CN116016601A - Situation awareness equipment-based operation data acquisition method, equipment and medium - Google Patents
Situation awareness equipment-based operation data acquisition method, equipment and medium Download PDFInfo
- Publication number
- CN116016601A CN116016601A CN202211732538.2A CN202211732538A CN116016601A CN 116016601 A CN116016601 A CN 116016601A CN 202211732538 A CN202211732538 A CN 202211732538A CN 116016601 A CN116016601 A CN 116016601A
- Authority
- CN
- China
- Prior art keywords
- operation data
- data acquisition
- equipment
- acquisition
- alarm
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Testing And Monitoring For Control Systems (AREA)
Abstract
The application relates to a situation awareness equipment-based operation data acquisition method, equipment and medium, comprising the following steps: s101, presetting operation data acquisition parameters based on operation data acquisition requirements of plant side equipment, wherein the operation data acquisition parameters comprise, but are not limited to: region, group, IP list, equipment type, acquisition frequency, time interval and operation data type; s102, generating a starting command of an operation data acquisition script based on the preset operation data acquisition parameters; s103, uploading the operation data acquisition script to the plant side equipment; s104, remotely starting the operation data acquisition script according to the starting command, and acquiring the operation data of the plant side equipment according to the received command by the operation data acquisition script. By decoupling the operation data acquisition reporting service from the application software, the range of the operation data acquisition target device is enlarged.
Description
Technical Field
The application relates to the technical field of industrial control safety, in particular to a situation awareness equipment-based operation data acquisition method, equipment and medium.
Background
The energy industry internet platform security situation awareness (hereinafter referred to as situation awareness) is an important component of the energy industry internet platform, and is a security situation awareness platform which is constructed by the national ministry of China and all energy groups together, so that situation awareness and traceability evidence collection of various network security of the energy industry internet are realized. The security situation awareness station side platform (hereinafter referred to as a station side platform) is a network security comprehensive detection system deployed at each energy group station, and is composed of special equipment such as a data acquisition device and a station level analysis platform, and general equipment such as a firewall, a switch and an encryption machine.
The station side platform bears the important role of station network data acquisition and network security situation analysis, and the running condition of station side platform equipment directly influences the decision effectiveness of situation awareness. Therefore, the operation state data of the station side platform equipment needs to be acquired and analyzed, the operation condition of the station side platform equipment can be analyzed, and the software and hardware of the equipment can be kept in an optimal working state at all times, so that the data can be analyzed and reported stably and accurately. The current plant side equipment collects part of operation data in an active collection and timing reporting mode, generally supports reporting of specified performance data in a syslog mode for general equipment such as switches, firewalls and encryptors, and generally installs data collection service and timing reporting service for special equipment such as a data collection device and a plant level analysis platform, synchronizes the operation data to a center side platform through the timing reporting service, and then analyzes and displays various operation data by a situation perception center side platform application.
In the prior art, the running state data is actively reported by the state sensing station side platform equipment through a data interface or syslog, and the reported data is processed and displayed by the state sensing center side platform, but the running state data acquisition reporting function is integrated in the application software of the state sensing system station side equipment, so that the coupling degree between the running state data acquisition reporting function and the application software is too high, and the modification and the expansion of the running state data acquisition capacity are not facilitated.
Disclosure of Invention
The application provides a situation awareness equipment-based operation data acquisition method, equipment and medium, which expand the range of operation data acquisition target equipment by decoupling operation data acquisition reporting service from application software.
In a first aspect, the present application provides a situation awareness apparatus-based operation data acquisition method, including the following steps: s101, presetting operation data acquisition parameters based on operation data acquisition requirements of plant side equipment, wherein the operation data acquisition parameters comprise, but are not limited to: region, group, IP list, equipment type, acquisition frequency, time interval and operation data type; s102, generating a starting command of an operation data acquisition script based on the preset operation data acquisition parameters; s103, uploading the operation data acquisition script to the plant side equipment; s104, remotely starting the operation data acquisition script according to the starting command, and acquiring the operation data of the plant side equipment according to the received command by the operation data acquisition script.
