Blood plasma separator data transmission method and device

Abstract

The invention provides a plasma separator data transmission method and device, and is applied to the technical field of data processing. When network interruption is detected, an edge computing node receives original data and stores the original data locally; when detecting that the network is recovered, the edge computing node sends the locally stored original data to a far-end central system; comparing the original data uploaded by the edge computing node with the original data stored in the far-end central system in the far-end central system; the far-end center system stores the received original data according to a comparison result and detects whether the uploaded data conflicts with the self-stored data or not; if the conflict exists, updating and recording the original data according to a preset rule; and if the conflict does not exist, updating and recording the original data, thereby completing data synchronization and data consistency. Therefore, the method has the beneficial effects that the data is not lost during the network interruption period, and the complete synchronization and consistency maintenance of the data are realized after the network is recovered.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and particularly to a method and device for data transmission of a plasma separator. Background Art

[0002] As an important medical device, a plasma separator is widely used in clinical separation and treatment of various blood components. During the operation of the device, a large amount of operation data, device status parameters, patient physiological parameters, and various alarm and event records are generated and processed in real time. These data are of irreplaceable value for real-time monitoring of the device operation status, evaluation of the effectiveness of the treatment process, ensuring the safety of patients' lives, and subsequent clinical analysis, quality control, and device maintenance. These data are characterized by a fast generation speed, a large data volume, and high requirements for real-time performance, especially the fluctuations of key physiological parameters and device abnormal alarm information.

[0003] In the actual medical environment, especially in the complex building structures within large hospitals, temporarily established field medical points, or space-constrained mobile medical units, the deployment and stability of network infrastructure often face challenges. Wired network cabling may be inconvenient, and wireless network signals are vulnerable to electromagnetic interference from building materials, other medical devices, or physical obstructions, resulting in unstable network connections, limited bandwidth, or high latency. Under such network conditions, it is difficult to directly and completely upload the massive original real-time data generated by the plasma separator to a remote central server located in the hospital information center or the cloud. Limited network bandwidth may become a bottleneck for data transmission, leading to data upload delays, backlogs, or even losses, affecting the timely utilization of data and the effectiveness of decision-making.

[0004] In order to design an efficient, reliable, and secure data synchronization and conflict resolution mechanism under multiple constraints of resource limitation, data sensitivity, and unstable network connections, and ensure that the original data produced by the plasma separator can be reliably synchronized and data integrity and consistency can be maintained after the network is restored, is a key technical problem that urgently needs to be solved in the current plasma separator data transmission application.

[0005] Aiming at the above problems, the existing technologies urgently need to be improved. Summary of the Invention

[0006] In view of the deficiencies of the above-mentioned prior art, this application provides a method and device for data transmission of a plasma separator, which has the beneficial effects of realizing data non-loss during network interruption, and realizing complete data synchronization and consistency maintenance after the network is restored.

[0007] First aspect, a data transmission method for a plasma separator, an edge computing node is deployed inside the plasma separator, and the edge computing node is used to receive the original data generated by the plasma separator and upload the original data to a remote central system through a network. The method includes the steps: S1: When detecting a network interruption, control the edge computing node to continue receiving the original data and store it locally; S2: When detecting network recovery, control the edge computing node to send the original data stored locally to the remote central system; S3: Compare the original data uploaded by the edge computing node with the original data stored in the remote central system to obtain a comparison result; S4: According to the comparison result, control the remote central system to store the received original data and detect whether there is a conflict between the original data and the original data stored in the remote central system; S5: If there is a conflict, update and record the original data according to a preset conflict handling rule; if there is no conflict, update and record the original data.

[0008] A data transmission method for a plasma separator proposed in this application ensures that data is not lost during a network interruption by having the edge computing node receive and store the original data locally when a network interruption is detected. When network recovery is detected, the edge computing node sends the original data stored locally to the remote central system. This resumes data transmission. The original data uploaded by the edge computing node is compared with the original data stored in the remote central system in the remote central system to generate a comparison result. This provides a basis for data synchronization and conflict handling. The remote central system stores the received original data according to the comparison result and detects whether there is a conflict between the uploaded data and the data stored by itself. This identifies situations of data inconsistency. If there is a conflict, the remote central system updates and records the original data according to a preset rule. This resolves data conflicts and maintains data consistency. If there is no conflict, the remote central system updates and records the original data, thus completing data synchronization. Therefore, the method proposed in this application has the beneficial effects of achieving data non-loss during a network interruption and achieving complete data synchronization and consistency maintenance after network recovery.

[0009] Further, step S1 includes: S11: Monitor the network connection in real time. When detecting a network interruption, determine the type of network interruption; S12: When the type of network interruption is a physical line fault or network congestion, store the original data locally using a circular queue storage method; S13: When the type of network interruption is server maintenance, an incremental storage method is adopted, and only the original data that has changed compared with the original data successfully uploaded to the remote central system last time is stored locally to save resources.

[0010] A data transmission method for a plasma separator proposed in this application, by distinguishing the type of network interruption and adopting corresponding storage strategies (circular queue or incremental storage), this technical solution solves the problem of rapid resource depletion that may be caused by simple local storage, improves the efficiency and persistence of local storage, and enables edge computing nodes to more effectively manage local data storage in different network interruption scenarios.

