Auxiliary machine device holographic perception twin mapping method and system

Abstract

The application discloses a kind of auxiliary machine equipment holographic perception twin mapping methods, belong to data processing technical field, comprising: based on the connection relationship of multiple auxiliary machine equipment, corresponding virtual twin topology network is constructed, network contains the virtual node corresponding to each device, multiple protocol resolver is built-in in each node;By obtaining the original data message sent by corresponding physical device through different protocols;The message received by the same node is cross-verified, and the standard state data package containing state parameters and quality identification is output;Based on upstream and downstream virtual nodes, and the state data package of upstream node is forwarded to downstream node;All upstream state data packages received by downstream node are fused with self state data package, to form aggregate data block;Determine node anomaly based on aggregate data block, and when abnormal, according to state parameter change time sequence, trace back and determine the initial virtual node that first abnormal occurs.The application realizes the unified trusted perception and fault tracing of equipment group.

Description

Technical Field

[0001] This application relates to the field of data processing, and in particular to a method and system for holographic perception twin mapping of auxiliary equipment. Background Technology

[0002] In the production processes of power plants such as thermal and nuclear power plants, auxiliary equipment is a key support for ensuring the safe, stable, and economical operation of main equipment such as boilers, steam turbines, and generators. These auxiliary machines include, but are not limited to, various pumps, fans, compressors, cooling towers, heat exchangers, and related valves and actuators. They are connected according to strict process logic, forming complex subsystems such as flue gas systems, steam-water systems, cooling systems, and fuel supply systems. Real-time, accurate, and comprehensive monitoring of the operating status of these auxiliary equipment groups is the core foundation for preventing unplanned shutdowns, improving unit efficiency, achieving condition-based maintenance, and building smart power plants.

[0003] Currently, power plants primarily rely on distributed control systems (DCS), programmable logic controller (PLC) networks, and some independently installed online monitoring devices for monitoring auxiliary equipment. However, the existing technology system involves a wide range of auxiliary equipment sources, with both new and old equipment present, and their control systems and data interfaces employ complex communication protocols. For example, a modern variable frequency feedwater pump may use Profinet communication, while its adjacent older regulating valve still uses Modbus RTU. Meanwhile, newly added intelligent vibration sensors may support OPCUA. Existing DCS or data acquisition systems often require the configuration of numerous protocol conversion gateways and customized drivers, resulting in complex system architectures, high integration and maintenance costs, and difficulty in achieving unified access and native parsing of low-latency, high-concurrency auxiliary equipment data across the entire plant. Data fragmentation is severe, and traditional DCS displays primarily present data from individual measurement points in the form of process flow diagrams, with alarm mechanisms based on independent parameter thresholds. This approach fails to digitally represent the physical connections and functional coupling relationships between auxiliary equipment. Furthermore, when a fault occurs, root cause localization relies on manual experience, which is inefficient and lacks accuracy. Summary of the Invention

[0004] This application provides a holographic sensing twin mapping method and system for auxiliary equipment to improve the above-mentioned problems.

[0005] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, embodiments of this application propose a holographic sensing twin mapping method for auxiliary equipment, applicable to a holographic sensing twin mapping system for auxiliary equipment, the system including multiple auxiliary equipment, the method comprising: Based on the connection relationship of multiple auxiliary devices, a corresponding virtual twin topology network is constructed in the digital space. The virtual twin topology network includes virtual nodes corresponding to each auxiliary device, and each virtual node includes a parser that can resolve at least two communication protocols. Based on the corresponding parsers of multiple virtual nodes, the original data packets sent by the corresponding virtual nodes through different communication protocols are obtained. The original data packets contain one or more original data values ​​collected by the auxiliary equipment. Cross-validate multiple raw data packets received by the same virtual node and output a status data packet corresponding to the virtual node. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​used to characterize the operating attributes of the auxiliary equipment corresponding to the virtual node. Based on the virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the status data packets output by the upstream virtual nodes are forwarded to one or more downstream virtual nodes; The downstream virtual node will merge the status data packets received from all the upstream virtual nodes with its own generated status data packets to form an aggregated data block. The aggregated data block is used to characterize the overall operating status of the local node group consisting of the downstream virtual node and all the upstream virtual nodes connected to the downstream virtual node. If the value of any status parameter in any status data packet in the aggregated data block exceeds the preset normal operating range threshold, or if the corresponding quality identifier of any status data packet is invalid, then the corresponding virtual node is determined to be in an abnormal state. When at least one virtual node is determined to be in an abnormal state, the initial virtual node whose state parameters first become abnormal is determined based on the time sequence of changes in the state parameters of all associated virtual nodes in the aggregated data block.

[0006] In conjunction with the first aspect, optionally, cross-validation is performed on multiple raw data packets received by the same virtual node, and a status data packet corresponding to the virtual node is output. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​characterizing the operating attributes of the auxiliary equipment corresponding to the virtual node, including: Obtain multiple candidate data values ​​corresponding to the same physical quantity based on multiple raw data messages; Based on preset device parameters, multiple candidate data values ​​are verified. If all candidate data values ​​are within the valid value range defined by the device parameters, and the deviation between multiple candidate data values ​​is less than the first preset threshold, then the average of multiple candidate data values ​​is determined as the state parameter value. If at least one of the multiple candidate data values ​​exceeds the valid value range, or the deviation between them is greater than or equal to the first preset threshold, then the data source credibility corresponding to each candidate data value is obtained, and the candidate data value with the highest credibility is determined as the state parameter value.

[0007] In conjunction with the first aspect, optionally, if at least one of the multiple candidate data values ​​exceeds the valid value range, or the deviation between them is greater than or equal to a first preset threshold, then the data source credibility corresponding to each candidate data value is obtained, and the candidate data value with the highest credibility is determined as the state parameter value, including: Obtain the data timestamp and data source device status score corresponding to each candidate data value; The first confidence level is determined based on the time difference between the data timestamp and the current system time. The larger the time difference, the lower the confidence level of the first confidence level. The second confidence sub-item is determined based on the device status of the data source, wherein the device status score is positively correlated with the second confidence sub-item; Based on preset weights, the first confidence sub-item and the second confidence sub-item are weighted and calculated to obtain the data source confidence corresponding to the candidate data value.

