Industrial alarm system and method based on computing engine

Abstract

The invention discloses an industrial alarm system based on a computing engine and an implementation method of the industrial alarm system. The industrial alarm system comprises a business rule management subsystem and a calculation engine subsystem. And the business rule management subsystem comprises a business rule configuration module, a business rule application module and a task management module, and is used for user-oriented self-defining business rules according to requirements, selecting rule types to maintain alarm items and establishing a relation between the alarm items and tasks. The calculation engine subsystem comprises an alarm item synchronization module, a real-time data processing module, a rule calculation module, an alarm storage module and a message pushing module; all the modules work cooperatively to ensure timely synchronization of alarm rules, efficient data processing, accurate calculation of the rules, safe storage of results and instant notification of alarm information. According to the scheme, coupling of alarm rule calculation and services is effectively reduced, a calculation engine is independent of the services to carry out distributed dynamic expansion, meanwhile, the service rules are customized for a user, and then the flexibility and adaptability of the system are enhanced.

Description

Technical Field

[0001] The present invention relates to the field of industrial automation, and in particular to an industrial alarm system based on a computing engine and an implementation method thereof. Background Art

[0002] Traditional industrial alarm systems are usually closely tied to specific business processes, and alarm calculations are often embedded in business logic. Although this binding method can meet the needs of specific business scenarios, it also brings many limitations and challenges.

[0003] First, due to the deep coupling between alarm calculation and business logic, the system lacks flexibility and scalability when dealing with complex and changing production environments. When production processes change or new monitoring requirements arise, the system often needs to be redesigned and developed extensively, increasing the system's maintenance costs and implementation difficulties.

[0004] In addition, traditional alarm systems often fail to fully function when faced with massive amounts of data and real-time processing requirements. With the development of Industrial Internet of Things (IIoT) technology, the amount of data is growing exponentially, and how to extract effective information from it and respond in a timely manner has become a major challenge for existing systems.

[0005] Therefore, there is an urgent need for an industrial alarm system based on an independent computing engine, which can be separated from specific business logic and realize independent deployment and centralized management of alarm calculation. Summary of the invention

[0006] The purpose of the present invention is to provide an industrial alarm system based on a computing engine and an implementation method to solve the limitations brought about by the deep coupling of alarm calculation and business logic, and to achieve independence and efficiency of alarm business calculation.

[0007] In order to achieve the above object, the technical solution provided by the present invention is as follows:

[0008] An industrial alarm system based on a computing engine includes a business rule management subsystem and a computing engine subsystem;

[0009] The business rule management subsystem includes:

[0010] Business rule configuration module, which is used by users to create business rules and publish rules through the front-end interface, and store the rules in the database;

[0011] Business rule application module, which allows users to maintain alarm items based on custom rule types or system built-in rule types through the front-end interface and store them in the database;

[0012] The task management module is used for users to create task objects through the front-end interface, and then select alarm items to bind to the task objects, establish the association between the alarm items and the task objects, and store them in the database and data middleware;

[0013] The above computing engine subsystem includes:

[0014] The alarm item synchronization module is used to monitor changes in data middleware task versions and synchronize alarm items and custom rules;

[0015] Real-time data processing module, used to collect and preprocess time series data;

[0016] A rule calculation module is used to calculate the alarm rules according to the time series value and the business rules to which the alarm items belong and output the calculation results;

[0017] Alarm storage module, used for storage processing of calculation results;

[0018] The message push module is used to monitor whether the calculation result data meets the notification conditions. When the notification conditions are met, an alarm message is sent to relevant personnel.

[0019] The present invention uses the user-oriented task management mode as the link and the computing engine as the core to achieve the decoupling of business and computing. The user associates the alarm business configuration data with the task, and then the computing engine actively seizes the task to calculate the alarm business rules. Secondly, the user can set the task parameters to realize the engine's customized operation according to the task parameters and the user's customized business rules to adapt to more complex business scenarios.

