Equipment monitoring method and device, computer equipment, storage medium and program product

Abstract

The invention discloses an equipment monitoring method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: setting burying points in a data acquisition system of equipment; acquiring burying point data of the data acquisition system through the burying point; and monitoring the burying point data to obtain a monitoring result. The buried point is arranged in the data acquisition system in the power system, so that buried point data during operation of the data acquisition system is acquired through the buried point, and acquisition of various data (such as acquired power consumption data, operation data of the data acquisition system and the like) of the data acquisition system is realized; the whole operation process of the data acquisition system can be monitored through the burying point data, so that the abnormality of the power consumption data acquired by the data acquisition system, the abnormality of equipment connected with the data acquisition system and the like can be found in time, and various abnormalities influencing the power consumption data acquisition can be processed in time; and the operation stability of the power system is improved.

Description

Technical Field

[0001] The present application belongs to the technical field of monitoring equipment in a power system, and in particular, relates to a monitoring method for equipment, a monitoring device, a computer device, a computer-readable storage medium, and a computer program product. Background Art

[0002] With the continuous development of power systems and the improvement of their intelligence level, higher requirements are placed on the collection and processing of power consumption information. Power systems generally include data acquisition systems and various installed electric meters. The data acquisition system is used to obtain the collected power consumption data of each electric meter. Due to the diverse environments for collecting power consumption information, there is also a risk of failure of equipment such as electric meters, which may lead to inaccurate collected power consumption information, thus affecting the stable operation of the power system. Summary of the invention

[0003] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a device monitoring method, a monitoring device, a computer device, a computer-readable storage medium and a computer program product, which can monitor various abnormal conditions in the process of collecting electricity consumption information, thereby facilitating the handling of abnormalities and ensuring the stable operation of the power system.

[0004] In a first aspect, the present application provides a monitoring method, comprising setting a buried point in a data acquisition system of a device; acquiring buried point data of the data acquisition system through the buried point; and monitoring the buried point data to obtain a monitoring result.

[0005] In a second aspect, the present application provides a monitoring device, the monitoring device comprising:

[0006] The setting module is used to set the buried points in the data acquisition system of the device;

[0007] An acquisition module, which acquires the buried point data of the data acquisition system through the buried points;

[0008] The monitoring module is used to monitor the buried point data to obtain monitoring results.

[0009] In a third aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned monitoring method when executed by a processor.

[0010] In a fourth aspect, the present application provides a computer device, comprising a processor and a memory, wherein the memory stores a computer program, and the computer program implements the above-mentioned monitoring method when executed by the processor.

[0011] In a fifth aspect, the present application provides a computer program product, including a computer program, which implements the above-mentioned monitoring method when executed by a processor.

[0012] The monitoring method, monitoring device, computer equipment, computer-readable storage medium and computer program product of the equipment provided in the embodiments of the present application set buried points in the data acquisition system of the power system, thereby acquiring buried point data during the operation of the data acquisition system through the buried points, thereby realizing the collection of various data of the data acquisition system (such as the acquired power consumption data, the operation data of the data acquisition system itself, etc.). The entire operation process of the data acquisition system can be monitored through the buried point data, so as to timely discover anomalies in the power consumption data collected by the data acquisition system and anomalies of the equipment connected to the data acquisition system, so as to facilitate timely processing of various anomalies that affect the collection of power consumption data, which is beneficial to improving the operation stability of the power system.

[0013] Additional aspects and advantages of the embodiments of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the embodiments of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0015] Figure 1 It is a schematic diagram of an application scenario of the monitoring method provided in an embodiment of the present application;

[0016] Figure 2 It is a flowchart of the monitoring method provided in the embodiment of the present application;

[0017] Figure 3 It is a flowchart of the monitoring method provided in the embodiment of the present application;

[0018] Figure 4 It is a flowchart of the monitoring method provided in the embodiment of the present application;

[0019] Figure 5 It is a module schematic diagram of the monitoring device provided in an embodiment of the present application;

[0020] Figure 6 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as limiting the present application.