[0008] In conjunction with the first aspect, optionally, cross-validation is performed on multiple raw data packets received by the same virtual node, and a status data packet corresponding to the virtual node is output. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​characterizing the operating attributes of the auxiliary equipment corresponding to the virtual node, including: If the state parameter value is the mean of multiple candidate data values, and the deviation between multiple candidate data values ​​is less than the first preset threshold, then the state parameter is assigned a first type of quality label, and the first type of quality label represents that the data is high-confidence valid data. If the state parameter value is the candidate data value with the highest credibility, then the state parameter is assigned a second type of quality label. The second type of quality label represents that the data is verified valid data. If the confidence level of all candidate data values ​​is less than the second preset threshold or is missing, then a third quality label is assigned to the state parameter. The third quality label indicates that the data is invalid.

[0009] In conjunction with the first aspect, optionally, based on the virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the state data packets output by the upstream virtual nodes are forwarded to one or more downstream virtual nodes, including: Obtain the process connection relationship configuration file of multiple auxiliary equipment, which defines the physical connection relationship and process flow direction between each auxiliary equipment; Based on the process connection relationship configuration file, in the virtual twin topology network, the virtual node corresponding to the auxiliary equipment located in the upstream process position in the physical connection is defined as the upstream virtual node, and the virtual node corresponding to the auxiliary equipment located in the downstream process position in the physical connection is defined as the downstream virtual node.

[0010] In conjunction with the first aspect, optionally, based on the virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the state data packets output by the upstream virtual nodes are forwarded to one or more downstream virtual nodes, including: To obtain the transmission direction of state data packets in the virtual twin topology network, if the state data packet output by any virtual node is allowed to be sent to another virtual node, then the virtual node that sends the state data packet is defined as the upstream virtual node of the virtual node that receives the state data packet, and the virtual node that receives the state data packet is defined as the downstream virtual node of the virtual node that sends the state data packet.

[0011] In conjunction with the first aspect, optionally, when at least one virtual node is determined to be in an abnormal state, the initial virtual node whose state parameters first became abnormal is determined based on the time sequence of changes in the state parameters of all associated virtual nodes in the aggregated data block, including: Obtain the rated parameters of the auxiliary equipment, and determine the normal operating range thresholds corresponding to the status parameters based on the rated parameters; Get the first state parameter that first exceeds the normal operating range threshold and the first timestamp of the state parameter in each virtual node that is judged to be in an abnormal state in the aggregated data block, and define the state parameter as an abnormal state parameter. Determine the earliest timestamp from the first timestamp of all abnormal state parameters; The virtual node corresponding to the abnormal state parameter of the earliest timestamp is determined as the initial virtual node.

[0012] Secondly, this application proposes a holographic sensing twin mapping system for auxiliary equipment, the system comprising multiple auxiliary equipment, and the system is configured as follows: Based on the connection relationship of multiple auxiliary devices, a corresponding virtual twin topology network is constructed in the digital space. The virtual twin topology network includes virtual nodes corresponding to each auxiliary device, and each virtual node includes a parser that can resolve at least two communication protocols. Based on the corresponding parsers of multiple virtual nodes, the original data packets sent by the corresponding virtual nodes through different communication protocols are obtained. The original data packets contain one or more original data values ​​collected by the auxiliary equipment. Cross-validate multiple raw data packets received by the same virtual node and output a status data packet corresponding to the virtual node. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​used to characterize the operating attributes of the auxiliary equipment corresponding to the virtual node. Based on the virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the status data packets output by the upstream virtual nodes are forwarded to one or more downstream virtual nodes; The downstream virtual node will merge the status data packets received from all the upstream virtual nodes with its own generated status data packets to form an aggregated data block. The aggregated data block is used to characterize the overall operating status of the local node group consisting of the downstream virtual node and all the upstream virtual nodes connected to the downstream virtual node. If the value of any status parameter in any status data packet in the aggregated data block exceeds the preset normal operating range threshold, or if the corresponding quality identifier of any status data packet is invalid, then the corresponding virtual node is determined to be in an abnormal state. When at least one virtual node is determined to be in an abnormal state, the initial virtual node whose state parameters first become abnormal is determined based on the time sequence of changes in the state parameters of all associated virtual nodes in the aggregated data block.

[0013] In conjunction with the second aspect, optionally, the system is configured as follows: Cross-validation is performed on multiple raw data packets received from the same virtual node, and a status data packet corresponding to the virtual node is output. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​characterizing the operating attributes of the auxiliary equipment corresponding to the virtual node, including: Obtain multiple candidate data values ​​corresponding to the same physical quantity based on multiple raw data messages; Based on preset device parameters, multiple candidate data values ​​are verified. If all candidate data values ​​are within the valid value range defined by the device parameters, and the deviation between multiple candidate data values ​​is less than the first preset threshold, then the average of multiple candidate data values ​​is determined as the state parameter value. If at least one of the multiple candidate data values ​​exceeds the valid value range, or the deviation between them is greater than or equal to the first preset threshold, then the data source credibility corresponding to each candidate data value is obtained, and the candidate data value with the highest credibility is determined as the state parameter value.

[0014] In conjunction with the second aspect, optionally, the system is configured as follows: If at least one of the multiple candidate data values ​​exceeds the valid value range, or the deviation between them is greater than or equal to a first preset threshold, then the data source credibility corresponding to each candidate data value is obtained, and the candidate data value with the highest credibility is determined as the state parameter value, including: Obtain the data timestamp and data source device status score corresponding to each candidate data value; The first confidence level is determined based on the time difference between the data timestamp and the current system time. The larger the time difference, the lower the confidence level of the first confidence level. The second confidence sub-item is determined based on the device status of the data source, wherein the device status score is positively correlated with the second confidence sub-item; Based on preset weights, the first confidence sub-item and the second confidence sub-item are weighted and calculated to obtain the data source confidence corresponding to the candidate data value.

[0015] In conjunction with the second aspect, optionally, the system is configured as follows: Cross-validation is performed on multiple raw data packets received from the same virtual node, and a status data packet corresponding to the virtual node is output. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​characterizing the operating attributes of the auxiliary equipment corresponding to the virtual node, including: If the state parameter value is the mean of multiple candidate data values, and the deviation between multiple candidate data values ​​is less than the first preset threshold, then the state parameter is assigned a first type of quality label, and the first type of quality label represents that the data is high-confidence valid data. If the state parameter value is the candidate data value with the highest credibility, then the state parameter is assigned a second type of quality label. The second type of quality label represents that the data is verified valid data. If the confidence level of all candidate data values ​​is less than the second preset threshold or is missing, then a third quality label is assigned to the state parameter. The third quality label indicates that the data is invalid.

