Intelligent management method and system for prefabricated part transfer and storage based on multi-source data fusion

Abstract

The invention provides an intelligent management method and system for prefabricated part transfer and storage based on multi-source data fusion, and the method comprises the steps: constructing a prefabricated part position recognition device based on a Beidou positioning technology and a visual positioning technology, and achieving unified time synchronization with UTC as a time reference; positioning and identifying spatial position information, an image spatial positioning reference and component attribute information of the prefabricated component based on a prefabricated component position identification device; constructing an equipment data fusion and management software system, and integrally binding the spatial position information, the image spatial positioning reference and the component attribute information based on the equipment data fusion and management software system to obtain a unique identity code of the component; and on the basis of the unique identity code of the component, the factory-oriented intelligent management and scheduling optimization of the prefabricated component are realized. According to the invention, full-process intelligent management of the prefabricated parts from positioning, identification and information storage to transfer and storage, stacking optimization and factory dispatching is realized.

Description

Technical Field

[0001] This invention belongs to the field of digital and intelligent management technology for engineering construction, specifically relating to an intelligent management method and system for the transfer and storage of prefabricated components based on multi-source data fusion. Background Technology

[0002] Precast components are widely used in the construction of transportation infrastructure such as bridges, railways, and highways. With the expansion of prefabricated construction, the number of precast components on-site is large, their specifications are complex, batches are frequent, and their stacking is dynamically changing. Traditional methods relying on manual scheduling present several problems: (1) Low search efficiency: The component location record is delayed and the positioning error is large, and the on-site search is time-consuming; (2) Inconsistent information: Attribute information such as component size, production date, and purpose is scattered in paper or isolated systems, making it difficult to be consistent with location data and to link in a timely manner; (3) Lack of optimization in scheduling: The transfer and outgoing paths, order, and stacking schemes fail to combine real-time location and attribute data, resulting in more secondary handling and higher energy consumption; (4) High safety risks: personnel and large equipment work together, and there is a lack of process control and alarm based on a unified spatial and temporal benchmark.

[0003] Existing technologies have introduced high-precision positioning and image recognition, but they mostly focus on single-point breakthroughs and lack an integrated solution that combines high-precision positioning with a unified time reference, image spatial positioning reference, and component attribute information to further drive intelligent migration and factory management. Therefore, it is necessary to propose a systematic approach that takes BeiDou + visual positioning as the core, UTC / GPS time as the unified reference, multi-source data fusion as the means, and intelligent factory management as the goal. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides an intelligent management method and system for the transfer and storage of prefabricated components based on multi-source data fusion. Under a unified time reference, combined with BeiDou high-precision positioning and image spatial positioning reference, the component attribute information output by image recognition is used to establish a hierarchical and modular software architecture, realizing intelligent management of the entire process of prefabricated components from positioning, identification, information storage, to transfer, stacking optimization and factory scheduling.

[0005] To achieve the above objectives, the present invention provides the following solution: A method for intelligent management of prefabricated component transfer based on multi-source data fusion, the method comprising: Based on BeiDou positioning technology and combined with visual positioning technology, a prefabricated component location identification device is constructed, and UTC is used as the time reference to achieve unified time synchronization; Based on the precast component location identification device, the spatial location information, image spatial positioning reference and component attribute information of the precast component are identified; Construct a software system for equipment data fusion and management, and based on the software system, integrate and bind spatial location information, image spatial positioning benchmarks and component attribute information to obtain a unique identification code for the component; Based on the unique identification code of the component, intelligent management and scheduling optimization of prefabricated components are realized for shipment.

[0006] Preferred methods for achieving unified time synchronization using UTC as the time base include: The PPS pulses and time messages output by the GNSS receiver are used as a unified time source. A time series is formed by adopting a "dual-channel" synchronization strategy. Based on the time series, a synchronization controller is used to align the BeiDou positioning data, IMU attitude, image acquisition sequence and component attribute information under the same GPS time system.

[0007] Preferably, the equipment data fusion and management software system includes: a control layer, a data layer, and a display layer; The control layer is responsible for time synchronization, triggering mechanisms, and multi-sensor coordination. The data layer is used to store fused data in a unified format, including: timestamps, spatial locations, poses, image indexes, component attribute information, and events; The display layer is used to overlay spatial location, component attribute information, and inventory information to achieve a unified display of prefabricated component identification, positioning, and status.

[0008] Preferably, the method for obtaining a unique identification code for a component by integrating spatial location information, image spatial positioning benchmarks, and component attribute information based on a device data fusion and management software system includes: Establish a multi-level coordinate transformation chain from "camera coordinate system → carrier coordinate system → station-centered coordinate system → geocentric-ground-fixed coordinate system", specifically including: Transformation from camera coordinate system to carrier coordinate system: ; in, ; in, The coordinates are in the carrier coordinate system. The coordinates are in a Cartesian coordinate system. Transformation parameters from camera coordinate system to carrier coordinate system , , The matrix, It is a rotation matrix that represents the rotation from the image space rectangular coordinate system S to the carrier coordinate system b; It is a rotation matrix representing the rotation from the carrier coordinate system b to the image space rectangular coordinate system S, R x R y R z These are rotation matrices that rotate about the x-axis, y-axis, and z-axis, respectively. , , These are the rotation parameters between the carrier coordinate system and the image space rectangular coordinate system; Transformation from carrier coordinate system to station center coordinate system: To transform the coordinates from the station-centered coordinate system to the carrier coordinate system, first rotate around the z-axis; then around the x-axis; and finally around the y-axis, then we have: ; in, ; in, The coordinates are in the station-centered coordinate system. It is a rotation matrix representing the rotation from the carrier coordinate system b to the station center coordinate system l, where r is the roll angle and p is the pitch angle. These are the transformation parameters from the carrier coordinate system to the station center coordinate system; Transformation from station-centered coordinate system to Earth-centered and Earth-fixed coordinate system: To convert coordinates from the station-centered coordinate system to the WGS84 coordinate system: first rotate around the x-axis; then rotate around the z-axis; finally, translate the local horizontal coordinate system origin to the WGS84 coordinate system origin. Then we have: ; in, ; in, This represents the spatial rectangular coordinates of the object point in the Earth-centered Earth-fixed coordinate system. This represents the coordinates of the station's origin in the geocentric coordinate system. It is a rotation matrix that represents the rotation from the station-centered coordinate system l to the geocentric coordinate system e, where L and B are the transformation parameters from the station-centered coordinate system to the geocentric coordinate system e. have to: .

