An industrial system status monitoring method, device, equipment and storage medium

Abstract

The present application discloses an industrial system status monitoring method, device, equipment and storage medium, relating to the industrial field, including: detecting by a preset node diagnosis server based on a first status data packet sent by a preset node diagnosis client and using a preset K-value clustering algorithm to obtain a corresponding first diagnosis result; detecting by an IO / P2P master service and an IO / P2P slave service based on a second status data packet sent by a preset controller and the preset K-value clustering algorithm to obtain a corresponding second diagnosis result; judging whether there is a change in the system device configuration based on the diagnosis result, and if so, triggering a corresponding diagnostic graph drawing operation to perform monitoring based on the determined system diagnostic graph. The present application uses a preset K-value clustering algorithm for detection and automatically executes a corresponding diagnostic graph drawing operation when the system device configuration changes, can directly reflect the root cause fault information points based on the system diagnostic graph and quickly locate the position of the faulty device, improving the detection efficiency and the system diagnosis accuracy.

Description

Technical Field

[0001] The present invention relates to the industrial field, and particularly to an industrial system status monitoring method, device, equipment and storage medium. Background Art

[0002] The DCS (Distributed Control System) adopts the basic design concept of decentralized control and centralized management and operation, and is widely used in various industrial fields. Generally, the DCS runs stably and rarely fails. However, if the system fails, it will disrupt the entire production order and directly affect production efficiency and economic benefits. Therefore, to avoid this situation, many current manufacturers' systems will add a system diagnosis and monitoring system. In the existing situation, if a fault occurs, a series of diagnostic errors or invalid diagnoses will be generated, bringing extra work to the actual work of the operator, and it is impossible to accurately report the real fault source quickly based on the diagnostic results, thus affecting the detection efficiency. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide an industrial system status monitoring method, device, equipment and storage medium, which can directly reflect the root fault information points based on the determined system diagnosis diagram and quickly locate the position of the faulty equipment, improving the detection efficiency and the system diagnosis accuracy. The specific solutions are as follows:

[0004] In a first aspect, the present application provides an industrial system status monitoring method, including:

[0005] Detecting the preset node diagnosis client by a preset node diagnosis server based on a first status data packet sent by the preset node diagnosis client and using a preset K-value clustering algorithm, obtaining a corresponding first diagnosis result and writing the first diagnosis result into a preset real-time database;

[0006] Detecting the preset controller by an IO / P2P master service and an IO / P2P slave service based on a second status data packet sent by the preset controller and the preset K-value clustering algorithm, obtaining a corresponding second diagnosis result and writing the second diagnosis result into the main server memory;

[0007] Judging whether there is a change in the current system device configuration. If so, triggering a corresponding diagnosis diagram drawing operation based on the first diagnosis result and the second diagnosis result, and sending the determined system diagnosis diagram to an operation node so that an operator can obtain the system diagnosis diagram through a preset human-computer interaction interface for corresponding monitoring operations.

[0008] Optionally, before the preset node diagnosis server detects the preset node diagnosis client based on the first status data packet sent by the preset node diagnosis client and using the preset K - value clustering algorithm, the following steps are also included:

[0009] Configure corresponding system diagnosis points for each operation node to obtain a number of preset node diagnosis clients; wherein, the system diagnosis points include analog - type diagnosis points and digital - type diagnosis points.

[0010] Optionally, the preset node diagnosis server detects the preset node diagnosis client based on the first status data packet sent by the preset node diagnosis client and using the preset K - value clustering algorithm to obtain the corresponding first diagnosis result, including:

[0011] The preset node diagnosis server processes the valid data in the first status data packet; the valid data includes status information corresponding to the preset node diagnosis client, status information of other preset node diagnosis clients of the same type, and diagnosis information.

[0012] Normalize the processed valid data based on the preset data normalization rule to obtain corresponding data to be detected, and use the preset K - value clustering algorithm to analyze and calculate the data to be detected to obtain the corresponding first diagnosis K - value.

[0013] Judge whether the difference between the first diagnosis K - value and the first preset K - value is greater than the first preset threshold, and determine the corresponding node status information based on the judgment result to obtain the corresponding first diagnosis result.

[0014] Optionally, after the preset node diagnosis server writes the first diagnosis result into the preset real - time database, the following steps are also included:

[0015] Each operation node sends a diagnosis result request to the preset real - time database through the 128 network and the 129 network respectively according to the preset data acquisition period to obtain the node status information corresponding to all operation nodes.

[0016] Optionally, after the preset node diagnosis server writes the first diagnosis result into the preset real - time database, the following steps are also included:

[0017] When the preset real - time database does not receive the data packet containing the first diagnosis result sent by the preset node diagnosis server within the preset time period, it is determined that the preset node diagnosis client has a fault.

[0018] Optionally, the IO / P2P master service and the IO / P2P slave service detect the preset controller based on the second status data packet sent by the preset controller and the preset K-value clustering algorithm, and obtain corresponding second diagnostic results, including:

[0019] The IO / P2P master service and the IO / P2P slave service analyze and calculate the controller status data and the corresponding module status data in the second status data packet based on the preset K-value clustering algorithm to obtain corresponding second diagnostic K-values;

[0020] Judge whether the difference between the second diagnostic K-value and the second preset K-value is greater than the second preset threshold, and determine the corresponding controller status information based on the judgment result to obtain the corresponding second diagnostic result.

[0021] Optionally, judging whether there is a change in the current system device configuration based on the first diagnostic result and the second diagnostic result. If so, trigger the corresponding diagnostic graph drawing operation, including:

[0022] Create a new canvas by calling a preset image drawing script;

[0023] When there is a change in the system device configuration, obtain the corresponding system device information, and determine a corresponding number of system symbols based on the system device information; the system device information includes device status information and device parameter information;

[0024] Perform corresponding diagnostic graph drawing operations on the canvas based on the preset image drawing script, the system device information, and the several system symbols.

[0025] In a second aspect, the present application provides an industrial system status monitoring device, including:

[0026] A first status diagnosis module, configured to detect the preset node diagnosis client by a preset node diagnosis server based on a first status data packet sent by the preset node diagnosis client and using a preset K-value clustering algorithm, obtain a corresponding first diagnostic result, and write the first diagnostic result into a preset real-time database;

[0027] A second status diagnosis module, configured to detect the preset controller by an IO / P2P master service and an IO / P2P slave service based on a second status data packet sent by the preset controller and the preset K-value clustering algorithm, obtain a corresponding second diagnostic result, and write the second diagnostic result into the main server memory;

[0028] A monitoring operation execution module, configured to determine whether there is a change in the current system device configuration. If so, trigger a corresponding diagnostic graph drawing operation based on the first diagnostic result and the second diagnostic result, and send the determined system diagnostic graph to an operation node so that an operator can obtain the system diagnostic graph through a preset human-machine interaction interface to perform corresponding monitoring operations.

[0029] In a third aspect, the present application provides an electronic device, including:

[0030] A memory, configured to store a computer program;

[0031] A processor, configured to execute the computer program to implement the steps of the industrial system status monitoring method described above.

[0032] In a fourth aspect, the present application provides a computer-readable storage medium, configured to store a computer program, and when the computer program is executed by a processor, implement the steps of the industrial system status monitoring method described above.

[0033] It can be seen that in the present application, through a preset node diagnosis server, based on the first status data packet sent by a preset node diagnosis client and using a preset K-value clustering algorithm to detect the preset node diagnosis client, a corresponding first diagnostic result is obtained and the first diagnostic result is written into a preset real-time database; through an IO / P2P master service and an IO / P2P slave service, based on the second status data packet sent by a preset controller and the preset K-value clustering algorithm to detect the preset controller, a corresponding second diagnostic result is obtained and the second diagnostic result is written into the main server memory; determine whether there is a change in the current system device configuration. If so, trigger a corresponding diagnostic graph drawing operation based on the first diagnostic result and the second diagnostic result, and send the determined system diagnostic graph to an operation node so that an operator can obtain the system diagnostic graph through a preset human-machine interaction interface to perform corresponding monitoring operations. The present application uses a preset K-value clustering algorithm for detection and automatically executes a corresponding diagnostic graph drawing operation when the system device configuration changes, and can directly reflect the root cause fault information points based on the determined system diagnostic graph and quickly locate the position of the faulty device, improving the detection efficiency and the system diagnosis accuracy. Description of the Drawings

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0035] Figure 1Flowchart of an industrial system status monitoring method provided by this application;

[0036] Figure 2 Schematic diagram of a specific operation node diagnosis process provided by this application;

[0037] Figure 3 Schematic diagram of a specific controller status diagnosis process provided by this application;

[0038] Figure 4 Schematic diagram of a specific DCS system structure provided by this application;

[0039] Figure 5 Flowchart of a specific industrial system status monitoring method provided by this application;

[0040] Figure 6 Specific system status diagram provided by this application;

[0041] Figure 7 Schematic diagram of a specific controller failure provided by this application;

[0042] Figure 8 Schematic diagram of a specific operation node information provided by this application;

[0043] Figure 9 Schematic diagram of a specific IO module status provided by this application;

[0044] Figure 10 Schematic diagram of a specific controller status provided by this application;

[0045] Figure 11 Flowchart of a specific industrial system status monitoring method provided by this application;

[0046] Figure 12 Flowchart of a specific industrial system status monitoring method provided by this application;

[0047] Figure 13 Schematic diagram of the structure of an industrial system status monitoring device provided by this application;

[0048] Figure 14 Structure diagram of an electronic device provided by this application. Specific implementation mode

[0049] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0050] In the existing situation, if a fault occurs, a series of diagnostic errors or invalid diagnoses will occur in a chain, bringing extra work to the actual work of the operator, and it is impossible to accurately report the real fault source quickly based on the diagnostic results, thus affecting the detection efficiency. For this reason, the present application provides an industrial system status monitoring solution, which can directly reflect the root fault information point based on the determined system diagnostic diagram and quickly locate the position of the faulty device, improving the detection efficiency and the system diagnostic accuracy.

