Method and system for dynamic control of materials based on magnetic levitation conveying line and medium

Abstract

The application provides a material dynamic control method, system and medium based on a magnetic suspension conveying line, which comprises the following steps: constructing a digital twin of the magnetic suspension conveying line, generating a stator network topology, and establishing a multi-layer index; assigning a unique address to each node in the stator network based on an analog-digital computer mechanism, establishing an address-topology association table and an address cache; performing address query based on a local search and global search strategy, locating the stator entity and path branch according to the target address; performing pre-binding and seamless switching of stator entity and path analysis based on a sliding window prediction algorithm and a double-buffer control mechanism; performing multi-actuator entity conflict judgment and priority analysis based on time and space graphs to obtain an analysis result, triggering stator network topology rollback and re-planning the path when the analysis result is abnormal; and realizing continuous, stable and efficient operation of the magnetic suspension conveying line in a complex topology and high concurrency scene through linkage closed-loop control.

Description

Technical Field

[0001] This application relates to the field of material conveying control technology, and more specifically, to a material dynamic control method, system and medium based on a magnetic levitation conveyor line. Background Technology

[0002] Magnetic levitation transport technology, with its advantages of being contactless, low-friction, and high-precision, is widely used in smart manufacturing and flexible production lines. However, in complex topologies and high-concurrency scenarios, existing control systems still face the following challenges:

[0003] Dynamic topology changes: When the production line is expanded or restructured, a lot of time is required to reconfigure the control logic, making it difficult to quickly adapt to new stator module combinations;

[0004] Cross-module continuous control: When the mover crosses different stator modules, there is a lack of a unified state synchronization and prediction mechanism, which can easily lead to speed jitter, positioning error or control gap.

[0005] Multi-motor cooperative scheduling: The lack of scalable conflict detection and priority allocation strategies for multiple motors running in parallel can easily lead to congestion, deadlock, or resource preemption.

[0006] Weak anomaly recovery capability: anomalies such as communication delays and module offline are difficult to identify and isolate in a timely manner, and topology-level rollback and path replanning lack algorithmic support;

[0007] Insufficient virtual-physical linkage: The lack of a closed-loop mechanism for data flow between the digital twin environment and the physical control system makes it difficult to synchronize simulation and actual operation.

[0008] Therefore, a control scheme for a magnetic levitation transport line that can take into account topological flexibility, continuous cross-module control, multi-motor cooperative scheduling, and anomaly self-healing capability is needed. Summary of the Invention

[0009] The purpose of this application is to provide a material dynamic control method, system and medium based on magnetic levitation conveyor lines. Through hierarchical graph structure management, modular address mapping, sliding window prediction, double buffer switching, multi-motor conflict scheduling and virtual-real linkage closed-loop control, the continuous, stable and efficient operation of magnetic levitation conveyor lines in complex topology and high-concurrency scenarios is realized.

[0010] This application also provides a material dynamic control method based on a magnetic levitation conveyor line, including:

[0011] Construct a digital twin of the magnetic levitation transport line, generate the stator network topology, and establish a multi-layer index;

[0012] A unique address is assigned to each node in the stator network based on the analog-to-digital computation mechanism, and an address-to-topology association table and address cache are established.

[0013] Address queries are performed based on local and global search strategies, and the target entity and path branch are located based on the target address.

[0014] Based on the sliding window prediction algorithm and the double buffer control mechanism, the stator entity and path analysis are pre-bound and seamlessly switched.

[0015] Based on time and space graphs, conflict determination and priority analysis of multiple moving sub-entities are performed to obtain analysis results. When the analysis results are abnormal, the stator network topology rollback is triggered to replan the path.

[0016] Optionally, in the material dynamic control method based on a magnetic levitation conveyor line described in the embodiments of this application, the stator network topology construction process includes:

[0017] Create a fixed entity, which includes a main branch, branch branches, and merge branches, with each branch associated with a path function;

[0018] A directed graph is formed based on parent-child relationships, and an adjacency list is used to store connection information, supporting one-to-many and many-to-one topologies;

[0019] Perform a depth-first traversal of the topology, detect loop structures, and record the set of key nodes of the loop path;

[0020] A multi-layer index is constructed, which includes a physical layer, a logical layer, and a scheduling layer. The physical layer records the module connection relationship, the logical layer is grouped by module address, and the scheduling layer maintains the state of the moving part.