Preferably, the method further comprises the following steps: s105, the operation data acquisition script uploads an acquisition result to a data processing module of the center side platform according to the acquisition frequency in the operation data acquisition parameters; s106, the data processing module generates alarm information according to the acquisition result and the operation data alarm rule; wherein the operational data alert rules include operational data alert threshold rules and operational data alert trend rules, the operational data alert threshold rules including, but not limited to,: the operation value of the operation data is higher than the preset value for n times or lower than the preset value for n times; the operational data alert trend rules include, but are not limited to: the running value of the running data is continuously increased n times or continuously decreased n times or the increasing rate is higher than the preset value or the decreasing rate is lower than the preset value.
Preferably, the method further comprises the following steps: and S107, the data processing module generates an operation trend graph according to the acquisition result.
Preferably, the method further comprises the following steps: s108, pushing the generated alarm information to an alarm sending module of the center side platform and pushing the generated running trend graph to a report display module of the center side platform by the data processing module, wherein the alarm sending module sends the alarm information, and the report display module displays the running trend graph of the plant side equipment through a webpage.
Preferably, if the acquired result meets the operation data alarm threshold rule or the operation data alarm trend rule, JSON data is also generated; wherein attributes of the JSON data include, but are not limited to: alarm equipment IP, alarm rule type, alarm details.
Preferably, if the JSON data is received, the alarm sending module sends a notification in a way of email or short message WeChat.
Preferably, the step S102 includes: s1021, determining an acquisition range, if the acquisition range is a region or a group, searching out the IP of all the plant side equipment in a plant information database, and determining the IP of specific equipment according to the type of the plant side equipment to be monitored; if the IP list is the IP list of the station side equipment, storing the IP list under a local IP list file to provide inquiry; and S1022, splicing and starting commands according to the acquisition frequency, the time interval and the operation data types in the operation data acquisition parameters.
Preferably, the step S103 includes: and reading the local IP list file through a task scheduling module of the center side platform, traversing the IP in the local IP list file, and transmitting the operation data acquisition script to the appointed directory of the plant side equipment corresponding to the IP.
In a second aspect, the present application further provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the above method are implemented when the processor executes the computer program.
In a third aspect, a computer readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method described above.
The application has at least the following advantages:
according to the first aspect, an independent operation data acquisition script is transmitted to the plant side equipment, a starting command of the operation data acquisition script is generated through preset operation data acquisition parameters, the operation data acquisition script on the plant side equipment is started remotely, the operation data acquisition script can acquire corresponding operation data by utilizing commands, environments and the like of an operating system, and an acquisition function is not required to be integrated in application software of the plant side equipment; therefore, by decoupling the operation data acquisition reporting service from the application software, the range of the operation data acquisition target equipment is enlarged, customization of reporting requirements can be realized, and flexible expansion of operation data acquisition types and logics is realized;
in the second aspect, according to the threshold value of the operation data and the trend alarming rule, the operation data acquisition reporting service is decoupled from the application software, so that the system capability is correctly evaluated, the weakness of the equipment is timely identified, the tuning direction is indicated, the problems in the software are found, and the stability and the reliability are verified.
Drawings
FIG. 1 is a diagram showing an application environment for a situation awareness apparatus-based operation data collection method in one embodiment;
FIG. 2 is a flow chart showing a situation awareness apparatus-based operation data collection method according to an embodiment;
FIG. 3 is a flow chart showing the process of generating a start command for running the data acquisition script in step S102 according to one embodiment;
FIG. 4 is a trend chart showing the memory usage of the plant-side equipment during operation in one embodiment;
FIG. 5 is a trend graph showing CPC usage when plant-side equipment is running in one embodiment;
fig. 6 is a schematic structural diagram of a computer device in one embodiment.