[0020] The present invention also provides an industrial alarm method based on a computing engine, the steps of which are as follows:

[0021] 1) Users create business rules and publish rules through the front-end interface and store the rules in the database; the rules include the following information: rule type identification, rule name, rule content, and publishing status;

[0022] 2) The user maintains the alarm items through the front-end interface according to the custom rule type or the system built-in rule type and stores them in the database; the alarm items include the following information: business data source, business rule type and parameters, and notification configuration content data;

[0023] 3) The user creates a task object through the front-end interface, and then selects an alarm item to bind to the task object, establishes an association between the alarm item and the task object, and stores it in the database and data middleware; the task object information includes the task execution time, whether it is enabled and the cycle parameters; the data middleware records the mapping relationship between the task and the engine through the task pool, and the relationship is one-to-one; the task pool records the task identifier and the initial value of the version corresponding to the task; the database stores the association information between the task object and the alarm item; the association information between the task object and the alarm item includes the list data of the task identifier and the corresponding associated alarm item identifier, and the relationship is one-to-many;

[0024] 4) Monitor the changes in the data middleware task version through the alarm item synchronization module that runs independently in the computing engine subsystem, and synchronize the alarm items and custom rules;

[0025] 5) The real-time data processing module running independently in the computing engine subsystem detects whether the synchronized task is in the execution time period. If it is in the execution time period, the real-time value and timestamp of the data point are read from the corresponding data source according to the execution cycle according to the data point configuration information, stored in the timestamp value object and pushed to the real-time value memory queue;

[0026] 6) Detect whether there is a timestamp value object in the real-time value memory queue through the rule calculation module running independently in the calculation engine subsystem. If there is a timestamp value object, match the corresponding data point real-time value according to the system built-in rule or custom rule corresponding to the alarm item for calculation, and save the calculation result generated by the operation as a calculation result object, which is pushed to the alarm storage module through the calculation result memory queue or the data middleware; wherein, if the calculation result object is a real-time alarm, the calculation result object data is simultaneously saved to the real-time alarm area of ​​the data middleware;

[0027] 7) Determine whether there is a calculation result object in the calculation result memory queue or the data middleware through the alarm storage module running independently in the calculation engine subsystem. If there is calculation result data, parse the calculation result data and store it in the database;

[0028] 8) The message push module running independently in the computing engine subsystem determines whether the real-time alarm area data in the data middleware matches the corresponding alarm item notification configuration conditions, and determines whether the notification configuration conditions are met. If the message push conditions are met, the message is sent according to the push configuration.

[0029] More specifically:

[0030] 1) Users create business rules and publish rules through the front-end interface and store the rules in the database;

[0031] Furthermore, the user creates rules through the business rule configuration module, and the rule information includes: rule identifier, rule name, rule content, and release status; wherein the rule content is the Java code containing the user-defined rule logic;

[0032] 2) Users maintain alarm items through the front-end interface according to custom rule types or system built-in rule types and store them in the database;

[0033] Furthermore, the custom rule type is that the business rule application module reads the rule type identifier published by the rule configuration module through a scheduled task, and then compares the local rule type identifier with the published rule type identifier to check whether there is an unincluded type. If so, it is bound to the local custom rule type list.

[0034] Furthermore, the system built-in rule type is the rule type logic that has been implemented by the calculation engine subsystem.

[0035] Furthermore, the alarm item information is data including business data source, business rule type and parameters, and notification configuration content.

[0036] 3) The user creates a task object through the front-end interface, then selects an alarm item to bind to the task object, establishes an association between the alarm item and the task object, and stores it in the database and data middleware;

[0037] Furthermore, the user creates a task object through the task management module. The task management module supports the creation of task objects including the definition of task execution time, whether to enable and cycle parameter configuration, and stores them in the database. At the same time, the task identifier and the initial version value corresponding to the task are recorded in the task pool in the data middleware.

[0038] Furthermore, the task pool is used to record the mapping relationship between tasks and engines, and the relationship is one-to-one.

[0039] Furthermore, the initial value of the version is a random uuid string identifier.

[0040] Furthermore, the information associated with the task management module and the alarm item stored in the database is: the alarm item identifier and the task identifier.

[0041] Furthermore, the task management module and alarm item association information stored in the data middleware is the task identifier and the corresponding alarm item list data, and the relationship between them is one-to-many.