[0021] Topology verification and updates are accomplished through incremental graph construction and hash verification.

[0022] Optionally, in the material dynamic control method based on a magnetic levitation conveyor line described in the embodiments of this application, a unique address is assigned to each node in the stator network based on a modular digital computation mechanism, the steps of which include:

[0023] Set the initial address and modulus of the main branch of the stator entity;

[0024] The base address of the fixed-child entity is calculated recursively based on the parent-child relationship. When encountering a cyclic structure, the logical position is distinguished by the periodically increasing modulus.

[0025] A bidirectional mapping from addresses to graph nodes is maintained through an address-topology association table, and an LRU cache is used to improve query efficiency.

[0026] Optionally, in the material dynamic control method based on a magnetic levitation conveyor line described in the embodiments of this application, address query is performed based on local search and global search strategies, specifically including:

[0027] Configure the initial base address (BaseAddress) and module (Module) for the stator entity;

[0028] Calculate the base address of the child entity based on the parent-child relationship;

[0029] If a loop structure is detected, increment the modulus periodically at the loop start point to ensure that the logical address is unique.

[0030] Calculate the actual address and store it in the address-topology association table;

[0031] Based on the address lookup service, local searches are performed first. If no match is found, a global search is performed by traversing the hierarchical index.

[0032] For frequently accessed addresses, LRU caching and bitmasks are used to accelerate parsing.

[0033] Optionally, in the material dynamic control method based on a magnetic levitation conveyor line described in the embodiments of this application, the multi-moving sub-entity conflict determination and priority analysis specifically includes:

[0034] Analyze the list of occupied intervals for each stator entity's future time window, perform cross-analysis based on the list of occupied intervals, and perform conflict detection.

[0035] Dynamic priority is calculated by combining work order urgency, remaining path length, and energy consumption model indicators.

[0036] When a potential deadlock is detected, the Banker's Algorithm is used to generate a safe sequence and trigger local path replanning.

[0037] Optionally, in the material dynamic control method based on a magnetic levitation conveyor line described in the embodiments of this application, the stator entity and path analysis are pre-bound and seamlessly switched, specifically including:

[0038] Real-time acquisition of the position and velocity status of moving sub-entities, and fusion of sensor data using Kalman filtering;

[0039] Construct a sliding window prediction sequence of length k, estimate the future position of the moving sub-entity, and query the corresponding stator module;

[0040] A control channel is pre-established for the predicted target module to complete parameter distribution and handshake.

[0041] A dual-buffer structure is used to manage control parameters, with the active buffer used for current control and the standby buffer used for modules that are about to be switched over.

[0042] During switching, a buffer hot switch is performed to ensure continuous control and data consistency during the process of the actuator crossing modules;

[0043] If the prediction error exceeds the threshold, an adaptive adjustment is triggered, updating the window parameters or rebinding the target module.

[0044] Secondly, embodiments of this application provide a material dynamic control system based on a magnetic levitation conveyor line. The system includes a memory and a processor. The memory includes a program for a material dynamic control method based on a magnetic levitation conveyor line. When the program for the material dynamic control method based on a magnetic levitation conveyor line is executed by the processor, it implements the following steps:

[0045] Construct a digital twin of the magnetic levitation transport line, generate the stator network topology, and establish a multi-layer index;

[0046] A unique address is assigned to each node in the stator network based on the analog-to-digital computation mechanism, and an address-to-topology association table and address cache are established.

[0047] Address queries are performed based on local and global search strategies, and the target entity and path branch are located based on the target address.

[0048] Based on the sliding window prediction algorithm and the double buffer control mechanism, the stator entity and path analysis are pre-bound and seamlessly switched.

[0049] Based on time and space graphs, conflict determination and priority analysis of multiple moving sub-entities are performed to obtain analysis results. When the analysis results are abnormal, the stator network topology rollback is triggered to replan the path.

