Industrial mobile equipment digital twin data transmission system, method, and apparatus

Abstract

This application relates to a digital twin data transmission system, method, and device for industrial moving equipment, belonging to the field of data transmission technology. The system includes: adding a unified timestamp to data through a clock synchronization protocol at the edge transmission layer to achieve nanosecond-level clock synchronization across all nodes, ensuring time consistency of multi-source data; uniformly converting heterogeneous protocol data into a target format based on preset mapping rules, eliminating protocol barriers and simplifying the topology; reducing the end-to-end transmission latency of core data to milliseconds through a dual-link redundant transmission mechanism, achieving lossless switching between primary and backup links, and avoiding data loss due to single-point failures; hierarchically and compressing target format data, significantly reducing the amount of uploaded data and effectively saving network bandwidth and cloud storage resources; and sending feedback control commands generated in the cloud to the physical equipment PLC after security verification and priority scheduling, realizing closed-loop control of the digital twin drive and ensuring stable operation in complex industrial environments.

Description

Technical Field

[0001] This application relates to the field of data transmission technology, specifically to a digital twin data transmission system, method, and equipment for industrial moving equipment. Background Technology

[0002] Industrial moving equipment (such as centrifugal compressors, reciprocating compressors, steam turbines, fans, and pumps) serves as core production units in pillar industries of the national economy, including energy, petrochemicals, and metallurgy. The safety and efficiency of their operation are of paramount importance. Digital twin technology, a key technology for achieving intelligent operation and closed-loop optimization of such equipment, hinges on the precise, real-time state mapping between physical entities and virtual models. Data transmission, acting as the "central nervous system" connecting the physical and digital worlds, directly determines the simulation confidence, early warning timeliness, and control effectiveness of the digital twin system.

[0003] However, despite the widespread adoption of the digital twin concept in industry, in practical applications, the existing data transmission architecture still faces severe technical bottlenecks when dealing with the complex and ever-changing operating environment of industrial dynamic equipment, making it difficult to meet the twin requirements of highly dynamic and high-precision equipment.

[0004] Specifically, the numerous brands of equipment in industrial settings result in complex communication protocols. Existing data transmission solutions often employ protocol gateways for point-to-point protocol conversion. This chain-like conversion structure not only increases network topology complexity but, more importantly, introduces cumulative latency and single-point-of-failure risks. Considering that monitoring fast variables such as vibration and shaft displacement of moving equipment requires millisecond or even sub-millisecond response times, the traditional "acquisition-conversion-aggregation-upload" serial processing mode often generates end-to-end latency of tens or even hundreds of milliseconds, failing to meet the high-fidelity reproduction requirements of digital twin models for transient equipment conditions.

[0005] Secondly, industrial moving equipment, especially high-speed rotating machinery, typically uses high-frequency sampling (e.g., above 10kHz) for vibration monitoring, resulting in a single device generating terabytes of data per day. This data includes both a large amount of "plain" data under steady-state conditions and "characteristic" data during equipment start-up, shutdown, changes in operating conditions, and the onset of faults. Traditional transmission strategies often adopt a "one-size-fits-all" approach, uploading all data indiscriminately. This not only leads to the inefficient use of network bandwidth and a sharp increase in cloud storage costs, but also causes truly valuable key characteristic data to be submerged in massive amounts of redundant data, severely impacting the efficiency and accuracy of subsequent mechanistic and AI model analysis. Summary of the Invention

[0006] In view of this, this application provides a digital twin data transmission system, method and device for industrial moving equipment. The main purpose is to solve the technical problems of traditional data transmission architecture lacking edge intelligent processing capabilities, failing to perform hierarchical data governance, and failing to establish a link guarantee mechanism that matches the high real-time and high reliability requirements of industrial sites, thus failing to meet the full-link optimization requirements of industrial moving equipment digital twin system for data flow.

[0007] In a first aspect, this application provides an industrial motion equipment digital twin data transmission system, comprising: a physical motion equipment layer, an edge transmission layer, and a cloud twin layer; The physical motion device layer is communicatively connected to the edge transmission layer. The physical motion device layer is used to collect real-time operating data of industrial motion devices and transmit the real-time operating data to the edge transmission layer through a heterogeneous protocol. The edge transport layer is communicatively connected to the cloud twin layer. The edge transport layer receives the real-time running data, adds a unified timestamp to the real-time running data through a clock synchronization protocol to obtain timestamped real-time running data, and converts the timestamped real-time running data into target format data based on a preset unified information model mapping rule. The target format data is then cleaned and graded, and corresponding adaptive compression processing is performed according to the grading results to obtain graded compressed data. The graded compressed data is then subjected to double encryption processing to obtain encrypted data, and the encrypted data is transmitted to the cloud twin layer through a dual-link redundancy consisting of a TSN link and a 5G URLLC link. The cloud twin layer is used to receive the encrypted data and sequentially perform double decryption, decompression, and timestamp calibration on the encrypted data to obtain synchronized data; input the synchronized data into the virtual twin model to drive the virtual twin model to perform state updates; perform simulation analysis based on the synchronized data using the updated virtual twin model to generate feedback control commands; and after security verification and priority scheduling, send the feedback control commands back to the edge transmission layer through the dual links. The edge transmission layer is also used to receive the feedback control command, parse and verify the feedback control command, and send it to the PLC controller of the physical device layer to regulate the operating status of the physical device and complete closed-loop control.

[0008] Secondly, this application provides a method for transmitting digital twin data of industrial moving equipment, including: Real-time operating data of industrial moving equipment is collected through the physical moving equipment layer, and the real-time operating data is transmitted to the edge transmission layer through a heterogeneous protocol; The real-time running data is given a unified timestamp by the clock synchronization protocol of the edge transmission layer to obtain real-time running data marked with timestamps. Based on the preset unified information model mapping rules, the real-time running data marked with timestamps is uniformly converted into target format data. The target format data is cleaned and graded, and corresponding adaptive compression is performed according to the grading results to obtain graded compressed data. The graded compressed data is then subjected to double encryption to obtain encrypted data, which is then transmitted to the cloud twin layer through a dual-link redundancy consisting of a TSN link and a 5G URLLC link. The encrypted data is sequentially subjected to double decryption, decompression, and timestamp calibration through the cloud twin layer to obtain synchronized data. The synchronized data is then input into the virtual twin model to drive the virtual twin model to update its state. The updated virtual twin model performs simulation analysis based on the synchronized data to generate feedback control commands. After security verification and priority scheduling, the feedback control commands are sent back to the edge transmission layer through the dual links. The feedback control commands are parsed and verified by the edge transmission layer and sent to the PLC controller of the physical device layer to regulate the operating status of the physical device and complete closed-loop control.