[0011] Further, step S12 includes: S121: When the type of network interruption is physical line failure or network congestion, obtain the data type of the original data; the data type includes real-time monitoring data, alarm data, and operation logs; S122: Divide the local storage area into a high-priority data storage area and a low-priority data storage area, and store the alarm data or the real-time monitoring data in the high-priority data storage area, and store the operation logs in the low-priority data storage area; S123: When the high-priority data storage area is full, the alarm data or the real-time monitoring data newly added to the circular queue will overwrite the operation logs that entered the low-priority data storage area earliest.

[0012] A data transmission method for a plasma separator proposed in this application, this solution ensures that when the high-priority storage area is full, the storage space of low-priority data (operation logs) is preferentially sacrificed to save new high-priority data (alarm data or real-time monitoring data), thereby maximizing the retention of information that is more critical for subsequent data synchronization and clinical decision-making, and improving the effectiveness and value of locally stored data.

[0013] Further, in step S122, the step of dividing the local storage area into a high-priority data storage area and a low-priority data storage area includes: S1221: Obtain the duration of the network interruption and the generation rate of each type of original data; S1222: If the duration of the network interruption is greater than or equal to the first preset time, or the generation rate of the alarm data and the real-time monitoring data in the original data is greater than or equal to the first preset rate, then make the size of the high-priority data storage area larger than the size of the low-priority data storage area, otherwise, make the size of the high-priority data storage area equal to the size of the low-priority data storage area.

[0014] A method for transmitting plasma separator data proposed in this application dynamically adjusts the size of the storage area based on the network interruption duration and data generation rate. This technical solution makes the division of the local storage area more flexible and adaptable, can optimize the allocation of storage resources according to the actual situation, and improves the reliability of storing high-priority data during network interruptions. The technical features of obtaining the network interruption duration and data generation rate provide a basis for judgment; the technical feature of adjusting the storage area size according to the judgment result realizes the dynamic allocation of storage resources.

[0015] Further, step S2 includes: S21: When detecting network recovery, query the original data that the edge computing node has not uploaded, sort it according to the timestamps of the original data to form a data queue to be uploaded; S22: Obtain the network bandwidth, the CPU utilization rate of the edge node, and the memory occupancy rate, evaluate the available resources of the edge computing node, and determine the maximum upload quantity of the original data that can be uploaded at one time according to the available resources; S23: Compress the original data with the maximum upload quantity using the LZ4 fast compression algorithm to obtain compressed data packets, divide the compressed data packets into multiple data packets, and add sequence numbers to each data packet; S24: After the remote central system receives the data packets, reorganize them according to the sequence numbers to restore the compressed data packets, and decompress the compressed data packets to obtain the original data.

[0016] Further, step S22 includes: S221: Calculate the first data volume that can be transmitted per unit time according to the network bandwidth; S222: Calculate the data processing rate of the edge computing node according to the CPU utilization rate of the edge node and the memory occupancy rate; S223: Obtain the current remaining power of the edge computing node, calculate the working time of the edge computing node under the remaining power based on the remaining power, and calculate the second data volume that the edge computing node can process before the power runs out according to the working time and the data processing rate; S224: Compare the first data volume with the second data volume, and select the smaller of the first data volume or the second data volume as the maximum upload quantity.

[0017] Further, step S3 includes: S31: Extract the version number of the original data uploaded by the edge computing node; S32: According to the version number, determine whether there is a historical version in the remote central system. If not, the comparison result is that the original data is new data; S33: If there is a historical version, the comparison result is that the original data is non-new data.

[0018] Further, step S4 includes: S41: When the comparison result is that the original data is new data, control the remote central system to directly update and record the received original data; S42: When the comparison result is that the original data is non-new data, control the remote central system to extract the timestamp of the original data; S43: Compare the timestamp of the original data with the historical timestamp of the corresponding historical version data stored in the remote central system. If the timestamp is later than the historical timestamp, it is determined that there is no conflict; otherwise, it is determined that there is a conflict.

[0019] Further, the preset conflict handling rules at least include a data priority policy and an artificial arbitration policy. Step S5 includes: S51: If there is a conflict, select the data priority policy. The data priority policy includes: obtaining the data type of the data corresponding to the conflict, comparing the priorities of the data types, and selecting the original data corresponding to the data type with a higher priority for updating and recording; S53: When the priorities of the data types are equal, select the artificial arbitration policy. The artificial arbitration policy includes: marking the data corresponding to the conflict as pending manual processing, generating an alarm message containing detailed conflict information to notify relevant personnel for processing, and updating and recording the original data according to the feedback processing result.

[0020] In a second aspect, a plasma separator data transmission device, characterized in that it is applied to the steps of any one of the above methods, and the device includes: The first control module: When detecting a network interruption, control the edge computing node to continue receiving the original data and store it locally; The second control module: When detecting a network recovery, control the edge computing node to send the original data stored locally to the remote central system; The comparison module: Compare the original data uploaded by the edge computing node with the original data stored in the remote central system to obtain a comparison result; The detection module: Control the remote central system to store the received original data according to the comparison result, and detect whether there is a conflict between the original data and the original data stored in the remote central system; Update module: If there is a conflict, update and record the original data according to the preset conflict handling rules; if there is no conflict, update and record the original data.