[0009] Preferred methods for intelligent management and scheduling optimization of prefabricated components before delivery, based on their unique identification codes, include: Write the unique identification code of the component into the preset database, and use this identification code as the index to perform status changes and inventory statistics for the entire process of warehousing, transfer, and shipment, so as to achieve real-time consistency between identity binding and inventory dynamics. Based on order requirements, component attribute information, and scheduling constraints, a candidate list and priority for shipment are generated; Based on the candidate list and priority of the prefabricated components to be shipped, an objective function is set with the overall goal of reducing secondary handling, shortening travel distance, reducing the number of take-offs and landings and waiting time. Stacking optimization and path planning are carried out to realize intelligent management and scheduling optimization of prefabricated components for shipment.

[0010] The present invention also provides an intelligent management system for the transfer and storage of prefabricated components based on multi-source data fusion. The system is used to implement the aforementioned method and includes: a construction module, an identification module, a fusion module, and a management and scheduling module. The module is used to build a prefabricated component location identification device based on BeiDou positioning technology and combined with visual positioning technology, and to achieve unified time synchronization using UTC as the time reference. The identification module is used to locate and identify the spatial location information, image spatial positioning reference, and component attribute information of prefabricated components based on the prefabricated component location identification device. The fusion module is used to build a software system for fusion and management of equipment data, and to bind spatial location information, image spatial positioning benchmarks and component attribute information in an integrated manner based on the software system to obtain a unique identification code for the component. The management and scheduling module is used to achieve intelligent management and scheduling optimization of prefabricated components for shipment, based on the unique identification code of the components.

[0011] Preferred methods for achieving unified time synchronization using UTC as the time base include: The PPS pulses and time messages output by the GNSS receiver are used as a unified time source. A time series is formed by adopting a "dual-channel" synchronization strategy. Based on the time series, a synchronization controller is used to align the BeiDou positioning data, IMU attitude, image acquisition sequence and component attribute information under the same GPS time system.

[0012] Preferably, the equipment data fusion and management software system includes: a control layer, a data layer, and a display layer; The control layer is responsible for time synchronization, triggering mechanisms, and multi-sensor coordination. The data layer is used to store fused data in a unified format, including: timestamps, spatial locations, poses, image indexes, component attribute information, and events; The display layer is used to overlay spatial location, component attribute information, and inventory information to achieve a unified display of prefabricated component identification, positioning, and status.

[0013] Preferably, the method for obtaining a unique identification code for a component by integrating spatial location information, image spatial positioning benchmarks, and component attribute information based on a device data fusion and management software system includes: Establish a multi-level coordinate transformation chain from "camera coordinate system → carrier coordinate system → station-centered coordinate system → geocentric-ground-fixed coordinate system", specifically including: Transformation from camera coordinate system to carrier coordinate system: ; in, ; in, The coordinates are in the carrier coordinate system. The coordinates are in a Cartesian coordinate system. Transformation parameters from camera coordinate system to carrier coordinate system , , The matrix, It is a rotation matrix that represents the rotation from the image space rectangular coordinate system S to the carrier coordinate system b; It is a rotation matrix representing the rotation from the carrier coordinate system b to the image space rectangular coordinate system S, R x R y R z These are rotation matrices that rotate about the x-axis, y-axis, and z-axis, respectively. , , These are the rotation parameters between the carrier coordinate system and the image space rectangular coordinate system; Transformation from carrier coordinate system to station center coordinate system: To transform the coordinates from the station-centered coordinate system to the carrier coordinate system, first rotate around the z-axis; then around the x-axis; and finally around the y-axis, then we have: ; in, ; in, The coordinates are in the station-centered coordinate system. It is a rotation matrix representing the rotation from the carrier coordinate system b to the station center coordinate system l, where r is the roll angle and p is the pitch angle. These are the transformation parameters from the carrier coordinate system to the station center coordinate system; Transformation from station-centered coordinate system to Earth-centered and Earth-fixed coordinate system: To convert coordinates from the station-centered coordinate system to the WGS84 coordinate system: first rotate around the x-axis; then rotate around the z-axis; finally, translate the local horizontal coordinate system origin to the WGS84 coordinate system origin. Then we have: ; in, ; in, This represents the spatial rectangular coordinates of the object point in the Earth-centered Earth-fixed coordinate system. This represents the coordinates of the station's origin in the geocentric coordinate system. It is a rotation matrix that represents the rotation from the station-centered coordinate system l to the geocentric coordinate system e, where L and B are the transformation parameters from the station-centered coordinate system to the geocentric coordinate system e. have to: .

[0014] Preferably, the management and scheduling module includes: a binding unit, a factory candidate unit, and a scheduling unit; The binding unit is used to write the unique identification code of the component into a preset database, and to use this identification code as an index to perform status changes and inventory statistics for the entire process of warehousing, transfer, and shipment, so as to achieve real-time consistency between identification binding and inventory dynamics. The candidate unit for delivery is used to generate a list of candidate units for delivery and their priorities based on order requirements, component attribute information, and scheduling constraints. The scheduling unit is used to set an objective function based on the candidate list and priority of the prefabricated components to optimize stacking and plan the path, thereby realizing intelligent management and scheduling optimization of prefabricated components for delivery.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: Compared with existing technologies, this invention integrates BeiDou high-precision positioning, image spatial positioning benchmarks and component attribute information under a unified time reference, thereby improving the positioning and registration accuracy of components; achieving real-time consistency between inventory and status; significantly reducing transfer distance and operational energy consumption; improving system stability and scalability through distributed and keep-alive mechanisms; and lowering the operating threshold and improving on-site adaptability and security with B / S architecture and a simple UI. Attached Figure Description

[0016] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the overall process of the intelligent management method for the transfer and storage of prefabricated components based on multi-source data fusion according to an embodiment of the present invention; Figure 2 This is a flowchart of the communication keep-alive mechanism in an embodiment of the present invention; Figure 3 This is a schematic diagram of the module registration process in an embodiment of the present invention; Figure 4 This is a schematic diagram of the orientation elements within the camera according to an embodiment of the present invention; Figure 5 This is a schematic diagram of camera distortion (including radial and tangential directions) according to an embodiment of the present invention. Figure 6 This is a schematic diagram of data fusion in an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] Example 1 This invention provides an intelligent management method for the transfer and storage of prefabricated components based on multi-source data fusion, the method comprising: Based on BeiDou positioning technology and combined with visual positioning technology, a prefabricated component location identification device is constructed, and UTC is used as the time reference to achieve unified time synchronization; Based on the precast component location identification device, the spatial location information, image spatial positioning reference and component attribute information of the precast component are identified; Construct a software system for equipment data fusion and management, and based on the software system, integrate and bind spatial location information, image spatial positioning benchmarks and component attribute information to obtain a unique identification code for the component; Based on the unique identification code of the component, intelligent management and scheduling optimization of prefabricated components are realized for shipment.