[0051] See Figure 1 As shown in the figure, an embodiment of the present invention discloses an industrial system status monitoring method, including:

[0052] Step S11: Detect the preset node diagnosis client by using a preset K-value clustering algorithm based on the first status data packet sent by the preset node diagnosis client through a preset node diagnosis server, obtain the corresponding first diagnosis result, and write the first diagnosis result into a preset real-time database.

[0053] Based on the DCS control system, this embodiment performs diagnosis through a preset K-value clustering algorithm, thereby improving the effectiveness of device diagnosis. The system adds operation node information and service information, and some system diagnosis points will be generated for each operation node during the compilation of the engineering management program as the preset node diagnosis client. There are two types of system diagnosis points, namely "SYSAM" and "DV". Among them, "SYSAM" is an analog quantity type diagnosis used to collect analog quantity data such as load and utilization rate, and "DV" is a digital quantity type diagnosis for the good and bad states of devices, such as the node network cable state, where red represents the fault state and green represents the network connection state.

[0054] Combined with Figure 2 As shown in the figure, the preset node diagnosis client sends a status request to all the other preset node diagnosis clients of the same type in the system, integrates its own status information, the status information of the other preset node diagnosis clients of the same type received, and the diagnosis information to obtain a first status data packet, and then sends the first status data packet to the preset node diagnosis server to enhance the reliability of the diagnosis. The specific information involved in the diagnosis process includes the corresponding operation node number, 128 network status, 129 network status, CPU load, memory utilization rate, and management network load, etc. Among them, when sending status data packets between the preset node diagnosis clients and between the preset node diagnosis client and the preset node diagnosis server, corresponding reception results are returned.

[0055] Furthermore, the preset node diagnosis server needs to train on the normal data set in the system network environment. Therefore, it is necessary to first reasonably process the valid data in the received first status data packet. The valid data includes the status information corresponding to the preset node diagnosis client, the status information of other preset node diagnosis clients of the same type, and the diagnosis information, which can reduce the error impact of the data itself. Then, the processed valid data is normalized to obtain the corresponding data to be detected, which can reduce data redundancy and reduce unnecessary impacts caused by different orders of magnitude. Then, the preset K-value clustering algorithm is used to analyze and calculate the data to be detected to obtain the corresponding detection data, that is, the first diagnosis K-value. After that, it is judged that the difference between the first diagnosis K-value and the first preset K-value will be greater than the first preset threshold. If so, it indicates that a fault has occurred in the system device, and the corresponding node status information is determined to obtain the corresponding first diagnosis result. Finally, the diagnosis result is sent to the preset real-time database, and the preset real-time database writes the first diagnosis result into the cache data of the corresponding operation node. The OPS (Operator Service System) further displays the node status of all operation nodes on the human-computer interaction interface through the diagnosis information read from the preset real-time database. Among them, the first preset K-value and the first preset threshold can be configured by the system based on the device attribute information or by relevant staff.

[0056] It should be understood that the preset real-time database and the preset node diagnosis server are both located in the historical station in the system. The operation node sends a diagnosis data request to the preset real-time database on the historical station in the 128-network and 129-network cycles respectively according to the preset data acquisition period. And when the preset real-time database does not receive the data packet containing the first diagnosis result sent by the preset node diagnosis server within the preset time period, it is determined that the preset node diagnosis client is faulty. Among them, it can be understood that the preset time period can be configured by the system by default or by relevant operators. And the preset time period can be multiple consecutive preset data acquisition cycles.

[0057] Step S12: Detect the preset controller through the IO / P2P master service and the IO / P2P slave service based on the second status data packet sent by the preset controller and the preset K-value clustering algorithm, obtain the corresponding second diagnosis result, and write the second diagnosis result into the main server memory.