Detailed Description
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the singular is "a," an, "and/or" the "when used in this specification is taken to mean" the presence of a feature, step, operation, device, component, and/or combination thereof.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the embodiments of the present application will be described in detail below with reference to the accompanying drawings. However, as will be appreciated by those of ordinary skill in the art, in the various embodiments of the present application, numerous technical details have been set forth in order to provide a better understanding of the present application. However, the technical solutions claimed in the present application can be implemented without these technical details and with various changes and modifications based on the following embodiments. The following embodiments are divided for convenience of description, and should not be construed as limiting the specific implementation of the present application, and the embodiments may be combined with each other and cited with each other without contradiction.
For ease of understanding, a system to which the present application is applicable will first be described. The situation awareness equipment-based operation data acquisition method can be applied to a system architecture shown in fig. 1. The system comprises: a user space file server 103 and a terminal device 101, the terminal device 101 communicating with the user space file server 103 via a network. The user space file server 103 may be a file server based on nfsv3\v4 protocol, and operates in Linux environment, while NFS (network file system) is a network abstraction above the file system, and may allow a remote client running on the terminal device 101 to access through the network in a similar manner as a local file system. The terminal device 101 may be, but not limited to, various personal computers, notebook computers, smartphones, tablet computers, etc., and the user space file server 103 may be implemented as a stand-alone server or a server cluster composed of a plurality of servers.
Fig. 2 is a flow chart of a situation awareness device-based data collection method, which is provided in an embodiment of the present application, and the method may be executed by a user space file server in the system shown in fig. 1. As shown in fig. 2, the method may include the steps of:
s101, presetting operation data acquisition parameters based on operation data acquisition requirements of plant side equipment, wherein the operation data acquisition parameters comprise, but are not limited to: region, group, IP list, equipment type, acquisition frequency, time interval and operation data type;
s102, generating a starting command of an operation data acquisition script based on the preset operation data acquisition parameters;
s103, uploading the operation data acquisition script to the plant side equipment;
s104, remotely starting the operation data acquisition script according to the starting command, and acquiring the operation data of the plant side equipment according to the received command by the operation data acquisition script.
According to the method, according to the operation data acquisition requirements of the plant side equipment, operation data acquisition parameters can be preset in advance, the preset operation data acquisition parameters comprise regions, groups, IP lists, equipment types, acquisition frequencies, time intervals, operation data types and the like, and starting commands of operation data acquisition scripts can be generated according to the preset operation data acquisition parameters, so that the operation data acquisition scripts on the plant side equipment can be remotely started by transmitting an independent acquisition script to the plant side equipment, the operation data acquisition scripts can utilize commands, environments and the like carried by an operating system, the acquisition of corresponding operation data can be realized, the acquisition functions are not required to be integrated in application software of the plant side equipment, the decoupling of operation data acquisition reporting service and the application software is realized, the range of the operation data acquisition target equipment is enlarged, and customization of reporting requirements and flexible expansion of the operation data acquisition types and logic can be realized.
Each step is specifically described in detail below:
as shown in fig. 2, S101, based on the operation data acquisition requirement of the plant side device, operation data acquisition parameters are preset, where the operation data acquisition parameters include, but are not limited to: region, group, IP list, equipment type, acquisition frequency, time interval and operation data type;
in this embodiment, it should be noted that, the operation data of the current plant side device may include hardware performance data, such as CPU, memory, disk occupancy rate, etc., when the device is operated; operating system and business application running state data such as file inode occupancy, database connection number, data processing throughput, application service running state, etc. can also be included. Therefore, in the embodiment of the present application, the user may preset the operation data acquisition parameters based on the operation data acquisition requirement of the plant side device, where the operation data acquisition parameters include, but are not limited to: region, group, IP list, equipment type, collection frequency, time interval, operation data type, etc., for example, when the collection frequency is preset, the data collection device in the station side platform can collect and report the operation data of the station side equipment according to the preset collection frequency.
As shown in fig. 2, S102, generating a start command of the operation data acquisition script based on a preset operation data acquisition parameter;
in this embodiment, it should be noted that, the task scheduling module in the center side platform is configured to generate a start command for running the data acquisition script, and the task scheduling module generates the start command for running the data acquisition script based on the running data acquisition parameters preset by the user.