[0021] like Figures 1-6 As shown, the specific implementation process of the present invention is as follows: (1) Construct a high-precision precast component position identification device and achieve unified time synchronization: Based on BeiDou positioning technology and combined with visual positioning technology, it independently integrates BeiDou positioning sensors, combined navigation modules, image sensors, industrial control computers, and image recognition modules. With BeiDou positioning algorithm as the core and UTC as the time reference, it synchronously completes platform positioning, control, and prefabricated component image capture, and transmits the data to the operation terminal in real time, realizing accurate positioning and data acquisition of prefabricated components.

[0022] Specifically, in the implementation of this invention, the aforementioned BeiDou positioning sensor, integrated navigation module, image sensor, industrial control computer, and image recognition module do not operate independently in a separate manner. Instead, they are autonomously integrated through a unified structural layout, time triggering, and data interface to form a single high-precision prefabricated component position recognition device. In terms of hardware, this device integrates power supply, interface, and installation through a unified carrier platform. In terms of software, the industrial control computer centrally processes BeiDou positioning algorithms, image acquisition, attribute recognition, and data fusion. A unified time base is provided by a synchronization controller, enabling multiple sensors to work collaboratively within millisecond-level accuracy.

[0023] The system comprises several components: a BeiDou positioning sensor and a combined navigation module, which outputs high-precision position and attitude information; an image sensor that acquires component images and provides feature information; an image recognition module that extracts attributes from the images; an industrial control computer that performs time-series registration and formatted encapsulation of data from positioning, attitude, imagery, and attributes; and a synchronization controller that provides a unified timestamp and coordinates the triggering of all sensor acquisitions. The fused data is transmitted to the monitoring terminal via a network, enabling real-time display of component identification, positioning, and operational status. Simultaneously, the monitoring terminal receives the fused data and issues operational commands to each sensor device, forming a closed loop of data acquisition, task control, and status feedback.

[0024] Through the aforementioned autonomous integration method, the triggering mechanism, time reference, and data format among the various sensors are unified, enabling the high-precision prefabricated component position identification device to have independent and reliable multi-source data acquisition and fusion capabilities, providing complete and consistent basic data for subsequent time synchronization, coordinate registration, and intelligent scheduling.

[0025] For time synchronization, hardware time base alignment is achieved through the PPS pulses output by the Event Out interface of the GNSS receiver. Upon detecting a PPS pulse, the synchronization controller receives and parses the corresponding time message via serial or Ethernet port to obtain the PPS pulse time information. When the next PPS pulse is detected, the timestamp of the previous PPS pulse is added by 1 second, thus forming a continuous and accurate time series. Based on the time series, the synchronization controller triggers camera (image sensor) exposure based on a unified timestamp and distributes the synchronization timestamp to the integrated navigation module and other peripherals (such as laser scanners and single-beam echo sounders), unifying all sensors to the GPS time system. The monitoring terminal sends operation commands (configuration parameters, synchronization initialization, start task, pause, end task, etc.) to the synchronization controller via the network. Upon receiving the "start task" command, the synchronization controller records the working time and event information on the synchronization board and completes GNSS time synchronization, while simultaneously transmitting the recorded events back to the monitoring terminal in real time.

[0026] In the specific scheme, the PPS pulse and time message adopt a "dual-channel" time stamping strategy: PPS provides second-level hard triggering, and time message provides absolute time resolution; the combination of the two can align the time base of multi-source data within milliseconds or even better precision. To reduce the time difference caused by link latency and jitter, the synchronization controller can record and correct interface latency. For sensors such as cameras and IMUs, a unified "timestamp + trigger sequence number" dual-key mechanism is used to ensure a one-to-one correspondence between frame-level data and inertial navigation data, thereby avoiding the accumulation of time extrapolation errors in the subsequent data fusion stage.

[0027] (2) Construct a software system for equipment data fusion and management, and realize the integrated binding of component attribute information with spatial and temporal references: This invention adopts a layered architecture and modular design to establish a device data fusion and management software system that includes a control layer, a data layer, and a display layer. It completes multi-sensor access, parameter configuration, raw data storage and playback, real-time visualization, and interface services. It binds the intelligent tag attribute information obtained from image recognition with high-precision position, attitude, and unified timestamp to form a unique identification code for the component.

[0028] Specifically: 1) Control layer: Provides communication connection between multiple sensors and display and control system software, setting of working parameters, and issuance of system control commands (including camera triggering, GNSS / IMU reading, and gantry crane linkage control).

[0029] 2) Data layer: Stores raw data in a preset data format, including fields such as {timestamp, spatial coordinates, attitude, image index, component attribute information, operation event, equipment receipt}; the stored data also serves the display, control, playback and post-processing fusion.

[0030] 3) Display layer: Displays camera footage and positioning and attitude information in real time, and overlays component attribute information and inventory status to provide visualization of operational status, alarms and scheduling suggestions.

[0031] Through these layers of design, the equipment data fusion and management software system can process and manage data from multiple sensors, and simultaneously bind the smart tags obtained from image recognition with high-precision position, attitude, and timestamp data to form a unique identification code for the component.

[0032] Network communication uses rpclib for message packaging and parsing. Control commands, status information, and global message bus events are transmitted via TCP / IP to ensure reliability; real-time data is transmitted via UDP / IP multicast to reduce network load (see [link]). Figure 2 ). Figure 2This describes a connection detection and response processing flow based on network communication. First, the system checks for a logout request; if none is found, it continues with subsequent steps. The flow responds to the module's probe message request, establishes a connection between the client and the control system, and checks for successful connection. If the connection is successfully established, the system sends a test message request and waits for a response. If no response is received within a specified time, the system resends the request until a successful response is received or a timeout occurs. This flow is closely related to the network communication mechanism mentioned earlier (using rpclib for message packaging and parsing, and transmitting data via TCP / IP and UDP / IP), ensuring reliable transmission and effective processing of control commands, status information, and real-time data, thereby guaranteeing system stability and reliability. The control communication link has a keep-alive mechanism; periodic heartbeats and probes are used to instantly identify link anomalies and automatically reconnect. The module receives UDP multicast probe messages and sends back its own network information to complete authentication and dynamic registration with the module manager (see [link to module manager]). Figure 3 ).like Figure 3 As shown, when a module receives a probe message, it performs corresponding operations based on the current network status. If the module is not connected to the network, the system will automatically establish a connection and register, establishing a control connection. If the module is already connected, the system will ensure the establishment of a control connection and establish feedback transmission of the module's status. Through this mechanism, the system can promptly detect and handle network link anomalies and ensure the stability of the communication link through automatic reconnection. Furthermore, by receiving and sending back UDP multicast probe messages, the module achieves authentication and dynamic registration with the system. This is highly related to the keep-alive mechanism mentioned earlier, ensuring real-time communication and reliable connections between various modules in the system, further enhancing the system's stability and fault tolerance.