[0009] Thirdly, this application provides an electronic device, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the computer program to implement the industrial moving equipment digital twin data transmission method described in the second aspect.

[0010] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the industrial moving equipment digital twin data transmission method described in the second aspect.

[0011] By employing the above technical solutions, this application provides an industrial moving equipment digital twin data transmission system, method, and device. Compared with existing technologies, this application can collect real-time operating data of industrial moving equipment through the physical moving equipment layer and transmit the real-time operating data to the edge transmission layer through a heterogeneous protocol. A unified timestamp is added to the real-time operating data using the clock synchronization protocol of the edge transmission layer to obtain timestamped real-time operating data. Based on a preset unified information model mapping rule, the timestamped real-time operating data is uniformly converted into target format data. The target format data is cleaned and graded, and corresponding adaptive compression processing is performed according to the grading results to obtain graded compressed data. Double encryption processing is performed on the graded compressed data to obtain encrypted data, which is then transmitted to 5G via a TSN link. The URLLC link forms a dual-link redundant transmission to the cloud twin layer; the cloud twin layer sequentially performs double decryption, decompression, and timestamp calibration on the encrypted data to obtain synchronized data; the synchronized data is input into the virtual twin model to drive the virtual twin model to update its state; the updated virtual twin model performs simulation analysis based on the synchronized data to generate feedback control commands; the feedback control commands are then sent back to the edge transmission layer via dual links after security verification and priority scheduling; the edge transmission layer parses and verifies the feedback control commands and sends them to the PLC controller of the physical device layer to regulate the operating state of the physical device, completing closed-loop control.

[0012] By adopting the above technical solution, this application addresses the technical problems in existing technologies where the numerous brands of industrial field equipment lead to complex communication protocols, and where traditional chain-based protocol conversion structures increase network topology complexity, introduce cumulative latency, and pose single-point failure risks. It achieves this by using an edge transmission layer based on preset unified information model mapping rules to uniformly convert heterogeneous protocol data (such as Modbus and Profinet) into a target format (such as OPC UA PubSub), eliminating protocol barriers and simplifying the topology. Simultaneously, this application employs the IEEE 1588 PTP clock synchronization protocol to add a unified timestamp to the data, achieving nanosecond-level clock synchronization across all nodes and ensuring time consistency of multi-source data. Combined with a dual-link redundant transmission mechanism of "TSN Time-Sensitive Network + 5G URLLC," the end-to-end transmission latency of core data can be reduced to milliseconds or even lower. This architecture effectively breaks through the performance bottleneck of the traditional "acquisition-conversion-aggregation-upload" serial processing mode, meeting the real-time requirements of digital twin models for high-fidelity reproduction of equipment transient operating conditions.

[0013] To address the technical problems of existing technologies that use a "one-size-fits-all" approach to upload all high-frequency sampling data, resulting in inefficient network bandwidth usage, escalating cloud storage costs, and key feature data being overwhelmed by massive amounts of redundant data, this application introduces an intelligent data grading and adaptive compression mechanism at the edge transmission layer. Through cleaning and grading, the system can distinguish between core data (such as fault features and data exceeding thresholds) and non-core data (such as steady-state, flat data) based on mechanistic rules or lightweight AI models, and perform corresponding adaptive compression (low-loss compression to preserve the fidelity of core data, and deep compression to reduce redundancy of non-core data). This on-demand transmission strategy significantly reduces the amount of uploaded data while fully preserving fault features, effectively saving network bandwidth and cloud storage resources, and improving the efficiency and accuracy of subsequent mechanistic and AI model analysis.

[0014] To address the lack of link assurance mechanisms in existing transmission solutions that match the high real-time and high reliability requirements of industrial environments, this application constructs a comprehensive security and reliability assurance system. In terms of security, double encryption ensures the confidentiality and integrity of data during upload and download. Regarding reliability, a dual-link redundancy mechanism utilizing TSN and 5G URLLC enables seamless switching between primary and backup links, preventing data loss due to single-point failures. Furthermore, feedback control commands generated in the cloud are securely verified and prioritized before being sent to the physical device PLC, achieving closed-loop control via digital twin drive and ensuring stable system operation in complex industrial environments.

[0015] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 An overall architecture diagram of an industrial dynamic equipment digital twin data transmission system provided in this application embodiment; Figure 2This application provides a schematic diagram of data transmission parameters for a wind turbine embodiment. Figure 3 This application provides a schematic diagram of data transmission parameters for a centrifugal pump embodiment. Figure 4 A flowchart illustrating a digital twin data transmission method for industrial moving equipment provided in this application embodiment; Figure 5 A schematic flowchart illustrating a digital twin data transmission method for industrial moving equipment provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an industrial dynamic equipment digital twin data transmission device provided in an embodiment of this application. Detailed Implementation

[0019] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of this application, including various details to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0020] The following description, with reference to the accompanying drawings, describes an industrial moving equipment digital twin data transmission system, method, and apparatus according to embodiments of this application.

[0021] This application provides a digital twin data transmission system, method, and device for industrial moving equipment. The main purpose is to solve the technical problems of traditional data transmission architecture lacking edge intelligent processing capabilities, failing to perform hierarchical data governance, and failing to establish a link guarantee mechanism that matches the high real-time and high reliability requirements of industrial sites, thus failing to meet the full-link optimization requirements of industrial moving equipment digital twin systems for data flow.

[0022] like Figure 1 As shown, embodiments of this application provide an industrial moving equipment digital twin data transmission system. Through clock synchronization, unified protocol mapping, intelligent hierarchical compression, dual encryption, dual-link redundancy, and closed-loop feedback, the system optimizes the entire data link process to achieve real-time, reliable, efficient, and secure data transmission between physical moving equipment and the virtual twin model. The system may include a three-layer closed-loop transmission architecture: a physical moving equipment layer, an edge transmission layer, and a cloud twin layer. Each layer's modules work collaboratively to achieve a closed-loop process from data acquisition, edge governance, secure cloud migration to feedback control. The physical motion device layer communicates with the edge transmission layer. The physical motion device layer can be used to collect real-time operating data of industrial motion devices and transmit the real-time operating data to the edge transmission layer through heterogeneous industrial protocols such as Modbus, Profinet, MQTT, and OPC UA.

[0023] The edge transport layer communicates with the cloud twin layer. As the core bearer layer of this application, the edge transport layer receives real-time operational data from the physical device layer. This layer first adds a unified high-precision timestamp to the multi-source real-time operational data using a clock synchronization module, obtaining timestamped real-time operational data. Subsequently, based on a preset unified information model mapping rule, the timestamped real-time operational data from different protocols is uniformly converted into target format data. The converted target format data is cleaned and graded, and adaptive compression is performed according to the grading results to obtain graded compressed data. Finally, through a dual-link redundant transmission mechanism consisting of a Time-Sensitive Network (TSN) link and a 5G Ultra-Reliable Low-Latency Communication (5G URLLC) link, the encrypted data is reliably uploaded to the cloud twin layer.

[0024] The cloud-based twin layer receives encrypted data uploaded from the edge transport layer. It sequentially performs double decryption, decompression, and timestamp calibration on the encrypted data to recover the original data (i.e., synchronized data). The recovered original data is input into the virtual twin model to drive its real-time state synchronization. The updated virtual twin model performs simulation analysis based on real-time data to generate feedback control commands. After security verification and priority scheduling, the feedback control commands are sent back to the edge transport layer via dual links.

[0025] The edge transmission layer is also used to receive feedback control commands from the cloud, parse and sign the feedback control commands, and finally send them to the PLC controller of the physical device layer to regulate the operating status of the physical device, thereby completing the complete closed-loop control.

[0026] In this embodiment, the physical motion device layer may include industrial motion devices, various sensors, and PLC controllers; Industrial moving equipment typically includes, but is not limited to, rotating machinery such as compressors, fans, and centrifugal pumps. Various sensors (such as vibration, temperature, pressure, and flow sensors) are installed at key measuring points of the industrial moving equipment to collect real-time operating data. Real-time operating data includes at least vibration data, temperature data, speed data, current data, pressure data, and operating status command data. The acquisition frequency range for vibration and rotational speed data is 100Hz-10kHz, while the acquisition frequency range for temperature and pressure data is 1Hz-10Hz, with adaptive adjustments based on the rate of parameter change; for example, Figure 2 As shown, in the wind turbine application scenario, the vibration data acquisition frequency can be set to 5kHz, the temperature data acquisition frequency can be set to 5Hz, the speed data acquisition frequency can be set to 1kHz, the pressure data acquisition frequency can be set to 2Hz, and the PLC controller data acquisition frequency can be set to 1Hz. Taking vibration data acquisition frequency as an example, when the vibration amplitude increases sharply, the acquisition frequency automatically increases from 5kHz to 10kHz to capture transient fault characteristics; for example... Figure 3 As shown, in centrifugal pump applications, for example, to adapt to the pump's rotational speed characteristics, the vibration frequency can be reduced to 3kHz, and a flow sensor (5Hz) can be added to monitor sudden changes, and the temperature grading threshold can be adjusted to 75℃, etc.

[0027] The PLC controller can execute feedback control commands issued by the system (such as speed adjustment and emergency stop) to directly regulate the operating status of industrial moving equipment. In particular, this system supports smart sensors with IEEE 802.1AS hardware timestamp function to ensure time accuracy from the source.

[0028] In this embodiment, the edge transmission layer is the core processing unit of the system. The edge transmission layer may include a clock synchronization module, an edge gateway, a protocol conversion module, a data preprocessing module, an encryption module, and a link redundancy module. Among them, the clock synchronization module can use the IEEE 1588 clock synchronization protocol (PTP) to realize nanosecond-level clock synchronization between all sensors, PLC controllers and edge gateways, add a unified timestamp to all collected real-time running data, and obtain real-time running data marked with timestamps, with a synchronization accuracy better than 100 nanoseconds; As a boundary clock, the edge gateway provides a synchronization source for industrial moving equipment that supports the IEEE 1588 clock synchronization protocol. For traditional equipment that does not support the IEEE 1588 clock synchronization protocol, the edge gateway uses a transparent clock function to record the dwell time of data packets in the network node and perform time base calibration, thereby ensuring that the timestamps from multiple data sources have a high degree of consistency.

[0029] The protocol conversion module receives real-time operational data marked with timestamps. First, it automatically identifies the heterogeneous industrial protocols corresponding to the timestamped real-time operational data, such as Modbus RTU, Profinet, and MQTT, using Deep Packet Inspection (DPI) technology. Then, based on a preset unified information model and protocol mapping rules, it uniformly maps and converts the timestamped real-time operational data of different heterogeneous industrial protocols into the target format data of the OPC UA PubSub protocol. For example, it maps the bearing temperature value in the Modbus register and the temperature value in the Profinet slot to a standardized node representing the same physical meaning in the OPC UA PubSub namespace. This module supports custom mapping rules; when connecting new devices, expansion can be completed simply by updating the mapping file, without modifying the core code.

[0030] The data preprocessing module first cleans the data in the target format. Specifically, a sliding window combined with... The principle or interquartile range (IQR) method is used to clean the target format data to remove abnormal jump data, invalid data and duplicate data packets in the target format data, so as to obtain the cleaned target format data. Subsequently, intelligent classification processing can be performed on the cleaned target format data to obtain core data and non-core data. The classification strategy may include: mechanism rules and AI-assisted classification. The mechanism rule can be: automatically mark variables that are associated with protection interlock logic or whose current value has exceeded the preset alarm threshold as core data (e.g., data with vibration ≥3mm / s in the fan scenario, or data with temperature ≥75℃ in the centrifugal pump scenario). AI-assisted classification can be achieved by deploying a lightweight autoencoder model at the edge to calculate the reconstruction error of the cleaned target format data window in real time. When the reconstruction error exceeds a preset threshold, the system determines that an abnormal pattern has appeared in the data and automatically promotes the relevant feature data to core data. The remaining data is marked as non-core data.

[0031] Finally, for the cleaned target format data marked as core data (i.e., high-value data), a low-loss compression algorithm (such as Zstandard or Rotating Door Technique (SDT)) can be used for compression to obtain hierarchically compressed data, ensuring data fidelity (a compression ratio of 1:1.5 to 1:2 is recommended). For the cleaned target format data marked as non-core data (i.e., redundant data), a high compression ratio algorithm (such as LZMA2 or time-optimized Gorilla compression) is used to maximize the reduction of data size (a compression ratio of 1:5 or higher) to obtain hierarchically compressed data. After preprocessing, core data is given priority to occupy the transmission link, while non-core data is transmitted when the link is idle to avoid transmission congestion.

[0032] The encryption module can be used to perform double encryption on hierarchically compressed data to obtain encrypted data. The first layer of encryption uses the AES-256-GCM algorithm to authenticate and encrypt the data payload of the hierarchically compressed data, while also providing confidentiality and integrity checks, resulting in first-layer encrypted data. The second layer of encryption uses the national standard SM4-CTR algorithm to further encapsulate the first-layer encrypted data, meeting the requirements of critical infrastructure for self-control and compliance, resulting in encrypted data. A CRC32 checksum is also added.

[0033] Furthermore, during the encryption process, a dynamic key rotation strategy can be adopted, using a key management system (KMS) to periodically rotate keys (typically every 24 hours). In addition, employing the Shamir threshold scheme to fragment and store keys in the edge gateway's TPM chip, cloud server, and offline management terminal significantly enhances the security of key storage and use.

[0034] The link redundancy module constructs and manages a dual transmission link of "TSN Time-Sensitive Network + 5G URLLC". Among them, the TSN link serves as the primary working link, used to carry encrypted data and ensure that the core data transmission latency is controlled within 1ms; the 5G URLLC link serves as a hot standby link.

[0035] The link redundancy module can monitor the link status of the TSN link in real time (such as signal strength and transmission delay). When the signal strength of the TSN link is detected to be lower than the preset threshold (such as lower than -70dBm) or the transmission delay exceeds the preset threshold (such as more than 5ms), link switching is triggered. During the handover process, a data packet replication and sequence number deduplication mechanism can be used to seamlessly switch encrypted data to the 5G URLLC link for transmission. That is, before the handover, key data packets are sent simultaneously through dual links, and the receiving end deduplicates them according to the sequence number, thereby achieving a lossless handover with a handover time of less than 200ms and zero packet loss.

[0036] In this embodiment, the cloud twin layer may include a data parsing module, a virtual twin model, a data storage module, and an instruction security circuit breaker module; The data parsing module receives encrypted data from the edge transport layer and performs double decryption (SM4-CTR decryption followed by AES-256-GCM decryption) and decompression (selecting the appropriate decompression algorithm based on the data type) in the reverse order of encryption. Afterward, the decrypted and decompressed data is timestamped to recover synchronized data with globally consistent timing.

[0037] A virtual twin model is a digital mirror image of a physical device in the cloud. It can receive synchronous data to drive state updates, continuously updating its own state parameters. Based on the latest synchronous data, the updated virtual twin model performs dynamic simulations, fault diagnosis, and performance prediction, and generates feedback control commands based on the analysis results, such as speed adjustment commands, fault diagnosis commands, or emergency stop commands.

[0038] The data storage module is responsible for storing real-time runtime data (such as time-series waveforms) from the synchronized data to a time-series database (such as InfluxDB), and storing device static configuration data, event records, etc., to a relational database (such as MySQL). To ensure data security, the database is protected using Transparent Data Encryption (TDE).

[0039] The instruction safety circuit breaker module can be used to receive feedback control instructions generated by the virtual twin model. Before issuing the instructions, the module checks the safety compliance of the feedback control instructions. If the frequency or amplitude of the feedback control instructions exceeds the preset safety policy (e.g., receiving more than 3 emergency stop instructions within 1 minute), it is determined to be abnormal, and the local circuit breaker mechanism is immediately triggered to prevent the instructions from being issued and to send an alarm signal. Only when the feedback control instructions pass the safety verification will they be assigned a transmission priority (e.g., emergency instructions receive the highest priority), and then sent back to the edge transmission layer via the TSN / 5G dual link, and finally executed by the PLC controller.

[0040] like Figure 4 As shown, firstly, the sensors and PLC controllers in the physical moving equipment layer can collect real-time operating data of industrial moving equipment, including parameters such as vibration, temperature, speed, and pressure. Simultaneously, the edge transmission layer can use the IEEE 1588 protocol to achieve nanosecond-level clock synchronization across all nodes, adding a unified timestamp to each frame of data collected to ensure time consistency across multiple data sources.

[0041] Next, the protocol conversion module can identify the industrial protocols used by the data (including Modbus, Profinet, MQTT, OPC UA, etc.) through deep packet inspection, and convert data of different protocol formats into the OPC UA PubSub protocol format based on the preset unified information model mapping rules, thus eliminating protocol barriers.

[0042] Secondly, the data preprocessing module can sequentially perform data cleaning (i.e., using a sliding window combined with...). The principles or interquartile range method are used to remove abnormal jump data, invalid data and duplicate data, data classification based on mechanism and lightweight AI model, adaptive compression (low loss compression of core data / deep compression of non-core data) and priority queue scheduling.

[0043] Next, the encryption module performs dual encryption of the compressed data using AES-256-GCM and SM4-CTR, and employs dynamic key rotation and Shamir threshold fragmentation storage to enhance key security. The encrypted data is redundantly transmitted via the TSN link (primary link, latency <1ms) and the 5G URLLC link (hot standby link). The system monitors the TSN link status in real time, and when signal strength or latency exceeds the threshold, it achieves lossless handover with a handover time of <200ms through packet replication and sequence number deduplication mechanisms.

[0044] Furthermore, the cloud-based data parsing module can sequentially perform double decryption, decompression, and timestamp calibration on the received encrypted data to recover the synchronized data. This data drives the virtual twin model to perform state synchronization updates and is also stored in the time-series database InfluxDB and the relational database MySQL.

[0045] Finally, the virtual twin model can generate feedback control commands (such as adjustment commands or shutdown commands) based on synchronous data. After the commands are verified by the safety circuit breaker (triggered by a circuit breaker alarm when the frequency or amplitude exceeds the threshold), they are sent back to the edge transmission layer with the highest priority through the TSN link, and finally executed by the PLC controller to complete the closed-loop control of the physical equipment's operating status.

[0046] like Figure 5 As shown, embodiments of this application provide a method for transmitting digital twin data of industrial moving equipment. This method can be applied to the aforementioned digital twin data transmission system for industrial moving equipment. The method may include: Step 101: Collect real-time operating data of industrial moving equipment through the physical moving equipment layer, and transmit the real-time operating data to the edge transmission layer through a heterogeneous protocol.

[0047] In this embodiment, various sensors (including vibration, temperature, pressure, and flow sensors) and PLC controllers in the physical moving equipment layer collect real-time operating data of industrial moving equipment (such as compressors, fans, and centrifugal pumps) according to a preset acquisition frequency. The collected data includes at least vibration data, temperature data, rotational speed data, current data, pressure data, and operating status command data. The acquisition frequency is adaptively adjusted according to the rate of parameter change: the acquisition frequency range for vibration and rotational speed data is 100Hz to 10kHz, and the acquisition frequency range for temperature and pressure data is 1Hz to 10Hz. After acquisition, the real-time operating data is transmitted upwards to the edge transmission layer via heterogeneous industrial protocols such as Modbus, Profinet, and MQTT.

[0048] Step 102: Add a unified timestamp to the real-time running data through the clock synchronization protocol of the edge transmission layer to obtain the real-time running data marked with timestamps, and convert the real-time running data marked with timestamps into target format data based on the preset unified information model mapping rules.

[0049] In this embodiment, after receiving real-time operational data, the edge transmission layer first uses the clock synchronization module to achieve nanosecond-level clock synchronization among all sensors, PLCs, and edge gateway nodes using the IEEE 1588 Time Protocol (PTP). A globally unified high-precision timestamp is added to each frame of data, resulting in real-time operational data with a timestamp. The synchronization accuracy is better than 100 nanoseconds. For traditional devices that do not support PTP, the edge gateway uses a transparent clock function to record dwell time for time base calibration.

[0050] Subsequently, the protocol conversion module automatically identifies the heterogeneous industrial protocols (including Modbus RTU, Profinet, MQTT, OPC UA, etc.) used in the data through Deep Packet Inspection (DPI) technology. Based on a preset unified information model and protocol mapping rules, it uniformly converts data in different protocol formats into the target format data. The target format data is the OPC UA PubSub protocol format. For example, the bearing temperature value in the Modbus register and the temperature value in the Profinet slot are uniformly mapped to the same standardized node under the OPC UA PubSub namespace. This process supports custom mapping rules, and new device protocols can be extended by updating the mapping file.

[0051] Step 103: Clean and classify the target format data, perform corresponding adaptive compression processing based on the classification results to obtain classified compressed data; perform double encryption processing on the classified compressed data to obtain encrypted data, and transmit the encrypted data to the cloud twin layer through dual-link redundancy composed of TSN link and 5G URLLC link.

[0052] In the data preprocessing stage, the target format data can first be cleaned. Specifically, a sliding window combined with... The principle or interquartile range (IQR) method is used to clean the target format data to remove abnormal transition data, invalid data and duplicate data packets, so as to obtain cleaned target format data.

[0053] Subsequently, intelligent classification processing can be performed on the cleaned target format data to obtain core data and non-core data. The classification strategy may include: mechanism rules and AI-assisted classification. The mechanism rule can be: automatically mark variables that are associated with protection interlock logic or whose current value has exceeded the preset alarm threshold as core data (e.g., data with vibration ≥3mm / s in the fan scenario, or data with temperature ≥75℃ in the centrifugal pump scenario). AI-assisted classification can be achieved by deploying a lightweight autoencoder model at the edge to calculate the reconstruction error of the cleaned target format data window in real time. When the reconstruction error exceeds a preset threshold, the system determines that an abnormal pattern has appeared in the data and automatically promotes the relevant feature data to core data. The remaining data is marked as non-core data.

[0054] Next, the cleaned target format data (i.e., high-value data) marked as core data can be compressed using low-loss compression algorithms (such as Zstandard or Rotating Door Technique (SDT)) to obtain hierarchically compressed data, ensuring data fidelity (compression ratio recommended to be 1:1.5 to 1:2). For the cleaned target format data (i.e., redundant data) marked as non-core data, a high compression ratio algorithm (such as LZMA2 or time-optimized Gorilla compression) is used to maximize the reduction of data size (compression ratio can reach 1:5 or higher), resulting in hierarchically compressed data. After preprocessing, core data is given priority to occupy the transmission link, while non-core data is transmitted when the link is idle to avoid transmission congestion.

[0055] Next, the hierarchically compressed data can be subjected to double encryption to obtain encrypted data. The first layer of encryption uses the AES-256-GCM algorithm to authenticate and encrypt the data payload of the hierarchically compressed data, while also providing confidentiality and integrity checks, resulting in first-layer encrypted data. The second layer of encryption uses the national standard SM4-CTR algorithm to further encapsulate the first-layer encrypted data, meeting the requirements of critical infrastructure for independent control and compliance, resulting in encrypted data. A CRC32 checksum is also added.

[0056] Finally, after encryption, the encrypted data can be transmitted to the cloud twin layer via a dual-link architecture of "TSN (Time-Sensitive Network) + 5G URLLC" constructed using the link redundancy module. The TSN link serves as the primary link, ensuring core data transmission latency is controlled within 1ms; the 5G URLLC link acts as a hot standby link. The system monitors the TSN link status in real time. When the signal strength is detected to be below -70dBm or the transmission latency exceeds 5ms, a link switch is triggered through a "packet duplication and sequence number deduplication" mechanism. The switchover time is less than 200ms, achieving lossless switching with zero packet loss.

[0057] Step 104: The encrypted data is sequentially decrypted, decompressed, and timestamped through the cloud twin layer to obtain synchronized data; the synchronized data is input into the virtual twin model to drive the virtual twin model to update its state; the updated virtual twin model is used to perform simulation analysis based on the synchronized data to generate feedback control commands; and the feedback control commands are sent back to the edge transmission layer through dual links after security verification and priority scheduling.

[0058] Specifically, the data parsing module of the cloud twin layer can receive encrypted data and perform double decryption (first SM4-CTR decryption, then AES-256-GCM decryption), decompression (selecting the corresponding decompression algorithm according to the data type), and timestamp calibration in sequence to restore the synchronized data.

[0059] This synchronization data is input into the virtual twin model to drive the model's state to be updated in real time in sync with the physical device. On the other hand, real-time running data is stored in the time-series database InfluxDB, and static configuration data is stored in the relational database MySQL. Transparent Data Encryption (TDE) is used to protect the stored data.

[0060] The updated virtual twin model performs dynamic simulation, fault diagnosis, and performance prediction based on synchronous data, and generates feedback control commands accordingly. These feedback control commands include, but are not limited to, speed adjustment commands, fault diagnosis commands, and emergency stop commands.

[0061] The generated feedback control commands first enter the command security circuit breaker module for security verification: if the command frequency or amplitude exceeds the preset security policy (for example, more than 3 emergency stop commands are received within 1 minute), the local circuit breaker is triggered and an alarm is set to prevent the command from being sent. Commands that pass the security verification undergo protocol conversion, encryption, and priority processing (emergency commands receive the highest priority) in the same way as uplink data, and are then sent back to the edge transmission layer via the TSN / 5G dual link.

[0062] Step 105: Parse and verify the feedback control commands through the edge transmission layer, and send them to the PLC controller of the physical device layer to regulate the operating status of the physical device and complete the closed-loop control.

[0063] Specifically, the edge transmission layer can receive feedback control commands from the cloud, parse the commands, and verify their digital signatures. Once verified, the feedback control commands are sent to the PLC controller in the physical moving equipment layer. The PLC controller then executes corresponding actions (such as adjusting the inverter speed, closing valves, or triggering an emergency stop), completing the closed-loop control of the industrial moving equipment's operating status.

[0064] Thus, through steps 101 to 105 above, a complete closed-loop data transmission process has been achieved, from physical device data acquisition, edge governance, secure cloud migration to cloud analysis, instruction generation, and reverse control, ensuring real-time, reliable, efficient, and secure data transmission between physical devices and the virtual twin model.

[0065] In summary, according to the digital twin data transmission method for industrial moving equipment provided in this application, compared with the existing technology, this application can collect real-time operating data of industrial moving equipment through the physical moving equipment layer and transmit the real-time operating data to the edge transmission layer through a heterogeneous protocol; add a unified timestamp to the real-time operating data through the clock synchronization protocol of the edge transmission layer to obtain real-time operating data marked with timestamps, and convert the real-time operating data marked with timestamps into target format data based on a preset unified information model mapping rule; clean and classify the target format data, perform corresponding adaptive compression processing according to the classification results to obtain classified compressed data; perform double encryption processing on the classified compressed data to obtain encrypted data, and transmit the encrypted data to 5G via the TSN link. The URLLC link forms a dual-link redundant transmission to the cloud twin layer; the cloud twin layer sequentially performs double decryption, decompression, and timestamp calibration on the encrypted data to obtain synchronized data; the synchronized data is input into the virtual twin model to drive the virtual twin model to update its state; the updated virtual twin model performs simulation analysis based on the synchronized data to generate feedback control commands; the feedback control commands are then sent back to the edge transmission layer via dual links after security verification and priority scheduling; the edge transmission layer parses and verifies the feedback control commands and sends them to the PLC controller of the physical device layer to regulate the operating state of the physical device, completing closed-loop control.

[0066] By adopting the above technical solution, this application addresses the technical problems in existing technologies where the numerous brands of industrial field equipment lead to complex communication protocols, and where traditional chain-based protocol conversion structures increase network topology complexity, introduce cumulative latency, and pose single-point failure risks. It achieves this by using an edge transmission layer based on preset unified information model mapping rules to uniformly convert heterogeneous protocol data (such as Modbus and Profinet) into a target format (such as OPC UA PubSub), eliminating protocol barriers and simplifying the topology. Simultaneously, this application employs the IEEE 1588 PTP clock synchronization protocol to add a unified timestamp to the data, achieving nanosecond-level clock synchronization across all nodes and ensuring time consistency of multi-source data. Combined with a dual-link redundant transmission mechanism of "TSN Time-Sensitive Network + 5G URLLC," the end-to-end transmission latency of core data can be reduced to milliseconds or even lower. This architecture effectively breaks through the performance bottleneck of the traditional "acquisition-conversion-aggregation-upload" serial processing mode, meeting the real-time requirements of digital twin models for high-fidelity reproduction of equipment transient operating conditions.

[0067] To address the technical problems of existing technologies that use a "one-size-fits-all" approach to upload all high-frequency sampling data, resulting in inefficient network bandwidth usage, escalating cloud storage costs, and key feature data being overwhelmed by massive amounts of redundant data, this application introduces an intelligent data grading and adaptive compression mechanism at the edge transmission layer. Through cleaning and grading, the system can distinguish between core data (such as fault features and data exceeding thresholds) and non-core data (such as steady-state, flat data) based on mechanistic rules or lightweight AI models, and perform corresponding adaptive compression (low-loss compression to preserve the fidelity of core data, and deep compression to reduce redundancy of non-core data). This on-demand transmission strategy significantly reduces the amount of uploaded data while fully preserving fault features, effectively saving network bandwidth and cloud storage resources, and improving the efficiency and accuracy of subsequent mechanistic and AI model analysis.

[0068] To address the lack of link assurance mechanisms in existing transmission solutions that match the high real-time and high reliability requirements of industrial environments, this application constructs a comprehensive security and reliability assurance system. In terms of security, double encryption ensures the confidentiality and integrity of data during upload and download. Regarding reliability, a dual-link redundancy mechanism utilizing TSN and 5G URLLC enables seamless switching between primary and backup links, preventing data loss due to single-point failures. Furthermore, feedback control commands generated in the cloud are securely verified and prioritized before being sent to the physical device PLC, achieving closed-loop control via digital twin drive and ensuring stable system operation in complex industrial environments.

[0069] Based on the above Figure 5 The specific implementation of the method shown in this embodiment provides an industrial dynamic equipment digital twin data transmission device, such as... Figure 6 As shown, the device includes: a data acquisition module 31, a conversion module 32, a processing module 33, an analysis module 34, and a verification module 35; The acquisition module 31 is used to acquire real-time operating data of industrial moving equipment through the physical moving equipment layer, and transmit the real-time operating data to the edge transmission layer through a heterogeneous protocol; The conversion module 32 is used to add a unified timestamp to the real-time running data through the clock synchronization protocol of the edge transmission layer to obtain real-time running data marked with timestamps, and to convert the real-time running data marked with timestamps into target format data based on the preset unified information model mapping rules. Processing module 33 is used to clean and classify the target format data, perform corresponding adaptive compression processing according to the classification result to obtain classified compressed data; perform double encryption processing on the classified compressed data to obtain encrypted data, and transmit the encrypted data to the cloud twin layer through dual-link redundancy composed of TSN link and 5G URLLC link. Analysis module 34 is used to sequentially perform double decryption, decompression, and timestamp calibration on the encrypted data through the cloud twin layer to obtain synchronized data; input the synchronized data into the virtual twin model to drive the virtual twin model to perform state updates; perform simulation analysis based on the synchronized data through the updated virtual twin model to generate feedback control commands; and after security verification and priority scheduling, send the feedback control commands back to the edge transmission layer through the dual links. The verification module 35 is used to parse and verify the feedback control command through the edge transmission layer and send it to the PLC controller of the physical device layer to regulate the operating status of the physical device and complete the closed-loop control.

[0070] It should be noted that other corresponding descriptions of the functional units involved in the industrial dynamic equipment digital twin data transmission device provided in this embodiment can be found in the following references. Figure 5 The corresponding description in [the document] will not be repeated here.

[0071] Based on the above, Figure 5 Accordingly, this embodiment also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method. Figure 5 The method shown.

[0072] Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause a computer device (such as personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of this application.

[0073] Based on the above, Figure 5 The method shown, and Figure 6 To achieve the above objectives, the present application also provides an electronic device, comprising a storage medium and a processor; the storage medium for storing a computer program; and the processor for executing the computer program to implement the above-described virtual device embodiments. Figure 5 The method shown.

[0074] Optionally, the aforementioned physical devices may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB interfaces, card reader interfaces, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Wi-Fi interfaces), etc.

[0075] Those skilled in the art will understand that the physical device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine certain components, or have different component arrangements.

[0076] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the aforementioned physical device, supporting the operation of the industrial moving equipment digital twin data transmission program and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the industrial moving equipment digital twin data transmission physical device.

[0077] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms, or it can be implemented by hardware. By applying the solution of this embodiment, compared with the existing technology, this application can collect real-time operating data of industrial moving equipment through the physical moving equipment layer, and transmit the real-time operating data to the edge transmission layer through a heterogeneous protocol; add a unified timestamp to the real-time operating data through the clock synchronization protocol of the edge transmission layer to obtain real-time operating data marked with timestamps, and convert the real-time operating data marked with timestamps into target format data based on a preset unified information model mapping rule; clean and classify the target format data, perform corresponding adaptive compression processing according to the classification results, and obtain classified compressed data; perform double encryption processing on the classified compressed data to obtain encrypted data, and transmit the encrypted data to 5G through the TSN link. The URLLC link forms a dual-link redundant transmission to the cloud twin layer; the cloud twin layer sequentially performs double decryption, decompression, and timestamp calibration on the encrypted data to obtain synchronized data; the synchronized data is input into the virtual twin model to drive the virtual twin model to update its state; the updated virtual twin model performs simulation analysis based on the synchronized data to generate feedback control commands; the feedback control commands are then sent back to the edge transmission layer via dual links after security verification and priority scheduling; the edge transmission layer parses and verifies the feedback control commands and sends them to the PLC controller of the physical device layer to regulate the operating state of the physical device, completing closed-loop control.

[0078] By adopting the above technical solution, this application addresses the technical problems in existing technologies where the numerous brands of industrial field equipment lead to complex communication protocols, and where traditional chain-based protocol conversion structures increase network topology complexity, introduce cumulative latency, and pose single-point failure risks. It achieves this by using an edge transmission layer based on preset unified information model mapping rules to uniformly convert heterogeneous protocol data (such as Modbus and Profinet) into a target format (such as OPC UA PubSub), eliminating protocol barriers and simplifying the topology. Simultaneously, this application employs the IEEE 1588 PTP clock synchronization protocol to add a unified timestamp to the data, achieving nanosecond-level clock synchronization across all nodes and ensuring time consistency of multi-source data. Combined with a dual-link redundant transmission mechanism of "TSN Time-Sensitive Network + 5G URLLC," the end-to-end transmission latency of core data can be reduced to milliseconds or even lower. This architecture effectively breaks through the performance bottleneck of the traditional "acquisition-conversion-aggregation-upload" serial processing mode, meeting the real-time requirements of digital twin models for high-fidelity reproduction of equipment transient operating conditions.

[0079] To address the technical problems of existing technologies that use a "one-size-fits-all" approach to upload all high-frequency sampling data, resulting in inefficient network bandwidth usage, escalating cloud storage costs, and key feature data being overwhelmed by massive amounts of redundant data, this application introduces an intelligent data grading and adaptive compression mechanism at the edge transmission layer. Through cleaning and grading, the system can distinguish between core data (such as fault features and data exceeding thresholds) and non-core data (such as steady-state, flat data) based on mechanistic rules or lightweight AI models, and perform corresponding adaptive compression (low-loss compression to preserve the fidelity of core data, and deep compression to reduce redundancy of non-core data). This on-demand transmission strategy significantly reduces the amount of uploaded data while fully preserving fault features, effectively saving network bandwidth and cloud storage resources, and improving the efficiency and accuracy of subsequent mechanistic and AI model analysis.

[0080] To address the lack of link assurance mechanisms in existing transmission solutions that match the high real-time and high reliability requirements of industrial environments, this application constructs a comprehensive security and reliability assurance system. In terms of security, double encryption ensures the confidentiality and integrity of data during upload and download. Regarding reliability, a dual-link redundancy mechanism utilizing TSN and 5G URLLC enables seamless switching between primary and backup links, preventing data loss due to single-point failures. Furthermore, feedback control commands generated in the cloud are securely verified and prioritized before being sent to the physical device PLC, achieving closed-loop control via digital twin drive and ensuring stable system operation in complex industrial environments.

[0081] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" or any other variations thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0082] The above are merely specific embodiments of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to these embodiments, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. An industrial mobile equipment digital twin data transmission system, characterized by, The system includes: a physical device layer, an edge transmission layer, and a cloud twin layer; The physical motion device layer is communicatively connected to the edge transmission layer. The physical motion device layer is used to collect real-time operating data of industrial motion devices and transmit the real-time operating data to the edge transmission layer through a heterogeneous protocol. The edge transport layer is communicatively connected to the cloud twin layer. The edge transport layer receives the real-time running data, adds a unified timestamp to the real-time running data through a clock synchronization protocol to obtain timestamped real-time running data, and converts the timestamped real-time running data into target format data based on a preset unified information model mapping rule. The target format data is then cleaned and graded, and corresponding adaptive compression processing is performed according to the grading results to obtain graded compressed data. The graded compressed data is then subjected to double encryption processing to obtain encrypted data, and the encrypted data is transmitted to the cloud twin layer through a dual-link redundancy consisting of a TSN link and a 5G URLLC link. The cloud twin layer is used to receive the encrypted data and sequentially perform double decryption, decompression, and timestamp calibration on the encrypted data to obtain synchronized data; input the synchronized data into the virtual twin model to drive the virtual twin model to perform state updates; perform simulation analysis based on the synchronized data using the updated virtual twin model to generate feedback control commands; and after security verification and priority scheduling, send the feedback control commands back to the edge transmission layer through the dual links. The edge transmission layer is also used to receive the feedback control command, parse and verify the feedback control command, and send it to the PLC controller of the physical device layer to regulate the operating status of the physical device and complete closed-loop control.