After receiving preset operation data acquisition parameters, the task scheduling module generates a starting command as follows:
as shown in fig. 3, S1021, determining an acquisition range, if the acquisition range is a region or a group, retrieving the IP of all the plant side devices in the plant information database, and determining a specific device IP according to the type of the plant side device to be monitored; if the IP list is the IP list of the station side equipment, the IP list is stored under a local IP list file to provide inquiry.
In this embodiment, it should be noted that, first, there are a plurality of stations, and there are a plurality of different types of station side devices, such as a main platform, a standby platform, etc., where each station side device has a corresponding device IP, when a user defines an acquisition range, a certain device under a certain region or a certain group may be selected, at this time, the device IPs of all the station side devices under the region or the group selected by the user are first retrieved from a station information database, and then, a specific device IP is determined according to the device type of the station side device to be monitored. Or the user can also directly provide the IP list of the station side equipment and store the IP list under the local IP list file to provide the inquiry.
As shown in fig. 3, S1022 is executed according to the collection frequency, the time interval, and the operation data type in the operation data collection parameters.
In this embodiment, it should be noted that, after determining the device IP of the plant-station side device to be monitored, the task scheduling module in the center-side platform splices the start command according to the collection frequency, the time interval, the operation data type, and the like in the operation data collection parameter, where the start command is mainly used to remotely start the operation data collection script to perform data collection on the plant-station side device.
S103, uploading an operation data acquisition script to plant side equipment as shown in FIG. 2;
in this embodiment, it should be noted that, after generating a start command of an operation data acquisition script, the task scheduling module uploads the operation data acquisition script to the plant side device, and the main content is that the task scheduling module reads a local IP list file, traverses an IP therein, and transmits the operation data acquisition script to a designated directory of the plant side device corresponding to the IP through a scp (secure copy) command. Where the scp command is a command for securely copying files to and from the remote system to the local via the SSH protocol.
As shown in fig. 2, S104, a running data acquisition script is remotely started according to a start command, and the running data acquisition script acquires the running data of the plant side equipment according to the received command.
In this embodiment, it should be noted that, when the task scheduling module transmits the operation data acquisition script to the designated directory of the plant side device corresponding to the IP, the task scheduling module will remotely execute the start command generated in step S102, remotely start the operation data acquisition script through the start command, and acquire the operation data of the plant side device after the operation data acquisition script receives the command.
The task scheduling module executes ssh (Secure Shell) command by taking the start command of the operation data acquisition script generated in step S102 as a parameter, and remotely starts the operation data acquisition script transmitted to the plant side device.
In this embodiment, it should also be noted that, the running data acquisition script uses a generator mode, so that the running data acquisition result and the acquisition logic can be separated, so as to implement finer control over the data acquisition process, and further improve the flexible expansion capability of the running data acquisition variety and the acquisition logic. The operation data acquisition script comprises four modules, an operation data module, a constructor module, a recorder module and a starting module, wherein the operation data module is used for defining and storing different types of operation data of the plant station side equipment. The constructor module is used for outputting according to the command to be analyzed, and calculating or extracting real operation data. The recorder module is used for recording Info types generated by the directors and uploading the acquisition results to the data processing module of the center side platform according to the acquisition frequency. The starting module is responsible for starting to collect the operation data of the plant side equipment, and mainly starts to collect the operation data according to the collection frequency, the time interval, the operation data type parameters and the like preset in the step S101.
As shown in fig. 2, the collecting method in this embodiment further includes: s105, uploading a collection result to a data processing module of the center side platform according to the collection frequency in the operation data collection parameters by the operation data collection script;
s106, the data processing module generates alarm information according to the acquisition result and the operation data alarm rule; wherein the operational data alert rules include operational data alert threshold rules and operational data alert trend rules, the operational data alert threshold rules including, but not limited to,: the operation value of the operation data is higher than the preset value for n times or lower than the preset value for n times; operational data alert trend rules include, but are not limited to: the running value of the running data is continuously increased n times or continuously decreased n times or the increasing rate is higher than the preset value or the decreasing rate is lower than the preset value.