[0042] 4) The alarm item synchronization module monitors whether there are enabled unassigned tasks in the data middleware. If so, the task is preempted through a distributed lock. If the task is preempted successfully, the task identifier and the engine identifier in the task pool are bound in a one-to-one relationship. If the task preemption fails, the task preemption is performed again. If the task preemption is successful, the data middleware is monitored to see whether the engine identifier bound to the task is consistent with its own identifier. If not, the task is preempted again. If they are consistent, the data middleware task version is monitored to see whether it is consistent with the engine record version. If they are consistent, the version records are monitored in the next synchronization cycle to see whether they are consistent. If they are inconsistent, the alarm item configuration information and task configuration parameters stored in the bound task in the data middleware are loaded. Then, the bound task execution time and cycle configuration are read, wherein the task execution time is read to set the execution time period of the real-time data processing module, and the task cycle is read to set the execution cycle of the real-time data processing module. Secondly, read the alarm item data bound to the task, parse the data point configuration information contained in the alarm item data and push it to the real-time data processing module; parse the business rule information contained in the alarm item data and push it to the rule calculation module; if there are custom rules, load the rule content according to the custom rule type and dynamically create a custom rule object; parse the alarm item notification configuration information contained in the alarm item data and push it to the message push module. Finally, the synchronization is completed and enters the next synchronization cycle to continue to monitor whether the task binding identifier is consistent with the engine identifier.

[0043] 5) The real-time data processing module detects whether the synchronized task is in the execution time period. If it is in the execution time period, the real-time value and timestamp of the data point are read from the corresponding data source according to the data point configuration information according to the execution cycle, stored in the timestamp value object and pushed to the real-time value memory queue.

[0044] Furthermore, the format of the timestamp value object is: data point identifier, data point real-time value, data point timestamp.

[0045] 6) The rule calculation module detects whether there is a timestamp numerical object in the real-time value memory queue. If there is a timestamp numerical object, it matches the corresponding data point real-time value according to the system built-in rules or custom rules corresponding to the alarm item, and the calculation result generated by the operation is saved as a calculation result object, which is pushed to the alarm storage module through the calculation result memory queue or the data middleware; among them, if the calculation result object is a real-time alarm, the calculation result object data is also saved in the real-time alarm area of ​​the data middleware.

[0046] Furthermore, the calculation result object format is: corresponding alarm item configuration data, alarm start time, and alarm end time.

[0047] Furthermore, the data format of the real-time alarm area of ​​the data middleware is a key-value pair that maps the alarm item identifier to the real-time alarm data.

[0048] 7) The alarm storage module determines whether there is a calculation result object in the calculation result memory queue or the data middleware. If there is calculation result data, the calculation result data is parsed and stored in the database.

[0049] 8) The message push module determines whether the real-time alarm area data in the data middleware matches the corresponding alarm item notification configuration conditions, and determines whether the notification configuration conditions are met. If the message push conditions are met, the message is sent according to the push configuration.

[0050] In the above invention, both the business rule management subsystem and the computing engine subsystem can be distributed and dynamically expanded, wherein each computing engine subsystem will create a unique engine identifier after deployment.

[0051] In the above invention, the database supports MYSQL, SQL server, and Oracle database.

[0052] In the above invention, the memory queue adopts Java's LinkedBlockingQueue blocking queue.

[0053] Compared with the prior art, the present invention has the following advantages:

[0054] 1. Alarm calculation independence: By introducing an independent calculation engine, alarm calculation is decoupled from specific business processes, so that alarm logic can be deployed and managed independently of business logic. This not only improves the flexibility and scalability of the system, but also reduces the complexity of system maintenance and upgrades.

[0055] 2. Unified management and optimization of alarm strategies: By centrally managing alarm rules and strategies, the present invention can effectively reduce false alarms and missed alarms, optimize the configuration and adjustment of alarm strategies, and achieve comprehensive coverage and support for different business scenarios.

[0056] 3. Improve the adaptability and scalability of the system: The alarm system designed by the present invention can flexibly adapt to the needs of different industrial environments, support multiple data sources and complex business logic, and can be expanded and upgraded according to actual needs to meet the needs of future business development.

[0057] In summary, the present invention significantly improves the performance, reliability and intelligence level of the industrial alarm system through the introduction of an independent computing engine and the application of advanced technologies, thereby providing safer and more efficient monitoring and alarm services for industrial production. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic diagram of the system of the present invention;

[0059] Figure 2 This is a flowchart of the business rule application module;

[0060] Figure 3 This is a flowchart of the task management module;

[0061] Figure 4 This is a schematic diagram of the alarm item synchronization module flow of the present invention;

[0062] Figure 5 This is a flow chart of the real-time data processing module of the present invention;

[0063] Figure 6 This is a schematic diagram of the rule calculation module flow of the present invention;

[0064] Figure 7 This is a flow chart of the message push module of the present invention;

[0065] Figure 8 It is a schematic diagram of the alarm storage module flow of the present invention. DETAILED DESCRIPTION

[0066] The technical solution of the present invention is further described in detail below through specific implementation methods.