[0050] Optionally, in the material dynamic control system based on a magnetic levitation conveyor line described in the embodiments of this application, the stator network topology construction process includes:

[0051] Create a fixed entity, which includes a main branch, branch branches, and merge branches, with each branch associated with a path function;

[0052] A directed graph is formed based on parent-child relationships, and an adjacency list is used to store connection information, supporting one-to-many and many-to-one topologies;

[0053] Perform a depth-first traversal of the topology, detect loop structures, and record the set of key nodes of the loop path;

[0054] A multi-layer index is constructed, which includes a physical layer, a logical layer, and a scheduling layer. The physical layer records the module connection relationship, the logical layer is grouped by module address, and the scheduling layer maintains the state of the moving part.

[0055] Topology verification and updates are accomplished through incremental graph construction and hash verification.

[0056] Optionally, in the material dynamic control system based on a magnetic levitation conveyor line described in the embodiments of this application, a unique address is assigned to each node in the stator network based on a modular digital computation mechanism. The steps include:

[0057] Set the initial address and modulus of the main branch of the stator entity;

[0058] The base address of the fixed-child entity is calculated recursively based on the parent-child relationship. When encountering a cyclic structure, the logical position is distinguished by the periodically increasing modulus.

[0059] A bidirectional mapping from addresses to graph nodes is maintained through an address-topology association table, and an LRU cache is used to improve query efficiency.

[0060] Thirdly, embodiments of this application also provide a computer-readable storage medium, which includes a material dynamic control method program based on a magnetic levitation conveyor line. When the material dynamic control method program based on a magnetic levitation conveyor line is executed by a processor, it implements the steps of the material dynamic control method based on a magnetic levitation conveyor line as described in any of the above claims.

[0061] As can be seen from the above, the material dynamic control method, system, and medium based on a magnetic levitation conveyor line provided in this application embodiment generate a stator network topology and establish a multi-layer index by constructing a digital twin of the magnetic levitation conveyor line; assign a unique address to each node in the stator network based on a modular-to-digital computation mechanism, and establish an address-to-topology association table and address cache; perform address queries based on local search and global search strategies, and locate stator entities and path branches according to the target address; perform pre-binding and seamless switching of stator entity and path analysis based on a sliding window prediction algorithm and a double buffer control mechanism; perform multi-moving sub-entity conflict judgment and priority analysis based on time and space graphs to obtain analysis results; when the analysis results are abnormal, trigger stator network topology rollback and replan the path; through hierarchical graph structure management, modular address mapping, sliding window prediction, double buffer switching, multi-moving sub-entity conflict scheduling, and virtual-real linkage closed-loop control, the continuous, stable, and efficient operation of the magnetic levitation conveyor line in complex topology and high-concurrency scenarios is realized. Attached Figure Description

[0062] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0063] Figure 1A flowchart of a material dynamic control method based on a magnetic levitation conveyor line provided in an embodiment of this application;

[0064] Figure 2 A flowchart illustrating the stator network topology construction and hierarchical indexing process for a material dynamic control method based on a magnetic levitation conveyor line, as provided in this application embodiment.

[0065] Figure 3 A flowchart illustrating the modular address calculation and query process for a material dynamic control method based on a magnetic levitation conveyor line, as provided in this application embodiment.

[0066] Figure 4 A flowchart of sliding window prediction and double buffer switching for a material dynamic control method based on a magnetic levitation conveyor line provided in an embodiment of this application;

[0067] Figure 5 A flowchart of multi-motor conflict scheduling and deadlock prevention for a material dynamic control method based on a magnetic levitation conveyor line provided in an embodiment of this application;

[0068] Figure 6 A flowchart illustrating the virtual-real linkage closed-loop control and anomaly recovery process of the material dynamic control method based on a magnetic levitation conveyor line provided in this application embodiment. Detailed Implementation

[0069] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0070] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0071] Please refer to Figure 1 , Figure 1This is a flowchart illustrating a material dynamic control method based on a magnetic levitation conveyor line according to some embodiments of this application. This material dynamic control method based on a magnetic levitation conveyor line is used in a terminal device and includes the following steps:

[0072] S101, construct a digital twin of the magnetic levitation transport line, generate the stator network topology, and establish a multi-layer index;

[0073] Specifically, the stator network topology includes:

[0074] Adjacency lists and sparse vectors are used to store the connection relationships of the stator modules;

[0075] Establish a hierarchical graph index that includes a physical topology layer, a logical grouping layer, and a dynamic scheduling layer;

[0076] A depth-first traversal algorithm is used to detect loop structures and record key nodes of the loop path to support path switching strategies.