[0033] In terms of stability and ease of operation, the system adopts a distributed design: each module runs as an independent process, and an anomaly in one module does not affect other modules; during module operation, parameter and job information snapshots are taken, allowing for "pause-troubleshooting-resumption"; the core functions adopt a B / S architecture, which can be accessed by PC, tablet, and mobile browsers; the main interface has permanent operations such as "create task, start task, pause task, end task", while low-frequency operations such as initialization, exit, and close are placed in pop-up menus.

[0034] In the specific solution, the image recognition module only acts as an attribute information provider, outputting "smart tag" information such as the component's size, production date, and purpose. The system integrates this attribute information with "spatial location (given by Beidou + integrated navigation), attitude information, and unified timestamp" to construct a "component unique identification code = (spatial location + attitude + attribute + timestamp)". This code serves as the primary key to drive the real-time updating and traceability of inventory ledgers and full lifecycle records (warehousing, transfer, shelf, and shipment).

[0035] In a preferred embodiment of the present invention, to achieve the integrated fusion of BeiDou high-precision positioning, image spatial positioning reference, and component attribute information, the present invention constructs a multi-sensor collaborative model under a unified time reference. It employs a hierarchical architecture, coordinate transformation chain, exterior orientation element solution, and attribute binding mechanism to achieve unified modeling and dynamic updating of component spatial position, attitude, and smart tag information. The fusion process includes steps such as time synchronization, coordinate registration, image point-object point correspondence calculation, and primary key binding of attributes and spatial position, as detailed below: First, in terms of time reference, time synchronization is achieved by the method described in (1) constructing a high-precision prefabricated component position identification device and realizing unified time synchronization.

[0036] Secondly, regarding the unification of spatial coordinates, a multi-level coordinate transformation chain is established, consisting of "camera coordinate system → carrier coordinate system → station-centered coordinate system → geocentric-ground-fixed coordinate system (ECEF)", specifically including: Let the image point coordinates in the image space rectangular coordinate system be (x, y), and the corresponding camera center coordinates be (x, y). s ,Y s Z s The coordinates of the object point in the carrier coordinate system are (X... b ,Y b Z b The three-dimensional coordinates of the object point (i.e., the projection point of the prefabricated component in the space at the instant of imaging) in the camera coordinate system are (X... c ,Y c Z c Then, a six-parameter model is used to transform the coordinates from the camera coordinate system to the carrier coordinate system: in, This represents the coordinates (X, Y) of the object point in the carrier coordinate system. b ,Y b Z b ), This represents the three-dimensional coordinates (X, Y, F, Z) of the object point in the camera coordinate system. c ,Y c Z c In this embodiment, similar representations all refer to coordinates in the corresponding coordinate system. R is the Rodrigue rotation matrix composed of Rodrigue parameters a, b, and c, and T... cb Let be the translation vector. In photogrammetry, the image point, object point, and photographic center must satisfy the collinearity condition, i.e., the collinearity equation: Where (X,Y,Z) are the three-dimensional spatial coordinates of the object point in the object space coordinate system, f is the camera principal distance, (x0,y0) are the coordinates of the principal image point, and λ is a scaling factor used to scale the direction vector in the imaging geometry to the object space scale, ensuring that the image point direction and the object point direction remain collinear in three-dimensional space. To improve the stability of attitude calculation, this invention uses the Rodrigue rotation matrix instead of Euler angles. The Rodrigue parameters a, b, and c are solved by least squares conditional adjustment, constructing the following adjustment model: Where A is the observation coefficient matrix, and v is the correction number for the observations. Let be the coefficient matrix of the parameters to be determined, δ be the correction number of the rotation and translation parameters, and W be the closure difference vector; establish 2n collinearity equations for n pairs of feature points, and obtain the exterior orientation elements and registration parameters by iteratively solving to minimize the residuals.

[0037] Then, the carrier coordinate system is transformed to the station center coordinate system through a three-dimensional rotation transformation of pitch angle, roll angle, and yaw angle. Then, the rectangular coordinates of the station center origin in the BeiDou position coordinate system (i.e., the geocentric coordinate system, ECEF) are obtained through the latitude and longitude information of the local horizontal coordinate system (i.e., the station center coordinate system) in the WGS84 system, realizing the following transformation: Among them, R se Let be the rotation matrix from the local horizontal coordinate system to ECEF. This represents the spatial rectangular coordinates (X, Y) of the object point under ECEF. e ,Y e Z e ), This represents the corresponding camera center coordinates (X, Y) in the image space rectangular coordinate system. s ,Y s Z s ), This indicates the coordinates (X, Y) of the origin of the station in ECEF. oe ,Y oe Z oe ).

[0038] Furthermore, regarding attribute fusion, the image recognition module outputs intelligent tag attribute information such as the component's size, production date, and purpose, and integrates it with its corresponding "BeiDou position coordinates, carrier attitude (IMU output), and image frame timestamp" to form a "component unique identification code = (spatial location + attitude + attribute + timestamp)". This unique identification code serves as the primary key of the full lifecycle database, spanning the entire process from warehousing, transfer, shelf placement, and factory shipment, achieving a unified index of location, attributes, images, and events.

[0039] Finally, in terms of software architecture, the equipment data fusion and management software system adopts a layered model of control layer, data layer, and display layer. The control layer is responsible for time synchronization, triggering mechanism, and multi-sensor coordination; the data layer stores fused data in a unified format, including fields such as {timestamp, spatial coordinates, attitude, image index, component attribute information, operation event, equipment receipt}; the display layer overlays spatial location, identification attributes, and inventory information in real time, realizing a unified display of component identification, positioning, and status. All modules communicate through a global message bus, with control commands transmitted via TCP / IP and real-time data multicast via UDP / IP, ensuring the real-time performance and stability of the multi-sensor fusion process.

[0040] Through the above multi-source fusion method, deep fusion of BeiDou positioning, image spatial positioning and component attribute information under a unified time and space reference is achieved, which significantly improves the consistency of component positioning, registration and identification, and provides a complete, accurate and traceable data foundation for subsequent migration optimization, stacking planning and factory scheduling.

[0041] Furthermore, establishing a multi-level coordinate transformation chain from "camera coordinate system → carrier coordinate system → station-centered coordinate system → geocentric-ground-fixed coordinate system" also includes: To ensure fusion accuracy, the system introduces integrated calibration and coordinate transformation. Single-camera intrinsic parameter calibration (see...) Figure 4 , Figure 5 ): Camera principal distance f, image principal point coordinates (x0, y0), radial distortion. Rotation parameters between the carrier coordinate system and the image space Cartesian coordinate system. , , Translation parameters The transformation yields the coordinates (X, Y, Z) of the object point in the image space rectangular coordinate system. Cam .