[0021] Beneficial effects: A data transmission method and device for a plasma separator proposed in this application. When a network interruption is detected, the edge computing node receives the original data and stores it locally, ensuring that data is not lost during the network interruption. When a network recovery is detected, the edge computing node sends the original data stored locally to the remote central system, resuming data transmission. In the remote central system, the original data uploaded by the edge computing node is compared with the original data stored in the remote central system to generate a comparison result, providing a basis for data synchronization and conflict handling. The remote central system stores the received original data according to the comparison result and detects whether there is a conflict between the uploaded data and its own stored data, identifying situations of data inconsistency. If there is a conflict, the remote central system updates and records the original data according to the preset rules, resolving the data conflict and maintaining data consistency. If there is no conflict, the remote central system updates and records the original data, thus completing data synchronization. Therefore, the method proposed in this application has the beneficial effect of achieving data non-loss during network interruption and achieving complete data synchronization and consistency maintenance after network recovery. Description of the Drawings

[0022] Figure 1 It is a flowchart of a data transmission method for a plasma separator proposed in this application.

[0023] Figure 2 It is a structural diagram of a data transmission device for a plasma separator proposed in this application.

[0024] Figure 3 It is a structural block diagram of a data transmission method and device for a plasma separator proposed in this application.

[0025] Label description: 201, First control module; 202, Second control module; 203, Comparison module; 204, Detection module; 205, Update module. Detailed Embodiments

[0026] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and marked in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application to be protected, but only represents the selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0027] It should be noted that similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, terms such as "first", "second", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0028] Please refer to Figure 1 , Figure 3 , a method for data transmission of a plasma separator. An edge computing node is deployed inside the plasma separator. The edge computing node is used to receive the original data generated by the plasma separator and upload the original data to a remote central system through a network. The method includes the steps of: S1: When detecting a network interruption, control the edge computing node to continue receiving the original data and store it locally; S2: When detecting a network recovery, control the edge computing node to send the original data stored locally to the remote central system; S3: Compare the original data uploaded by the edge computing node with the original data stored in the remote central system to obtain a comparison result; S4: Control the remote central system to store the received original data according to the comparison result, and detect whether there is a conflict between the original data and the original data stored in the remote central system; S5: If there is a conflict, update and record the original data according to the preset conflict handling rules; if there is no conflict, update and record the original data.

[0029] Among them, in step S1, when detecting a network connection interruption, the edge computing node receives the original data generated by the plasma separator and stores it in a local storage medium. Thereby, it is ensured that the data generated during the period when the network is unavailable will not be lost.

[0030] In step S2, when the network connection recovery is detected, the edge computing node reads the locally stored data and sends it to the remote central system via the network connection. This enables the data accumulated during the network interruption to be transmitted to the central system.

[0031] In step S3, after receiving the data uploaded by the edge computing node, the remote central system performs a comparison operation, comparing the uploaded data with the data it has already stored itself, and generates a comparison result, which indicates the relationship between the uploaded data and the existing data, such as whether it is new data or a modification to the existing data.

[0032] In step S4, based on the comparison result, the remote central system decides how to process the received data, including whether to directly store it and whether conflict detection is required. If there is an inconsistency between the uploaded data and the data stored in the remote central system, the system will detect a conflict.

[0033] In step S5, when a data conflict is detected, the system resolves the conflict according to the preset rules and updates or records the final data version. If there is no conflict, the received data is directly updated or recorded. Through this series of steps, reliable transmission, synchronization, and conflict management of the plasma separator data in an unstable network environment are achieved.

[0034] Specifically, this method establishes a data transmission link between the plasma separator edge computing node and the remote central system.

[0035] When the edge computing node detects that the network connection to the remote central system is interrupted, such as through the failure of periodic network connectivity checks, the edge computing node no longer attempts to upload the newly generated raw data, but writes this data into its internal local storage unit. The edge computing node continuously receives the raw data generated by the plasma separator and caches it locally until the network is restored.

[0036] Once the edge computing node detects that the network connection has been restored, such as through a successful network connectivity check, it initiates the upload process of the locally stored data. The locally stored data is read in the order of generation time or other preset order and sent to the remote central system via the network. After receiving the data sent by the edge computing node, the remote central system compares each received raw data record with the corresponding data already stored in its own database.

[0037] The comparison can be based on data identifiers, timestamps, or version numbers to determine whether the uploaded data is a new record or a modification of an existing record. Based on the comparison result, the remote central system decides how to process the received data. If the comparison result indicates that the uploaded data is new data, it is directly stored in the database. If the comparison result indicates that the uploaded data may be associated with existing data, the system further detects whether there are conflicts. For example, if the timestamp of the uploaded data is earlier than or equal to the latest timestamp of the stored data, it indicates a conflict.

[0038] If a conflict is detected, the system will call a preset conflict handling rule, such as selecting the final data version based on data type priority or manually, and updating the records in the database. At the same time, the conflict event may be recorded. If there is no conflict, for example, the uploaded data is an update of an existing record and the timestamp is later than the existing record, the record in the database is directly updated. Thus, it ensures that the data of the edge node can be reliably synchronized to the central system after a network interruption, and solves the problem of data inconsistency that may occur in a distributed environment.

[0039] Furthermore, step S1 includes: S11: Monitor the network connection in real time. When a network interruption is detected, determine the type of network interruption; S12: When the type of network interruption is a physical line failure or network congestion, store the original data locally using a circular queue storage method; S13: When the type of network interruption is server maintenance, use an incremental storage method to store only the original data that has changed compared to the original data successfully uploaded to the remote central system last time, in order to save resources.

[0040] Among them, the real-time monitoring of the network connection can be achieved by the edge computing node periodically sending probe packets to the remote central system and checking the response, or by listening to the change of the network interface status.