[0016] In conjunction with the second aspect, optionally, the system is configured as follows: Based on a virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the state data packets output by the upstream virtual node are forwarded to one or more downstream virtual nodes, including: Obtain the process connection relationship configuration file of multiple auxiliary equipment, which defines the physical connection relationship and process flow direction between each auxiliary equipment; Based on the process connection relationship configuration file, in the virtual twin topology network, the virtual node corresponding to the auxiliary equipment located in the upstream process position in the physical connection is defined as the upstream virtual node, and the virtual node corresponding to the auxiliary equipment located in the downstream process position in the physical connection is defined as the downstream virtual node.

[0017] In conjunction with the second aspect, optionally, the system is configured as follows: Based on a virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the state data packets output by the upstream virtual node are forwarded to one or more downstream virtual nodes, including: To obtain the transmission direction of state data packets in the virtual twin topology network, if the state data packet output by any virtual node is allowed to be sent to another virtual node, then the virtual node that sends the state data packet is defined as the upstream virtual node of the virtual node that receives the state data packet, and the virtual node that receives the state data packet is defined as the downstream virtual node of the virtual node that sends the state data packet.

[0018] In conjunction with the second aspect, optionally, the system is configured as follows: When at least one virtual node is determined to be in an abnormal state, the initial virtual node whose state parameters first became abnormal is determined based on the time sequence of changes in the state parameters of all associated virtual nodes in the aggregated data block, including: Obtain the rated parameters of the auxiliary equipment, and determine the normal operating range thresholds corresponding to the status parameters based on the rated parameters; Get the first state parameter that first exceeds the normal operating range threshold and the first timestamp of the state parameter in each virtual node that is judged to be in an abnormal state in the aggregated data block, and define the state parameter as an abnormal state parameter. Determine the earliest timestamp from the first timestamp of all abnormal state parameters; The virtual node corresponding to the abnormal state parameter of the earliest timestamp is determined as the initial virtual node.

[0019] A third aspect of this invention provides an electronic device, which includes: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method proposed in the first aspect of the present invention.

[0020] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in the first aspect of the present invention.

[0021] In summary, the above methods and systems have the following technical effects: This invention discloses a holographic perception twin mapping method for auxiliary equipment, comprising: constructing a corresponding virtual twin topology network based on the connection relationship of multiple auxiliary equipment, wherein the network includes virtual nodes corresponding to each equipment, and each node has a built-in multi-protocol parser; obtaining the original data packets sent by the corresponding physical equipment through different protocols through the parser; performing cross-validation on multiple original packets received by the same node, and outputting a standard status data packet containing status parameters and quality identifiers; defining upstream and downstream virtual nodes based on the topology network, and forwarding the status data packets of the upstream node to the downstream node; the downstream node merging all received upstream status data packets with its own status data packets to form an aggregated data block; determining node anomalies based on the aggregated data block, and tracing back and determining the initial virtual node where the anomaly first occurred based on the time sequence of status parameter changes when an anomaly occurs. This invention achieves unified and reliable perception and fault tracing of a group of equipment. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating a holographic sensing twin mapping method for auxiliary equipment proposed in an embodiment of this application. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] This application proposes a holographic sensing twin mapping method for auxiliary equipment, applicable to a holographic sensing twin mapping system for auxiliary equipment, the system comprising multiple auxiliary equipment. Please refer to [link to relevant documentation]. Figure 1 The method includes the following steps: S101: Based on the connection relationship of multiple auxiliary devices, a corresponding virtual twin topology network is constructed in the digital space. The virtual twin topology network includes virtual nodes corresponding to each auxiliary device, and each virtual node includes a parser that can resolve at least two communication protocols.

[0025] This application uses power plant auxiliary equipment as an example. Specifically, taking the auxiliary equipment system of a thermal power plant as an example, it can be understood to include various devices such as feedwater pumps, condensers, cooling towers, fans, and circulating water pumps. These devices are interconnected through physical media such as pipes, cables, ducts, and control signal lines, forming defined physical and functional relationships. For example, a condensate pump extracts condensate from the condenser, pressurizes it, and delivers it to the low-pressure heater; the outlet duct of a fan is connected to the inlet of an air preheater. Based on these clearly identified physical connections, a corresponding virtual twin topology network can be created within the computer system. This network is a digital model composed of virtual nodes and their connection logic. Each virtual node in the network uniquely corresponds to a physical auxiliary device, becoming a proxy for that device in digital space. For example, a feedwater pump virtual node is created for the physical feedwater pump, and a condenser virtual node is created for the physical condenser.

[0026] S102: Based on the corresponding parsers of multiple virtual nodes, obtain the raw data packets sent by the corresponding virtual nodes through different communication protocols. The raw data packets contain one or more raw data values ​​collected by the auxiliary equipment.

[0027] Understandably, each virtual node establishes a communication connection with its corresponding physical auxiliary equipment based on the protocol types supported by its internally configured resolver. The equipment, according to its own inherent communication protocol rules, periodically or triggered by events, organizes data representing its own state into messages of a specific format and sends them. For example, the resolver of a virtual node corresponding to a feedwater pump might be configured to listen on a Modbus TCP protocol port to receive data frames conforming to the Modbus TCP format sent from the feedwater pump controller; while the resolver of a virtual node corresponding to a condenser temperature sensor might be configured to handle both PROFIBUS and OPCUA protocols, thus it can obtain data streams from the same sensor from a PROFIBUS network or an OPCUA server. Specific protocols are not limited in this application.

[0028] S103: Cross-validate multiple raw data packets received by the same virtual node and output a status data packet corresponding to the virtual node. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​used to characterize the operating attributes of the auxiliary equipment corresponding to the virtual node.

[0029] Understandably, a virtual node may receive multiple raw data packets containing the same operational attribute of its corresponding physical auxiliary equipment through different communication paths or protocol interfaces. For example, a virtual node representing a water pump may simultaneously obtain current readings from a smart sensor installed on the motor via the Profibus protocol, and also obtain the output current value from the pump's frequency converter via the ModbusTCP protocol. Both data packets carry the raw numerical value characterizing the physical quantity of motor current.

[0030] As is understandable, cross-validation involves comparing and analyzing multiple raw data values ​​originating from different data channels but pointing to the same physical meaning. The system places these values ​​in a unified context, such as performing time synchronization alignment, and performs logical verification based on the known reasonable range of the physical quantity, device nameplate parameters, or the historical reliability of each data source. Its purpose is to identify and eliminate values ​​that are obviously abnormal, seriously contradictory, or transmitted incorrectly.