[0058] Specifically, the P2P (peer-to-peer) service or IO (Input Output) service sends a status request to the controller under different communication conditions (P2P direct communication, IO indirect communication) and receives the status packet data returned by the controller. Combining Figure 3 As shown, different from node diagnosis, at this time, redundant services are used to collect status data of the controller and the corresponding modules respectively to increase the diagnostic strength of the hardware device control system. The IO / P2P main service and the IO / P2P slave service analyze and calculate the controller status data and the corresponding module status data in the second status data packet based on the preset K-value clustering algorithm to obtain the corresponding second diagnostic K-value, and then determine whether the difference between the second diagnostic K-value and the second preset K-value is greater than the second preset threshold. Based on the judgment result, the corresponding controller status information is determined to obtain the corresponding second diagnostic result, and the second diagnostic result is written into the main server memory. It can be understood that if so, it indicates that the device has a fault, and the corresponding controller status information is determined to obtain the corresponding second diagnostic result. After that, the OPS requests the controller status information from the IO / P2P main service for corresponding interface display.

[0059] Step S13: Determine whether there is a change in the current system device configuration. If so, trigger the corresponding diagnostic diagram drawing operation based on the first diagnostic result and the second diagnostic result, and send the determined system diagnostic diagram to the operation node so that the operator can obtain the system diagnostic diagram through the preset human-computer interaction interface for corresponding monitoring operations.

[0060] In this embodiment, the system diagnostic diagram is divided into three layers for display in a nested manner, including the system status diagram, the module status diagram, and the channel status diagram. In this way, the classification is clear and progressive, making monitoring more convenient. It should be understood that the system diagnostic diagram is automatically generated as the system configuration changes, without spending a lot of time and manpower in the early engineering configuration, and the display effect is exactly the same as the actual on-site environment layout. When a certain detection point fails, the specific damage status display and the device location can be determined by viewing the system diagnostic diagram, quickly finding the fault source, and reducing the impact of system faults on the production environment.

[0061] Specifically, the system diagnostic diagram generated by the human-machine interface is implemented by MakeSysDev.js written in JavaScript language by the corresponding engineering management software. MakeIOdev.js consists of three parts: a drawing script, a flowchart, and symbols. Among them, the flowchart is the basis for the human-machine interface display. The drawing script is the interface layout and drawing process of the human-machine interface. The symbols are the symbols abstracted from each component in the system. Each symbol abstracts the information to be diagnosed in the system into a lamp color state or text display. Combined with Figure 4 In the shown drawing process, the engineering management software first calls a preset image drawing script to create a canvas, and then determines whether there is a change in the current system device configuration. If so, it obtains the corresponding system device information and triggers the corresponding diagnostic diagram drawing operation based on the first diagnostic result and the second diagnostic result. The system device information includes device status information and device parameter information. It can be understood that the device status information includes the first diagnostic result and the second diagnostic result. Then, based on the system device information, a corresponding number of system symbols are determined and added, and the corresponding device parameter information is set to the number of system symbols. Then, according to the preset image drawing script, the positions of the number of system symbols are moved to be the same as the actual configuration layout. Based on the preset image drawing script, the system device information, and the number of system symbols, corresponding diagnostic diagram drawing operations are performed on the canvas to obtain the corresponding system diagnostic diagram. The display effect of the system diagnostic diagram is the same as the actual system layout, which is convenient for quickly finding faulty devices. And the way of drawing the picture is written in JavaScript language, separated from the business. Different diagrams only need to maintain two parts: the "drawing script" and the "system symbols", which is conducive to business expansion and program platformization. The display style of the system diagnostic diagram can be customized based on the requirements of different industrial control systems. And because of using the symbol method, the configuration is simple and convenient for device expansion.

[0062] It can be further understood that based on Figure 5 the shown DCS system structure diagram, the system diagnostic diagram shown in Figures 6 to 10 can be obtained. Among them, Figure 6 is the system state diagram, which shows the running state of the devices in the current system architecture layer. Among them, the node information and running state of the operator station, engineer station, and historical station can be viewed. Red indicates that the program has not been started, and green indicates that the program has been running. The status of the services provided by the historical station to each node can be intuitively viewed. Green represents the host, yellow represents the slave, and red indicates that the service has failed. The running state of the main control unit and the controller running load lamp. Figure 7It is a diagram of controller failure instances. When a device in the controller has a fault, a red light will flash in the controller to indicate the alarm status. All devices in the system are connected to the corresponding network status. Each device is connected to the bus, namely the 128 network and the 129 network respectively. The color of the connection line indicates the communication status of the device in the network. Green indicates normal communication, and red indicates communication failure. Figure 8 It is a schematic diagram of operation node information. This interface will pop up when the operation node is clicked. Figure 9 It is a schematic diagram of the IO module status. When the controller, including the main cabinet and all expansion cabinets, is clicked in the system status diagram, the running status of all IO cards and power supplies in the control cabinet as shown in Figure 9 will pop up. It can display the cabinet temperature (range: -20 to 60 °C), the running status of the main controller, the diagnostic information of the main controller, the running status of the IO-BUS module, the running status of the cabinet power supply, the detailed description information and running status of the IO module. Clicking on the controller icon can pop up the schematic diagram of the controller status as shown in Figure 10 to obtain an enlarged window of the main controller panel, where the running, redundant, and engineering status information can be viewed, and different colors are used to represent the current status of the device.