[0041] After detecting a network connection interruption, the edge computing node performs the operation of determining the type of network interruption. The determination of the type can be based on network error codes, connection attempt results, or specific network signals or server status information received. For example, a connection timeout or an unreachable route may indicate a physical line failure or congestion, while receiving a specific maintenance status code returned by the server indicates server maintenance.

[0042] When it is determined to be a physical line fault or network congestion, the local storage adopts a circular queue structure. This means that the local storage space is organized into a buffer with a fixed size, and the newly received data is added to the tail of the queue. When the buffer is full, the new data will overwrite the oldest data at the head of the queue. Thus, the local storage always retains the latest raw data, and the use of the storage space is limited within a preset range to avoid infinite growth.

[0043] When it is determined to be server maintenance, the local storage adopts an incremental method. The edge computing node will maintain a snapshot or mark that records the status of the last successfully uploaded data. The newly received raw data will be compared with this snapshot, and only the changed data records (e.g., value changes, new records) will be stored locally. The unchanged data will not be stored, thus significantly reducing the amount of data stored locally.

[0044] Using circular queue storage can ensure that the edge node continuously receives and retains the latest raw data within the limited local storage space, guaranteeing that new data with high timeliness requirements can be preferentially uploaded after the network is restored, or making room for new data by overwriting old data when the storage space is insufficient, improving the persistence of data storage.

[0045] Adopting the incremental storage method, only the parts that have changed compared with the last successfully uploaded data are recorded, avoiding storing a large amount of duplicate data or data that the remote system cannot process temporarily, greatly saving the local storage space and processing resources.

[0046] Thus, selecting the appropriate storage strategy according to the type of network interruption optimizes the local data management efficiency of the edge computing node in the case of network instability or interruption, and improves the robustness of the system.

[0047] Further, step S12 includes: S121: When the type of network interruption is a physical line fault or network congestion, obtain the data type of the raw data; the data type includes real-time monitoring data, alarm data, and operation logs; S122: Divide the local storage area into a high-priority data storage area and a low-priority data storage area, and store the alarm data or real-time monitoring data in the high-priority data storage area, and store the operation logs in the low-priority data storage area; S123: When the high-priority data storage area is full, the newly added alarm data or real-time monitoring data in the circular queue will overwrite the operation logs that entered the low-priority data storage area earliest.

[0048] Specifically, this method solves the problem that important data may be overwritten and lost due to limited local storage space during network interruption.

[0049] The edge computing node continuously monitors the network connection status. When a network interruption is detected and the interruption type is determined to be a physical line fault or network congestion, the local data storage mechanism is started. The received raw data is first identified for its data type, such as alarm data, real-time monitoring data, or operation logs.

[0050] Based on the importance of the data type, the system logically divides the local storage space into two areas: a high-priority storage area for storing data with higher importance (alarm data, real-time monitoring data), and a low-priority storage area for storing data with lower importance (operation logs). The received data is directed to the corresponding storage area according to its type. Both the high-priority storage area and the low-priority storage area manage data in a circular queue manner, that is, when new data is written, if the storage area is full, the earliest data in the storage area will be overwritten. However, in order to preferentially retain important data, when the high-priority storage area reaches its storage limit and needs to receive new high-priority data, the system does not directly overwrite the data in the high-priority storage area, but checks the low-priority storage area. At this time, the earliest-written operation log in the low-priority storage area will be deleted to make room for the new high-priority data, and then the new high-priority data is written into the high-priority storage area.

[0051] This mechanism ensures that in the case of continuous influx of high-priority data and tight local storage resources, the storage space of operation logs is preferentially sacrificed to save more critical alarm data and real-time monitoring data, thus maximizing the integrity of important data and improving the effectiveness of locally stored data.

[0052] Furthermore, in step S122, the step of dividing the local storage area into a high-priority data storage area and a low-priority data storage area includes: S1221: Obtain the duration of the network interruption and the generation rate of each type of raw data; S1222: If the duration of the network interruption is greater than or equal to the first preset time, or the generation rate of alarm data and real-time monitoring data in the raw data is greater than or equal to the first preset rate, then make the size of the high-priority data storage area larger than the size of the low-priority data storage area; otherwise, make the size of the high-priority data storage area equal to the size of the low-priority data storage area.

[0053] Among them, the duration of the network interruption can be calculated by continuously monitoring the network connection status and recording the start and end time points of the interruption.

[0054] The generation rate of each type of raw data can be obtained by counting the number of different types of data (such as real-time monitoring data, alarm data, operation logs) received per unit time.

[0055] Determining whether the network interruption duration is greater than or equal to a first preset time and whether the generation rate of alarm data or real-time monitoring data is greater than or equal to a first preset rate is achieved by comparing the obtained actual values with the preset thresholds.

[0056] Among them, the first preset time refers to the maximum allowable network interruption time. When this time is reached, the storage area for storing high-priority data in the edge computing node will be full; similarly, the first preset rate is the maximum allowable data generation rate. When this rate is reached, the storage area for storing high-priority data in the edge computing node will be full.

[0057] According to the comparison results, dynamically adjust the size ratio of the high-priority data storage area and the low-priority data storage area in the local storage area, for example, by adjusting the number of memory blocks or the capacity limit allocated to these two areas.

[0058] Specifically, this technical solution solves the problem that during a network interruption, the fixed division ratio of the local storage area cannot adapt to the change of the network interruption duration and the change of the generation rate of different types of raw data.

[0059] By obtaining in real time the duration of the network interruption and the generation rates of various types of raw data such as real-time monitoring data, alarm data, and operation logs generated by the plasma separator, the system can evaluate the current data storage pressure and priority requirements.