[0067] like Figure 1 The figure shows a logic diagram of the industrial alarm system based on the computing engine and the implementation method of the present invention. The specific implementation method steps are as follows:

[0068] 1) Users maintain custom rule data according to business needs through the business rule configuration module;

[0069] 2) If Figure 2 As shown, the business rule application module will periodically synchronize the custom rules published by the business rule module, and compare whether there are any non-existent rule types in the local custom rule types. If there are, they will be added to the local custom rule types. Users can select the system built-in rule type or the custom maintenance rule type according to business needs, and then configure the data source information, rule parameter information, and notification configuration information to maintain the alarm items.

[0070] 3) If Figure 3 As shown, in the task management module, the user configures the task parameters and saves the task parameter configuration information to the redis middleware and MySQL, wherein the task identifier and the initial value of the version corresponding to the task are recorded in the redis middleware task pool; then the alarm item is selected to be associated with the task and the task and alarm item association information are stored in MySQL, and the task alarm item association information and task configuration data are saved in the redis middleware at the same time, wherein the task management module and the alarm item association information stored in the redis middleware are the task identifier and the corresponding associated alarm item list data, and the relationship is one-to-many.

[0071] 4) If Figure 4 As shown, the alarm item synchronization module of the computing engine subsystem monitors whether there is an enabled unassigned task in the redis middleware. If so, the task is preempted through a distributed lock; if the task preemption is successful, the task identifier and the engine identifier in the task pool are bound in a one-to-one relationship. If the task preemption fails, the task preemption work is performed again; if the task preemption is successful, the redis middleware is monitored to see whether the engine identifier bound to the task is consistent with its own identifier, and if not, the task is preempted again; if they are consistent, the redis middleware task version is monitored to see whether it is consistent with the engine record version, and if they are consistent, the version record is monitored in the next synchronization cycle to see whether they are consistent; if they are inconsistent, the alarm item configuration information and task configuration parameters stored in the bound task in the redis middleware are loaded; then, the bound task execution time and cycle configuration are read, wherein the reading of the task execution time is used to set the execution time period of the real-time data processing module, and the reading of the task cycle is used to set the execution cycle of the real-time data processing module. Secondly, read the alarm item data bound to the task, parse the data point configuration information contained in the alarm item data and push it to the real-time data processing module; parse the business rule information contained in the alarm item data and push it to the rule calculation module; if there are custom rules, load the rule content according to the custom rule type and dynamically create a custom rule object; parse the alarm item notification configuration information contained in the alarm item data and push it to the message push module. Finally, the synchronization is completed and enters the next synchronization cycle to continue to monitor whether the task binding identifier is consistent with the engine identifier.

[0072] 4) If Figure 5 As shown, the real-time data processing module detects whether the synchronized task is in the execution time period. If it is in the execution time period, it parses the data point configuration information, reads the real-time value and timestamp from the corresponding data source according to the execution cycle, stores them in the timestamp value object and pushes them to the real-time value memory queue.

[0073] 5) If Figure 6 As shown, the rule calculation module detects whether there is a timestamp value object in the real-time value memory queue. If there is a timestamp value object, it matches the corresponding data point real-time value according to the system built-in rule or custom rule corresponding to the alarm item for calculation. The calculation result generated by the operation is saved as a calculation result object, and is pushed to the alarm storage module through the calculation result memory queue or Kafka middleware; among them, if the calculation result object is a real-time alarm, the calculation result object data is also saved in the redis middleware real-time alarm area.

[0074] 9) If Figure 7As shown, the message push module determines whether the real-time alarm area data in the redis middleware matches the corresponding alarm item notification configuration conditions, and determines whether the notification configuration conditions are met. If the message push is met, the message is sent according to the push configuration. The message push module detects and determines whether the real-time alarm area data in the redis middleware meets the notification configuration conditions. If the message push is met, the message is sent according to the push configuration.

[0075] 10) As Figure 8 As shown, the alarm storage module determines whether there is a calculation result object in the calculation result memory queue or the Kafka middleware. If there is calculation result data, the calculation result data is parsed and stored in MYSQL.

[0076] The above description is only a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements without departing from the principle of the present invention, and these improvements should also be regarded as within the protection scope of the present invention.

Claims

1. An industrial alarm system based on a computing engine, characterized in that: Includes business rule management subsystem and calculation engine subsystem; The business rule management subsystem includes: Business rule configuration module, which is used by users to create business rules and publish rules through the front-end interface, and store the rules in the database; Business rule application module, which allows users to maintain alarm items through the front-end interface according to custom rule types or system built-in rule types and store them in the database; The task management module is used for users to create task objects through the front-end interface, and then select alarm items to bind to the task objects, establish the association between the alarm items and the task objects, and store them in the database and data middleware; The computing engine subsystem includes: The alarm item synchronization module is used to monitor changes in data middleware task versions and synchronize alarm items and custom rules; Real-time data processing module, used to collect and preprocess time series data; A rule calculation module is used to calculate the alarm rules according to the time series value and the business rules to which the alarm items belong and output the calculation results; Alarm storage module, used for storage processing of calculation results; The message push module is used to monitor whether the calculation result data meets the notification conditions. When the notification conditions are met, an alarm message is sent to relevant personnel.

2. The industrial alarm system based on the computing engine according to claim 1, characterized in that: The rules created in the business rule configuration module include the following information: rule type identification, rule name, rule content, and release status.

3. The industrial alarm system based on computing engine according to claim 2, characterized in that: The business rule application module has the following implementation steps: reading the rule type identifier published by the rule configuration module through a scheduled task, then comparing the local rule type identifier with the published rule type identifier, checking whether there is an unincluded type, and if so, binding it to the local custom rule type list; the user selects a custom rule type or a system built-in rule type, and then maintains the data source, rule parameters and notification configuration data to create an alarm item; the system built-in rule type is the rule type logic that has been implemented by the computing engine subsystem; the alarm item includes the following information: business data source, business rule type and parameters, and notification configuration content data.

4. The industrial alarm system based on the computing engine according to claim 3, characterized in that: The task object information in the task management module includes the task execution time, whether it is enabled and the cycle parameters. At the same time, the task identifier and the initial value of the version corresponding to the task are recorded in the task pool of the data middleware, and the association information between the task object and the alarm item is stored in the database; the task pool is used to record the mapping relationship between the task and the engine, and the relationship is one-to-one; the association information between the task object and the alarm item includes the list data of the task identifier and the corresponding associated alarm item identifier, and the relationship is one-to-many.

5. The industrial alarm system based on the computing engine according to claim 4, characterized in that: The alarm item synchronization module is an independent running module in the computing engine subsystem, and its implementation steps are as follows: Step S1: Monitor whether there are any unassigned tasks enabled in the data middleware. If so, preempt the tasks through distributed locks. If the task preemption succeeds, bind the task ID and the engine ID in the task pool to a one-to-one relationship, and go to step S2. If the task preemption fails, go to step S1. Step S2: Monitoring data middleware whether the task binding engine identifier is consistent with its own identifier, inconsistent to step S1, consistent to step S3; Step S3: monitor whether the data middleware task version is consistent with the engine record version. If it is consistent, go to step S2; if it is inconsistent, go to step S4; Step S4: Load the alarm item configuration information and task configuration parameters stored in the task bound to the data middleware; Step S5: Reading the bound task execution time and cycle configuration, wherein the task execution time is used to set the execution time period of the real-time data processing module, and the task cycle is used to set the execution cycle of the real-time data processing module; Step S6: Read the alarm item data bound under the task, wherein the data point configuration information contained in the alarm item data is parsed and pushed to the real-time data processing module; the business rule information contained in the alarm item data is parsed and pushed to the rule calculation module; if there is a custom rule, the rule content is loaded according to the custom rule type and the custom rule object is dynamically created; the alarm item notification configuration information contained in the alarm item data is parsed and pushed to the message push module; After the synchronization is completed, go to step S2.