[0077] S102, based on the analog-to-digital computation mechanism, assigns a unique address to each node in the stator network, and establishes an address-topology association table and address cache;

[0078] S103, perform address query based on local and global search strategies, and locate sub-entities and path branches according to the target address;

[0079] It should be noted that the address lookup service includes:

[0080] Starting from the current node of the active entity, perform a local range search and check the address range of the parent entity and the child entity branches;

[0081] When a local search fails, a global search is performed by traversing the hierarchical index.

[0082] For multiple candidate paths, the target path is determined according to the preset traffic distribution strategy, which prioritizes the shortest path, load balancing, or randomization.

[0083] S104, based on the sliding window prediction algorithm and the double buffer control mechanism, performs pre-binding and seamless switching of stator entity and path analysis;

[0084] Specifically, the sliding window prediction algorithm includes:

[0085] Based on the mover velocity v and the system sampling period Δt, a k-step sliding window is constructed to predict the position at the next k × Δt time.

[0086] By querying the target stator module through path prediction results, control channel pre-binding and parameter distribution can be completed in advance;

[0087] A double-buffered structure is used to maintain the active and backup buffers for control parameters, ensuring data consistency during switching.

[0088] S105 performs conflict determination and priority analysis of multiple moving sub-entities based on time and space graphs, and obtains analysis results. When the analysis results are abnormal, the stator network topology rollback is triggered to replan the path.

[0089] Specifically, exception handling includes:

[0090] The recovery strategy library is matched according to the anomaly type such as module offline, communication delay, mover stall or sensor drift.

[0091] Maintain timestamped snapshots of the topology, and roll back to the most recent stable state and re-execute predictions and scheduling when an anomaly occurs;

[0092] At loop structures or branch nodes, special control strategies are employed to prevent the mover from entering an infinite loop. The stator network supports elevator integration for transferring the mover between stator networks at different heights, specifically including:

[0093] Configure multiple workstation addresses for the elevator, with each address corresponding to the stator network at a different height level;

[0094] When the moving part needs to move across a height, the elevator is first moved to the target workstation, and the module of the associated stator entity is updated synchronously.

[0095] After the elevator completes its operation, the absolute address and path of the moving part are recalculated to maintain continuous transportation in three-dimensional space.

[0096] like Figure 2 As shown in the embodiment of the present invention, the stator network topology construction process includes:

[0097] S201, Create a fixed entity, which includes a main branch, branch branches, and merge branches, with each branch associated with a path function;

[0098] S202 forms a directed graph based on parent-child relationships and uses an adjacency list to store connection information, supporting one-to-many and many-to-one topologies;

[0099] S203 performs a depth-first traversal of the topology, detects loop structures, and records the set of key nodes in the loop path;

[0100] S204, construct a multi-layer index, which includes a physical layer, a logical layer and a scheduling layer. The physical layer records the module connection relationship, the logical layer is grouped by module address, and the scheduling layer maintains the state of the moving part.

[0101] S205 completes topology verification and updates through incremental graph construction and hash verification.

[0102] The physical layer records the module connection relationships, the logic layer groups modules by address, and the scheduling layer maintains the state of the actuators.

[0103] like Figure 3 As shown, according to an embodiment of the present invention, assigning a unique address to each node in a stator network based on a modular multiplication (MM / D) mechanism includes the following steps:

[0104] S301 sets the initial address and modulus of the main branch of the stator entity;

[0105] S302, calculates the base address of the fixed entity recursively based on the parent-child relationship, and distinguishes the logical position by periodically increasing the modulus when encountering a loop structure;

[0106] S303 maintains a bidirectional mapping from addresses to graph nodes through an address and topology association table, and uses an LRU cache to improve query efficiency.

[0107] According to an embodiment of the present invention, address lookup is performed based on local search and global search strategies, specifically including:

[0108] Configure the initial base address (BaseAddress) and module (Module) for the stator entity;

[0109] Calculate the base address of the child entity based on the parent-child relationship;

[0110] If a loop structure is detected, increment the modulus periodically at the loop start point to ensure that the logical address is unique.