[0060] When the network is interrupted for a long time or the high-priority data (alarm data, real-time monitoring data) is generated at a relatively fast speed, the system determines that it is necessary to prioritize ensuring the storage space for high-priority data. Therefore, the size of the high-priority data storage area is dynamically set to be larger than that of the low-priority data storage area. This ensures that in the case of limited storage resources, key data such as alarms and real-time monitoring has more space to be stored, reducing the risk of being overwritten and lost by subsequent data. Conversely, when the network interruption time is not long and the generation rate of high-priority data is not high, the system determines that there is no need to overly tilt resources, and the high-priority and low-priority storage areas can be set to the same size to balance the storage requirements of different types of data. Thus, the division of the local storage area is more flexible, and it can optimize the allocation of storage resources according to the actual operating environment and data characteristics, improving the reliability of high-priority data storage during network interruptions. Furthermore, step S2 includes: S21: When detecting that the network has recovered, query the raw data that has not been uploaded by the edge computing node, sort it according to the timestamps of the generated raw data, and form a data queue to be uploaded. S22: Obtain the network bandwidth, the CPU utilization rate of the edge node, and the memory occupancy rate, evaluate the available resources of the edge computing node, and determine the maximum upload quantity of the original data that can be uploaded at one time according to the available resources; S23: Compress the original data with the maximum upload quantity by using the LZ4 fast compression algorithm to obtain a compressed data packet, split the compressed data packet into multiple data packets, and add a sequence number to each data packet; S24: After the remote central system receives the data packets, reorganize them according to the sequence numbers to restore the compressed data packet, and decompress the compressed data packet to obtain the original data.

[0061] Specifically, this technical solution solves the problem of how to control the sending process to adapt to the network and edge node resource limitations when sending locally stored data from the edge computing node to the remote central system after the network is restored.

[0062] First, when it is detected that the network connection is restored, the system queries the data that is locally stored in the edge computing node but has not been successfully uploaded to the remote central system. These data are sorted according to the timestamps when they are generated to form an ordered queue of data to be uploaded.

[0063] Next, the system obtains the system resource information such as the current network bandwidth, the CPU utilization rate of the edge node, and the memory occupancy rate in real time. Based on this information, the system evaluates the resource capabilities of the edge computing node currently available for data upload. According to the evaluation results, the system calculates and determines the maximum number of data records that can be selected and processed from the queue of data to be uploaded at one time.

[0064] Then, the system selects the maximum number of original data records from the head of the queue of data to be uploaded, and uses the LZ4 fast compression algorithm to compress these data to generate a compressed data packet. For the convenience of transmission and processing at the receiving end, these compressed data packets are split into multiple smaller data packets, and each split data packet is assigned a unique sequence number. These data packets with sequence numbers are then sent to the remote central system through the network. After the remote central system receives these data packets, it will perform caching and reorganization operations according to the sequence numbers carried by each data packet until the complete compressed data packet is restored.

[0065] Finally, the remote central system decompresses the reorganized compressed data packet to obtain the original plasma separator data. In this way, the data transmission process can be dynamically adjusted according to the real-time network and edge node resource conditions, avoiding resource bottlenecks. At the same time, the data transmission efficiency and reliability are improved through compression, packet splitting, and adding sequence numbers, ensuring the orderly and complete synchronization of the locally stored data after the network is restored.

[0066] Further, step S22 includes: S221: Calculate the first data volume that can be transmitted per unit time according to the network bandwidth; S222: Calculate the data processing rate of the edge computing node according to the CPU utilization rate and memory occupancy rate of the edge node; S223: Obtain the current remaining power of the edge computing node, calculate the working time of the edge computing node based on the remaining power, and calculate the second data volume that the edge computing node can process before the power runs out according to the working time and the data processing rate; S224: Compare the first data volume with the second data volume, and select the smaller of the first data volume or the second data volume as the maximum upload quantity.

[0067] Specifically, this solution aims to solve the problem that when the edge node uploads the locally stored data to the remote central system after the network is restored, the upload may fail due to insufficient network bandwidth, limited processing capacity of the edge node, or insufficient remaining power.

[0068] After detecting the network restoration, first query and sort the data to be uploaded by timestamp to form an ordered queue. Subsequently, by obtaining the current network bandwidth, calculate the maximum data volume allowed to be transmitted by the network per unit time, which represents the upper limit of the network transmission capacity. The specific calculation formula is: D1 = B / BitsPerByte T_unit, D1 is the first data volume, B is the network bandwidth, BitsPerByte is the conversion coefficient between bits and bytes, which can be set to 8, and T_unit is the unit time, which can be set to 1 second.

[0069] Meanwhile, monitor the CPU utilization rate and memory occupancy rate of the edge computing node, evaluate its current data processing ability, and calculate the data processing rate. Specifically, the steps for calculating the data processing rate include: Obtain the current CPU utilization rate U_cpu and memory utilization rate U_mem of the edge computing node; Obtain the maximum processing rate R_cpu_max when the edge computing node is only restricted by the CPU and the maximum processing rate R_mem_max when it is only restricted by the memory; Calculate the CPU-limited processing rate Rate_cpu of the edge computing node at the current CPU utilization rate, where Rate_cpu = (1 - U_cpu) R_cpu_max; Calculate the memory-limited processing rate Rate_mem of the edge computing node at the current memory utilization rate, where Rate_mem = (1 - U_mem) R_mem_max; Determine that the data processing rate R_proc of the edge computing node is the smaller value of the CPU-limited processing rate Rate_cpu and the memory-limited processing rate Rate_mem, where R_proc = min(Rate_cpu, Rate_mem).

[0070] Among them, U_cpu represents the current CPU utilization rate, with a range of [0, 1]; U_mem represents the current memory utilization rate, with a range of [0, 1]; R_cpu_max represents the maximum data processing rate determined only by the CPU performance when the memory resources are sufficient; R_mem_max represents the maximum data processing rate determined only by the memory system performance when the CPU resources are sufficient; Rate_cpu represents the maximum processing rate allowed by the CPU at the current CPU utilization rate; Rate_mem represents the maximum processing rate allowed by the memory system at the current memory utilization rate; R_proc represents the data processing rate of the edge computing node finally calculated.

[0071] Furthermore, obtain the remaining power of the edge computing node currently, and estimate the time that the node can continue to work before the power runs out based on this power. Combine the data processing rate to calculate the second data volume that the edge node can process and prepare to upload before the power runs out. Specifically, the steps to calculate the second data volume include: D2 = R_proc T, where T = B_rem / P_proc; P_proc = f(U_cpu, U_mem).

[0072] Among them, D2 is the second data volume, R_proc is the data processing rate, T is the time that the node can continue to work before the power runs out estimated based on this power, B_rem is the remaining power; P_proc is the instantaneous processing rate of the edge computing node, and f(Rate_cpu, Rate_mem) is a function describing the relationship between power consumption and CPU utilization rate and memory occupancy rate.

[0073] Finally, compare the first data volume calculated based on the network bandwidth with the second data volume calculated based on the remaining power and processing capacity, and select the smaller value of the two as the maximum data volume that can be uploaded at one time currently.

[0074] Thus, the upper limit of the data volume that the edge node can reliably complete the upload task is determined under the current network, processing capacity, and energy status. According to the determined maximum upload quantity, the data to be uploaded is compressed and sub-packaged to improve the transmission efficiency and reliability. After the remote central system receives the data packet, it performs recombination and decompression to restore the original data. By comprehensively considering the network, processing capacity, and energy status, this solution improves the success rate and reliability of data uploads and avoids upload interruptions caused by insufficient resources or battery depletion.

[0075] Further, step S3 includes: S31: Extract the version number of the original data uploaded by the edge computing node; S32: According to the version number, determine whether there is a historical version in the remote central system. If not, the comparison result is that the original data is new data; S33: If there is a historical version, the comparison result is that the original data is non-new data.

[0076] Among them, extracting the version number of the original data uploaded by the edge computing node, the version number can be a unique identifier associated with the original data. Determining whether there is a historical version in the remote central system according to the version number involves query operations based on the extracted version number in the database or storage system of the remote central system. If the query result shows that there is no data record matching the version number, it is determined that there is no historical version. If the query result returns a data record matching the version number, it is determined that there is a historical version. Thus, according to the judgment result of whether there is a historical version, it is determined whether the uploaded original data is new data or non-new data.

[0077] Further, step S4 includes: S41: When the comparison result is that the original data is new data, control the remote central system to directly update and record the received original data; S42: When the comparison result is that the original data is non-new data, control the remote central system to extract the timestamp of the original data; S43: Compare the timestamp of the original data with the historical timestamp of the corresponding historical version data stored in the remote central system. If the timestamp is later than the historical timestamp, it is determined that there is no conflict, otherwise, it is determined that there is a conflict.

[0078] Specifically, this technical solution solves the problem of how to determine whether there is a conflict between the data uploaded by the edge computing node and the corresponding historical version data stored in the remote central system when the data is determined to be non-new data.

[0079] When the comparison result shows that the uploaded original data is new data, the remote central system directly stores and records the data. This corresponds to the first upload of data or a completely new record, and at this time, there is no possibility of conflict with the existing data, and the processing process is direct and efficient. When the uploaded data is non-new data, it is necessary to determine whether the uploaded data conflicts with the corresponding historical version data in the remote central system.

[0080] By extracting the timestamp contained in the uploaded original data and comparing it with the timestamp of the corresponding historical version of the data stored in the remote central system, the new and old relationship of the data can be judged based on the time sequence. If the timestamp of the uploaded data is later than the timestamp of the historical version, it is considered that the data is updated in chronological order and there is no conflict, and subsequent update operations can be performed. If the timestamp of the uploaded data is earlier than or equal to the timestamp of the historical version, it is considered that the uploaded data is an old version and there is a conflict, and corresponding conflict handling is required.

[0081] By introducing and comparing the timestamps of the data, a conflict detection mechanism based on time sequence is provided, providing a clear judgment basis for subsequent conflict handling, and ensuring that potential data inconsistencies can be identified for non-new data during the data synchronization process.

[0082] Furthermore, the preset conflict handling rules at least include a data priority policy and an artificial arbitration policy, and step S5 includes: S51: If there is a conflict, select the data priority policy. The data priority policy includes: obtaining the data type of the data corresponding to the conflict, comparing the priorities of the data types, and selecting the original data corresponding to the data type with the higher priority for update and recording; S53: When the priorities of the data types are equal, select the artificial arbitration policy. The artificial arbitration policy includes: marking the data corresponding to the conflict as pending manual processing, generating an alarm message containing detailed conflict information to notify relevant personnel for processing, and updating and recording the original data according to the feedback processing result.

[0083] Specifically, when the edge computing node uploads the original data stored locally to the remote central system after the network is restored, and the remote central system detects a conflict between the uploaded data and the data it has stored itself after comparison, the conflict handling process will be started.

[0084] First, the system executes a data priority policy. For example, if a conflict occurs between an alarm data record uploaded by an edge node and an operation log record already existing in the remote central system, the system will identify the alarm data type and the operation log type. According to the preset priority rules (for example, the priority of alarm data is higher than that of operation logs), the system will automatically select the alarm data as the valid data and update the records in the remote central system with this alarm data. If a conflict occurs between two data of the same type (for example, two real-time monitoring data records), or the priority policy cannot clearly judge (for example, the type priorities of the two conflicting data are equal), then the system will enable the manual arbitration policy. At this time, the conflicting data will be marked by the system, and an alarm message containing detailed conflict information (such as data timestamp, type, conflict content difference, etc.) will be generated.

[0085] This alarm message will be sent to the preset relevant personnel (such as system administrators or clinical medical staff) for manual processing. After receiving the alarm, the relevant personnel can view the conflict details and decide which version of the data to retain or how to merge the data based on the actual situation and professional judgment.

[0086] After the system receives the manual processing result, it will finally update and record the data in the remote central system according to this result. Thus, by combining automated priority processing and manual intervention, the accuracy and consistency of data in various conflict scenarios are ensured. Especially when dealing with medical data with extremely high accuracy requirements, a reliable conflict resolution mechanism is provided.

[0087] Please refer to Figure 2 , a plasma separator data transmission device, characterized in that it is applied to the steps of any of the above methods, and the device includes: The first control module 201: When detecting a network interruption, control the edge computing node to continue receiving the original data and store it locally; The second control module 202: When detecting a network recovery, control the edge computing node to send the original data stored locally to the remote central system; The comparison module 203: Compare the original data uploaded by the edge computing node with the original data stored in the remote central system to obtain a comparison result; The detection module 204: Control the remote central system to store the received original data according to the comparison result, and detect whether there is a conflict between the original data and the original data stored in the remote central system; The update module 205: If there is a conflict, update and record the original data according to the preset conflict handling rules; if there is no conflict, update and record the original data.

[0088] Among them, the device includes a first control module 201, a second control module 202, a comparison module 203, a detection module 204, and an update module 205.

[0089] The first control module 201 is used to control the edge computing node to receive the original data and store it locally when the network connection is interrupted. Thus, even when the network is unavailable, the data generated by the plasma separator will not be lost, ensuring the continuity of the data.

[0090] The second control module 202 is used to control the edge computing node to send the locally stored data to the remote central system when the network connection is restored. This enables the data accumulated during the network interruption to be uploaded in a timely manner after the network is restored, achieving data completion.

[0091] The comparison module 203 is used to compare the data uploaded by the edge computing node with the data stored in the remote central system and generate a comparison result. This comparison result is the basis for subsequent data processing and conflict detection.

[0092] The detection module 204 controls the remote central system to store the received data according to the comparison result and detects whether there is a conflict between the uploaded data and the data stored in the remote central system. This ensures that the data undergoes a consistency check before being incorporated into the central system.

[0093] The update module 205 processes the data according to the detection result. If there is a conflict, the data is updated and recorded according to the preset rules; if there is no conflict, the data is directly updated and recorded. This ensures the consistency and integrity of the data between the edge and the central system.

[0094] Specifically, this device is applied to the data transmission process of the plasma separator. When the plasma separator generates original data during operation, the edge computing node receives this data. Under normal network conditions, the data can be directly uploaded to the remote central system. When the network connection is interrupted, the first control module 201 is activated, controlling the edge computing node to stop attempting to upload and instead write the received original data into the local storage area inside the edge node. In this way, all the data generated during the network interruption is safely stored locally.

[0095] When the first control module 201 or an independent network monitoring mechanism detects that the network connection is restored, the second control module 202 starts to work, controlling the edge computing node to read the locally stored data and initiating the data transmission process to the remote central system.

[0096] After the remote central system receives the data uploaded by the edge node, the comparison module 203 compares this data with the existing data in the central system to determine whether the uploaded data is new data or an update to the existing data.

[0097] Subsequently, based on the comparison result, the detection module 204 decides how to process the received data and checks for data conflicts, such as different versions or timestamps of the same data in the edge and central systems.

[0098] Finally, based on the judgment result of the detection module, the update module 205 performs corresponding data update and recording operations. If there is a conflict, it resolves the conflict according to the preset conflict handling rules (such as based on data type priority or manual intervention) and then performs the update; if there is no conflict, it directly merges the uploaded data into the database of the central system.

[0099] Through this series of steps, the device ensures that in an environment with unstable network, the data of the plasma separator can be reliably transmitted from the edge to the center, and maintains the integrity and consistency of the data.

[0100] In this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0101] The above description is only for the embodiments of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A method for transmitting data of a plasma separator, characterized in that An edge computing node is deployed inside the plasma separator. The edge computing node is used to receive the raw data generated by the plasma separator and upload the raw data to a remote central system through a network. The method includes the following steps: S1: When a network interruption is detected, control the edge computing node to continue receiving the raw data and store it locally; S2: When network recovery is detected, control the edge computing node to send the raw data stored locally to the remote central system; S3: Compare the raw data uploaded by the edge computing node with the raw data stored in the remote central system to obtain a comparison result; S4: Control the remote central system to store the received raw data according to the comparison result, and detect whether there is a conflict between the raw data and the raw data stored in the remote central system; S5: If there is a conflict, update and record the raw data according to a preset conflict handling rule; if there is no conflict, update and record the raw data.

2. The data transmission method of a plasma separator according to claim 1, characterized in that, Step S1 includes: S11: Monitor the network connection in real time. When a network interruption is detected, determine the type of network interruption; S12: When the type of network interruption is a physical line fault or network congestion, store the raw data locally using a circular queue storage method; S13: When the type of network interruption is server maintenance, use an incremental storage method to store only the raw data that has changed compared to the raw data successfully uploaded to the remote central system last time to save resources.

3. A method for transmitting plasma separator data according to claim 2, characterized in that, Step S12 includes: S121: When the type of network interruption is a physical line fault or network congestion, obtain the data type of the raw data; the data type includes real-time monitoring data, alarm data, and operation logs; S122: Divide the local storage area into a high-priority data storage area and a low-priority data storage area, and store the alarm data or the real-time monitoring data in the high-priority data storage area, and store the operation logs in the low-priority data storage area; S123: When the high-priority data storage area is full, let the newly added alarm data or real-time monitoring data in the circular queue overwrite the operation logs that entered the low-priority data storage area earliest.

4. A method for transmitting data of a plasma separator according to claim 3, characterized in that, In step S122, the step of dividing the local storage area into a high-priority data storage area and a low-priority data storage area includes: S1221: Obtain the duration of the network interruption and the generation rate of each type of raw data; S1222: If the duration of the network interruption is greater than or equal to a first preset time, or the generation rate of the alarm data and the real-time monitoring data in the raw data is greater than or equal to a first preset rate, make the size of the high-priority data storage area larger than the size of the low-priority data storage area; otherwise, make the size of the high-priority data storage area equal to the size of the low-priority data storage area.

5. A method for transmitting data of a plasma separator according to claim 1, characterized in that, Step S2 includes: S21: When detecting network recovery, query the original data not uploaded by the edge computing node, sort it according to the timestamps generated from the original data, and form a data queue to be uploaded. S22: Obtain the network bandwidth, CPU utilization rate of the edge node, and memory occupancy rate, evaluate the available resources of the edge computing node, and determine the maximum upload quantity of the original data that can be uploaded at one time according to the available resources. S23: Compress the original data with the maximum upload quantity using the LZ4 fast compression algorithm to obtain a compressed data packet, split the compressed data packet into multiple data packets, and add sequence numbers to each data packet. S24: After the remote central system receives the data packets, reorganize them according to the sequence numbers to restore the compressed data packet, and decompress the compressed data packet to obtain the original data.

6. A method for transmitting data of a plasma separator according to claim 5, characterized in that, Step S22 includes: S221: Calculate the first data volume that can be transmitted per unit time according to the network bandwidth. S222: Calculate the data processing rate of the edge computing node according to the CPU utilization rate of the edge node and the memory occupancy rate. S223: Obtain the remaining power of the edge computing node currently, based on the remaining power, calculate the working time of the edge computing node under the remaining power, and calculate the second data volume that the edge computing node can process before the power runs out according to the working time and the data processing rate. S224: Compare the first data volume with the second data volume, and select the smaller of the first data volume or the second data volume as the maximum upload quantity.

7. A method for data transmission of a plasma separator according to claim 1, characterized in that, Step S3 includes: S31: Extract the version number of the original data uploaded by the edge computing node. S32: According to the version number, determine whether there is a historical version in the remote central system. If not, the comparison result is that the original data is new data. S33: If there is a historical version, the comparison result is that the original data is non-new data.

8. A method for transmitting data of a plasma separator according to claim 7, characterized in that, Step S4 includes: S41: When the comparison result is that the original data is new data, control the remote central system to directly update and record the received original data. S42: When the comparison result is that the original data is non-new data, control the remote central system to extract the timestamp of the original data. S43: Compare the timestamp of the original data with the historical timestamp of the corresponding historical version data stored in the remote central system. If the timestamp is later than the historical timestamp, it is determined that there is no conflict; otherwise, it is determined that there is a conflict.

9. A method for transmitting data of a plasma separator according to claim 8, characterized in that The preset conflict handling rules at least include a data priority strategy and an artificial arbitration strategy. Step S5 includes: S51: If there is a conflict, select the data priority strategy. The data priority strategy includes: obtaining the data type of the data corresponding to the conflict, comparing the priorities of the data types, and selecting the original data corresponding to the data type with a higher priority to update and record. S53: When the priorities of the data types are equal, select an artificial arbitration strategy, which includes: marking the data corresponding to the conflict as to be processed manually, generating an alarm message containing detailed conflict information to notify relevant personnel for processing, and updating and recording the original data according to the feedback processing result.

10. A data transmission device for a plasma separator, characterized in that, Applied to the steps of the method according to any one of the above claims 1-9, the device includes: The first control module: when detecting a network interruption, control the edge computing node to continue receiving the original data and store it locally; The second control module: when detecting a network recovery, control the edge computing node to send the original data stored locally to the remote central system; The comparison module: compare the original data uploaded by the edge computing node with the original data stored in the remote central system to obtain a comparison result; The detection module: control the remote central system to store the received original data according to the comparison result, and detect whether there is a conflict between the original data and the original data stored in the remote central system; The update module: if there is a conflict, update and record the original data according to a preset conflict handling rule; if there is no conflict, update and record the original data.

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