[0031] For example, step S103 may include the following steps: S1031: Obtain multiple candidate data values ​​corresponding to the same physical quantity based on multiple raw data messages.

[0032] S1032: Verify multiple candidate data values ​​based on preset device parameters. If all candidate data values ​​are within the valid value range defined by the device parameters, and the deviation between multiple candidate data values ​​is less than the first preset threshold, then determine the average of multiple candidate data values ​​as the state parameter value.

[0033] Specifically, preset equipment parameters related to the physical quantity and its corresponding equipment can be invoked. These parameters clearly define the allowed numerical boundaries of the physical quantity under normal operating conditions, i.e., the effective value range. For example, for the physical quantity of the bearing temperature of a water pump, its effective value range may be preset to 10 degrees Celsius to 90 degrees Celsius.

[0034] Furthermore, all candidate data values ​​can be compared and verified against this valid value range one by one. The purpose of this verification is to filter out obviously unreasonable data from a physical probability perspective. For example, if a candidate value shows 200 degrees Celsius, which exceeds the normal temperature range that the bearing material can withstand, then this value is identified as abnormal at this stage.

[0035] Based on the above validity checks, the consistency between multiple candidate data values ​​can be further analyzed. For example, the deviations between all valid candidate values ​​can be calculated, and each deviation value can be compared to a pre-defined first threshold. This threshold defines the maximum range of differences allowed for readings from different data sources to be considered consistent, i.e., representing the same true state, for a specific application scenario.

[0036] Understandably, the system determines that these data have high inherent consistency and reliability only if all candidate data values ​​are within a preset valid value range and all deviations between them are less than a first preset threshold. Under this condition, the arithmetic mean of these candidate data values ​​can be used as the final determined state parameter value. For example, if the bearing temperature readings from three independent sensors are 65.1 degrees Celsius, 65.3 degrees Celsius, and 64.9 degrees Celsius, respectively, and they are all within the valid range with minimal deviations between them, then the system will calculate their average value of 65.1 degrees Celsius as the authoritative value of the bearing temperature state parameter at that moment.

[0037] S1033: If at least one of the multiple candidate data values ​​exceeds the valid value range, or the deviation between them is greater than or equal to the first preset threshold, then obtain the data source credibility corresponding to each candidate data value, and determine the candidate data value with the highest credibility as the state parameter value.

[0038] Understandably, among multiple candidate data values, at least one value exceeds the valid value range predefined by the device parameters; or, although all candidate data values ​​are within the valid value range, the deviation between them reaches or exceeds the first preset threshold, indicating that there is a non-negligible contradiction between the data.

[0039] For example, the data timestamp and data source device status score corresponding to each candidate data value can be obtained, and a first confidence sub-item can be determined based on the time difference between the data timestamp and the current system time. The larger the time difference, the lower the first confidence sub-item. Then, a second confidence sub-item can be determined based on the data source device status. The device status score is positively correlated with the second confidence sub-item. The first confidence sub-item and the second confidence sub-item are weighted according to a preset weight to obtain the data source confidence corresponding to the candidate data value.

[0040] Understandably, one can first obtain the precise timestamp of the candidate data value when it was generated or sent by its data source, as well as the current status score of the data source device, i.e., the physical device such as the sensor or controller providing the data. The device status score is a pre-generated value reflecting the health and reliability of the device itself, generated through other monitoring mechanisms. Specific scoring criteria vary depending on the device and are not limited in this application.

[0041] The calculation process generates two independent confidence sub-items. The first confidence sub-item is derived based on the freshness of the data. For example, the difference between the data timestamp and the current system time can be calculated, i.e., the age of the data. According to preset rules, the larger this time difference, the older the data, and the lower the value of its corresponding first confidence sub-item.

[0042] The second confidence level item is directly related to the health status of the data source device. For example, the obtained device status score can be converted into the second confidence level item through a preset mapping relationship. This mapping relationship ensures that the higher the device score, the better its status, and the higher the corresponding value of the second confidence level item.

[0043] Furthermore, regarding quality labels, if the state parameter value is the mean of multiple candidate data values, and the deviations among the multiple candidate data values ​​are all less than a first preset threshold, then the state parameter is assigned a first-type quality label, which represents high-confidence valid data. If the state parameter value is the candidate data value with the highest confidence, then the state parameter is assigned a second-type quality label, which represents verified valid data. If the confidence levels corresponding to all candidate data values ​​are less than the second preset threshold or are missing, then the state parameter is assigned a third-type quality label, which represents invalid data.

[0044] Understandably, when a state parameter value is determined to be the arithmetic mean of multiple candidate data values, and the mutual deviations among these candidate data values ​​do not exceed a first preset threshold, a first-class quality label may be assigned to the state parameter. The conditions for generating this label indicate that multiple independent data sources provide highly consistent valid readings, and the final result is derived based on data fusion. Therefore, this label is used to characterize this state parameter as valid data with high confidence.

[0045] When a status parameter value is directly determined from multiple candidate data values ​​through an arbitration process by selecting the one with the highest confidence, a second-type quality label may be assigned to that status parameter. The conditions for generating this label indicate that there are conflicts or partial anomalies among the data, and the final value originates from the selection of a single optimal data source. Therefore, this label is used to characterize that this status parameter is valid data confirmed through a verification process.

[0046] When the reliability of the data source corresponding to all candidate data values ​​is below a preset second threshold, or when no candidate data values ​​can be obtained at all, a third quality label may be assigned to this status parameter. The conditions for generating this label indicate that the reliability of all available data sources is insufficient or the data is completely missing; therefore, this label is used to explicitly characterize this status parameter as invalid data.

[0047] After verification, this step generates a standardized state data packet as output for the virtual node. This data packet represents the state of the physical device in the digital space at the current moment. The data packet encapsulates one or more state parameters. Each state parameter corresponds to a key operational attribute of the device, and its value is the final result determined based on the aforementioned verification and fusion logic of multiple raw data streams. For example, the motor current state parameter of a water pump might be determined as the average of two valid raw data streams.

[0048] S104: Based on the virtual twin topology network, define upstream virtual nodes and downstream virtual nodes, and forward the status data packets output by the upstream virtual nodes to one or more downstream virtual nodes.

[0049] For example, the upstream and downstream roles of virtual nodes can be defined based on the actual connections, process flow sequence, or energy / material flow between physical devices mapped by the virtual twin topology network. Understandably, if the output of device A directly supplies or significantly affects the operation of device B, then in the digital twin network, the virtual node representing device A is defined as an upstream virtual node representing device B; conversely, the virtual node representing device B is defined as a downstream virtual node. This definition ensures that the logical relationships in the digital network align with the causal relationships in the physical world.

[0050] Specifically, as one implementation method, a process connection relationship configuration file for multiple auxiliary equipment can be obtained. The process connection relationship configuration file defines the physical connection relationship and process flow direction between each auxiliary equipment. Then, based on the process connection relationship configuration file, in the virtual twin topology network, the virtual node corresponding to the auxiliary equipment in the upstream process position in the physical connection is defined as the upstream virtual node, and the virtual node corresponding to the auxiliary equipment in the downstream process position in the physical connection is defined as the downstream virtual node.

[0051] Understandably, the process connection configuration file, in data form, clearly defines two key relationships between all relevant auxiliary equipment in the actual factory: first, the physical connection between equipment, such as which equipment's outlet pipe connects to another equipment's inlet; and second, the inherent direction determined based on the process flow or media flow direction, i.e., the process flow direction. For example, the file will clearly record that the output end of the feedwater pump is connected to the input end of the high-pressure heater, and that the process flow direction is from the pump to the heater.

[0052] Map the definitions in this configuration file to the constructed virtual twin topology network. For each pair of physical devices with process flow relationships specified in the configuration file, the system finds its corresponding virtual node in the virtual network. The virtual node corresponding to the physical device located upstream in the configuration file is defined as the upstream virtual node in the numerical relationship; at the same time, the virtual node corresponding to the physical device located downstream in the configuration file is defined as the downstream virtual node.

[0053] Of course, in this embodiment, since it is based on a virtual twin topology network, the transmission direction of the state data packets in the virtual twin topology network can also be directly obtained. If the state data packets output by any virtual node are allowed to be sent to another virtual node, the virtual node that sends the state data packets is defined as the upstream virtual node of the virtual node that receives the state data packets, and the virtual node that receives the state data packets is defined as the downstream virtual node of the virtual node that sends the state data packets.

[0054] Understandably, without relying on external process configuration files, it is possible to directly observe and utilize the established state packet transmission rules within the network.

[0055] For example, in this virtual twin topology network, a set of rules regarding the forwarding paths of state data packets has been pre-configured or dynamically. These rules specify which other virtual nodes any virtual node can send its generated state data packets to. The directional relationship between nodes can be determined by querying these predetermined forwarding rules. Specifically, for any two virtual nodes in the network, if the forwarding rules allow virtual node A to send its state data packets to virtual node B, then according to the definition in this embodiment, the sending virtual node A is identified as the upstream virtual node of the receiving virtual node B; correspondingly, the receiving virtual node B is identified as the downstream virtual node of the sending virtual node A.

[0056] Furthermore, after completing the role definition, a data forwarding path can be established. Each upstream virtual node, when generating its own state data packet, will not only use it for its own analysis, but will also actively send its state data packet to one or more designated downstream virtual nodes according to the predetermined topology connection rules.

[0057] For example, in a power plant's boiler feedwater system, a virtual node representing a feedwater pump is defined as an upstream node of the virtual node representing the boiler economizer. Once the feedwater pump virtual node has encapsulated its status parameters such as vibration, temperature, and flow rate, it forwards its status data packets to the economizer virtual node. Similarly, a condenser virtual node may be a downstream node of multiple circulating water pump virtual nodes simultaneously, and therefore it will receive status data packets from all of these upstream pump nodes.

[0058] S105: The downstream virtual node will merge the status data packets received from all the upstream virtual nodes with its own generated status data packets to form an aggregated data block. The aggregated data block is used to characterize the overall operating status of the local node group consisting of the downstream virtual node and all the upstream virtual nodes connected to the downstream virtual node.

[0059] Understandably, each independent downstream node can perform this step independently. Understandably, because the input of a downstream virtual node contains two types of data: one is the standardized state data packet it generates, representing the state of its corresponding physical device; the other is the state data packets it receives from all other devices defined as its upstream virtual nodes.

[0060] Understandably, this node does not simply aggregate or list these data packets, but rather fuses them. This processing may involve correlation analysis of key status parameters from multiple data packets, feature extraction, calculation of statistical indicators, or evaluation of overall performance. The specific algorithm depends on the process characteristics and monitoring objectives of this local equipment group.

[0061] For example, suppose that in a virtual twin topology network, a virtual node representing a high-pressure heater is defined as a downstream virtual node. It receives status data packets from its upstream virtual nodes, representing the feedwater pump, the pre-control valve, and the inlet flow meter, respectively. At the same time, it also generates its own status data packets representing the physical state of the high-pressure heater, such as the tube-side temperature and the shell-side pressure.

[0062] The data fusion processing performed by this high-pressure heater virtual node involves correlation analysis and comprehensive calculation of the parameters contained in these four state data packets. For example, it might perform the following operations: By utilizing the outlet pressure parameters in the upstream water supply pump status data packet, the instantaneous flow rate parameters in the upstream inlet flow meter status data packet, and the inlet and outlet temperature difference parameters in the system's own status data packet, combined with physical constants such as the specific heat capacity of water, the heat exchange efficiency or power consumption per unit flow rate of the water supply subsystem can be calculated in real time.

[0063] Similarly, the deviation between the opening command and the actual opening of the upstream pre-regulating valve, combined with the vibration amplitude of the feedwater pump and the pressure fluctuation of its own shell side, can be used to calculate a feedwater circuit stability index between 0 and 1 through a predefined rule or model.

[0064] Of course, we can also compare the key parameters of each upstream device, such as the efficiency of the pump and the degree of deviation of the valve response hysteresis from its rated value or historical best value, while considering the quality label level in each status data packet, to find the device link that currently limits the overall performance of the subsystem.

[0065] Understandably, all the above calculation results, along with the core raw parameters used for the calculations and their quality indicators, will be jointly encapsulated and organized into a new, structured data entity, namely, an aggregated data block. This aggregated data block contains the information that "the overall energy efficiency of this water supply unit, composed of pumps, valves, flow meters, and heaters, is X%, its operational stability is Y%, and the main limiting factor currently lies in device Z." This aggregated data block is used to characterize the overall operating status of this local node group (water supply unit).

[0066] The fusion process generates a new structured data object, the aggregated data block. This aggregated data block logically encapsulates and represents the real-time operational status of the entire device set, comprised of a specific downstream virtual node and all connected upstream virtual nodes that directly supply it with status data. In other words, it no longer describes the status of a single device, such as a pump, but rather the overall health, efficiency, and stability of a minimal unit with a specific function, such as a complete water supply booster unit, including pre-filters, pumps, outlet valves, etc.

[0067] S106: If the value of any status parameter in any status data packet in the aggregated data block exceeds the preset normal operating range threshold, or if the corresponding quality identifier of any status data packet is invalid, then the corresponding virtual node is determined to be in an abnormal state.

[0068] Specifically, each status parameter value recorded in the data packet can be compared with its predefined normal operating range threshold. This threshold is a reasonable range determined based on the device's rated parameters and historical operating statistics. If any status parameter value is found to exceed its specific threshold range, a judgment is immediately triggered, identifying the virtual node that generated the status data packet, i.e., the corresponding physical device, as being in an abnormal state. Simultaneously, the quality identifier attached to each status data packet is checked. The quality identifier indicates the reliability level of the status parameters within the data packet. If the quality identifier of any status data packet is marked as invalid, the system will directly determine that the virtual node corresponding to that data packet is in an abnormal state, regardless of its internal parameter values. For example, if a status data packet from a pressure sensor in the aggregated data block has its quality identifier marked as invalid due to continuous communication interruption, then the virtual node of that sensor is determined to be abnormal.

[0069] S107: When at least one virtual node is determined to be in an abnormal state, the initial virtual node whose state parameters first become abnormal is determined based on the time sequence of state parameter changes of all associated virtual nodes in the aggregated data block.

[0070] Understandably, the process begins by extracting each virtual node deemed abnormal from the aggregated data block. The exact time point at which its abnormal state parameters first exceeded the preset normal operating range threshold is recorded—the first timestamp. Then, all these collected first timestamps are compared, and the earliest one is selected. This earliest timestamp marks the moment when the first observable parameter exceeding the limit event occurs within the current local node group. The virtual node to which the abnormal state parameters corresponding to this earliest timestamp are assigned is identified as the initial virtual node where the state parameters first became abnormal. This determination means that, in the current abnormal event chain, the physical device corresponding to this node is identified as the most likely initial source of failure or initiator of the anomaly. Through this step, the process from discovering an anomaly to locating its origin is realized, providing crucial time-series evidence for accurate root cause analysis.

[0071] This invention discloses a holographic perception twin mapping method for auxiliary equipment, comprising: constructing a corresponding virtual twin topology network based on the connection relationship of multiple auxiliary equipment, wherein the network includes virtual nodes corresponding to each equipment, and each node has a built-in multi-protocol parser; obtaining the original data packets sent by the corresponding physical equipment through different protocols through the parser; performing cross-validation on multiple original packets received by the same node, and outputting a standard status data packet containing status parameters and quality identifiers; defining upstream and downstream virtual nodes based on the topology network, and forwarding the status data packets of the upstream node to the downstream node; the downstream node merging all received upstream status data packets with its own status data packets to form an aggregated data block; determining node anomalies based on the aggregated data block, and tracing back and determining the initial virtual node where the anomaly first occurred based on the time sequence of status parameter changes when an anomaly occurs. This invention achieves unified and reliable perception and fault tracing of a group of equipment.

[0072] Based on the same inventive concept, this application proposes a holographic sensing twin mapping system for auxiliary equipment. The system includes multiple auxiliary equipment and is configured as follows: Based on the connection relationship of multiple auxiliary devices, a corresponding virtual twin topology network is constructed in the digital space. The virtual twin topology network includes virtual nodes corresponding to each auxiliary device, and each virtual node includes a parser that can resolve at least two communication protocols. Based on the corresponding parsers of multiple virtual nodes, the original data packets sent by the corresponding virtual nodes through different communication protocols are obtained. The original data packets contain one or more original data values ​​collected by the auxiliary equipment. Cross-validate multiple raw data packets received by the same virtual node and output a status data packet corresponding to the virtual node. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​used to characterize the operating attributes of the auxiliary equipment corresponding to the virtual node. Based on the virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the status data packets output by the upstream virtual nodes are forwarded to one or more downstream virtual nodes; The downstream virtual node will merge the status data packets received from all the upstream virtual nodes with its own generated status data packets to form an aggregated data block. The aggregated data block is used to characterize the overall operating status of the local node group consisting of the downstream virtual node and all the upstream virtual nodes connected to the downstream virtual node. If the value of any status parameter in any status data packet in the aggregated data block exceeds the preset normal operating range threshold, or if the corresponding quality identifier of any status data packet is invalid, then the corresponding virtual node is determined to be in an abnormal state. When at least one virtual node is determined to be in an abnormal state, the initial virtual node whose state parameters first become abnormal is determined based on the time sequence of changes in the state parameters of all associated virtual nodes in the aggregated data block.

[0073] Optionally, the system is configured as follows: Cross-validation is performed on multiple raw data packets received from the same virtual node, and a status data packet corresponding to the virtual node is output. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​characterizing the operating attributes of the auxiliary equipment corresponding to the virtual node, including: Obtain multiple candidate data values ​​corresponding to the same physical quantity based on multiple raw data messages; Based on preset device parameters, multiple candidate data values ​​are verified. If all candidate data values ​​are within the valid value range defined by the device parameters, and the deviation between multiple candidate data values ​​is less than the first preset threshold, then the average of multiple candidate data values ​​is determined as the state parameter value. If at least one of the multiple candidate data values ​​exceeds the valid value range, or the deviation between them is greater than or equal to the first preset threshold, then the data source credibility corresponding to each candidate data value is obtained, and the candidate data value with the highest credibility is determined as the state parameter value.

[0074] Optionally, the system is configured as follows: If at least one of the multiple candidate data values ​​exceeds the valid value range, or the deviation between them is greater than or equal to a first preset threshold, then the data source credibility corresponding to each candidate data value is obtained, and the candidate data value with the highest credibility is determined as the state parameter value, including: Obtain the data timestamp and data source device status score corresponding to each candidate data value; The first confidence level is determined based on the time difference between the data timestamp and the current system time. The larger the time difference, the lower the confidence level of the first confidence level. The second confidence sub-item is determined based on the device status of the data source, wherein the device status score is positively correlated with the second confidence sub-item; Based on preset weights, the first confidence sub-item and the second confidence sub-item are weighted and calculated to obtain the data source confidence corresponding to the candidate data value.

[0075] Optionally, the system is configured as follows: Cross-validation is performed on multiple raw data packets received from the same virtual node, and a status data packet corresponding to the virtual node is output. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​characterizing the operating attributes of the auxiliary equipment corresponding to the virtual node, including: If the state parameter value is the mean of multiple candidate data values, and the deviation between multiple candidate data values ​​is less than the first preset threshold, then the state parameter is assigned a first type of quality label, and the first type of quality label represents that the data is high-confidence valid data. If the state parameter value is the candidate data value with the highest credibility, then the state parameter is assigned a second type of quality label. The second type of quality label represents that the data is verified valid data. If the confidence level of all candidate data values ​​is less than the second preset threshold or is missing, then a third quality label is assigned to the state parameter. The third quality label indicates that the data is invalid.

[0076] Optionally, the system is configured as follows: Based on a virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the state data packets output by the upstream virtual node are forwarded to one or more downstream virtual nodes, including: Obtain the process connection relationship configuration file of multiple auxiliary equipment, which defines the physical connection relationship and process flow direction between each auxiliary equipment; Based on the process connection relationship configuration file, in the virtual twin topology network, the virtual node corresponding to the auxiliary equipment located in the upstream process position in the physical connection is defined as the upstream virtual node, and the virtual node corresponding to the auxiliary equipment located in the downstream process position in the physical connection is defined as the downstream virtual node.

[0077] Optionally, the system is configured as follows: Based on a virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the state data packets output by the upstream virtual node are forwarded to one or more downstream virtual nodes, including: To obtain the transmission direction of state data packets in the virtual twin topology network, if the state data packet output by any virtual node is allowed to be sent to another virtual node, then the virtual node that sends the state data packet is defined as the upstream virtual node of the virtual node that receives the state data packet, and the virtual node that receives the state data packet is defined as the downstream virtual node of the virtual node that sends the state data packet.

[0078] Optionally, the system is configured as follows: When at least one virtual node is determined to be in an abnormal state, the initial virtual node whose state parameters first became abnormal is determined based on the time sequence of changes in the state parameters of all associated virtual nodes in the aggregated data block, including: Obtain the rated parameters of the auxiliary equipment, and determine the normal operating range thresholds corresponding to the status parameters based on the rated parameters; Get the first state parameter that first exceeds the normal operating range threshold and the first timestamp of the state parameter in each virtual node that is judged to be in an abnormal state in the aggregated data block, and define the state parameter as an abnormal state parameter. Determine the earliest timestamp from the first timestamp of all abnormal state parameters; The virtual node corresponding to the abnormal state parameter of the earliest timestamp is determined as the initial virtual node.

[0079] Based on the same inventive concept, embodiments of this application also propose an electronic device, which includes: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the auxiliary device holographic perception twin mapping method of the present application embodiments.

[0080] Furthermore, to achieve the above objectives, embodiments of this application also propose a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the auxiliary equipment holographic perception twin mapping method of this application.

[0081] The following is a detailed introduction to the various components of the electronic device: In this context, the processor is the control center of the electronic device. It can be a single processor or a collective term for multiple processing elements. For example, a processor can be one or more central processing units (CPUs), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0082] Alternatively, the processor can perform various functions of the electronic device by running or executing software programs stored in memory and by calling data stored in memory.

[0083] The memory is used to store the software program that executes the solution of the present invention, and the execution is controlled by the processor. The specific implementation method can be referred to the above method embodiment, which will not be repeated here.

[0084] Optionally, the memory can be read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, random access memory (RAM) or other types of dynamic storage devices capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory can be integrated with the processor or exist independently and coupled to the processor through an interface circuit of an electronic device; the embodiments of the present invention do not specifically limit this.

[0085] A transceiver is used to communicate with network devices or with terminal devices.

[0086] Optionally, the transceiver may include a receiver and a transmitter. The receiver is used to implement the receiving function, and the transmitter is used to implement the sending function.

[0087] Optionally, the transceiver can be integrated with the processor or exist independently and coupled to the processor through the router's interface circuit. This embodiment of the invention does not specifically limit this.

[0088] Furthermore, the technical effects of the electronic device can be referred to the technical effects of the data transmission method in the above method embodiments, and will not be repeated here.

[0089] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0090] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDRSDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DRRAM).

[0091] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0092] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0093] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0094] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0095] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

Claims

1. A holographic sensing twin mapping method for auxiliary equipment, characterized in that, A holographic sensing twin mapping system for auxiliary equipment is applicable, the system comprising multiple auxiliary equipment, the method comprising: Based on the connection relationship of multiple auxiliary devices, a corresponding virtual twin topology network is constructed in the digital space, wherein the virtual twin topology network includes virtual nodes corresponding to each auxiliary device, and each virtual node includes a parser capable of resolving at least two communication protocols; Based on the corresponding parsers of multiple virtual nodes, the original data packets sent by the corresponding virtual nodes through different communication protocols are obtained, and the original data packets contain one or more original data values ​​collected by the auxiliary equipment. Cross-validation is performed on multiple original data packets received by the same virtual node, and a status data packet corresponding to the virtual node is output. The status data packet contains one or more status parameters and a corresponding quality identifier. The status parameters are status values ​​used to characterize the operating attributes of the auxiliary equipment corresponding to the virtual node. Based on the virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the status data packets output by the upstream virtual nodes are forwarded to one or more downstream virtual nodes; The downstream virtual node will merge the received status data packets from all the upstream virtual nodes with its own generated status data packets to form an aggregated data block. The aggregated data block is used to characterize the overall operating status of the local node group composed of the downstream virtual node and all the upstream virtual nodes connected to the downstream virtual node. If the value of any status parameter in any status data packet in the aggregated data block exceeds the preset normal operating range threshold, or if the corresponding quality identifier of any status data packet is invalid, then the corresponding virtual node is determined to be in an abnormal state. When at least one of the virtual nodes is determined to be in an abnormal state, the initial virtual node whose state parameters first become abnormal is determined based on the time sequence of changes in the state parameters of all associated virtual nodes in the aggregated data block.

2. The holographic sensing twin mapping method for auxiliary equipment according to claim 1, characterized in that, Cross-validation is performed on multiple original data packets received by the same virtual node, and a status data packet corresponding to the virtual node is output. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​characterizing the operating attributes of the auxiliary equipment corresponding to the virtual node, including: Based on the multiple original data messages, obtain multiple candidate data values ​​corresponding to the same physical quantity; Based on preset device parameters, multiple candidate data values ​​are verified. If all candidate data values ​​are within the valid value range defined by the device parameters, and the deviation between multiple candidate data values ​​is less than a first preset threshold, then the average of multiple candidate data values ​​is determined as the state parameter value. If at least one of the candidate data values ​​exceeds the valid value range, or the deviation between them is greater than or equal to the first preset threshold, then the data source credibility corresponding to each candidate data value is obtained, and the candidate data value with the highest credibility is determined as the state parameter value.

3. The holographic sensing twin mapping method for auxiliary equipment according to claim 2, characterized in that, If at least one of the candidate data values ​​exceeds the valid value range, or the deviation between them is greater than or equal to the first preset threshold, then the data source credibility corresponding to each candidate data value is obtained, and the candidate data value with the highest credibility is determined as the state parameter value, including: Obtain the data timestamp and data source device status score corresponding to each candidate data value; Based on the time difference between the data timestamp and the current system time, a first confidence sub-item is determined, wherein the larger the time difference, the lower the first confidence sub-item. A second credibility sub-item is determined based on the device status of the data source, wherein the device status score is positively correlated with the second credibility sub-item; Based on preset weights, the first confidence sub-item and the second confidence sub-item are weighted and calculated to obtain the data source confidence corresponding to the candidate data value.

4. The holographic sensing twin mapping method for auxiliary equipment according to claim 2, characterized in that, Cross-validation is performed on multiple original data packets received by the same virtual node, and a status data packet corresponding to the virtual node is output. The status data packet contains one or more status parameters and corresponding quality identifiers. The status parameters are status values ​​characterizing the operating attributes of the auxiliary equipment corresponding to the virtual node, including: If the state parameter value is the mean of multiple candidate data values, and the deviation between multiple candidate data values ​​is less than the first preset threshold, then the state parameter is assigned a first type of quality label, and the first type of quality label represents data with high confidence and validity. If the state parameter value is the candidate data value with the highest credibility, then the state parameter is assigned a second type of quality identifier, and the second type of quality identifier represents that the data is verified valid data; If the confidence level corresponding to all candidate data values ​​is less than the second preset threshold or is missing, then a third quality identifier is assigned to the state parameter, and the third quality identifier indicates that the data is invalid.

5. The holographic sensing twin mapping method for auxiliary equipment according to claim 1, characterized in that, Based on the virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the status data packets output by the upstream virtual nodes are forwarded to one or more of the downstream virtual nodes, including: Obtain a process connection relationship configuration file for multiple auxiliary equipment, wherein the process connection relationship configuration file defines the physical connection relationship and process flow direction between each of the auxiliary equipment; Based on the process connection configuration file, in the virtual twin topology network, the virtual node corresponding to the auxiliary equipment located in the upstream process position in the physical connection is defined as the upstream virtual node, and the virtual node corresponding to the auxiliary equipment located in the downstream process position in the physical connection is defined as the downstream virtual node.

6. The holographic sensing twin mapping method for auxiliary equipment according to claim 1, characterized in that, Based on the virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the status data packets output by the upstream virtual nodes are forwarded to one or more of the downstream virtual nodes, including: The transmission direction of the state data packets in the virtual twin topology network is obtained. If the state data packets output by any virtual node are allowed to be sent to another virtual node, the virtual node that sends the state data packets is defined as the upstream virtual node of the virtual node that receives the state data packets, and the virtual node that receives the state data packets is defined as the downstream virtual node of the virtual node that sends the state data packets.

7. The holographic sensing twin mapping method for auxiliary equipment according to claim 1, characterized in that, When at least one of the virtual nodes is determined to be in an abnormal state, the initial virtual node whose state parameters first became abnormal is determined based on the time sequence of changes in the state parameters of all associated virtual nodes in the aggregated data block, including: Obtain the rated parameters of the auxiliary equipment, and determine the normal operating range threshold corresponding to the status parameter based on the rated parameters; Obtain any state parameter that first exceeds the normal operating range threshold and the first timestamp corresponding to the state parameter from each virtual node in the aggregated data block that is determined to be in an abnormal state, and define the state parameter as an abnormal state parameter. From the first timestamps of all the abnormal state parameters, determine the earliest timestamp of the earliest time. The virtual node corresponding to the abnormal state parameter corresponding to the earliest timestamp is determined as the initial virtual node.

8. A holographic sensing twin mapping system for auxiliary equipment, characterized in that, The system includes multiple auxiliary devices, and the system is configured as follows: Based on the connection relationship of multiple auxiliary devices, a corresponding virtual twin topology network is constructed in the digital space, wherein the virtual twin topology network includes virtual nodes corresponding to each auxiliary device, and each virtual node includes a parser capable of resolving at least two communication protocols; Based on the corresponding parsers of multiple virtual nodes, the original data packets sent by the corresponding virtual nodes through different communication protocols are obtained, and the original data packets contain one or more original data values ​​collected by the auxiliary equipment. Cross-validation is performed on multiple original data packets received by the same virtual node, and a status data packet corresponding to the virtual node is output. The status data packet contains one or more status parameters and a corresponding quality identifier. The status parameters are status values ​​used to characterize the operating attributes of the auxiliary equipment corresponding to the virtual node. Based on the virtual twin topology network, upstream virtual nodes and downstream virtual nodes are defined, and the status data packets output by the upstream virtual nodes are forwarded to one or more downstream virtual nodes; The downstream virtual node will merge the received status data packets from all the upstream virtual nodes with its own generated status data packets to form an aggregated data block. The aggregated data block is used to characterize the overall operating status of the local node group composed of the downstream virtual node and all the upstream virtual nodes connected to the downstream virtual node. If the value of any status parameter in any status data packet in the aggregated data block exceeds the preset normal operating range threshold, or if the corresponding quality identifier of any status data packet is invalid, then the corresponding virtual node is determined to be in an abnormal state. When at least one of the virtual nodes is determined to be in an abnormal state, the initial virtual node whose state parameters first become abnormal is determined based on the time sequence of changes in the state parameters of all associated virtual nodes in the aggregated data block.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; And, a memory that is communicatively connected to at least one processor; The memory stores instructions that can be executed by at least one processor, which enables the at least one processor to perform the method as claimed in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the method as claimed in any one of claims 1-7.

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