[0063] It can be seen that in the embodiment of the present application, the preset node diagnosis server detects the preset node diagnosis client based on the first status data packet sent by the preset node diagnosis client and uses the preset K-value clustering algorithm to obtain the corresponding first diagnosis result and write the first diagnosis result into the preset real-time database; the IO / P2P main service and the IO / P2P slave service detect the preset controller based on the second status data packet sent by the preset controller and the preset K-value clustering algorithm to obtain the corresponding second diagnosis result and write the second diagnosis result into the main server memory; it is judged whether there is a change in the current system device configuration. If so, the corresponding diagnostic diagram drawing operation is triggered based on the first diagnosis result and the second diagnosis result, and the determined system diagnostic diagram is sent to the operation node so that the operator can obtain the system diagnostic diagram through the preset human-computer interaction interface for corresponding monitoring operations. This embodiment uses the preset K-value clustering algorithm for detection and automatically executes the corresponding diagnostic diagram drawing operation when the system device configuration changes, which can directly reflect the root cause fault information point based on the determined system diagnostic diagram and quickly locate the position of the faulty device, improving the detection efficiency and the system diagnosis accuracy.

[0064] As can be seen from the previous embodiment, the present application performs corresponding node status diagnosis and controller status diagnosis and sends the system diagnostic diagram determined based on the diagnosis result to the operation node for monitoring. Therefore, this embodiment will next describe the process of node status diagnosis in detail. See Figure 11As shown in the figure, an embodiment of the present invention discloses an industrial system status monitoring method, including:

[0065] Step S21: Process the valid data in the first status data packet through a preset node diagnosis server; the valid data includes status information corresponding to a preset node diagnosis client, status information of other preset node diagnosis clients of the same type, and diagnosis information.

[0066] Step S22: Normalize the processed valid data based on a preset data normalization rule to obtain corresponding data to be detected, and analyze and calculate the data to be detected using a preset K - value clustering algorithm to obtain a corresponding first diagnosis K - value.

[0067] Step S23: Determine whether the difference between the first diagnosis K - value and a first preset K - value is greater than a first preset threshold, and determine corresponding node status information based on the judgment result to obtain a corresponding first diagnosis result.

[0068] Among them, the specific processes of the above - mentioned steps S21 to S23 can refer to the corresponding content disclosed in the foregoing embodiments and will not be elaborated here.

[0069] It can be seen that in the embodiment of the present application, the valid data in the first status data packet is processed through a preset node diagnosis server; the valid data includes status information corresponding to a preset node diagnosis client, status information of other preset node diagnosis clients of the same type, and diagnosis information. The processed valid data is normalized based on a preset data normalization rule to obtain corresponding data to be detected, and the data to be detected is analyzed and calculated using a preset K - value clustering algorithm to obtain a corresponding first diagnosis K - value. Determine whether the difference between the first diagnosis K - value and a first preset K - value is greater than a first preset threshold, and determine corresponding node status information based on the judgment result to obtain a corresponding first diagnosis result. Through the preset node diagnosis server, the corresponding node status diagnosis is performed by using the preset K - value clustering algorithm and the received first status data packet, thereby improving the node detection efficiency and diagnosis accuracy.

[0070] As can be seen from the foregoing embodiments, the present application performs corresponding node status diagnosis and controller status diagnosis, and sends the system diagnosis diagram determined based on the diagnosis result to the operation node for monitoring. Therefore, the process of controller status diagnosis will be described in detail in this embodiment. Refer to Figure 12 As shown in the figure, an embodiment of the present invention discloses an industrial system status monitoring method, including:

[0071] Step S31: Analyze and calculate the controller status data and the corresponding module status data in the second status data packet through the IO / P2P master service and the IO / P2P slave service based on the preset K - value clustering algorithm to obtain the corresponding second diagnostic K - value.

[0072] Step S32: Determine whether the difference between the second diagnostic K - value and the second preset K - value is greater than the second preset threshold, and determine the corresponding controller status information based on the judgment result to obtain the corresponding second diagnostic result.

[0073] Among them, for the specific processes of the above - mentioned Step S31 and Step S32, reference can be made to the corresponding content disclosed in the foregoing embodiments, and details will not be elaborated here.

