Real-time transmission method, system and device for PLC data and storage medium

Abstract

The invention belongs to the technical field of data processing, and particularly relates to a real-time transmission method, system and device for PLC data and a storage medium. The invention aims to solve the problems of data transmission delay, packet loss and even interruption in the prior art. And data formats acquired by the PLC are diversified and are not compatible with a cloud platform, and data loss or errors are easy to occur in a format conversion process. Comprising the following steps: periodically carrying out data acquisition from a PLC (Programmable Logic Controller) by utilizing edge computing equipment according to a preset sampling frequency to obtain acquired data; preprocessing the collected data to obtain preprocessed data; analyzing the preprocessed data in real time to obtain an analysis result, and judging whether the PLC is abnormal or not based on the analysis result: if yes, generating alarm information and a fault diagnosis report, and packaging the alarm information and the fault diagnosis report to generate to-be-transmitted data; if not, packaging the preprocessed data to generate data to be transmitted; and transmitting the to-be-transmitted data to a cloud server by using a dynamic scheduling strategy method according to the network condition and the data priority.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and in particular relates to a real-time transmission method, system, device and storage medium for PLC data. Background Art

[0002] In industrial automation scenarios, programmable logic controllers (PLCs), as core control devices, play a vital role in ensuring the continuity and stability of production processes. Real-time monitoring of PLC operating status and effective fault debugging can help promptly identify and resolve potential issues, thereby reducing downtime and improving production efficiency.

[0003] In existing technologies, through real-time monitoring of the operating data of PLCs and related equipment, once the monitoring system detects an abnormal situation, such as excessive temperature or abnormal pressure, it can immediately notify relevant personnel for processing. By analyzing and collecting detailed fault debug data, engineers can quickly determine the root cause of the problem, effectively debug the fault, and promptly discover and solve potential problems, thereby reducing downtime and improving production efficiency.

[0004] The existing technology has the following technical problems: 1. The industrial field network environment is complex and changeable, with problems such as signal interference, insufficient bandwidth, and incomplete network coverage, which lead to data transmission delays, packet loss, and even interruptions.

[0005] 2. The data formats collected by PLC are diverse and incompatible with the cloud platform. Data loss or errors are prone to occur during the format conversion process. At the same time, the PLC's own computing power is limited, making it difficult to complete efficient preprocessing before data transmission, which increases network transmission pressure.

[0006] 3. With the integration of industrial networks and the Internet, data transmission faces security threats such as hacker attacks and virus intrusions. Some PLC devices lack complete encryption and authentication mechanisms and cannot ensure data security.

[0007] 4. The communication protocols and interface standards of PLCs of different brands and models vary greatly, making it difficult to adapt to cloud platforms. In addition, the high costs of hardware upgrades and communications limit the efficient implementation of data transmission. Summary of the Invention

[0008] The present invention provides a real-time transmission method, system, device and storage medium for PLC data, aiming to solve the technical problems existing in the above-mentioned prior art, such as data transmission delay, packet loss and even interruption; the data formats collected by PLC are diverse and incompatible with cloud platforms, and data loss or errors are prone to occur during format conversion; there is a lack of complete encryption and authentication mechanisms, which cannot ensure data security; and difficult adaptation to cloud platforms.

[0009] The present invention solves the above technical problems with the following technical solutions: A method for real-time transmission of PLC data, comprising: Use edge computing devices to periodically collect data from the PLC according to the preset sampling frequency to obtain collected data; Preprocessing the collected data to obtain preprocessed data; Perform real-time analysis on the pre-processed data to obtain analysis results, and determine whether the PLC has an abnormality based on the analysis results: If so, an alarm message and a fault diagnosis report are generated and packaged to generate data to be transmitted; If not, the pre-processed data is packaged to generate data to be transmitted; According to the network status and data priority, the data to be transmitted is transmitted to the cloud server using a dynamic scheduling strategy method.

[0010] Furthermore, the above also includes: Utilizing a cloud server to receive and store the data to be transmitted; Utilize the cloud server to perform real-time analysis on the data to be transmitted to obtain status information of the PLC; The cloud server is used to visualize the status information through a visual interactive interface.

[0011] Furthermore, the pre-processing of the collected data specifically includes: Converting the data format of the collected data into a unified format; The noise of the collected data in a unified format is removed by using a filtering method to obtain denoised data; The denoised data is mapped into a preset range using a normalization method to obtain preprocessed data.

[0012] Furthermore, the above-mentioned real-time analysis of the pre-processed data obtains analysis results specifically including: Performing feature extraction on the preprocessed data to obtain feature data; Performing cluster analysis on the feature data to obtain data categories of the feature data; The characteristic data and data categories are input into a preset fault diagnosis model to perform fault diagnosis analysis and obtain analysis results.

[0013] Furthermore, the above-mentioned inputting the characteristic data and data categories into a preset fault diagnosis model to perform fault diagnosis analysis specifically includes: Acquiring the characteristic data, using the fault diagnosis model to predict the probability of a fault occurring, and obtaining a fault prediction result; Matching the data category of the fault prediction result to obtain the fault category of the fault prediction result; wherein the analysis result includes the fault prediction result and the fault category.

[0014] Furthermore, the above-mentioned determination of whether the PLC is abnormal based on the analysis results specifically includes: Determine whether the analysis results are outside the preset normal operating parameters: If so, an alarm message and a fault diagnosis report are generated and packaged to generate data to be transmitted; If not, the pre-processed data is packaged to generate data to be transmitted.

[0015] Furthermore, the above-mentioned method of using a dynamic scheduling strategy to transmit the data to be transmitted to the cloud server according to the network status and data priority specifically includes: Prioritize all data to be transmitted and transmit them in descending order of priority; When the bandwidth is insufficient, the data to be transmitted with a lower priority is cached or transmitted later.

[0016] In a second aspect, in order to solve the above technical problems, the present invention further provides a real-time transmission system for PLC data, comprising: The data acquisition module is used to periodically collect data from the PLC according to a preset sampling frequency using the edge computing device to obtain collected data; A preprocessing module, used for preprocessing the collected data to obtain preprocessed data; The data analysis module is used to perform real-time analysis on the pre-processed data to obtain analysis results, and determine whether there is an abnormality in the PLC based on the analysis results: If so, an alarm message and a fault diagnosis report are generated and packaged to generate data to be transmitted; If not, the pre-processed data is packaged to generate data to be transmitted; The real-time transmission module is used to transmit the data to be transmitted to the cloud server using a dynamic scheduling strategy method according to network conditions and data priority.

[0017] In a third aspect, in order to solve the above-mentioned technical problems, the present invention also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, the real-time transmission method of PLC data of the present application is implemented.

[0018] In a fourth aspect, in order to solve the above-mentioned technical problems, the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the real-time transmission method of PLC data of the present application is implemented.

[0019] Compared with the prior art, the present invention has the following advantages: 1. The present invention processes data locally through edge computing devices, reducing data transmission volume and delay, and can quickly transmit key data to the cloud, realizing real-time monitoring of PLC operating status and rapid response to faults.

[0020] 2. The present invention compresses and prioritizes data, rationally schedules transmission, reduces unnecessary data transmission, and lowers network communication costs, making it particularly suitable for cost-sensitive industrial scenarios.

[0021] 3. The edge computing device of the present invention processes data locally, and can still ensure monitoring and early warning functions in the event of network failure; reliable communication protocols and encryption technology ensure the security of data transmission.

[0022] 4. The edge computing device of the present invention serves as an intermediate layer and can adapt to PLCs and cloud platforms of different brands to solve compatibility issues; through software upgrades and function expansions, it can meet the ever-changing needs of industrial production and improve system scalability.

[0023] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 A schematic flow chart of a method for real-time transmission of PLC data according to an embodiment of the present invention is shown; Figure 2 A schematic structural diagram of a real-time transmission system for PLC data according to an embodiment of the present invention is shown; Figure 3 A schematic structural diagram of an electronic device according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0027] Figure 1 FIG. 1 shows a flow chart of a method for real-time transmission of PLC data according to an embodiment of the present invention, as shown in FIG. Figure 1 As shown, a real-time transmission method of PLC data according to an embodiment of the present invention includes: Use edge computing devices to periodically collect data from the PLC according to the preset sampling frequency to obtain collected data; Preprocessing the collected data to obtain preprocessed data; Perform real-time analysis on the pre-processed data to obtain analysis results, and determine whether the PLC has an abnormality based on the analysis results: If so, an alarm message and a fault diagnosis report are generated and packaged to generate data to be transmitted; If not, the pre-processed data is packaged to generate data to be transmitted; According to the network status and data priority, the data to be transmitted is transmitted to the cloud server using a dynamic scheduling strategy method.

[0028] In this embodiment, the edge computing device is deployed at the industrial site. The edge computing device establishes a connection with the PLC through communication methods such as industrial Ethernet and field bus, and is connected to the cloud server through a wireless network or wired network.

[0029] In this embodiment, the edge computing device is equipped with a high-performance processor, large-capacity memory and storage devices, and multiple communication interfaces, and has functions such as data collection, processing, storage and communication.

[0030] Optionally, also include: Utilizing a cloud server to receive and store the data to be transmitted; Utilize the cloud server to perform real-time analysis on the data to be transmitted to obtain status information of the PLC; The cloud server is used to visualize the status information through a visual interactive interface.

[0031] Optionally, preprocessing the collected data specifically includes: Converting the data format of the collected data into a unified format; In this embodiment, the data fields in a unified format are named and labeled to ensure clear semantics.

[0032] The noise of the collected data in a unified format is removed by using a filtering method to obtain denoised data; The denoised data is mapped into a preset range using a normalization method to obtain preprocessed data.

[0033] Optionally, performing real-time analysis on the pre-processed data to obtain analysis results specifically includes: Performing feature extraction on the preprocessed data to obtain feature data; Performing cluster analysis on the feature data to obtain data categories of the feature data; The characteristic data and data categories are input into a preset fault diagnosis model to perform fault diagnosis analysis and obtain analysis results.

[0034] In this embodiment, feature extraction is performed on the pre-processed data using data analysis methods, including statistical analysis algorithms, spectrum analysis algorithms, and pattern recognition algorithms. Fault diagnosis models include rule-based fault diagnosis models, case-based fault diagnosis models, and neural network-based fault diagnosis models.

[0035] Optionally, inputting the characteristic data and data categories into a preset fault diagnosis model to perform fault diagnosis analysis specifically includes: Acquiring the characteristic data, using the fault diagnosis model to predict the probability of a fault occurring, and obtaining a fault prediction result; Matching the data category of the fault prediction result to obtain the fault category of the fault prediction result; wherein the analysis result includes the fault prediction result and the fault category.

[0036] In this embodiment, the fault diagnosis model is trained through machine learning methods and historical data, so that the fault diagnosis model can provide early warning of potential faults. Once an abnormality is detected or a fault is predicted, an alarm message and a fault diagnosis report are immediately generated.

[0037] Optionally, judging whether the PLC is abnormal based on the analysis results specifically includes: Determine whether the analysis results are outside the preset normal operating parameters: If so, an alarm message and a fault diagnosis report are generated and packaged to generate data to be transmitted; If not, the pre-processed data is packaged to generate data to be transmitted.

[0038] In this embodiment, for data to be transmitted to the cloud, the edge computing device uses an efficient data compression algorithm to compress it to reduce the transmission volume.

[0039] Optionally, according to the network status and data priority, using a dynamic scheduling strategy method to transmit the data to be transmitted to the cloud server specifically includes: Prioritize all data to be transmitted and transmit them in descending order of priority; When the bandwidth is insufficient, the data to be transmitted with a lower priority is cached or transmitted later.

[0040] In this embodiment, users can view PLC operating status, monitoring data, and fault diagnosis reports in real time through the cloud platform, allowing them to perform remote debugging and maintenance operations. The cloud server also uses big data analysis and artificial intelligence technologies to deeply mine historical data, providing optimization suggestions and decision support for industrial production.

[0041] Based on Figure 1 Based on the same principle as the method shown in , the embodiment of the present invention also provides a real-time transmission system for PLC data, such as Figure 2 As shown in , including: The data acquisition module is used to periodically collect data from the PLC according to a preset sampling frequency using the edge computing device to obtain collected data; A preprocessing module, used for preprocessing the collected data to obtain preprocessed data; The data analysis module is used to perform real-time analysis on the pre-processed data to obtain analysis results, and determine whether there is an abnormality in the PLC based on the analysis results: If so, an alarm message and a fault diagnosis report are generated and packaged to generate data to be transmitted; If not, the pre-processed data is packaged to generate data to be transmitted; The real-time transmission module is used to transmit the data to be transmitted to the cloud server using a dynamic scheduling strategy method according to network conditions and data priority.

[0042] Optionally, also include: The cloud server is used to receive and store the data to be transmitted; perform real-time analysis on the data to be transmitted to obtain status information of the PLC; and visualize the status information through a visual interactive interface.

[0043] The real-time transmission system of PLC data in the embodiment of the present invention can execute the real-time transmission method of PLC data provided by the embodiment of the present invention, and its implementation principle is similar. The actions performed by each module and unit in the real-time transmission system of PLC data in each embodiment of the present invention correspond to the steps in the real-time transmission method of PLC data in each embodiment of the present invention. For the detailed functional description of each module of the real-time transmission system of PLC data, please refer to the description in the corresponding real-time transmission method of PLC data shown in the previous text, and will not be repeated here.

[0044] Among them, the above-mentioned real-time transmission system of PLC data can be a computer program (including program code) running in a computer device, for example, the real-time transmission system of PLC data is an application software; the application software can be used to execute the corresponding steps in the method provided in the embodiment of the present invention.

[0045] The modules involved in the embodiments of the present invention may be implemented in software or hardware, wherein the name of a module does not necessarily limit the module itself.