[0022] For ease of understanding, the application scenarios of this application are first introduced below:

[0023] See also Figure 1 , Figure 1 1 is an application scenario diagram of a monitoring method provided in an embodiment of the present application. The application scenario provided in the present application includes a monitoring server 101, a data collection server 102 and an electricity collector 103, and the monitoring method provided in the present application can be executed by the monitoring server 101.

[0024] Among them, the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), as well as big data and artificial intelligence platforms, but the embodiments of the present application do not limit this.

[0025] The monitoring server 101 is connected to the data collection server 102 in communication, and the data collection server 102 is connected to each power consumption collector 103 in communication.

[0026] The power collector 103 may be a smart meter installed at the user end, which can monitor power parameters such as voltage, current, power factor, etc. in real time, and collect information such as switch status and transformer temperature.

[0027] In some embodiments, the application scenario also includes a database 104, and the database 104 is respectively connected to the monitoring server 101 and the data acquisition server 102 in communication, so as to achieve data sharing.

[0028] Optionally, the monitoring method involved in the present application can be implemented based on cloud technology.

[0029] Among them, cloud technology refers to a hosting technology that unifies hardware, software, network and other resources within a wide area network or local area network to achieve data calculation, storage, processing and sharing.

[0030] Cloud technology is a general term for network technology, information technology, integration technology, management platform technology, application technology, etc. based on the cloud computing business model. It can form a resource pool, which can be used on demand and is flexible and convenient. Cloud computing technology will become an important support. The backend services of the technical network system require a large amount of computing and storage resources, such as video websites, picture websites and more portal websites. With the rapid development and application of the Internet industry, in the future, each item may have its own identification mark, which needs to be transmitted to the backend system for logical processing. Data of different levels will be processed separately. All kinds of industry data need strong system backing support, which can only be achieved through cloud computing.

[0031] The monitoring method of the present application can be implemented based on cloud computing. Cloud computing is a computing model that distributes computing tasks on a resource pool composed of a large number of computers, so that various application systems can obtain computing power, storage space and information services as needed. The network that provides resources is called a "cloud". The resources in the "cloud" are infinitely expandable in the eyes of users, and can be obtained at any time, used on demand, expanded at any time, and paid for by use.

[0032] As a provider of basic cloud computing capabilities, a cloud computing resource pool (referred to as a cloud platform, generally referred to as an IaaS (Infrastructure as a Service) platform) will be established, and various types of virtual resources will be deployed in the resource pool for external customers to choose to use. The cloud computing resource pool mainly includes: computing devices (virtualized machines, including operating systems), storage devices, and network devices.

[0033] The monitoring method in the embodiment of the present application can be executed by a computer device, and the computer device can be the above-mentioned monitoring server.

[0034] Based on the introduction of the above application scenarios, the embodiment of the present application provides a monitoring method, which is described in detail below:

[0035] See also Figure 2 A monitoring method provided in an embodiment of the present application is implemented by steps 011 to 013, which are described in detail below.

[0036] Step 011: Set up tracking points in the data acquisition system of the device.

[0037] The device may be the aforementioned power collector for collecting power consumption data. It is understood that the device may also be other devices for data collection, such as devices for collecting environmental data (such as cameras, various sensors, etc.).

[0038] The data collection system may be run in a data collection server connected to each electricity collector. The data collection system includes multiple functional modules to perform various user data collection tasks.

[0039] Optionally, the data collection system realizes data interaction between the collected data and other business systems through an interface server to ensure data sharing and effective use.

[0040] Among them, tracking is a common technology in software development, which is used to collect data in the software system. Through tracking, the data corresponding to the tracking program can be tracked.

[0041] For example, if the tracking program is used to obtain the electricity consumption data collected by the data acquisition system, the tracking program can obtain the electricity consumption data in real time.

[0042] Optionally, you can implement the tracking setting by writing a tracking program into the code of the data acquisition system; or, you can define the tracking logic through a configuration file or an external service. You can update the tracking settings without modifying the code. This method is more flexible and allows you to adjust the tracking logic without republishing the system.