[0042] The conversion model is as follows: In the formula, This represents the coordinates (X, Y, Z) of the object point in the image space rectangular coordinate system. Cam , This represents the coordinates (X, Y, Z) of the object point in the Earth-centered, Earth-fixed coordinate system. ECEF , This indicates the coordinates (X, Y) of the center of the carrier in the Earth-centered, Earth-fixed coordinate system at the moment of taking the photo. P ,Y P Z P P represents the spatial rectangular coordinate vector of the origin of the carrier coordinate system under ECEF at the time of taking the picture. is the rotation matrix from the geocentric-ground-fixed coordinate system to the local horizontal coordinate system; Cam represents the camera coordinate system, BFS represents the carrier coordinate system, L' represents the local horizontal coordinate system (station-centered coordinate system), and ECEF represents the geocentric-ground-fixed coordinate system; This represents the rotation matrix used to transform from the local horizontal coordinate system to the carrier coordinate system. This represents the translation vector of the camera coordinate system relative to the carrier coordinate system. This represents the rotation matrix that transforms the vehicle coordinate system to the camera coordinate system.

[0043] In the image space rectangular coordinate system, the image point coordinates, the camera center, and the object point satisfy a collinear relationship, and the collinearity equation can be written as: Among them, (F) x F y F represents the image point coordinates in the image space rectangular coordinate system. x F y These represent the horizontal and vertical coordinates of the image points, respectively; Δx and Δy are the changes or error terms of the point coordinates; a1-a3 are the rotation matrix parameters from the camera coordinate system to the carrier coordinate system; b1-b3 are the rotation matrix parameters from the carrier coordinate system to the station-centered coordinate system; c1-c3 are the rotation matrix parameters from the station-centered coordinate system to the geocentric coordinate system (Earth center, Earth fixed coordinate system, WGS84, etc.).

[0044] This invention replaces Euler angle rotation with Rodrigues rotation matrix R to improve solution stability, wherein: Here, Δ represents the error term, which is used to describe the correction amount during rotation or translation.

[0045] After solving for the Rodrigues parameters a, b, and c, the rotation parameters are obtained through conversion. , , ,but , , and This is the desired external orientation element.

[0046] Linear optimization of the above equation, considering the errors in the observations, and using the parameterized conditional adjustment function model for parameter solution, the adjusted correction model becomes: Where V is the residual vector, representing the difference between the observed and estimated values. This is the corrected estimate obtained after adjustment, taking observation errors into account. The observation coefficient matrix A is: Here, diag represents a diagonal matrix.

[0047] For each element a in the observation coefficient matrix A n have: Where n represents n pairs of feature points, and each pair of feature points can be represented by two collinear equations; r, p, and h represent the carrier attitude information recorded by the inertial navigation system: roll angle r, pitch angle p, and yaw angle h; ) represents the spatial coordinates of the local horizontal coordinate system origin in the geocentric coordinate system, and f is the camera principal distance.

[0048] The coefficient matrix of the parameters to be determined: ,in: in, for The matrix; a, b, c and This represents the Rodrigues parameter and three translation values. W is the closed difference vector. ,in: Among them, (x) n ,y n (X) represents the coordinates of the nth image point. n ,Y n Z n ) represents the coordinates in the object space coordinate system.

[0049] Column least squares conditional extremum function : Where P'' is the weight matrix, representing the uncertainty or accuracy of the observed data; V is the residual vector, representing the difference between the observed and estimated values; and K is the Lagrange multiplier vector, used to introduce the conditional equation into the extremum function to constrain the observed residuals to satisfy the geometric or physical constraints.

[0050] Since each sensor in the system has errors, each observation needs to be considered when determining the weights. At the same time, in order to reduce the complexity of the weighting, the scheme sets the covariance between the observations to zero, that is, they are uncorrelated with each other.

[0051] Among them, P'' nrepresents the covariance matrix of the observations; diag represents the diagonal matrix.

[0052] The adjustment is performed using the least squares principle, and the parameters are solved iteratively. If the solution results meet the accuracy requirements, the iteration terminates, and the registration parameters are obtained.

[0053] Image and positioning / attitude data fusion and multi-coordinate system transformation: Multi-sensor data fusion in the system, such as Figure 6 As shown, image analysis, spatial integration, time synchronization, GNSS data, inertial navigation data, and joint sensor calibration are integrated into image data and positioning and attitude data, which are then fused. Image analysis extracts position information, spatial integration fuses data from different sensors, time synchronization ensures data consistency, and GNSS and inertial navigation data complement each other to provide accurate positioning and attitude estimation. Joint sensor calibration further improves the accuracy of data fusion. Ultimately, this fused data provides the system with high-precision positioning and attitude information, supporting subsequent multi-coordinate system transformations and intelligent management. This involves parameters for transforming from the camera coordinate system to the carrier coordinate system. , , Rotation parameters between the carrier coordinate system and the image space rectangular coordinate system , , Roll angle r, pitch angle p, and transformation parameters from the carrier coordinate system to the station center coordinate system And the transformation parameters L, B, from the station-centered coordinate system to the geocentric coordinate system , .

[0054] a. Transformation from camera coordinate system to carrier coordinate system: ; in, ; in, Transformation parameters from camera coordinate system to carrier coordinate system , , The matrix, , , These are the rotation parameters between the carrier coordinate system and the image space rectangular coordinate system; It is a rotation matrix that represents the rotation from the image space rectangular coordinate system (S) to the carrier coordinate system (b); R is a rotation matrix representing the rotation from the carrier coordinate system (b) to the image space rectangular coordinate system (S). x R y R zIt is a rotation matrix that rotates about the x-axis, y-axis, and z-axis respectively.

[0055] b. Transformation from the carrier coordinate system to the station center coordinate system: Roll angle r: The angle between the x-axis and the horizontal direction; Pitch angle p: The angle between the y-axis and the horizontal direction; Yaw angle h: The angle between the forward direction (xoy plane) and true north, with clockwise being positive.

[0056] To transform the coordinates from the station-centered coordinate system to the carrier coordinate system, first rotate around the z-axis; then around the x-axis; and finally around the y-axis, then we have: ; in, ; Where r is the roll angle, p is the pitch angle, These are the transformation parameters from the carrier coordinate system to the station center coordinate system. That is, the coordinates in the station-centered coordinate system; It is a rotation matrix that represents the rotation from the carrier coordinate system (b) to the station center coordinate system (l).

[0057] c. Transformation from station-centered coordinate system to geocentric / geostatic coordinate system: The origin of the station's coordinate system has latitude and longitude coordinates e and l in WGS84. Let the coordinates of the scan point in the ECEF coordinate system be (X... e ,Y e Z e To convert coordinates from the station-centered coordinate system to the WGS84 coordinate system: first rotate around the x-axis; then rotate around the z-axis; finally translate the local horizontal coordinate system origin to the WGS84 coordinate system origin, then we have: ; in, It is a rotation matrix that represents the rotation from the station-centered coordinate system (l) to the geocentric geofixed coordinate system (e).