[0074] It can be seen that in the embodiment of the present application, the IO / P2P master service and the IO / P2P slave service analyze and calculate the controller status data and the corresponding module status data in the second status data packet based on the preset K - value clustering algorithm to obtain the corresponding second diagnostic K - value. Determine whether the difference between the second diagnostic K - value and the second preset K - value is greater than the second preset threshold, and determine the corresponding controller status information based on the judgment result to obtain the corresponding second diagnostic result. Through the IO / P2P master service and the IO / P2P slave service, based on the preset K - value clustering algorithm and the received second status data packet, the status diagnosis of the corresponding controller and related modules is performed, thereby improving the controller diagnosis efficiency.

[0075] See Figure 13 As shown, the embodiment of the present application also correspondingly discloses an industrial system status monitoring device, including:

[0076] The first - status diagnosis module 11 is configured to detect the preset node diagnosis client through the preset node diagnosis server based on the first status data packet sent by the preset node diagnosis client and using the preset K - value clustering algorithm, obtain the corresponding first diagnostic result, and write the first diagnostic result into the preset real - time database;

[0077] The second - status diagnosis module 12 is configured to detect the preset controller through the IO / P2P master service and the IO / P2P slave service based on the second status data packet sent by the preset controller and the preset K - value clustering algorithm, obtain the corresponding second diagnostic result, and write the second diagnostic result into the main server memory;

[0078] The monitoring operation execution module 13 is used to determine whether there is a change in the current system device configuration. If so, it triggers corresponding diagnostic graph drawing operations based on the first diagnostic result and the second diagnostic result, and sends the determined system diagnostic graph to the operation node so that the operator can obtain the system diagnostic graph through a preset human-computer interaction interface for corresponding monitoring operations.

[0079] Among them, for the more specific working processes of the above-mentioned various modules, reference can be made to the corresponding content disclosed in the foregoing embodiments, and details will not be elaborated herein.

[0080] Thus, in this application, the preset node diagnosis server detects the preset node diagnosis client based on the first status data packet sent by the preset node diagnosis client and uses the preset K-value clustering algorithm to obtain the corresponding first diagnostic result and write the first diagnostic result into the preset real-time database; the IO / P2P master service and the IO / P2P slave service detect the preset controller based on the second status data packet sent by the preset controller and the preset K-value clustering algorithm to obtain the corresponding second diagnostic result and write the second diagnostic result into the main server memory; determine whether there is a change in the current system device configuration. If so, trigger corresponding diagnostic graph drawing operations based on the first diagnostic result and the second diagnostic result, and send the determined system diagnostic graph to the operation node so that the operator can obtain the system diagnostic graph through a preset human-computer interaction interface for corresponding monitoring operations. This application uses the preset K-value clustering algorithm for detection and automatically executes corresponding diagnostic graph drawing operations when the system device configuration changes, can directly reflect the root cause fault information points based on the determined system diagnostic graph and quickly locate the fault device position, improving the detection efficiency and the system diagnosis accuracy.

[0081] In some specific embodiments, the industrial system status monitoring may specifically further include:

[0082] The preset node diagnosis client configuration unit is used to configure corresponding system diagnosis points for each operation node to obtain a number of preset node diagnosis clients; wherein, the system diagnosis points include analog quantity type diagnosis points and switch quantity type diagnosis points.

[0083] In some specific embodiments, the first status diagnosis module 11 may specifically include:

[0084] The data processing unit is used to process the valid data in the first status data packet through the preset node diagnosis server; the valid data includes status information corresponding to the preset node diagnosis client, status information of other preset node diagnosis clients of the same type, and diagnostic information.

[0085] A first data calculation unit, configured to normalize the processed valid data based on a preset data normalization rule to obtain corresponding data to be detected, and analyze and calculate the data to be detected by using a preset K-value clustering algorithm to obtain a corresponding first diagnostic K-value;

[0086] A first result determination unit, configured to determine whether a difference between the first diagnostic K-value and a first preset K-value is greater than a first preset threshold, and determine corresponding node status information based on the determination result to obtain a corresponding first diagnostic result.

[0087] In some specific embodiments, the industrial system status monitoring may specifically further include:

[0088] A diagnostic result acquisition unit, configured to send diagnostic result requests to the preset real-time database through a 128 network and a 129 network respectively by each operation node according to a preset data acquisition period, so as to obtain the node status information corresponding to all operation nodes.

[0089] In some specific embodiments, the industrial system status monitoring may specifically further include:

[0090] A fault determination unit, configured to determine that the preset node diagnostic client is faulty when the preset real-time database does not receive a data packet containing the first diagnostic result sent by the preset node diagnostic server within a preset time period.

[0091] In some specific embodiments, the second status diagnosis module 12 may specifically include:

[0092] A second data calculation unit, configured to analyze and calculate the controller status data and corresponding module status data in the second status data packet through an IO / P2P master service and an IO / P2P slave service based on the preset K-value clustering algorithm to obtain a corresponding second diagnostic K-value;

[0093] A second result determination unit, configured to determine whether a difference between the second diagnostic K-value and a second preset K-value is greater than a second preset threshold, and determine corresponding controller status information based on the determination result to obtain a corresponding second diagnostic result.