[0043] For example, the present application may include multiple data processing modules in the data acquisition system, and a tracking point is set in each data processing module to track and obtain the data in each module.

[0044] In one example, the data collection system includes a task issuing module, a task parsing module and a task forwarding module.

[0045] Users can pre-establish various power consumption data collection tasks according to their needs. For example, if the power consumption data of area A is collected every 15 minutes, 96 points of power consumption data of each power consumption collector in area A can be obtained every day.

[0046] When the data collection system is running, it first traverses the list of all tasks that need to be executed, generates all required tasks through the task list, and writes all tasks into the database (such as Redis database).

[0047] The data sending module will send each task in the database. In the task sending module; the data parsing module is used to parse the task to determine the specific task content; the data forwarding module forwards the task to the corresponding power consumption collector so that the corresponding power consumption collector performs the corresponding operation to complete each task.

[0048] Optionally, corresponding tracking points can be established according to each task of the data acquisition system, so as to obtain the execution data of the entire process of each task.

[0049] For example, in the task issuing module, the task parsing module and the task forwarding module, corresponding tracking points can be established according to each task, so as to obtain various tracking point data of each task in the process of issuing, parsing and forwarding.

[0050] Step 012: Obtain the tracking point data of the data acquisition system through tracking point.

[0051] After setting up the tracking points, the tracking point data of the data acquisition system can be obtained through tracking point tracking. For example, in each data processing module of the data acquisition system, a corresponding tracking point is established for each task, so as to obtain the tracking point data when each data processing module processes each task.

[0052] Optionally, the data acquisition system is connected to a database for communication, and the burial point data acquired at each burial point can be stored in the database.

[0053] Optionally, the database may be a memory database, which has high read and write efficiency and can improve the real-time performance of acquiring buried point data.

[0054] For example, the in-memory database is a Redis database. Using Redis to store tracking data can effectively reduce the load pressure of traditional databases and avoid performance bottlenecks caused by frequent reading and writing of status information. Redis also supports cluster deployment and can be easily expanded horizontally to cope with the continuous growth in the number of devices. It has stronger scalability than traditional databases.

[0055] Step 013: Monitor the buried point data to obtain monitoring results.

[0056] Specifically, after acquiring the burying point data of each burying point into the database, the monitoring server can acquire the burying point data from the database in real time, thereby realizing real-time monitoring of the burying point data.

[0057] During the monitoring process, based on the acquired buried data, the entire collection process of the data acquisition system can be analyzed to determine the monitoring results (such as the execution status of each task). The monitoring results can be displayed to facilitate monitoring personnel to understand the task execution status in a timely manner. When problems arise in task execution, they can be corrected in a timely manner to ensure the accuracy of the data collected by the data acquisition system.

[0058] See also Figure 3 Optionally, the tracking data includes execution data of each task of the data acquisition system. Step 013 includes:

[0059] Step 0131: Monitor the execution data of each task to obtain the monitoring result corresponding to each task, where the monitoring result includes at least one of the task name, task execution time, task progress, task status and whether the task fails.

[0060] The execution data of a task refers to the relevant data during the execution of the task. For example, the execution data includes the power consumption data collected during the execution of the task, the content of the task, the execution progress of the task, whether the task is successfully executed, the task status, and the information of the power consumption collector corresponding to the task.

[0061] Specifically, since the data collection system generally collects power consumption data based on tasks, the monitoring of each task can be achieved by monitoring the execution of each task.

[0062] Since the tracking points have been set for each task in the data acquisition system, the execution data of each task executed by the data acquisition system can be obtained based on the tracking point data obtained based on the tracking point data corresponding to each task.

[0063] By monitoring the execution data of each task, the monitoring results corresponding to each task can be obtained, such as the monitoring results including the task name (corresponding task content), task execution time, task progress, task status (such as being in execution, paused, canceled, etc.) and at least one of whether the task failed.

[0064] In this way, the monitoring personnel can see the execution status of each task in real time, so that when there is an abnormality in the task (such as the task status becomes suspended, the task fails, the task is not executed at the task execution time, the task progress increases too slowly, etc.), the task can be corrected immediately to ensure the normal execution of each task and the accuracy of the electricity consumption data collected by each task.

[0065] Optionally, the monitoring result includes data anomaly information, the device is used to collect power consumption information, and the buried data includes power consumption information of each device collected by the data collection system. Step 013 includes:

[0066] Step 0132: Perform data quality detection on the power usage information of each device to obtain data anomaly information of the power usage information of each device.

[0067] Specifically, in addition to monitoring the overall execution of the task, the data quality of the collected data corresponding to the task can also be monitored to determine whether the collected data corresponding to each task has an abnormality and obtain data abnormality information. For example, the data abnormality information includes at least one of the following: flying abnormality, reverse abnormality, stop abnormality and null value abnormality.

[0068] The electricity consumption collector generally collects electricity consumption data based on a preset period, such as collecting electricity consumption data every 15 minutes. The electricity consumption collector can obtain 96 points of electricity consumption data every day.

[0069] For flying away anomaly, the difference between any power consumption data and the previous normal power consumption data is greater than the preset threshold; for reverse walking anomaly, any power consumption data is less than the previous normal power consumption data; for stop and go anomaly, multiple power consumption data are the same; for null value anomaly, any power consumption data does not exist.

[0070] The amount of electricity consumption data collected by each electricity consumption collector corresponding to the task is fixed every day. Based on various abnormal characteristics, data quality detection can be performed based on the electricity consumption data collected by each electricity consumption collector corresponding to the task, thereby obtaining data anomalies of the electricity consumption data collected by each electricity consumption collector.

[0071] In this way, by performing data quality detection on the power consumption data of each device corresponding to the task, data anomaly information of each device can be obtained, and the power consumption data collected by each device can be monitored. Therefore, if the data collected by any device is abnormal, an alarm can be issued in time to prompt the monitoring personnel to handle the device, ensuring the stable operation of each device, thereby improving the accuracy of the collected power consumption data.

[0072] In addition, accurate electricity consumption data can be used to count the energy consumption of equipment, which is conducive to discovering abnormal energy consumption events and providing guidance for power customers to save energy and reduce emissions. This helps power customers optimize their electricity usage strategies, reduce electricity costs, and improve energy efficiency.

[0073] Optionally, the tracking data includes the heartbeat timestamp of each device, and the monitoring result also includes status information. Step 013 includes:

[0074] Step 0133: When the heartbeat timestamp of the device times out, determine that the status information of the device is abnormally offline.

[0075] Specifically, in addition to monitoring the overall execution of the task and the power consumption data collected by the task, the status of the equipment can also be monitored. During the task execution process, the equipment generally needs to remain online at all times so that the collected power consumption data can be reported to the data collection system in a timely manner.

[0076] When the device is online, it will send a heartbeat signal to the data acquisition system at a preset frequency. After receiving the heartbeat signal, the data acquisition system can determine that the device is online and update the heartbeat timestamp in the device file based on the sending time of the heartbeat signal.

[0077] The buried data can also include the heartbeat timestamp of each device. By obtaining the heartbeat timestamp of each device, a timeout detection is performed on the heartbeat timestamp of each device. When the time difference between the heartbeat timestamp of the device and the current time is greater than the preset time difference (such as 10 seconds, 15 seconds, etc.), the status of the device can be determined to be offline. Since this is the task execution time, the offline of the device corresponding to the task is an abnormal situation. By monitoring the heartbeat timestamp, the status of each device of the task can be monitored to determine whether the device is abnormally offline. When the device is abnormally offline, the monitoring personnel can handle it in time to ensure the normal execution of the task, or suspend the task in time when it cannot continue to be executed to ensure the accurate execution of the task.

[0078] Optionally, when the target device is abnormally offline, the device file of the target device is deleted, the device file includes at least one of the device identification, status information and heartbeat timestamp of the target device, the target device is any device, and the device file is stored in the database; when the heartbeat packet of the target device is received again, the device file of the target device is rebuilt.

[0079] Specifically, the device files of the devices are generally stored in the database. In the case of any target device being abnormally offline, timely processing is required. Since the monitoring server generally cannot directly control the device, but the monitoring server is connected to the database, the monitoring server can delete the device files of the target device by operating the database. The device files include at least one of the device identification, status information and heartbeat timestamp of the target device, so as to avoid the abnormal device files of the target device from affecting the task.

[0080] Since the target device may be temporarily offline due to network fluctuations, the target device may be back online after a period of time. Therefore, when the heartbeat packet of the target device is received again, the device file of the target device can be rebuilt to obtain the power consumption data of the target device again to ensure the integrity of the task execution.

[0081] Optionally, the data acquisition system includes multiple gateways, the gateways are in communication connection with one or more devices, the buried data includes messages between each gateway and the corresponding device, and the monitoring result includes the number of abnormal messages. Step 013 includes:

[0082] Step 0134: Detect abnormal messages in the messages received by each gateway to determine the number of abnormal messages of each gateway.

[0083] Specifically, the data collection system is provided with multiple gateways, each gateway is responsible for acquiring the power consumption data of a part of the equipment, and the buried data can also acquire the messages sent and received by each gateway. It can be understood that when the equipment and / or gateway fails, or is attacked by a network attack, the messages sent and received by the gateway may be abnormal, resulting in the gateway being unable to normally acquire accurate power consumption data. Therefore, the messages sent and received by the gateway can be detected for abnormalities, so as to obtain the number of abnormal messages of the gateway by counting.

[0084] Optionally, by customizing the message header and setting a check bit in the message header, in the message between the gateway and the device, if the check bit exists in the message and the value of the check bit is a preset value, it can be determined that the message is normal, otherwise it is abnormal.

[0085] In this way, by monitoring the number of abnormal messages, monitoring personnel can promptly handle gateways that may have abnormalities and ensure the accuracy of gateway data collection.

[0086] Optionally, whether each gateway operates normally can be evaluated by the number of abnormal messages.

[0087] For example, when the ratio of the number of abnormal messages to the total number of messages is greater than a preset ratio, the gateway is determined to be abnormal; when the ratio of the number of abnormal messages to the total number of messages is less than a preset ratio, the gateway is determined to be normal.

[0088] The monitoring method of the equipment of the present application realizes the collection of various data of the data collection system (such as the acquired power consumption data, the operation data of the data collection system itself, etc.) by setting buried points in the data collection system of the power system, and the buried point data is obtained through the buried points. The entire operation process of the data collection system can be monitored through the buried point data, so as to timely discover the anomalies of various tasks performed by the data collection system, the anomalies of the power consumption data collected by the data collection system, the anomalies of the equipment connected to the data collection system, etc., so as to facilitate the timely processing of various anomalies that affect the collection of power consumption data, which is beneficial to improving the operation stability of the power system.

[0089] See also Figure 4 In some embodiments, the communication mode with the data acquisition system includes multiple modes, and the monitoring method further includes:

[0090] Step 014: When an abnormality occurs in the current communication mode, switch to other communication modes among multiple communication modes to communicate and obtain the buried point data.

[0091] Specifically, in order to improve the stability of monitoring, there are multiple communication modes between the data acquisition system and the monitoring server (for example, power line communication, wireless communication (such as 4G communication, Wifi communication, etc.)), and redundant communication modes are implemented. For example, there are multiple communication modes between the data acquisition system and the database, and there are multiple communication modes between the database and the monitoring server.

[0092] When an abnormality occurs in the current communication method used between the data acquisition system and the database (such as network failure or congestion), it is possible to promptly switch to other communication methods among the multiple communication methods for communication, thereby ensuring stable communication between the data acquisition system and the database.

[0093] When the current communication method used between the database and the monitoring server is abnormal (such as network failure or congestion), it can be switched to other communication methods among multiple communication methods in time to ensure stable communication between the database and the monitoring server.

[0094] In some embodiments, after the monitoring results are obtained, the monitoring results can be displayed in a visual manner, or the monitoring results can be broadcasted by voice, etc. In this way, the monitoring results can be displayed, so that the monitoring personnel can easily understand the monitoring results and improve the monitoring effect.

[0095] In some embodiments, abnormal alarm information is generated and displayed based on the monitoring results.

[0096] After obtaining the monitoring results, it is possible to automatically detect whether there are any abnormalities based on the monitoring results. For example, whether there are any task abnormalities (such as the task status changes to pause, the task fails, the task is not executed at the task execution time, the task progress increases too slowly, etc.), whether there are any data abnormalities (such as flying away abnormalities, reverse walking abnormalities, stopping abnormalities and null value abnormalities), whether there are any abnormal offline devices (such as the heartbeat timestamp timeout of the device), and whether there are any abnormalities in the gateway (such as the proportion of abnormal messages is greater than the preset proportion).

[0097] Based on the detected anomaly type, abnormal alarm information is generated, so that the abnormal alarm information can be displayed in time, prompting monitoring personnel to deal with the anomaly in time, ensuring the accuracy and stability of data collection, and reducing data loss and duplicate collection problems.

[0098] According to the method described in the above embodiment, the present application embodiment also provides a monitoring device 300 for executing the steps in the above monitoring method. Figure 5 , Figure 5 : is a schematic diagram of the structure of a monitoring device 300 provided in an embodiment of the present application. The monitoring device 300 includes:

[0099] The setting module 301 is used to set the buried point in the data acquisition system of the device;

[0100] An acquisition module 302 is used to acquire the buried point data of the data acquisition system through buried points;

[0101] The monitoring module 303 is used to monitor the buried point data to obtain monitoring results.

[0102] It should be noted that the specific details of each module unit in the above-mentioned monitoring device 300 have been described in detail in the embodiment of the above-mentioned monitoring method, and will not be repeated here.

[0103] In the embodiments of the present application, the term "module" or "unit" refers to a computer program or a part of a computer program with a predetermined function, and works together with other related parts to achieve a predetermined goal, and can be implemented in whole or in part by using software, hardware (such as processing circuits or memories) or a combination thereof. Similarly, a processor (or multiple processors or memories) can be used to implement one or more modules or units. In addition, each module or unit can be part of an overall module or unit that includes the function of the module or unit.

[0104] In some embodiments, the monitoring device in the embodiments of the present application can be implemented in hardware, such as a chip, or a component in a chip, such as an integrated circuit or a chip; the monitoring device can also be implemented in software, such as as an application installed in a chip.

[0105] Among them, chips, also known as integrated circuits (ICs), microcircuits or microchips, are the core components of modern electronic devices. They are made of semiconductor materials (usually silicon) and integrate millions or even billions of microelectronic components (such as transistors, resistors, capacitors, etc.) through a series of complex manufacturing processes to form an electronic circuit with specific functions. These components and their interconnections are manufactured on the same small silicon wafer. They are small in size, light in weight, but powerful in function. They are the basis of various electronic products such as computers, smart phones, home appliances, automobiles, medical equipment, etc.

[0106] In some embodiments, see Figure 6 , Figure 6 4 is a schematic diagram of the structure of a computer device provided in an embodiment of the present application. The computer device 400 includes a processor 401 and a memory 402. The memory 402 stores a computer program 403 that can be run on the processor 401. When the program 403 is executed by the processor 401, each process of the embodiment of the above-mentioned function restriction method is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0107] An embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the embodiment of the above-mentioned monitoring method are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0108] The processor may be the processor of the computer device in the above embodiment.

[0109] Among them, computer-readable media may include computer storage media and communication media. Computer storage media include volatile and non-volatile, removable and non-removable media implemented by any method or technology for storing information such as computer-readable instructions, data structures, program modules or other data. Computer storage media include RAM, ROM, Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), flash memory or other solid-state storage technology, CD-ROM, Digital Versatile Disc (DVD) or other optical storage, cassettes, magnetic tapes, disk storage or other magnetic storage devices. Of course, those skilled in the art will know that computer storage media are not limited to the above.

[0110] The embodiment of the present application also provides a computer program product, including a computer program, which implements the above-mentioned monitoring method when executed by a processor. The processor may be a processor of the computer device in the above-mentioned embodiment. When the computer program is executed by the processor, each process of the embodiment of the above-mentioned monitoring method is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0111] It is understandable that in the specific implementation of this application, data related to user identity or characteristics is involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0112] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A method for monitoring a device, characterized in that: include: Set up tracking points in the equipment’s data acquisition system; Acquire the buried point data of the data acquisition system through the buried points; The buried point data is monitored to obtain monitoring results.

2. The monitoring method according to claim 1, characterized in that: The data acquisition system includes multiple data processing modules, and each of the data processing modules is provided with a buried point.

3. The monitoring method according to claim 1, characterized in that: The step of acquiring the buried point data of the data acquisition system through buried points includes: The buried point data is obtained through the buried point and stored in a database.

4. The monitoring method according to claim 3, characterized in that: The database is an in-memory database.

5. The monitoring method according to claim 1, characterized in that: The buried data includes execution data of each task of the data acquisition system, and the monitoring of the buried data to obtain monitoring results includes: The execution data of each task is monitored to obtain a monitoring result corresponding to each task, wherein the monitoring result includes at least one of a task name, a task execution time, a task progress, a task status, and whether the task fails.

6. The monitoring method according to claim 1, characterized in that: The monitoring result includes data abnormality information, the device is used to collect power consumption information, the buried data includes power consumption information of each of the devices collected by the data collection system, and the buried data is monitored to obtain the monitoring result, including: Data quality detection is performed on the power usage information of each of the devices to obtain data anomaly information of the power usage information of each of the devices.

7. The monitoring method according to claim 1, characterized in that: The data abnormality information includes at least one of a flying abnormality, a reverse abnormality, a stopping abnormality and a null value abnormality.

8. The monitoring method according to claim 1, characterized in that: The buried data includes the heartbeat timestamp of each of the devices, the monitoring result also includes status information, and the monitoring of the buried data to obtain the monitoring result includes: When the heartbeat timestamp of the device times out, it is determined that the status information of the device is abnormally offline.

9. The monitoring method according to claim 8, characterized in that: Also includes: In the case where the target device is abnormally offline, deleting the device file of the target device, the device file including at least one of the device identification, status information and heartbeat timestamp of the target device, the target device is any of the devices, and the device file is stored in the database; When the heartbeat packet of the target device is received again, the device profile of the target device is rebuilt.

10. The monitoring method according to claim 1, characterized in that: There are multiple communication modes with the data acquisition system, and the method further includes: When an abnormality occurs in the current communication mode, switch to other communication modes among multiple communication modes to communicate to obtain the buried point data.

11. The monitoring method according to claim 10, characterized in that: The multiple communication modes include at least one of wireless communication and power line communication.

12. The monitoring method according to claim 1, characterized in that: The data acquisition system includes a plurality of gateways, the gateways are in communication connection with one or more of the devices, the buried data includes messages between each of the gateways and the corresponding devices, the monitoring result includes the number of abnormal messages, and the buried data is monitored to obtain the monitoring result, including: Detecting abnormal messages in the messages received by each of the gateways to determine the number of abnormal messages of each of the gateways.

13. The monitoring method according to claim 12, characterized in that: The message between the device and the gateway includes a check bit, and the abnormal message is determined based on the check bit.

14. The monitoring method according to claim 1, characterized in that: The method further comprises: The monitoring result is displayed.

15. The monitoring method according to any one of claims 1, 5, 6, 8 and 12, characterized in that: Also includes: Abnormal alarm information is generated and displayed based on the monitoring results.

16. A monitoring device, characterized in that: include: The setting module is used to set the buried points in the data acquisition system of the device; An acquisition module, used for acquiring the buried point data of the data acquisition system through the buried points; The monitoring module is used to monitor the buried point data to obtain monitoring results.

17. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the monitoring method according to any one of claims 1 to 15 is implemented.

18. A computer device, characterized in that: include: A processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the monitoring method according to any one of claims 1 to 15 is implemented.

19. A computer program product, characterized in that It comprises a computer program, which, when executed by a processor, implements the monitoring method according to any one of claims 1 to 15.

Images