[0058] have to: (3) Integrating high-precision spatial location information, image spatial positioning reference and attribute information to achieve intelligent transfer and factory management: Establish a full lifecycle database for components, and combine inbound and outbound information with on-site constraints to optimize component stacking locations, delivery order, and scheduling paths; issue work instructions to the gantry crane control terminal, and transmit the work process in a closed loop and continuously optimize it.

[0059] Step S3 specifically involves: First, writing the "unique component identification code" into the database, and then using this identification code as the index for status changes and inventory statistics across the entire process, including warehousing, transfer, and shipment, to achieve real-time consistency between identification binding and inventory dynamics. Subsequently, the factory generates a candidate shipment list and priority based on order requirements, component attributes (size, purpose, priority), and site constraints (road width, restricted areas, safety distances, equipment accessibility, and work windows), which is then submitted to the system. After obtaining the shipment list, the system optimizes stacking and path planning with the goals of reducing secondary handling, shortening travel distances, reducing the number of takeoffs and landings, and decreasing waiting time. It prioritizes rule- and constraint-based heuristic methods and reserves standardized APIs for expansion into reinforcement learning and swarm optimization strategies.

[0060] Regarding stacking optimization and path planning, this invention further proposes a comprehensive optimization method based on rule-based heuristics, constraint modeling, and path search, with the overall goal of reducing secondary handling, shortening travel distance, and reducing the number of takeoffs and landings and waiting time. First, an initial stacking scheme is generated based on the component's factory urgency, dimensional attributes, quality grade, and site zoning strategy. Then, using the mapping relationship between components and stacking grids as decision variables, the global operation sequence and equipment travel path are jointly modeled, and the initial scheme is iteratively optimized to output a feasible scheduling result that satisfies the constraints.

[0061] Specifically, based on the component set C' and the stacking location set P''', a binary allocation variable x is defined. i,p''' Indicate whether component i is placed at position p'''; and define w i W represents the weight parameter of component i, used to characterize the load-bearing requirements of this component during stacking; p''' The maximum load-bearing capacity of stacking location p''' is used to limit the stacking weight or number of stacking layers at that location, ensuring the stability and safety of the stacking position. The following constraints ensure that each component is assigned a unique location and meets the site's load-bearing capacity, stacking height, and accessibility requirements: In terms of path planning, the system constructs a topological graph G=(V,E) consisting of site roads, obstacles, restricted areas, and low-speed zones, and assigns a cost c(e) to each edge e∈E, where the cost c(e) comprehensively considers distance, estimated travel time, and safety risks. For the transport equipment at node v... s With v t For travel between locations, the optimal path is calculated using a graph search-based shortest path method (Dijkstra's algorithm). The solution process can be formalized as follows: Where π represents the number of nodes in the topological graph G=(V,E) starting from node v.s to target node v t A feasible driving path, the path consisting of a series of adjacent nodes or edges; This represents the optimal path that minimizes the path cost function among all feasible paths.

[0062] During the joint optimization phase, the system constructs the following optimization objective function for the scheduling scheme, taking stacking distance, operation sequence, equipment path length, and number of take-offs and landings as comprehensive costs: Among them, D total T is the total distance traveled across all paths. total N represents the total duration of the task. hoist Indicates the total number of takeoffs and landings, α, β, These are configurable weight parameters. By performing neighborhood search operations such as local swapping, position reallocation, and path 2-opt on the initial scheme, and iteratively evaluating the objective function value, the cost function J is gradually reduced, ultimately obtaining a job sequence and route that balances stacking feasibility and path optimality.

[0063] Furthermore, for applications with higher real-time requirements or frequent dynamic changes in the site, this invention provides a standardized API interface that can be connected to reinforcement learning or swarm optimization algorithms to achieve online adaptive scheduling optimization. When using a reinforcement learning scheme, the real-time inventory status, component attributes, and equipment location are combined to form a state vector s, and component allocation, stacking position selection, and the next target node are set as actions a'. A negative cost increment -ΔJ is used as the reward, forming a closed-loop learning process, thereby continuously improving the stability and efficiency of the scheduling strategy.

[0064] Through the above method, the present invention can achieve coordinated optimization of stacking layout and driving path under the premise of meeting stacking constraints, road accessibility and safety strategy, effectively reduce the probability of secondary handling of equipment, shorten the operation path length, reduce the number of take-off and landing and overall scheduling energy consumption, and improve the operation efficiency and safety of prefabricated component transfer and storage.

[0065] To formulate an executable plan, the system establishes an energy consumption assessment model (weighted by path length, number of takeoffs and landings, etc.) and jointly constrains it with safety policies (human-machine safety distance, low-speed zone, restricted area), outputting scheduling results that meet both energy consumption and safety requirements. The energy consumption assessment model specifically includes the following: Energy consumption reduction: During the lifting process, the component needs to overcome gravity and do work. The system is based on the component's mass m and the lifting height. The gravitational acceleration g and the number of takeoffs and landings n are estimated, and the hoisting mechanism efficiency η is combined with the results. hoist and declining energy recovery r regen Increase energy consumption Ehoist It can be represented as: Energy consumption during horizontal movement: Energy consumption during horizontal movement is mainly related to the path length D and the equipment drive efficiency η. drive Related factors, including rolling resistance and acceleration / deceleration behavior, are considered. Its energy consumption E travel It can be approximated as: Where μ is the equivalent rolling resistance coefficient. For running speed, n acc To speed up the number of times.

[0066] Waiting and auxiliary power consumption: While queuing, waiting for scheduling, or performing low-power tasks, the device still incurs basic power consumption. This portion of energy E idel According to the no-load power P idle Auxiliary equipment power P aux With waiting time t wait Perform linear accumulation: Energy consumption summary and weighted combination: The system combines the above energy consumption items according to preset weights to form an estimated total energy consumption for a single transfer: in, , , These are weighting coefficients set based on equipment characteristics and scheduling requirements, used to reflect the relative importance of each energy consumption item in the overall optimization objective.

[0067] The dispatching instructions are sent from the control layer to the gantry crane control terminal. Event and attitude data during the operation are transmitted back in real time to drive the rolling updates of inventory status and Gantt progress. When anomalies such as congestion, equipment alarms, or sudden weather changes occur, the system triggers plan recalculation and makes local adjustments to form a closed-loop execution.

[0068] In summary, this invention provides an intelligent management method for the transfer and storage of prefabricated components based on multi-source data fusion. Under a unified time reference, it integrates BeiDou high-precision positioning, image spatial positioning reference, and component attribute information to improve component positioning and registration accuracy; achieves real-time consistency between inventory and status; significantly reduces transfer distance and operational energy consumption; enhances system stability and scalability through distributed and keep-alive mechanisms; and lowers the operational threshold and improves on-site adaptability and security with B / S architecture and a simple UI.