[0046] Based on the same principle as the method shown in the embodiments of the present invention, an electronic device is also provided in the embodiments of the present invention, which may include but is not limited to: a processor and a memory; the memory is used to store computer programs; the processor is used to execute the method shown in any embodiment of the present invention by calling the computer program.

[0047] In an alternative embodiment, an electronic device is provided, such as Figure 3 As shown, Figure 3 The electronic device shown includes a processor and a memory. The processor and the memory are connected, for example, via a bus. Optionally, the electronic device may further include a transceiver, which can be used for data exchange between the electronic device and other electronic devices, such as data transmission and / or data reception. It should be noted that in actual applications, there is not limited to one transceiver, and the structure of the electronic device does not constitute a limitation on the embodiments of the present invention.

[0048] The memory is used to store application code (computer program) for executing the solution of the present invention, and the processor controls the execution of the application code. The processor is used to execute the application code stored in the memory to implement the content shown in the above method embodiment.

[0049] Among them, the electronic device can also be a terminal device, Figure 3 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0050] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding contents of the aforementioned method embodiment.

[0051] According to another aspect of the present invention, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various implementations described above.

[0052] The above description is merely a preferred embodiment of the present invention and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of disclosure involved in the present invention is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also includes other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned disclosed concepts. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in the present invention.

Claims

1. A real-time transmission method for PLC data, characterized in that: The method comprises: Use edge computing devices to periodically collect data from the PLC according to the preset sampling frequency to obtain collected data; Preprocessing the collected data to obtain preprocessed data; Perform real-time analysis on the pre-processed data to obtain analysis results, and determine whether the PLC has an abnormality based on the analysis results: If so, an alarm message and a fault diagnosis report are generated and packaged to generate data to be transmitted; If not, the pre-processed data is packaged to generate data to be transmitted; According to the network status and data priority, the data to be transmitted is transmitted to the cloud server using a dynamic scheduling strategy method.

2. A real-time transmission method for PLC data according to claim 1, characterized in that: Also includes: Utilizing a cloud server to receive and store the data to be transmitted; Utilize the cloud server to perform real-time analysis on the data to be transmitted to obtain the status information of the PLC; The cloud server is used to visualize the status information through a visual interactive interface.

3. The real-time transmission method of PLC data according to claim 1, characterized in that: Preprocessing the collected data specifically includes: Converting the data format of the collected data into a unified format; The noise of the collected data in a unified format is removed by using a filtering method to obtain denoised data; The denoised data is mapped into a preset range using a normalization method to obtain preprocessed data.

4. The real-time transmission method of PLC data according to claim 1, characterized in that: The pre-processed data is analyzed in real time to obtain analysis results including: Performing feature extraction on the preprocessed data to obtain feature data; Performing cluster analysis on the feature data to obtain data categories of the feature data; The characteristic data and data categories are input into a preset fault diagnosis model to perform fault diagnosis analysis and obtain analysis results.

5. A real-time transmission method for PLC data according to claim 4, characterized in that: Inputting the characteristic data and data categories into a preset fault diagnosis model to perform fault diagnosis analysis specifically includes: Acquiring the characteristic data, using the fault diagnosis model to predict the probability of a fault occurring, and obtaining a fault prediction result; Matching the data category of the fault prediction result to obtain the fault category of the fault prediction result; wherein the analysis result includes the fault prediction result and the fault category.

6. A real-time transmission method for PLC data according to claim 5, characterized in that: Determining whether the PLC has an abnormality based on the analysis results specifically includes: Determine whether the analysis results are outside the preset normal operating parameters: If so, an alarm message and a fault diagnosis report are generated and packaged to generate data to be transmitted; If not, the pre-processed data is packaged to generate data to be transmitted.

7. A method for real-time transmission of PLC data according to claim 1, characterized in that: According to the network status and data priority, the method of using a dynamic scheduling strategy to transmit the data to be transmitted to the cloud server specifically includes: Prioritize all data to be transmitted and transmit them in descending order of priority; When the bandwidth is insufficient, the data to be transmitted with a lower priority is cached or transmitted later.

8. A real-time transmission system for PLC data, characterized in that: include: The data acquisition module is used to periodically collect data from the PLC according to a preset sampling frequency using the edge computing device to obtain collected data; A preprocessing module, used for preprocessing the collected data to obtain preprocessed data; The data analysis module is used to perform real-time analysis on the pre-processed data to obtain analysis results, and determine whether there is an abnormality in the PLC based on the analysis results: If so, an alarm message and a fault diagnosis report are generated and packaged to generate data to be transmitted; If not, the pre-processed data is packaged to generate data to be transmitted; The real-time transmission module is used to transmit the data to be transmitted to the cloud server using a dynamic scheduling strategy method according to network conditions and data priority.

9. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer storage medium, characterized in that The computer storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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