[0094] In some specific embodiments, the monitoring operation execution module 13 may specifically include:

[0095] A canvas creation unit, configured to create a canvas by calling a preset image drawing script;

[0096] A symbol determination unit, configured to obtain corresponding system device information when there is a change in the system device configuration, and determine a corresponding number of system symbols based on the system device information; the system device information includes device status information and device parameter information.

[0097] A diagnostic graph drawing unit, configured to perform corresponding diagnostic graph drawing operations on the canvas based on the preset image drawing script, the system device information, and the several system symbols.

[0098] Furthermore, an embodiment of the present application also discloses an electronic device. Figure 14 It is a structural diagram of an electronic device 20 shown according to an exemplary embodiment, and the content in the figure should not be regarded as any limitation on the scope of use of the present application.

[0099] Figure 14 This is a schematic structural diagram of an electronic device 20 provided by an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. Among them, the memory 22 is used to store a computer program, and the computer program is loaded and executed by the processor 21 to implement the relevant steps in the industrial system status monitoring method disclosed in any of the foregoing embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0100] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows is any communication protocol applicable to the technical solution of the present application, and specific limitations are not imposed on it here; the input / output interface 25 is used to obtain external input data or output data to the outside, and its specific interface type can be selected according to specific application needs, and specific limitations are not made here.

[0101] In addition, as a carrier for resource storage, the memory 22 may be a read-only memory, a random access memory, a disk, or an optical disc, etc., and the resources stored thereon may include an operating system 221, a computer program 222, etc., and the storage method may be short-term storage or permanent storage.

[0102] Among them, the operating system 221 is used to manage and control each hardware device and the computer program 222 on the electronic device 20, and it may be Windows Server, Netware, Unix, Linux, etc. In addition to the computer program that can be used to complete the industrial system status monitoring method executed by the electronic device 20 disclosed in any of the foregoing embodiments, the computer program 222 may further include computer programs that can be used to complete other specific tasks.

[0103] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program. When the computer program is executed by a processor, it implements the industrial system status monitoring method disclosed above. For the specific steps of this method, reference may be made to the corresponding content disclosed in the foregoing embodiments, and details are not described herein again.

[0104] In the present specification, the various embodiments are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same or similar parts among the various embodiments, reference may be made to each other. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple. For related parts, reference may be made to the description in the method section.

[0105] Those skilled in the art can further realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed in this document can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the composition and steps of the examples have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0106] The steps of the methods or algorithms described in combination with the embodiments disclosed in this document can be directly implemented by hardware, software modules executed by a processor, or a combination of the two. The software modules can be placed in a random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium well-known in the technical field.

[0107] Finally, it should also be noted that 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. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising a..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the element.

[0108] The above has introduced the technical solution provided by this application in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. An industrial system status monitoring method, characterized in that, Including: The preset node diagnosis server diagnoses the first status data packet sent by the preset node diagnosis client and uses the preset K - value clustering algorithm to detect the preset node diagnosis client, obtains the corresponding first diagnosis result, and writes the first diagnosis result into the preset real - time database; The IO / P2P master service and the IO / P2P slave service detect the preset controller based on the second status data packet sent by the preset controller and the preset K - value clustering algorithm, obtain the corresponding second diagnosis result, and write the second diagnosis result into the main server memory; the P2P service in the IO / P2P master service and the IO / P2P slave service requests status data in a direct communication manner, and the IO service requests status data in an indirect communication manner; Judge whether there is a change in the current system device configuration. If so, trigger the corresponding diagnostic diagram drawing operation based on the first diagnosis result and the second diagnosis result, and send the determined system diagnostic diagram to the operation node so that the operator can obtain the system diagnostic diagram through the preset human - machine interaction interface for corresponding monitoring operations; the system diagnostic diagram is divided into three layers for display in a nested manner, including a system status diagram, a module status diagram, and a channel status diagram; The process that the preset node diagnosis server diagnoses the preset node diagnosis client based on the first status data packet sent by the preset node diagnosis client and uses the preset K - value clustering algorithm to obtain the corresponding first diagnosis result includes: The preset node diagnosis server processes the valid data in the first status data packet; the valid data includes the status information corresponding to the preset node diagnosis client, the status information of other preset node diagnosis clients of the same type, and diagnostic information; Normalize the processed valid data based on the preset data normalization rule to obtain the corresponding data to be detected, and use the preset K - value clustering algorithm to analyze and calculate the data to be detected to obtain the corresponding first diagnosis K - value; Judge whether the difference between the first diagnosis K - value and the first preset K - value is greater than the first preset threshold, and determine the corresponding node status information based on the judgment result to obtain the corresponding first diagnosis result; After the preset node diagnosis server writes the first diagnosis result into the preset real - time database, it further includes: Each operation node sends a diagnosis result request to the preset real - time database through the 128 network and the 129 network respectively according to the preset data acquisition period to obtain the node status information corresponding to all operation nodes.

2. The industrial system status monitoring method according to claim 1, characterized in that Before the preset node diagnosis server diagnoses the preset node diagnosis client based on the first status data packet sent by the preset node diagnosis client and uses the preset K - value clustering algorithm, it further includes: Configure corresponding system diagnosis points for each operation node to obtain a number of preset node diagnosis clients; among them, the system diagnosis points include analog - quantity - type diagnosis points and digital - quantity - type diagnosis points.

3. The industrial system status monitoring method according to claim 1, characterized in that, After the preset node diagnosis server writes the first diagnosis result into the preset real - time database, it further includes: When the preset real-time database does not receive the data packet containing the first diagnosis result sent by the preset node diagnosis server within the preset time period, it is determined that the preset node diagnosis client is faulty.

4. The industrial system status monitoring method according to claim 1, wherein, The detection of the preset controller through the IO / P2P master service and the IO / P2P slave service based on the second status data packet sent by the preset controller and the preset K-value clustering algorithm to obtain the corresponding second diagnosis result includes: Analyzing and calculating the controller status data and the corresponding module status data in the second status data packet through the IO / P2P master service and the IO / P2P slave service based on the preset K-value clustering algorithm to obtain the corresponding second diagnosis K-value; Judging whether the difference between the second diagnosis K-value and the second preset K-value is greater than the second preset threshold, and determining the corresponding controller status information based on the judgment result to obtain the corresponding second diagnosis result.

5. The industrial system status monitoring method according to any one of claims 1 to 4, characterized in that Based on the first diagnosis result and the second diagnosis result, judging whether there is a change in the current system device configuration. If so, triggering the corresponding diagnostic graph drawing operation, including: Creating a new canvas by calling a preset image drawing script; When there is a change in the system device configuration, obtaining the corresponding system device information, and determining a corresponding number of system symbols based on the system device information; the system device information includes device status information and device parameter information; Performing the corresponding diagnostic graph drawing operation on the canvas based on the preset image drawing script, the system device information, and the several system symbols.

6. An industrial system status monitoring device, characterized in that, Including: A first status diagnosis module for detecting the preset node diagnosis client through the preset node diagnosis server based on the first status data packet sent by the preset node diagnosis client and using the preset K-value clustering algorithm, obtaining the corresponding first diagnosis result and writing the first diagnosis result into the preset real-time database; A second status diagnosis module for detecting the preset controller through the IO / P2P master service and the IO / P2P slave service based on the second status data packet sent by the preset controller and the preset K-value clustering algorithm, obtaining the corresponding second diagnosis result and writing the second diagnosis result into the main server memory; the P2P service in the IO / P2P master service and the IO / P2P slave service requests status data in a direct communication manner, and the IO service requests status data in an indirect communication manner; A monitoring operation execution module for judging whether there is a change in the current system device configuration. If so, triggering the corresponding diagnostic graph drawing operation based on the first diagnosis result and the second diagnosis result, and sending the determined system diagnostic graph to the operation node so that the operator can obtain the system diagnostic graph through the preset human-computer interaction interface for corresponding monitoring operations; The system diagnostic graph is divided into three layers for display in a nested manner, including a system status graph, a module status graph, and a channel status graph; The first status diagnosis module includes: A data processing unit for processing the valid data in the first status data packet through a preset node diagnosis server; the valid data includes status information corresponding to a preset node diagnosis client, status information of other preset node diagnosis clients of the same type, and diagnosis information; A first data calculation unit for normalizing the processed valid data based on a preset data normalization rule to obtain corresponding data to be detected, and analyzing and calculating the data to be detected by using a preset K-value clustering algorithm to obtain a corresponding first diagnosis K-value; A first result determination unit for determining whether the difference between the first diagnosis K-value and a first preset K-value is greater than a first preset threshold, and determining corresponding node status information based on the determination result to obtain a corresponding first diagnosis result; The industrial system status monitoring device further includes: A diagnosis result acquisition unit for sending diagnosis result requests to the preset real-time database through the 128 network and the 129 network respectively by each operation node according to a preset data acquisition period, so as to obtain the node status information corresponding to all operation nodes.

7. An electronic device, characterized in that, Including: A memory for storing a computer program; A processor for executing the computer program to implement the industrial system status monitoring method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, For storing a computer program, the computer program, when executed by a processor, implements the industrial system status monitoring method according to any one of claims 1 to 5.

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