[0069] Example 2 Based on the same inventive concept, the present invention also provides an intelligent management system for the transfer and storage of prefabricated components based on multi-source data fusion, for implementing the aforementioned method. The system includes: a construction module, an identification module, a fusion module, and a management and scheduling module. The module is used to build a prefabricated component location identification device based on BeiDou positioning technology and combined with visual positioning technology, and to achieve unified time synchronization using UTC as the time reference. The identification module is used to locate and identify the spatial location information, image spatial positioning reference, and component attribute information of prefabricated components based on the prefabricated component location identification device. The fusion module is used to build a software system for fusion and management of equipment data, and to bind spatial location information, image spatial positioning benchmarks and component attribute information in an integrated manner based on the software system to obtain a unique identification code for the component. The management and scheduling module is used to achieve intelligent management and scheduling optimization of prefabricated components for shipment, based on the unique identification code of the components.

[0070] Furthermore, methods for achieving unified time synchronization using UTC as the time base include: The PPS pulses and time messages output by the GNSS receiver are used as a unified time source. A time series is formed by adopting a "dual-channel" synchronization strategy. Based on the time series, a synchronization controller is used to align the BeiDou positioning data, IMU attitude, image acquisition sequence and component attribute information under the same GPS time system.

[0071] Furthermore, the equipment data fusion and management software system includes: a control layer, a data layer, and a display layer; The control layer is responsible for time synchronization, triggering mechanisms, and multi-sensor coordination. The data layer is used to store fused data in a unified format, including: timestamps, spatial locations, poses, image indexes, component attribute information, and events; The display layer is used to overlay spatial location, component attribute information, and inventory information to achieve a unified display of prefabricated component identification, positioning, and status.

[0072] Furthermore, based on the equipment data fusion and management software system, methods for integrating spatial location information, image spatial positioning benchmarks, and component attribute information to obtain a unique component identification code include: Establish a multi-level coordinate transformation chain from "camera coordinate system → carrier coordinate system → station-centered coordinate system → geocentric-ground-fixed coordinate system", specifically including: Transformation from camera coordinate system to carrier coordinate system: ; in, ; in, The coordinates are in the carrier coordinate system. The coordinates are in a Cartesian coordinate system. Transformation parameters from camera coordinate system to carrier coordinate system , , The matrix, It is a rotation matrix that represents the rotation from the image space rectangular coordinate system S to the carrier coordinate system b; It is a rotation matrix representing the rotation from the carrier coordinate system b to the image space rectangular coordinate system S, R x R y R z These are rotation matrices that rotate about the x-axis, y-axis, and z-axis, respectively. , , These are the rotation parameters between the carrier coordinate system and the image space rectangular coordinate system; Transformation from carrier coordinate system to station center coordinate system: To transform the coordinates from the station-centered coordinate system to the carrier coordinate system, first rotate around the z-axis; then around the x-axis; and finally around the y-axis, then we have: ; in, ; in, The coordinates are in the station-centered coordinate system. It is a rotation matrix representing the rotation from the carrier coordinate system b to the station center coordinate system l, where r is the roll angle and p is the pitch angle. These are the transformation parameters from the carrier coordinate system to the station center coordinate system; Transformation from station-centered coordinate system to Earth-centered and Earth-fixed coordinate system: To convert coordinates from the station-centered coordinate system to the WGS84 coordinate system: first rotate around the x-axis; then rotate around the z-axis; finally, translate the local horizontal coordinate system origin to the WGS84 coordinate system origin. Then we have: ; in, ; in, This represents the spatial rectangular coordinates of the object point in the Earth-centered Earth-fixed coordinate system. This represents the coordinates of the station's origin in the geocentric coordinate system. It is a rotation matrix that represents the rotation from the station-centered coordinate system l to the geocentric coordinate system e, where L and B are the transformation parameters from the station-centered coordinate system to the geocentric coordinate system e. have to: .

[0073] Furthermore, the management and scheduling module includes: a binding unit, a factory candidate unit, and a scheduling unit; The binding unit is used to write the unique identification code of the component into a preset database, and to use this identification code as an index to perform status changes and inventory statistics for the entire process of warehousing, transfer, and shipment, so as to achieve real-time consistency between identification binding and inventory dynamics. The candidate unit for delivery is used to generate a list of candidate units for delivery and their priorities based on order requirements, component attribute information, and scheduling constraints. The scheduling unit is used to set an objective function based on the candidate list and priority of the prefabricated components to optimize stacking and plan the path, thereby realizing intelligent management and scheduling optimization of prefabricated components for delivery.

[0074] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for intelligent management of prefabricated component transfer based on multi-source data fusion, characterized in that, The method includes: Based on BeiDou positioning technology and combined with visual positioning technology, a prefabricated component location identification device is constructed, and UTC is used as the time reference to achieve unified time synchronization; Based on the precast component location identification device, the spatial location information, image spatial positioning reference and component attribute information of the precast component are identified; Construct a software system for equipment data fusion and management, and based on the software system, integrate and bind spatial location information, image spatial positioning benchmarks and component attribute information to obtain a unique identification code for the component; Based on the unique identification code of the component, intelligent management and scheduling optimization of prefabricated components are realized for shipment.

2. The method according to claim 1, characterized in that, Methods for achieving unified time synchronization using UTC as the time base include: The PPS pulses and time messages output by the GNSS receiver are used as a unified time source. A "dual-channel" synchronization strategy is adopted to form a time series. Based on the time series, a synchronization controller is used to align the BeiDou positioning data, IMU attitude, image acquisition sequence and component attribute information under the same GPS time system.

3. The method according to claim 1, characterized in that, The equipment data fusion and management software system includes: a control layer, a data layer, and a display layer; The control layer is responsible for time synchronization, triggering mechanisms, and multi-sensor coordination. The data layer is used to store fused data in a unified format, including: timestamps, spatial locations, poses, image indexes, component attribute information, and events; The display layer is used to overlay spatial location, component attribute information, and inventory information to achieve a unified display of prefabricated component identification, positioning, and status.

4. The method according to claim 3, characterized in that, Based on the equipment data fusion and management software system, the method of integrating spatial location information, image spatial positioning benchmarks, and component attribute information to obtain a unique component identification code includes: Establish a multi-level coordinate transformation chain: "camera coordinate system → carrier coordinate system → station-centered coordinate system → geocentric-geostatic coordinate system", specifically including: Transformation from camera coordinate system to carrier coordinate system: ； in, ； in, The coordinates are in the carrier coordinate system. The coordinates are in a Cartesian coordinate system. Transformation parameters from camera coordinate system to carrier coordinate system , , The matrix, It is a rotation matrix that represents the rotation from the image space rectangular coordinate system S to the carrier coordinate system b; It is a rotation matrix representing the rotation from the carrier coordinate system b to the image space rectangular coordinate system S, R x R y R z These are rotation matrices that rotate about the x-axis, y-axis, and z-axis, respectively. , , These are the rotation parameters between the carrier coordinate system and the image space rectangular coordinate system; Transformation from carrier coordinate system to station center coordinate system: To transform the coordinates from the station-centered coordinate system to the carrier coordinate system, first rotate around the z-axis; then around the x-axis; and finally around the y-axis, then we have: ； in, ； in, The coordinates are in the station-centered coordinate system. It is a rotation matrix representing the rotation from the carrier coordinate system b to the station center coordinate system l, where r is the roll angle and p is the pitch angle. These are the transformation parameters from the carrier coordinate system to the station center coordinate system; Transformation from station-centered coordinate system to Earth-centered and Earth-fixed coordinate system: To convert coordinates from the station-centered coordinate system to the WGS84 coordinate system: first rotate around the x-axis; then rotate around the z-axis; finally, translate the local horizontal coordinate system origin to the WGS84 coordinate system origin. Then we have: ； in, ； in, This represents the spatial rectangular coordinates of the object point in the Earth-centered Earth-fixed coordinate system. This represents the coordinates of the station's origin in the geocentric coordinate system. It is a rotation matrix that represents the rotation from the station-centered coordinate system l to the geocentric coordinate system e, where L and B are the transformation parameters from the station-centered coordinate system to the geocentric coordinate system e. have to: 。 5. The method according to claim 1, characterized in that, Methods for intelligent management and scheduling optimization of prefabricated components before delivery, based on their unique identification codes, include: Write the unique identification code of the component into the preset database, and use this identification code as the index to perform status changes and inventory statistics for the entire process of warehousing, transfer, and shipment, so as to achieve real-time consistency between identity binding and inventory dynamics. Based on order requirements, component attribute information, and scheduling constraints, a candidate list and priority for shipment are generated; Based on the candidate list and priority of the prefabricated components to be shipped, an objective function is set with the overall goal of reducing secondary handling, shortening travel distance, reducing the number of take-offs and landings and waiting time. Stacking optimization and path planning are carried out to realize intelligent management and scheduling optimization of prefabricated components for shipment.

6. An intelligent management system for the transfer and storage of prefabricated components based on multi-source data fusion, the system being used to implement the method described in any one of claims 1-5, characterized in that, The system includes: a construction module, an identification module, a fusion module, and a management and scheduling module; The module is used to build a prefabricated component location identification device based on BeiDou positioning technology and combined with visual positioning technology, and to achieve unified time synchronization using UTC as the time reference. The identification module is used to locate and identify the spatial location information, image spatial positioning reference, and component attribute information of prefabricated components based on the prefabricated component location identification device. The fusion module is used to build a software system for fusion and management of equipment data, and to bind spatial location information, image spatial positioning benchmarks and component attribute information in an integrated manner based on the software system to obtain a unique identification code for the component. The management and scheduling module is used to achieve intelligent management and scheduling optimization of prefabricated components for shipment, based on the unique identification code of the components.

7. The system according to claim 6, characterized in that, Methods for achieving unified time synchronization using UTC as the time base include: The PPS pulses and time messages output by the GNSS receiver are used as a unified time source. A "dual-channel" synchronization strategy is adopted to form a time series. Based on the time series, a synchronization controller is used to align the BeiDou positioning data, IMU attitude, image acquisition sequence and component attribute information under the same GPS time system.

8. The system according to claim 6, characterized in that, The equipment data fusion and management software system includes: a control layer, a data layer, and a display layer; The control layer is responsible for time synchronization, triggering mechanisms, and multi-sensor coordination. The data layer is used to store fused data in a unified format, including: timestamps, spatial locations, poses, image indexes, component attribute information, and events; The display layer is used to overlay spatial location, component attribute information, and inventory information to achieve a unified display of prefabricated component identification, positioning, and status.

9. The system according to claim 8, characterized in that, Based on the equipment data fusion and management software system, the method of integrating spatial location information, image spatial positioning benchmarks, and component attribute information to obtain a unique component identification code includes: Establish a multi-level coordinate transformation chain: "camera coordinate system → carrier coordinate system → station-centered coordinate system → geocentric-geostatic coordinate system", specifically including: Transformation from camera coordinate system to carrier coordinate system: ； in, ； in, The coordinates are in the carrier coordinate system. The coordinates are in a Cartesian coordinate system. Transformation parameters from camera coordinate system to carrier coordinate system , , The matrix, It is a rotation matrix that represents the rotation from the image space rectangular coordinate system S to the carrier coordinate system b; It is a rotation matrix representing the rotation from the carrier coordinate system b to the image space rectangular coordinate system S, R x R y R z These are rotation matrices that rotate about the x-axis, y-axis, and z-axis, respectively. , , These are the rotation parameters between the carrier coordinate system and the image space rectangular coordinate system; Transformation from carrier coordinate system to station center coordinate system: To transform the coordinates from the station-centered coordinate system to the carrier coordinate system, first rotate around the z-axis; then around the x-axis; and finally around the y-axis, then we have: ； in, ； in, The coordinates are in the station-centered coordinate system. It is a rotation matrix representing the rotation from the carrier coordinate system b to the station center coordinate system l, where r is the roll angle and p is the pitch angle. These are the transformation parameters from the carrier coordinate system to the station center coordinate system; Transformation from station-centered coordinate system to Earth-centered and Earth-fixed coordinate system: To convert coordinates from the station-centered coordinate system to the WGS84 coordinate system: first rotate around the x-axis; then rotate around the z-axis; finally, translate the local horizontal coordinate system origin to the WGS84 coordinate system origin. Then we have: ； in, ； in, This represents the spatial rectangular coordinates of the object point in the Earth-centered Earth-fixed coordinate system. This represents the coordinates of the station's origin in the geocentric coordinate system. It is a rotation matrix that represents the rotation from the station-centered coordinate system l to the geocentric coordinate system e, where L and B are the transformation parameters from the station-centered coordinate system to the geocentric coordinate system e. have to: 。 10. The system according to claim 6, characterized in that, The management and scheduling module includes: binding unit, factory candidate unit, and scheduling unit; The binding unit is used to write the unique identification code of the component into a preset database, and to use this identification code as an index to perform status changes and inventory statistics for the entire process of warehousing, transfer, and shipment, so as to achieve real-time consistency between identification binding and inventory dynamics. The candidate unit for delivery is used to generate a list of candidate units for delivery and their priorities based on order requirements, component attribute information, and scheduling constraints. The scheduling unit is used to set an objective function based on the candidate list and priority of the prefabricated components to optimize stacking and plan the path, thereby realizing intelligent management and scheduling optimization of prefabricated components for delivery.

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