LiDAR sampling time, the axial deformation data of the pipeline interface, the circumferential deformation data of the pipeline interface, and the axial deformation data of the pipeline hoisting end at each strain sampling time are updated.

[0106] In an optional embodiment of this application, the pipeline installation feature extraction module 302 can also be used for:

[0107] Based on the difference between the axial strain sensing data of the pipe interface fitting plane at each strain sampling time and the axial strain reference parameter of the pipe interface fitting plane, the axial strain increment of the pipe interface fitting plane at each strain sampling time is calculated. Based on the difference between the circumferential strain sensing data of the pipe interface fitting plane at each strain sampling time and the circumferential strain reference parameter of the pipe interface fitting plane, the circumferential strain increment of the pipe interface fitting plane at each strain sampling time is calculated.

[0108] Based on the difference between the axial strain sensing data of the adjacent hoisting circumferential plane and the axial strain reference parameter of the adjacent hoisting circumferential plane at each strain sampling time, the axial strain increment of the adjacent hoisting circumferential plane at each strain sampling time is calculated. Based on the difference between the circumferential strain sensing data of the adjacent hoisting circumferential plane and the circumferential strain reference parameter of the adjacent hoisting circumferential plane at each strain sampling time, the circumferential strain increment of the adjacent hoisting circumferential plane at each strain sampling time is calculated.

[0109] Based on the axial strain increment and circumferential strain increment of the fitting plane of the pipe interface, the dynamic interface plane normal vector increment corresponding to the dynamic interface plane normal vector is calculated. Based on the dynamic interface plane normal vector increment at each strain sampling time and the pipe interface axial deformation data at each lidar sampling time, the pipe interface axial deformation data at each strain sampling time is calculated.

[0110] Based on the circumferential strain increment of the fitted plane at the pipe interface, the dynamic eccentricity increment corresponding to the dynamic eccentricity and the dynamic major axis rotation angle increment corresponding to the dynamic major axis rotation angle are calculated. Based on the dynamic eccentricity increment, the dynamic major axis rotation angle increment at each strain sampling time, the dynamic eccentricity at each strain sampling time, and the dynamic major axis rotation angle at each lidar sampling time, the circumferential deformation data of the pipe interface at each strain sampling time are calculated.

[0111] Based on the axial strain increment and circumferential strain increment of the adjacent hoisting circumferential plane, the axial pointing vector increment of the pipe hoisting end corresponding to the axial pointing vector of the pipe hoisting end is calculated. Based on the axial pointing vector increment of the pipe hoisting end at each strain sampling time and the axial pointing vector of the pipe hoisting end at the lidar sampling time, the axial deformation data of the pipe hoisting end at each strain sampling time is calculated.

[0112] In an optional embodiment of this application, the docking compensation optimization solution module 303 can also be used for:

[0113] The feasible solution domain for docking compensation optimization is constructed based on the mechanical constraint parameters of the interface of the pipeline to be installed.

[0114] In the feasible solution domain of docking compensation optimization, the docking compensation parameters of the interface of the pipeline to be installed are obtained by optimizing the solution based on the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the docking compensation optimization algorithm.

[0115] In an optional embodiment of this application, the target pose data calculation module 304 may also be used for:

[0116] Based on the target installation interface location data and the docking compensation parameters of the pipe interface to be installed, the target location data of the pipe interface to be installed is calculated.

[0117] Based on the target installation interface attitude data and the attitude docking compensation parameters of the pipe interface to be installed, the target attitude data of the pipe interface to be installed is calculated.

[0118] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of a pipeline data processing method based on multi-source sensing as described above.

[0119] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0120] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The components described as separate parts may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this disclosure according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0121] The above-described embodiments are merely illustrative of several implementation methods of the embodiments of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the embodiments of this application, and these modifications and improvements all fall within the protection scope of the embodiments of this application.

Claims

1. A pipeline data processing method based on multi-source sensing, characterized in that, The method includes: Acquire static pose data of the target installation interface, multi-source sensing data of the pipeline to be installed, and mechanical constraint parameters of the pipeline interface to be installed; Based on the multi-source sensing data of the pipeline to be installed, the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the real-time installation environment data of the pipeline to be installed are extracted. Based on the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the mechanical constraint parameters of the interface of the pipeline to be installed, the docking compensation parameters of the interface of the pipeline to be installed are obtained by optimizing the solution using the docking compensation optimization algorithm. Based on the static pose data of the target installation interface and the docking compensation parameters of the pipe interface to be installed, the target pose data of the pipe interface to be installed is calculated. Based on the real-time pose data of the pipeline to be installed, the target pose data of the pipeline interface, and the real-time installation environment data of the pipeline, pipeline installation path planning and kinematic analysis are performed to generate pipeline installation motion trajectory control parameters.

2. The method according to claim 1, characterized in that, The multi-source sensing data for pipeline installation includes dynamic pipeline strain sensing data, dynamic lidar sensing data, dynamic inertial measurement sensing data, and dynamic environmental interference sensing data. The process of extracting real-time pose data, real-time deformation data, and real-time installation environment data of the pipeline to be installed based on the multi-source sensing data of the pipeline to be installed includes: Based on the dynamic pipeline strain sensing data and dynamic lidar sensing data, the real-time deformation data of the pipeline to be installed is extracted. Based on the dynamic inertial measurement sensing data, the real-time pose data of the pipeline to be installed is extracted; Based on the dynamic environmental interference sensing data, the real-time installation environment data of the pipeline to be installed is extracted.

3. The method according to claim 2, characterized in that, The real-time deformation data of the pipeline to be installed includes axial deformation data of the pipeline interface, circumferential deformation data of the pipeline interface, and axial deformation data of the pipeline hoisting end. The step of extracting real-time deformation data of the pipeline to be installed based on the dynamic pipeline strain sensing data and dynamic lidar sensing data includes: Based on the dynamic lidar sensing data, dynamic pipeline interface fitting plane model data and dynamic pipeline interface adjacent hoisting circumferential cutting plane model data are extracted, and the dynamic pipeline strain sensing data corresponding to the lidar sampling time of the dynamic lidar sensing data is set as the high-frequency update reference parameter of the dynamic lidar sensing data. The dynamic interface plane normal vector of the pipe interface plane is calculated based on the dynamic pipe interface fitting plane model data, and the axial deformation data of the pipe interface is set based on the dynamic pipe interface plane normal vector. The dynamic eccentricity and dynamic major axis rotation angle of the pipe interface plane are calculated based on the fitted plane model data of the dynamic pipe interface, and the circumferential deformation data of the pipe interface is set based on the dynamic eccentricity and dynamic major axis rotation angle. The coordinates of the midpoint of the dynamic pipe interface plane are calculated based on the fitted plane model data of the dynamic pipe interface. The coordinates of the midpoint of the dynamic lifting circumferential cutting plane are calculated based on the adjacent lifting circumferential cutting plane model data of the dynamic pipe interface. The coordinates of the midpoint of the dynamic lifting circumferential cutting plane are used as the starting point of the axial pointing vector and the coordinates of the midpoint of the dynamic pipe interface plane are used as the ending point of the axial pointing vector to construct the axial pointing vector of the pipe lifting end. The axial deformation data of the pipe lifting end is set based on the axial pointing vector of the pipe lifting end. Based on the dynamic pipeline strain sensing data at each strain sampling time within the laser radar sampling interval corresponding to the dynamic laser radar sensing data, combined with the high-frequency update reference parameters and the real-time deformation data of the pipeline to be installed corresponding to the laser radar sampling time, the axial deformation data of the pipeline interface, the circumferential deformation data of the pipeline interface, and the axial deformation data of the pipeline hoisting end at each strain sampling time are updated to obtain the axial deformation data of the pipeline interface, the circumferential deformation data of the pipeline interface, and the axial deformation data of the pipeline hoisting end at each strain sampling time.

4. The method according to claim 3, characterized in that, The dynamic pipeline strain sensing data includes axial strain sensing data of the pipeline interface fitting plane, circumferential strain sensing data of the pipeline interface fitting plane, axial strain sensing data of the adjacent hoisting circumferential cutting plane, and circumferential strain sensing data of the adjacent hoisting circumferential cutting plane. The high-frequency updated reference parameters include axial strain reference parameters of the pipeline interface fitting plane, circumferential strain reference parameters of the pipeline interface fitting plane, axial strain reference parameters of the adjacent hoisting circumferential cutting plane, and circumferential strain reference parameters of the adjacent hoisting circumferential cutting plane. The dynamic pipeline strain sensing data at each strain sampling time within the laser radar sampling interval corresponding to the dynamic laser radar sensing data, combined with the high-frequency updated reference parameters and the real-time deformation data of the pipeline to be installed corresponding to the laser radar sampling time, calculates the axial deformation data of the pipeline interface, the circumferential deformation data of the pipeline interface, and the axial deformation data of the pipeline hoisting end at each strain sampling time, including: Based on the difference between the axial strain sensing data of the pipe interface fitting plane at each strain sampling time and the axial strain reference parameter of the pipe interface fitting plane, the axial strain increment of the pipe interface fitting plane at each strain sampling time is calculated. Based on the difference between the circumferential strain sensing data of the pipe interface fitting plane at each strain sampling time and the circumferential strain reference parameter of the pipe interface fitting plane, the circumferential strain increment of the pipe interface fitting plane at each strain sampling time is calculated. Based on the difference between the axial strain sensing data of the adjacent hoisting circumferential plane and the axial strain reference parameter of the adjacent hoisting circumferential plane at each strain sampling time, the axial strain increment of the adjacent hoisting circumferential plane at each strain sampling time is calculated. Based on the difference between the circumferential strain sensing data of the adjacent hoisting circumferential plane and the circumferential strain reference parameter of the adjacent hoisting circumferential plane at each strain sampling time, the circumferential strain increment of the adjacent hoisting circumferential plane at each strain sampling time is calculated. Based on the axial strain increment of the fitting plane of the pipe interface and the circumferential strain increment of the fitting plane of the pipe interface, the dynamic interface plane normal vector increment corresponding to the dynamic interface plane normal vector is calculated. Based on the dynamic interface plane normal vector increment at each strain sampling time and the axial deformation data of the pipe interface at each lidar sampling time, the axial deformation data of the pipe interface at each strain sampling time is calculated. Based on the circumferential strain increment of the fitted plane of the pipe interface, the dynamic eccentricity increment corresponding to the dynamic eccentricity and the dynamic major axis rotation angle increment corresponding to the dynamic major axis rotation angle are calculated. Based on the dynamic eccentricity increment, the dynamic major axis rotation angle increment, the dynamic eccentricity corresponding to the lidar sampling time, and the dynamic major axis rotation angle corresponding to the lidar sampling time, the circumferential deformation data of the pipe interface at each strain sampling time are calculated. Based on the axial strain increment of the adjacent hoisting circumferential plane and the circumferential strain increment of the adjacent hoisting circumferential plane, the axial pointing vector increment of the pipe hoisting end corresponding to the axial pointing vector of the pipe hoisting end is calculated. Based on the axial pointing vector increment of the pipe hoisting end at each of the strain sampling times and the axial pointing vector of the pipe hoisting end corresponding to the lidar sampling time, the axial deformation data of the pipe hoisting end at each of the strain sampling times is calculated.

5. The method according to any one of claims 1 to 4, characterized in that, The process involves optimizing and solving for the docking compensation parameters of the pipe interface based on the real-time pose data of the pipe to be installed, the real-time deformation data of the pipe to be installed, and the mechanical constraint parameters of the pipe interface, combined with a docking compensation optimization algorithm. This includes: Based on the mechanical constraint parameters of the pipe interface to be installed, a feasible solution domain for docking compensation optimization is constructed. In the feasible solution domain of the docking compensation optimization, the docking compensation parameters of the interface of the pipeline to be installed are obtained by optimizing the solution based on the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the docking compensation optimization algorithm. The expression for the optimization loss function of the docking compensation optimization algorithm is as follows: In the formula, This refers to the docking compensation parameter vector corresponding to the docking compensation parameters of the pipe interface to be installed. The optimized loss function is... , and These are the deformation weighting coefficient, pose weighting coefficient, and stress weighting coefficient, respectively. This is a deformation compensation vector function based on the aforementioned docking compensation parameter vector. for The real-time deformation vector corresponding to the real-time deformation data of the pipeline to be installed at any given time. It is the second norm. This refers to the real-time pose vector corresponding to the real-time pose data of the pipeline to be installed. This is the equivalent stress calculation function for the pipe interface based on the aforementioned docking compensation parameter vector. The maximum allowable stress value, It is a function for maximizing the value.

6. The method according to claim 5, characterized in that: The mechanical constraint parameters of the pipe interface to be installed include the pipe interface tensile strain constraint parameters, the pipe interface compressive strain constraint parameters, and the pipe interface connection stiffness parameters.

7. The method according to claim 5, characterized in that, The docking compensation parameters for the pipe interface to be installed include the position docking compensation parameters and the attitude docking compensation parameters of the pipe interface to be installed. The static pose data of the target installation interface includes the position data and the attitude data of the target installation interface. The target pose data of the pipe interface to be installed includes the target position data and the target attitude data of the pipe interface to be installed. The step of calculating the target pose data of the pipe interface to be installed based on the static pose data of the target installation interface and the docking compensation parameters of the pipe interface to be installed includes: The target location data of the pipe interface to be installed is calculated based on the target installation interface location data and the docking compensation parameters of the pipe interface to be installed. The target attitude data of the pipe interface to be installed is calculated based on the target installation interface attitude data and the attitude docking compensation parameters of the pipe interface to be installed.

8. A pipeline data processing system based on multi-source sensing, characterized in that, The system includes: The pipeline installation data monitoring module is used to acquire static pose data of the target installation interface, static structural data of the pipeline to be installed, multi-source sensing data of the pipeline to be installed, and mechanical constraint parameters of the interface of the pipeline to be installed. The pipeline installation feature extraction module is used to extract real-time pose data, real-time deformation data, and real-time installation environment data of the pipeline to be installed based on the static structural data of the pipeline to be installed and the multi-source sensing data of the pipeline to be installed. The docking compensation optimization solution module is used to optimize and solve the docking compensation parameters of the interface of the pipeline to be installed based on the real-time pose data of the pipeline to be installed, the real-time deformation data of the pipeline to be installed, and the mechanical constraint parameters of the interface of the pipeline to be installed, combined with the docking compensation optimization algorithm. The target pose data calculation module is used to calculate the target pose data of the pipe interface to be installed based on the static pose data of the target installation interface and the docking compensation parameters of the pipe interface to be installed. The pipeline installation path planning module is used to perform pipeline installation path planning and kinematic analysis based on the real-time pose data of the pipeline to be installed, the target pose data of the interface of the pipeline to be installed, and the real-time installation environment data of the pipeline to be installed, and to generate pipeline installation motion trajectory control parameters.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

Images