In this embodiment, it should be noted that, the operation data acquisition script performs data acquisition according to the acquisition frequency in the preset operation data parameters and uploads the acquisition result to the data processing module of the center side platform at the same time, that is, the operation data acquisition script executes rsync command at regular time according to the acquisition frequency preset in step S101, and uploads the acquisition result file stored in the designated directory of the plant side device to the data processing module.
After receiving the acquisition result, the data processing module matches the uploaded acquisition result according to the operation data alarming rule and generates self-defined alarming information; wherein the operational data alert rules include operational data alert threshold rules and operational data alert trend rules, the operational data alert threshold rules including, but not limited to,: the operation value of the operation data is higher than the preset value n times or lower than the preset value n times. For example, if the CPU usage is higher than 90% three times in succession, one skilled in the art can define different thresholds according to various types of data, and the embodiment is not limited in particular. Operational data alert trend rules include, but are not limited to: the running value of the running data is continuously increased n times or continuously decreased n times or the increasing rate is higher than the preset value or the decreasing rate is lower than the preset value. For example, the number of database connections is continuously increased ten times, and one skilled in the art may define different trend rules according to various types of data, which is not limited in this embodiment.
As shown in fig. 2, further includes: and S107, the data processing module generates an operation trend chart according to the acquisition result.
In this embodiment, it should be noted that, the data processing module generates an operation data trend graph according to the collection result, where the generation mode of the operation data trend graph is as follows: and generating html codes of the operation data trend graph of the plant side equipment through pyechorts according to the operation data of the designated catalogue reported to the plant side equipment in the step S104.
In this embodiment, it should be further noted that if the operation data alarm threshold rule or the operation data alarm trend rule is triggered, a piece of JSON (JavaScriptObject Notation) data is further generated, where attributes of JSON data include, but are not limited to: the alarm equipment IP, the alarm rule type, the alarm details and the like, wherein the alarm details are threshold value/trend rule, actual value/actual trend.
As shown in fig. 2, further includes: s108, the data processing module pushes the generated alarm information to an alarm sending module of the center side platform and pushes the generated running trend graph to a report display module of the center side platform, the alarm sending module sends the alarm information, and the report display module displays the running trend graph of the plant side equipment through a webpage.
In this embodiment, it should be noted that, the data processing module pushes the generated alarm information to the alarm sending module of the center side platform, and the alarm sending module sends the alarm information in multiple modes; if the JSON data sent in step S107 is received, notification is also performed by means of email, short message, weChat, etc.
The data processing module pushes the generated operation data trend graph to a report display module of the center side platform, the report display module displays the operation data trend graph of the plant side equipment through a Web page, and according to the html code of the operation data trend graph of the plant side equipment generated in the step S107, a webpage frame is written by using a compact technology, and the html code of the operation data trend graph is introduced and displayed. The reaction technology is mainly used for constructing a User Interface (UI). A trend graph showing memory usage is shown in fig. 4, at 2022-11-29T01:13: the memory consumption occupied at 50 is 17424MB; as shown in fig. 5, which is a trend of CPU usage, at 2022-11-29T02:40: at 52, the CPU utilization was 33.38%.
Therefore, the real-time performance of the discovery of the operation problems is improved through the operation data alarm threshold and the alarm trend rule, and the accuracy of the positioning of the operation problems by the service personnel is improved through the centralized display of the operation data trend graph.
According to embodiments of the present application, there is also provided a computer device, a computer-readable storage medium.
As shown in fig. 6, is a block diagram of a computer device according to an embodiment of the present application. Computer equipment is intended to represent various forms of digital computers or mobile devices. Wherein the digital computer may comprise a desktop computer, a portable computer, a workstation, a personal digital assistant, a server, a mainframe computer, and other suitable computers. The mobile device may include a tablet, a smart phone, a wearable device, etc.