6. The industrial alarm system based on the computing engine according to claim 5, characterized in that: The real-time data processing module is an independently running module in the computing engine subsystem, and its implementation steps are as follows: detect whether the synchronized task is in the execution time period. If it is in the execution time period, read the real-time value and timestamp of the data point from the corresponding data source according to the execution cycle according to the data point configuration information, store it in the timestamp value object, and push it to the real-time value memory queue; the timestamp value object includes the following information: data point identifier, data point real-time value, data point timestamp.

7. The industrial alarm system based on computing engine and implementation method according to claim 6, characterized in that: The rule calculation module is an independently running module in the computing engine subsystem, and its implementation steps are as follows: detect whether there is a timestamp numerical object in the real-time value memory queue. If there is a timestamp numerical object, match the corresponding data point real-time value according to the system built-in rule or custom rule corresponding to the alarm item for calculation, and save the calculation result generated by the operation as a calculation result object, and push it to the alarm storage module through the calculation result memory queue or the data middleware; wherein, if the calculation result object is a real-time alarm, the calculation result object data is also saved in the real-time alarm area of ​​the data middleware; the calculation result object includes the following information, corresponding to the alarm item configuration data, the alarm start time, and the alarm end time; the data format of the real-time alarm area of ​​the data middleware is a key-value pair that maps the alarm item identifier to the corresponding real-time alarm data.

8. The industrial alarm system based on computing engine according to claim 7, characterized in that: The alarm storage module is an independent running module in the computing engine subsystem, and its implementation steps are as follows: determine whether there is a computing result object in the computing result memory queue or the data middleware, and if there is computing result data, parse the computing result data and store it in the database.

9. The industrial alarm system based on the computing engine according to claim 8, characterized in that: The message push module is an independently running module in the computing engine subsystem, and its implementation steps are as follows: determine whether the real-time alarm area data in the data middleware matches the corresponding alarm item notification configuration conditions, determine whether the notification configuration conditions are met, and if the message push conditions are met, send the message according to the push configuration.

10. An industrial alarm method based on a computing engine, characterized in that: The following steps are involved: 1) Users create business rules and publish rules through the front-end interface and store the rules in the database; rules Includes the following information: rule type identification, rule name, rule content, and release status; 2) The user maintains alarm items through the front-end interface according to the custom rule type or the system built-in rule type and stores them in the database; the alarm items include the following information: business data source, business rule type and parameters, and notification configuration content data; 3) The user creates a task object through the front-end interface, and then selects an alarm item to bind to the task object, establishes an association between the alarm item and the task object, and stores it in the database and data middleware; the task object information includes the task execution time, whether it is enabled and the cycle parameters; the data middleware records the mapping relationship between the task and the engine through the task pool, and the relationship is one-to-one; the task pool records the task identifier and the initial value of the version corresponding to the task; the database stores the association information between the task object and the alarm item; the association information between the task object and the alarm item includes the list data of the task identifier and the corresponding associated alarm item identifier, and the relationship is one-to-many; 4) Monitor the changes in the data middleware task version through the alarm item synchronization module that runs independently in the computing engine subsystem, and synchronize alarm items and custom rules; 5) The real-time data processing module running independently in the computing engine subsystem detects whether the synchronized task is in the execution time period. If it is in the execution time period, the real-time value and timestamp of the data point are read from the corresponding data source according to the execution cycle according to the data point configuration information, stored in the timestamp value object and pushed to the real-time value memory queue; 6) The rule calculation module running independently in the calculation engine subsystem detects whether there is a timestamp value object in the real-time value memory queue. If there is a timestamp value object, the real-time value of the corresponding data point is matched according to the system built-in rules or custom rules corresponding to the alarm item for calculation. The calculation result generated by the operation is saved as a calculation result object, and is pushed to the alarm storage module through the calculation result memory queue or the data middleware; among them, if the calculation result object is a real-time alarm, the calculation result object data is also saved in the real-time alarm area of ​​the data middleware; 7) Determine whether there is a calculation result object in the calculation result memory queue or data middleware through the alarm storage module running independently in the calculation engine subsystem. If there is calculation result data, parse the calculation result data and store it in the database; 8) The message push module running independently in the computing engine subsystem determines whether the real-time alarm area data in the data middleware matches the corresponding alarm item notification configuration conditions, and determines whether the notification configuration conditions are met. If the message push conditions are met, the message is sent according to the push configuration.

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