[0111] Calculate the actual address and store it in the address-topology association table;

[0112] Based on the address lookup service, local searches are performed first. If no match is found, a global search is performed by traversing the hierarchical index.

[0113] For frequently accessed addresses, LRU caching and bitmasks are used to accelerate parsing.

[0114] According to an embodiment of the present invention, the conflict determination and priority analysis of multi-movement sub-entities specifically includes:

[0115] Analyze the list of occupied intervals for each stator entity's future time window, perform cross-analysis based on the list of occupied intervals, and perform conflict detection.

[0116] Dynamic priority is calculated by combining work order urgency, remaining path length, and energy consumption model indicators.

[0117] When a potential deadlock is detected, the Banker's Algorithm is used to generate a safe sequence and trigger local path replanning.

[0118] It should be noted that this application constructs a stator network graph structure that supports multi-level indexing and records key nodes through cyclic detection;

[0119] Based on the modular address system of AddressWithModule = BaseAddress + Module × 10000, fast parsing is achieved by combining address caching and index tables;

[0120] By utilizing a sliding window prediction and double-buffered control mechanism, pre-binding and seamless switching of the actuator across modules are achieved;

[0121] A multi-motor conflict scheduling algorithm based on time-space interval graphs, combined with the banker's idea to prevent deadlock;

[0122] Quick recovery is achieved through an anomaly recovery strategy library and topology snapshot rollback, in case of communication delays or module offline.

[0123] By leveraging the virtual-physical linkage interface, a closed loop of two-way data flow between the digital twin and the physical device can be achieved.

[0124] like Figure 4 As shown in the embodiment of the present invention, the pre-binding and seamless switching of stator entities and path analysis specifically includes:

[0125] S401 collects the position and velocity status of moving sub-entities in real time and fuses the sensor data using Kalman filtering.

[0126] S402, construct a sliding window prediction sequence of length k, calculate the future position of the moving sub-entity, and query the corresponding stator module;

[0127] S403: Pre-establish a control channel for the predicted target module and complete parameter distribution and handshake.

[0128] The S404 uses a dual-buffer structure to manage control parameters. The active buffer is used for current control, and the standby buffer is used for modules that are about to be switched.

[0129] S405 performs buffer hot switching during switching to ensure continuous control and consistent data during the process of moving parts crossing modules;

[0130] S406 triggers adaptive adjustment when the prediction error exceeds the threshold, updating window parameters or rebinding the target module.

[0131] According to an embodiment of the present invention, please refer to Figure 5 The multi-move sub-conflict scheduling strategy in this embodiment includes:

[0132] S501, maintains an IntervalList of occupied intervals for each stator module for the future time window h;

[0133] S502, when a user requests to occupy a module or path segment, check whether the target time period conflicts with the already reserved interval;

[0134] S503: If a conflict occurs, dynamic priority is calculated based on the urgency of the work order, the remaining path length, and the energy consumption model.

[0135] S504 adds the lower-priority mover to the waiting queue and triggers local path replanning;

[0136] S505 uses the Banker's Algorithm to maintain the system's safe sequence and prevent deadlock caused by circular waits;

[0137] S506 dynamically adjusts the traffic splitting strategy and priority in loop structures or bottleneck paths to maintain system throughput.

[0138] Through the above scheduling mechanism, this embodiment can still maintain high concurrency and stability in high-density operation scenarios of multiple motion vehicles.

[0139] Please refer to Figure 6 The exception handling and virtual-real linkage process in this embodiment includes:

[0140] S601 monitors events such as the online status of the monitoring module, communication latency, abnormal motor speed, and sensor drift.

[0141] S602, Match the recovery strategy corresponding to the anomaly type, including path detour, address remapping or control terminal switching;

[0142] S603 periodically generates timestamped snapshots of the topology and rolls back to the most recent stable state when an anomaly occurs;

[0143] S604, re-execute sliding window prediction and conflict scheduling to ensure that the control logic is restored to consistency;

[0144] S605, the virtual-real linkage module completes bidirectional data stream transmission through mover drive messages, shaft status messages and system status messages;

[0145] The S606 enables online monitoring, parameter optimization, and performance tracking through closed-loop control between the digital twin and physical devices.

[0146] According to embodiments of the present invention, the system further includes elevator integration and three-dimensional path control, specifically including:

[0147] In scenarios supporting multi-level conveying, this embodiment integrates the elevator as a special stator entity into the topology, specifically including:

[0148] Configure multiple workstation addresses for the elevator, setting different height levels according to WorkstationAddress = BaseAddress + WorkstationIndex × 10000;

[0149] When the moving part needs to move across a height, the system first dispatches the elevator to move to the target workstation and simultaneously updates the module of the associated stator entity;

[0150] After the elevator completes its operation, the absolute address and switching path of the mover are recalculated using sliding window prediction to ensure cross-floor continuity.

[0151] During elevator operation, the conflict scheduling module locks the relevant path intervals to prevent other moving parts from entering the conflict area.

[0152] Secondly, embodiments of this application provide a material dynamic control system based on a magnetic levitation conveyor line. The system includes a memory and a processor. The memory includes a program for a material dynamic control method based on a magnetic levitation conveyor line. When the program for the material dynamic control method based on a magnetic levitation conveyor line is executed by the processor, it implements the following steps:

[0153] Construct a digital twin of the magnetic levitation transport line, generate the stator network topology, and establish a multi-layer index;

[0154] A unique address is assigned to each node in the stator network based on the analog-to-digital computation mechanism, and an address-to-topology association table and address cache are established.

[0155] Address queries are performed based on local and global search strategies, and the target entity and path branch are located based on the target address.

[0156] Based on the sliding window prediction algorithm and the double buffer control mechanism, the stator entity and path analysis are pre-bound and seamlessly switched.

[0157] Based on time and space graphs, conflict determination and priority analysis of multiple moving sub-entities are performed to obtain analysis results. When the analysis results are abnormal, the stator network topology rollback is triggered to replan the path.

[0158] It should be noted that the system uses an Entity-Component-System (ECS) architecture to manage conveyor line assets, including:

[0159] Stator network management module: responsible for stator entity creation, connection relationship maintenance, and loop detection;

[0160] Address service module: responsible for address calculation, caching, and querying;

[0161] Predictive control module: performs sliding window prediction, double-buffered switching, and multi-motor conflict scheduling;

[0162] Virtual-Real Linkage Module: Responsible for message interfaces, data synchronization, and exception rollback.

[0163] The virtual-physical linkage module achieves bidirectional data flow control between the virtual environment and physical devices through message interfaces, including mover drive messages, axis status messages, and system status messages.

[0164] Furthermore, the system architecture and implementation methods specifically include:

[0165] The magnetic levitation conveyor control system adopts an ECS architecture, and its core modules include:

[0166] Stator network management module: responsible for the creation of stator entities, topology maintenance, cycle detection and incremental updates;

[0167] Address service module: provides interfaces for address calculation, caching, indexing, and intelligent querying;

[0168] Predictive control module: Implements sliding window prediction, double buffer switching, multi-motor conflict scheduling, and deadlock prevention;

[0169] The virtual-real linkage module is responsible for the synchronization of actuator drive messages, axis status feedback, and system status.

[0170] Anomaly recovery module: manages topology snapshots, anomaly policy library, and path replanning;

[0171] Data service module: Provides context access interface based on GUID, supporting real-time monitoring and data analysis.

[0172] The system supports synchronous and asynchronous data transmission via message queues and a real-time bus, and can be deployed on industrial PCs or edge computing nodes. The program can be stored in computer-readable storage media, and when executed by a processor, it implements the functions of the aforementioned modules.

[0173] According to an embodiment of the present invention, the stator network topology construction process includes:

[0174] Create a fixed entity, which includes a main branch, branch branches, and merge branches, with each branch associated with a path function;

[0175] A directed graph is formed based on parent-child relationships, and an adjacency list is used to store connection information, supporting one-to-many and many-to-one topologies;

[0176] Perform a depth-first traversal of the topology, detect loop structures, and record the set of key nodes of the loop path;

[0177] A multi-layered index is constructed, consisting of a physical layer, a logical layer, and a scheduling layer. The physical layer records the module connection relationships, the logical layer groups modules by their addresses, and the scheduling layer maintains the state of the moving parts.

[0178] According to an embodiment of the present invention, assigning a unique address to each node in a stator network based on a modular multiplication mechanism includes the following steps:

[0179] Set the initial address and modulus of the main branch of the stator entity;

[0180] The base address of the fixed-child entity is calculated recursively based on the parent-child relationship. When encountering a cyclic structure, the logical position is distinguished by the periodically increasing modulus.

[0181] A bidirectional mapping from addresses to graph nodes is maintained through an address-topology association table, and an LRU cache is used to improve query efficiency.

[0182] A third aspect of the present invention provides a computer-readable storage medium including a material dynamic control method program based on a magnetic levitation conveyor line. When the material dynamic control method program based on a magnetic levitation conveyor line is executed by a processor, it implements the steps of the material dynamic control method based on a magnetic levitation conveyor line as described in any of the above claims.

[0183] This invention discloses a material dynamic control method, system, and medium based on a magnetic levitation conveyor line. It generates a stator network topology and establishes a multi-layer index by constructing a digital twin of the magnetic levitation conveyor line. A unique address is assigned to each node in the stator network based on a modular-to-digital computation mechanism, and an address-to-topology association table and address cache are established. Address queries are performed based on local and global search strategies to locate stator entities and path branches according to the target address. A sliding window prediction algorithm and a double-buffered control mechanism are used to pre-bind and seamlessly switch the analysis of stator entities and paths. Multi-moving sub-entity conflict determination and priority analysis are performed based on time and space graphs to obtain analysis results. When an anomaly occurs in the analysis results, a stator network topology rollback is triggered to replan the path. Through hierarchical graph structure management, modular address mapping, sliding window prediction, double-buffered switching, multi-moving sub-entity conflict scheduling, and virtual-real linkage closed-loop control, continuous, stable, and efficient operation of the magnetic levitation conveyor line in complex topologies and high-concurrency scenarios is achieved.

[0184] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0185] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0186] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0187] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0188] Alternatively, if the integrated units of the present invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. A material dynamic control method based on a magnetic levitation conveyor line, characterized in that, include: Construct a digital twin of the magnetic levitation transport line, generate the stator network topology, and establish a multi-layer index; A unique address is assigned to each node in the stator network based on the analog-to-digital computation mechanism, and an address-to-topology association table and address cache are established. Address queries are performed based on local and global search strategies, and the target entity and path branch are located based on the target address. Based on the sliding window prediction algorithm and the double buffer control mechanism, the stator entity and path analysis are pre-bound and seamlessly switched. Based on time and space graphs, conflict determination and priority analysis of multiple moving sub-entities are performed to obtain analysis results. When the analysis results are abnormal, the stator network topology rollback is triggered to replan the path. Pre-binding and seamless switching between stator entities and path analysis are performed, specifically including: Real-time acquisition of the position and velocity status of moving sub-entities, and fusion of sensor data using Kalman filtering; Construct a sliding window prediction sequence of length k, estimate the future position of the moving sub-entity, and query the corresponding stator module; A control channel is pre-established for the predicted target module to complete parameter distribution and handshake. A dual-buffer structure is used to manage control parameters, with the active buffer used for current control and the standby buffer used for modules that are about to be switched over. During switching, a buffer hot switch is performed to ensure continuous control and data consistency during the process of the actuator crossing modules; If the prediction error exceeds the threshold, an adaptive adjustment is triggered to update the window parameters or rebind the target module. Assigning a unique address to each node in the stator network based on the analog-to-digital computation mechanism includes the following steps: Set the initial address and modulus of the main branch of the stator entity; The base address of the fixed-child entity is calculated recursively based on the parent-child relationship. When encountering a cyclic structure, the logical position is distinguished by the periodically increasing modulus. A bidirectional mapping from addresses to graph nodes is maintained through an address-topology association table, and an LRU cache is used to improve query efficiency.