As shown in fig. 6, the apparatus 600 includes a computing unit 601, a ROM 602, a RAM 603, a bus 604, and an input/output (I/O) interface 605, and the computing unit 601, the ROM 602, and the RAM 603 are connected to each other through the bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The computing unit 601 may perform various processes in the method embodiments of the present application according to computer instructions stored in a Read Only Memory (ROM) 602 or computer instructions loaded from a storage unit 608 into a Random Access Memory (RAM) 603. The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. The computing unit 601 may include, but is not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), as well as any suitable processor, controller, microcontroller, etc. In some embodiments, the methods provided by embodiments of the present application may be implemented as a computer software program tangibly embodied on a computer-readable storage medium, such as storage unit 608.
The RAM 603 may also store various programs and data required for operation of the device 600. Part or all of the computer program may be loaded and/or installed onto the device 600 via the ROM 602 and/or the communication unit 609.
An input unit 606, an output unit 607, a storage unit 608, and a communication unit 609 in the device 600 may be connected to the I/O interface 605. Wherein the input unit 606 may be such as a keyboard, mouse, touch screen, microphone, etc.; the output unit 607 may be, for example, a display, a speaker, an indicator light, or the like. The device 600 is capable of exchanging information, data, etc. with other devices through the communication unit 609.
It should be noted that the device may also include other components necessary to achieve proper operation. It may also include only the components necessary to implement the present application, and not necessarily all the components shown in the figures.
Various implementations of the systems and techniques described here can be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof.
Computer instructions for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer instructions may be provided to a computing unit 601 such that the computer instructions, when executed by the computing unit 601, such as a processor, cause the steps involved in the method embodiments of the present application to be performed.
The computer readable storage medium provided herein may be a tangible medium that may contain, or store, computer instructions for performing the steps involved in the method embodiments of the present application. The computer readable storage medium may include, but is not limited to, storage media in the form of electronic, magnetic, optical, electromagnetic, and the like.
The above embodiments do not limit the scope of the application. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application are intended to be included within the scope of the present application.
Claims (10)
1. The situation awareness equipment-based operation data acquisition method is characterized by comprising the following steps of:
s101, presetting operation data acquisition parameters based on operation data acquisition requirements of plant side equipment, wherein the operation data acquisition parameters comprise, but are not limited to: region, group, IP list, equipment type, acquisition frequency, time interval and operation data type;
s102, generating a starting command of an operation data acquisition script based on the preset operation data acquisition parameters;
s103, uploading the operation data acquisition script to the plant side equipment;
s104, remotely starting the operation data acquisition script according to the starting command, and acquiring the operation data of the plant side equipment according to the received command by the operation data acquisition script.
2. The situation awareness equipment-based operational data collection method of claim 1 further comprising the steps of:
s105, the operation data acquisition script uploads an acquisition result to a data processing module of the center side platform according to the acquisition frequency in the operation data acquisition parameters;
s106, the data processing module generates alarm information according to the acquisition result and the operation data alarm rule; wherein the operational data alert rules include operational data alert threshold rules and operational data alert trend rules, the operational data alert threshold rules including, but not limited to,: the operation value of the operation data is higher than the preset value for n times or lower than the preset value for n times; the operational data alert trend rules include, but are not limited to: the running value of the running data is continuously increased n times or continuously decreased n times or the increasing rate is higher than the preset value or the decreasing rate is lower than the preset value.
3. The situation awareness equipment-based operational data collection method of claim 2 further comprising the steps of:
and S107, the data processing module generates an operation trend graph according to the acquisition result.
4. The situation awareness equipment-based operational data collection method of claim 3 further comprising the steps of:
s108, pushing the generated alarm information to an alarm sending module of the center side platform and pushing the generated running trend graph to a report display module of the center side platform by the data processing module, wherein the alarm sending module sends the alarm information, and the report display module displays the running trend graph of the plant side equipment through a webpage.