2. The industrial mobile equipment digital twin data transmission system of claim 1, wherein, The physical motion equipment layer includes industrial motion equipment, various sensors, and PLC controllers; The various sensors are used to collect real-time operating data of the industrial moving equipment. The real-time operating data includes at least vibration data, temperature data, rotational speed data, current data, pressure data, and operating status command data. The acquisition frequency range of the vibration data and the rotation speed data is 100Hz-10kHz, and the acquisition frequency range of the temperature data and the pressure data is 1Hz-10Hz, and the frequency is adaptively adjusted according to the rate of parameter change. The PLC controller is used to execute the received feedback control instructions to regulate the operating status of the industrial equipment.

3. The industrial moving equipment digital twin data transmission system according to claim 1, characterized in that, The edge transmission layer includes a clock synchronization module and an edge gateway; The clock synchronization module is used to achieve nanosecond-level clock synchronization of all nodes using the IEEE 1588 clock synchronization protocol, and to add a unified timestamp to all the collected real-time running data to obtain real-time running data marked with timestamps. The edge gateway acts as a boundary clock, providing a synchronization source for industrial moving equipment that supports the IEEE 1588 clock synchronization protocol. For industrial moving equipment that does not support the IEEE 1588 clock synchronization protocol, the transparent clock function records the dwell time for time base calibration to ensure the consistency of timestamps from multiple sources.

4. The industrial moving equipment digital twin data transmission system according to claim 3, characterized in that, The edge transmission layer also includes a protocol conversion module; The protocol conversion module is used to receive the real-time operation data marked with timestamps and identify the heterogeneous industrial protocols corresponding to the real-time operation data marked with timestamps through deep packet inspection technology. Based on the preset unified information model mapping rules, the real-time running data marked with timestamps from different heterogeneous industrial protocols are uniformly mapped and converted into target format data in the OPC UA PubSub protocol format; The protocol conversion module supports custom mapping rules and can extend new device protocols by updating the mapping file.

5. The industrial moving equipment digital twin data transmission system according to claim 4, characterized in that, The edge transmission layer also includes a data preprocessing module; The data preprocessing module is used to employ a sliding window combination The target format data is cleaned using the principle or interquartile range method to remove abnormal jump data, invalid data and duplicate data packets, and the cleaned target format data is obtained. The cleaned target format data is subjected to hierarchical processing to obtain core data and non-core data. The hierarchical processing specifically includes: marking variables associated with protection interlocks or exceeding alarm thresholds as core data based on mechanism rules; and calculating the reconstruction error of the cleaned target format data in real time using a lightweight autoencoder model deployed at the edge. When the reconstruction error exceeds a preset threshold, the relevant feature data is determined as the core data, and the remaining data is marked as non-core data. The cleaned target format data marked as the core data is compressed using a low-loss compression algorithm to obtain the hierarchical compressed data, and the cleaned target format data marked as the non-core data is compressed using a high compression ratio algorithm to obtain the hierarchical compressed data.

6. The industrial moving equipment digital twin data transmission system according to claim 5, characterized in that, The edge transmission layer also includes an encryption module; The encryption module is used to perform a first-level authentication encryption on the data payload of the hierarchical compressed data using the AES-256-GCM algorithm to obtain the first-level encrypted data; and to perform a second-level encapsulation on the first-level encrypted data using the national cryptographic SM4-CTR algorithm to obtain the encrypted data.

7. The industrial moving equipment digital twin data transmission system according to claim 6, characterized in that, The edge transmission layer also includes a link redundancy module; The link redundancy module is used to carry the encrypted data for transmission using the TSN link as the primary link and the 5G URLLC link as the backup link. The link status of the TSN link is monitored in real time. When the signal strength of the TSN link is detected to be lower than a preset threshold or the transmission delay exceeds a preset threshold, link switching is triggered. When link switching is triggered, a packet copying and sequence number deduplication mechanism is used to seamlessly switch the encrypted data to the 5G URLLC link for transmission, so as to achieve lossless switching with zero packet loss.

8. The industrial moving equipment digital twin data transmission system according to claim 1, characterized in that, The cloud-based twin layer includes a data parsing module, a virtual twin model, a data storage module, and an instruction security circuit breaker module; The data parsing module is used to receive the encrypted data, and sequentially perform double decryption and decompression on the encrypted data, and perform timestamp calibration on the decrypted and decompressed encrypted data to obtain the synchronization data; The virtual twin model is used to receive the synchronization data to drive the virtual twin model to perform state updates, and to perform simulation analysis based on the synchronization data using the updated virtual twin model to generate feedback control commands. The data storage module is used to store the real-time running data in the synchronization data into a time-series database, store the static configuration data into a relational database, and protect the stored data using transparent data encryption. The instruction security circuit breaker module is used to receive the feedback control instruction. If the frequency or amplitude of the feedback control instruction exceeds the preset security policy, it triggers local circuit breaker and alarms. Otherwise, the feedback control instruction after security verification and priority scheduling is sent back to the edge transmission layer through the dual link.

9. A method for transmitting digital twin data of industrial moving equipment, characterized in that, The method is applied to the industrial dynamic equipment digital twin data transmission system as described in any one of claims 1-8, and the method includes: Real-time operating data of industrial moving equipment is collected through the physical moving equipment layer, and the real-time operating data is transmitted to the edge transmission layer through a heterogeneous protocol; The real-time running data is given a unified timestamp by the clock synchronization protocol of the edge transmission layer to obtain real-time running data marked with timestamps. Based on the preset unified information model mapping rules, the real-time running data marked with timestamps is uniformly converted into target format data. The target format data is cleaned and graded, and corresponding adaptive compression is performed according to the grading results to obtain graded compressed data. The graded compressed data is then subjected to double encryption to obtain encrypted data, which is then transmitted to the cloud twin layer through a dual-link redundancy consisting of a TSN link and a 5G URLLC link. The encrypted data is sequentially subjected to double decryption, decompression, and timestamp calibration through the cloud twin layer to obtain synchronized data. The synchronized data is then input into the virtual twin model to drive the virtual twin model to update its state. The updated virtual twin model performs simulation analysis based on the synchronized data to generate feedback control commands. After security verification and priority scheduling, the feedback control commands are sent back to the edge transmission layer through the dual links. The feedback control commands are parsed and verified by the edge transmission layer and sent to the PLC controller of the physical device layer to regulate the operating status of the physical device and complete closed-loop control.

10. An electronic device comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the digital twin data transmission method for industrial moving equipment as described in claim 9.

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