2. The material dynamic control method based on a magnetic levitation conveyor line according to claim 1, characterized in that, The stator network topology construction process includes: Create a fixed entity, which includes a main branch, branch branches, and merge branches, with each branch associated with a path function; A directed graph is formed based on parent-child relationships, and an adjacency list is used to store connection information, supporting one-to-many and many-to-one topologies; Perform a depth-first traversal of the topology, detect loop structures, and record the set of key nodes of the loop path; A multi-layer index is constructed, which includes a physical layer, a logical layer, and a scheduling layer. The physical layer records the module connection relationship, the logical layer is grouped by module address, and the scheduling layer maintains the state of the moving part. Topology verification and updates are accomplished through incremental graph construction and hash verification.

3. The material dynamic control method based on a magnetic levitation conveyor line according to claim 1, characterized in that, Address lookup is performed based on local and global search strategies, specifically including: Configure the initial base address (BaseAddress) and module (Module) for the stator entity; Calculate the base address of the child entity based on the parent-child relationship; If a loop structure is detected, increment the modulus periodically at the loop start point to ensure that the logical address is unique. Calculate the actual address and store it in the address-topology association table; Based on the address lookup service, local searches are performed first. If no match is found, a global search is performed by traversing the hierarchical index. For frequently accessed addresses, LRU caching and bitmasks are used to accelerate parsing.

4. The material dynamic control method based on a magnetic levitation conveyor line according to claim 3, characterized in that, Conflict determination and priority analysis of multiple active sub-entities, specifically including: Analyze the list of occupied intervals for each stator entity's future time window, perform cross-analysis based on the list of occupied intervals, and perform conflict detection. Dynamic priority is calculated by combining work order urgency, remaining path length, and energy consumption model indicators. When a potential deadlock is detected, the Banker's Algorithm is used to generate a safe sequence and trigger local path replanning.

5. A material dynamic control system based on a magnetic levitation conveyor line, used to implement the method of claim 1, characterized in that, The system includes a memory and a processor. The memory contains a program for a material dynamic control method based on a magnetic levitation conveyor line. When the processor executes the program for the material dynamic control method based on the magnetic levitation conveyor line, it performs the following steps: Construct a digital twin of the magnetic levitation transport line, generate the stator network topology, and establish a multi-layer index; A unique address is assigned to each node in the stator network based on the analog-to-digital computation mechanism, and an address-to-topology association table and address cache are established. Address queries are performed based on local and global search strategies, and the target entity and path branch are located based on the target address. Based on the sliding window prediction algorithm and the double buffer control mechanism, the stator entity and path analysis are pre-bound and seamlessly switched. Based on time and space graphs, conflict determination and priority analysis of multiple moving sub-entities are performed to obtain analysis results. When the analysis results are abnormal, the stator network topology rollback is triggered to replan the path.

6. The material dynamic control system based on a magnetic levitation conveyor line according to claim 5, characterized in that, The stator network topology construction process includes: Create a fixed entity, which includes a main branch, branch branches, and merge branches, with each branch associated with a path function; A directed graph is formed based on parent-child relationships, and an adjacency list is used to store connection information, supporting one-to-many and many-to-one topologies; Perform a depth-first traversal of the topology, detect loop structures, and record the set of key nodes of the loop path; A multi-layer index is constructed, which includes a physical layer, a logical layer, and a scheduling layer. The physical layer records the module connection relationship, the logical layer is grouped by module address, and the scheduling layer maintains the state of the moving part. Topology verification and updates are accomplished through incremental graph construction and hash verification.

7. The material dynamic control system based on a magnetic levitation conveyor line according to claim 6, characterized in that, Assigning a unique address to each node in the stator network based on the analog-to-digital computation mechanism includes the following steps: Set the initial address and modulus of the main branch of the stator entity; The base address of the fixed-child entity is calculated recursively based on the parent-child relationship. When encountering a cyclic structure, the logical position is distinguished by the periodically increasing modulus. A bidirectional mapping from addresses to graph nodes is maintained through an address-topology association table, and an LRU cache is used to improve query efficiency.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a material dynamic control method program based on a magnetic levitation conveyor line. When the material dynamic control method program based on a magnetic levitation conveyor line is executed by a processor, it implements the steps of the material dynamic control method based on a magnetic levitation conveyor line as described in any one of claims 1 to 4.

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