5. The situation awareness equipment-based operation data acquisition method according to claim 4, wherein if an acquisition result meets the operation data alarm threshold rule or the operation data alarm trend rule, JSON data is also generated; wherein attributes of the JSON data include, but are not limited to: alarm equipment IP, alarm rule type, alarm details.
6. The situation awareness equipment-based operation data collection method according to claim 5, wherein the alert sending module sends the notification by way of email or short message WeChat if receiving the JSON data.
7. The situation awareness equipment-based operation data collection method according to any one of claims 1 to 6, wherein the step S102 includes:
s1021, determining an acquisition range, if the acquisition range is a region or a group, searching out the IP of all the plant side equipment in a plant information database, and determining the IP of specific equipment according to the type of the plant side equipment to be monitored; if the IP list is the IP list of the station side equipment, storing the IP list under a local IP list file to provide inquiry;
and S1022, splicing and starting commands according to the acquisition frequency, the time interval and the operation data types in the operation data acquisition parameters.
8. The situation awareness equipment-based operation data collection method according to claim 7, wherein the step S103 includes:
and reading the local IP list file through a task scheduling module of the center side platform, traversing the IP in the local IP list file, and transmitting the operation data acquisition script to the appointed directory of the plant side equipment corresponding to the IP.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 8 when the computer program is executed by the processor.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211732538.2A CN116016601A (en) | 2022-12-30 | 2022-12-30 | Situation awareness equipment-based operation data acquisition method, equipment and medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211732538.2A CN116016601A (en) | 2022-12-30 | 2022-12-30 | Situation awareness equipment-based operation data acquisition method, equipment and medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116016601A true CN116016601A (en) | 2023-04-25 |
Family
ID=86035135
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211732538.2A Pending CN116016601A (en) | 2022-12-30 | 2022-12-30 | Situation awareness equipment-based operation data acquisition method, equipment and medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116016601A (en) |
-
2022
- 2022-12-30 CN CN202211732538.2A patent/CN116016601A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10210036B2 (en) | Time series metric data modeling and prediction | |
| CN110574338B (en) | Root cause discovery method and system | |
| EP3373552A1 (en) | Multi-modal, multi-disciplinary feature discovery to detect cyber threats in electric power grid | |
| US10706229B2 (en) | Content aware heterogeneous log pattern comparative analysis engine | |
| CN111800443B (en) | Data processing system and method, device and electronic equipment | |
| CN112311617A (en) | Configured data monitoring and alarming method and system | |
| CN111352800A (en) | Big data cluster monitoring method and related equipment | |
| US10591970B2 (en) | Industrial asset management systems and methods thereof | |
| CN113112038B (en) | Intelligent monitoring and diagnostic analysis system, device, electronic equipment and storage medium | |
| JP2022033685A (en) | Method, apparatus, electronic device, computer readable storage medium and computer program for determining robustness | |
| US20190258725A1 (en) | Service regression detection using real-time anomaly detection of log data | |
| US20190197432A9 (en) | Automated meta parameter search for invariant based anomaly detectors in log analytics | |
| CN114091704A (en) | Alarm suppression method and device | |
| CN113742174A (en) | Cloud mobile phone application monitoring method and device, electronic equipment and storage medium | |
| CN116016601A (en) | Situation awareness equipment-based operation data acquisition method, equipment and medium | |
| CN111130882A (en) | Monitoring system and method of network equipment | |
| CN114756301B (en) | Log processing method, device and system | |
| CN114490560A (en) | Full-boundary power network data analysis method based on artificial intelligence technology | |
| CN108829563B (en) | Alarm method and alarm device | |
| CN113590447A (en) | Buried point processing method and device | |
| CN117632660B (en) | Application detection method, device, electronic equipment and computer readable medium | |
| US11797388B1 (en) | Systems and methods for lossless network restoration and syncing | |
| CN112948341B (en) | Method and apparatus for identifying anomalous network device logs | |
| CN114584455B (en) | Small and medium-sized high-performance cluster monitoring system based on enterprise WeChat | |
| CN114006801A (en) | Method and device for sending dynamic template, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication |