TWI881766B - Alarm system and alarm method - Google Patents

Abstract

The present invention provides an alarm system: comprising a parsing module, receiving abnormal data from a system, and parsing keywords of the abnormal data based on natural language processing, thereby determining the category and priority of the abnormal data according to the keywords; a task generation module, configured to store task data, and associate tasks based on first information and keywords, and the task data is associated with the corresponding processing means when the system is in different abnormal states; a task assignment module, configured to determine the relevance between multiple processing personnel and tasks based on the attendance rules and task experience of the tasks and multiple processing personnel, and assign the task to at least one of the multiple processing personnel based on the relevance; and a notification module, configured to send a notification to at least one of the processing personnel based on the priority.

Description

Alarm system and alarm method

The present invention relates to an alarm system, in particular to an intelligent classification, assignment and response technology to reduce the number of alarms and reduce the problem of reprocessing.

In daily system operation and maintenance, it is inevitable to deal with various system problems. These problems may include system failures, performance degradation, security vulnerabilities, etc., and effectively handling these problems is crucial to the stable operation of the system. Previous technologies in this area may include some basic alarm management systems, but these systems can often only handle alarm messages in a single way, lacking the refined classification and processing of different types of alarms. This may cause administrators to spend a lot of time and energy to handle a large number of alarms, while also increasing the risk of missing important alarms.

Specifically, maintenance personnel often encounter various problems, including message bombardment, inability to concentrate, and rework. These problems may lead to inefficiency, increase the workload of maintenance personnel, and even affect the stability and security of the system. Currently known alarm management systems often lack intelligent and automated features, cannot effectively handle a large number of alarm messages, and cannot solve the problem of administrators being unable to concentrate on handling events.

For example, the currently known alarm management system is a rule-based alarm management system. This system usually sets a series of rules to classify and process alarms according to their content. However, this system has certain limitations, such as weak processing capabilities for complex events, and prone to classification errors or missed events.

Another known alarm management system is based on a manual alarm processing system. This system usually relies on manual operation by maintenance personnel, who need to classify and process the alarm messages. However, such a system is inefficient, prone to errors, and unable to handle a large number of alarms. It also cannot solve the problem that maintenance personnel cannot concentrate on handling incidents.

In summary, there is a need for an intelligent alarm management system that can effectively solve problems in daily operation and maintenance and improve the efficiency and quality of system operation and maintenance.

The present invention provides an alarm system, comprising: a parsing module, receiving abnormal data from a system, and parsing out keywords of the abnormal data based on a natural language processing, thereby determining a category and a priority of the abnormal data according to the keywords; a task generation module, configured to store task data, and associate a task based on the task data and the keywords, wherein the task data is associated with the system being in different abnormal conditions. a task assignment module configured to determine the relevance between the multiple processing personnel and the task based on the task and the attendance rules and task experience of the multiple processing personnel, and assign the task to at least one of the multiple processing personnel based on the relevance; and a notification module configured to send a notification to at least one of the processing personnel based on the priority, wherein the notification includes the task.

In a specific embodiment, the analysis module determines the priority based on at least one of the severity, system type, weight, construction record, and online time of the abnormal data.

In a specific embodiment, when the parsing module receives multiple abnormal data and parses multiple keywords, the task generation module is configured to determine that the multiple abnormal data belong to the same source based on the multiple keywords, and merge the abnormal data from the same source into the task.

In a specific embodiment, a personnel monitoring module is further included, which is configured to generate the attendance rule according to at least one of the shift of the processing personnel and whether the processing personnel is on duty, and is configured to generate the task experience according to at least one of the system the processing personnel is responsible for, the assigned tasks and the task processing speed, and provide the attendance rule and the task experience to the task assignment module.

In a specific embodiment, a task monitoring module is further included, which is configured to monitor a first information, the first information includes at least one of the status of the task, the processing flow of the processing personnel, the processing method of the processing personnel, and the processing time of the processing personnel.

In a specific embodiment, the task monitoring module is configured to provide the first information to the task generation module so that the task generation module can further associate the task based on the first information.

In a specific embodiment, the task monitoring module is configured to provide the first information to the task assignment module, so that the task assignment module can further determine the relevance of the multiple processing personnel to the task based on the first information.

The present invention further provides an alarm method, comprising: a parsing step, receiving abnormal data from a system, and parsing out a keyword of the abnormal data based on a natural language processing, thereby determining a category and a priority of the abnormal data according to the keyword; a task generation step, storing a task data, and associating a task based on the task data and the keyword, wherein the task data is associated with the system in different The corresponding handling means in the abnormal state; a task assignment step, based on the task and the attendance rules and task experience of multiple processing personnel, thereby determining the relevance of the multiple processing personnel to the task, and assigning the task to at least one of the multiple processing personnel based on the relevance; and a notification step, based on the priority, sending a notification to at least one of the processing personnel, wherein the notification includes the task.

In a specific embodiment, the analysis step determines the priority based on at least one of the severity, system type, weight, construction record, and online time of the abnormal data.

In a specific embodiment, when the parsing step receives multiple abnormal data and parses multiple keywords, the task generation step determines that the multiple abnormal data belong to the same source based on the multiple keywords, and merges the abnormal data from the same source into the task.

In a specific embodiment, a personnel monitoring step is further included, the attendance rule is generated according to at least one of the shift of the processing personnel and whether the processing personnel is on duty, and the task experience is generated according to at least one of the system the processing personnel is responsible for, the assigned tasks and the task processing speed, and the attendance rule and the task experience are provided to the task assignment step, so that the task assignment step regenerates the task.

In a specific embodiment, a task monitoring step is further included, which monitors a first information, and the first information includes at least one of the status of the task, the processing flow of the processing personnel, the processing method of the processing personnel, and the processing time of the processing personnel.

In a specific embodiment, in the task monitoring module step, the first information is also provided to the task generation step, so that the task generation step further re-associates the task based on the first information.

In a specific embodiment, in the task monitoring module step, the first information is also provided to the task assignment step, so that the task assignment step further re-determines the relevance of the multiple processing personnel to the task based on the first information.

The aforementioned aspects and other aspects of the present invention will become more clear based on the following non-limiting detailed description of specific embodiments and with reference to the accompanying drawings.

100: Alarm system

110:Analysis module

120: Mission generation module

130:Task Assignment Module

140: Notification module

200: Personnel monitoring module

300: Mission monitoring module

P: Processing personnel

S: System

S210, S310: Analysis steps

S230, S330: Task generation step

S250, S350: Task assignment steps

S270, S370: Notification step

S305: Personnel monitoring steps

S390: Mission monitoring steps

The present invention can be further understood by referring to the following figures and descriptions. Non-limiting and non-exhaustive examples are described with reference to the following figures. The components in the figures are not necessarily actual sizes; the focus is on illustrating the structure and principle.

Figure 1 shows a schematic diagram of the alarm system of the present invention.

Figure 2 shows a flow chart of the first embodiment of the alarm method of the present invention.

Figure 3 is a schematic diagram illustrating abnormal data of the present invention.

Figure 4 shows a flow chart of the second embodiment of the alarm method of the present invention.

Figure 5 is a schematic diagram showing the personnel monitoring module of the present invention recording each processing personnel.

Figure 6 is a schematic diagram illustrating the first information of the present invention.

The present invention will be described more fully below with reference to the drawings, and specific exemplary embodiments are shown by way of example. However, the claimed subject matter may be embodied in many different forms, and therefore the construction of the claimed subject matter covered or applied for is not limited to any exemplary embodiment disclosed in this specification; the exemplary embodiments are merely illustrative. Similarly, the present invention is to provide a reasonably broad scope for the claimed subject matter applied for or covered. In addition, for example, the claimed subject matter may be embodied as a method, device, or system.

The term "one embodiment" used in this specification does not necessarily refer to the same specific embodiment, and the term "other (some/certain) embodiments" used in this specification does not necessarily refer to different specific embodiments. The purpose is, for example, that the claimed subject matter includes a combination of all or part of the exemplary specific embodiments.

First, the system architecture of the present invention is briefly described as follows, please refer to the schematic diagram of the alarm system of the present invention shown in Figure 1. The alarm system 100 of the present invention includes a parsing module 110, a task generation module 120, a task assignment module 130, a notification module 140, a personnel monitoring module 200 and a task monitoring module 300. The analysis module 110 is configured to receive abnormal data from one or more systems S, and analyze the keywords of the abnormal data based on a natural language processing (NLP), thereby determining a category and a priority of the abnormal data according to the keywords, wherein the system S is a system or device that sends abnormal data, such as a testing device, a process device, or a computer device, but not limited thereto, and the abnormal data includes error information, information that needs to be debugged, information about information security risks, and other information that is not conducive to the normal operation of the system S, but not limited thereto. The task generation module 120 is configured to store a task data and associate a task based on the task data and the keyword, wherein the task data is associated with the corresponding processing means when the system S is in different abnormal states, such as various means for solving abnormal data, wherein the task is a means or the best solution for solving abnormal data.

The task assignment module 130 is configured to determine the relevance between the multiple processing personnel and the task based on the task and the attendance rules and task experience of the multiple processing personnel, and assign the task to at least one of the multiple processing personnel P based on the relevance. The notification module 140 is configured to send a notification to at least one of the processing personnel P based on the priority, wherein the notification includes the task. The personnel monitoring module 200 is configured to generate the attendance rule based on at least one of the shift of the processing personnel P and whether the processing personnel P is on duty, and is configured to generate the task experience based on at least one of the system that the processing personnel P is responsible for, the assigned tasks and the task processing speed, and provide the attendance rule and the task experience to the task assignment module. The task monitoring module 300 is configured to monitor a first information, the first information includes at least one of the status of the task, the processing flow of the processing personnel P, the processing method of the processing personnel P, and the processing time of the processing personnel P, wherein the task monitoring module 300 is configured to provide the first information to the task generation module 120, so that the task generation module 120 further associates a new task based on the first information, wherein the task monitoring module 300 is configured to provide the first information to the task assignment module 130, so that the task assignment module 130 further determines the relevance of the plurality of processing personnel P and the task based on the first information.

Next, the technical means of the present invention will be described in detail. Please refer to the flowchart of the first embodiment of the alarm method of the present invention shown in FIG2. In the parsing step S210, the parsing module 110 is configured to receive abnormal data from one or more systems S, and parse out keywords of the abnormal data based on a natural language processing (NLP), thereby determining a category and a priority of the abnormal data according to the keywords. Specifically, please refer to the schematic diagram of abnormal data sent by system S as illustrated in Figure 3. The parsing module 110 parses the system type, alarm type, alarm Message, alarm Raw Message and timestamp shown in the figure into keywords based on natural language processing. For example, the corresponding system type is A, the alarm type is Error, the alarm Message, the partial text getinfo timeout while awaiting header recorded in the alarm Raw Message, and the timestamp is 2023-12-0100:01:00.000, wherein the system type can be, for example, financial type, core type, etc. represented by English letters or numbers, but is not limited to this, and the alarm type can be, for example, Fatal, Error or Bug, etc., but is not limited to this. Next, the analysis module 110 matches the severity, system type, weight, construction record, and online time of various abnormal data stored in the analysis module 110 based on the keywords, thereby determining the priority of the abnormal data. More specifically, the severity, system type, weight, construction record, and online time of the above-mentioned various abnormal data correspond to a score respectively, and the analysis module 110 scores the keywords based on the corresponding scores, and determines the priority of each abnormal data according to the score. In other embodiments of the present invention, natural language processing can be replaced by AI or regular expressions to realize the function of the analysis module 110.

In the task generation step S230, the task generation module 120 is configured to store a task data, and associate a task based on the task data and the keyword, wherein the task data is associated with the corresponding processing means when the system is in different abnormal states. Specifically, the task generation module 120 has access to the corresponding processing means when different systems are in different abnormal states. For example, when an Error signal appears in the process equipment, the task generation module 120 will match the corresponding processing means according to the keywords in the system, alarm type, alarm message, alarm raw message and timestamp parsed by the parsing module 110, thereby generating a task, which at least includes a processing means corresponding to the abnormal data. In a preferred embodiment of the present invention, the task can be three and annotated with an expected completion time. In one embodiment, when the parsing module 110 receives multiple abnormal data and parses multiple keywords, the task generation module 120 is configured to determine whether the multiple abnormal data belong to the same source based on the multiple keywords, and merge the abnormal data from the same source into the same task, so that the processing personnel P can avoid evaluating and processing each abnormal data.

In the task assignment step S250, the task assignment module 130 is configured to determine the relevance between the multiple processing personnel P and the task based on the task generated by the task generation module 120 and the attendance rules and task experience of multiple processing personnel P, and assign the task to at least one of the multiple processing personnel P based on the relevance, wherein the higher the relevance, for example, the task assignment module 130 determines that the processing personnel P has a processing method for processing similar abnormal data and even processes it faster, or the processing personnel P is unlikely to encounter the same situation again after processing similar abnormal data, and the lower the relevance, for example, the processing personnel P has no record of relevant processing methods. In a specific embodiment, the attendance rule is at least one of the shift of the processing personnel P and whether to go to work, and the task experience is the system type that the processing personnel P is responsible for, the assigned tasks, and the task processing speed.

In the notification step S270, the notification module 140 is configured to send a notification to at least one of the processing personnel based on the priority, wherein the notification at least includes the task. Specifically, the notification module 140 selects at least one notification tool (such as SMS, M+, E-mail or Line) based on the priority, and notifies in a hierarchical order. In a specific embodiment, when the priority is high, such as when the process equipment is shut down due to a power outage or other major emergency situation, the notification module 140 will send the notification to the processing personnel P and even the management level according to the level. Since the notification includes the task, the management level can follow up in real time and even adjust the direction of the processing means in a timely manner. In a specific embodiment, when the priority is low, for example, when a part of the monitoring equipment is not properly sensed, the notification module 140 will only send the notification to the processing personnel P and will not send it to the upper level, so that there will be no problem of rework. In a specific embodiment, if the first processing personnel P does not accept the task or rejects the task within a certain period of time, the notification module 140 will send a notification to the processing personnel P with the next highest relevance, and so on.

The following describes the alarm method of the second embodiment of the present invention. Referring to FIG. 4, the flowchart of the second embodiment of the alarm method of the present invention is shown, wherein the parsing step S310 and the task generation step S330 are the same as the parsing step S210 and the task generation step S230 of the first embodiment of the alarm method of the present invention, and will not be described in detail below. The second embodiment of the alarm method of the present invention also includes a personnel monitoring step S305 and a task monitoring step S390.

Please refer to the schematic diagrams of the personnel monitoring module 200 recording each processing personnel shown in FIG. 4 and FIG. 5. In the personnel monitoring step S305, the personnel monitoring module 200 is configured to generate the aforementioned attendance rules according to at least one of the shift of the processing personnel P and whether or not to go to work, and is configured to generate the aforementioned attendance rules according to the system type, assigned tasks and task processing speed of the processing personnel P. At least one of the above generates the aforementioned task experience, and provides the attendance rule and the task experience to the task assignment module 130. In a specific embodiment, the personnel monitoring module 200 and the task monitoring module 300 are connected in communication, and the personnel monitoring module 200 receives the result of each completion of the processing personnel P from the task monitoring module 300, thereby generating information on the task experience. In a specific embodiment, the personnel monitoring module 200 selects multiple processing personnel P from the processing personnel P who are currently on duty and not on duty and provides them to the task assignment module 130.

In the task assignment step S350, the task assignment module 130 is configured to determine the relevance between the multiple processing personnel P and the task based on the task generated by the task generation module 120 and the attendance rules and task experience of the multiple processing personnel P generated by the personnel monitoring module 200, and assign the task to at least one of the multiple processing personnel P based on the relevance, wherein the high relevance may be, for example, that the task assignment module 130 determines that the processing personnel P has a processing method for processing similar abnormal data and even processes it faster, or that the processing personnel P will not have the same state again after processing similar abnormal data, and the low relevance may be, for example, that the processing personnel P has no record of relevant processing methods.

In the notification step S370, similar to the notification step S270, the notification module 140 is configured to send a notification to at least one of the processing personnel based on the priority, wherein the notification at least includes the task.

Please refer to the schematic diagram of the first information of the present invention shown in Figure 6. In the task monitoring step S390, the task monitoring module 300 is configured to monitor a first information, which includes at least one of the status of the task, the processing flow of the processing personnel P, the processing method of the processing personnel P, and the processing time of the processing personnel P. In a specific embodiment, when processing, the processing personnel P reports the processing status to the task monitoring module 300. When the processing time of the processing personnel P exceeds the expected completion time in the task, the task monitoring step S390 will return to the task assignment step S350. The task monitoring module 300 provides the first information to the task assignment module 130, so that the task assignment module 130 can further re-determine the relevance of the plurality of processing personnel and the task based on the first information, and re-assign a suitable processing personnel P according to the relevance. Then, as in the notification step S370, the notification module 140 resends the notification to the reassigned processing personnel P.

In addition, the task monitoring module 300 is configured to provide the first information to the task generation module 120, so that the task generation module 120 can further associate the task based on the first information. Specifically, from the task monitoring step S390 to the task generation step S330, when the processing personnel P reports the processing flow and processing method to the task monitoring module 300 after processing, the task monitoring module 300 provides the first information to the task generation module 120 for access, so that the task generation module 120 can then associate the task with a better solution, and continue to execute the task assignment step S350 and the notification step S370.

In general, the present invention proposes an intelligent alarm system and alarm method. The present invention can use machine learning and natural language processing technologies to automatically classify and process abnormal data sent from the system. By analyzing the content and context of the abnormal data, the system can classify related abnormal data into the same event, generate corresponding processing tasks, and automatically assign them to corresponding processing personnel. In this way, the processing personnel can focus more on processing a single event without being disturbed by other abnormal data, thereby improving processing efficiency and accuracy. In addition, the present invention can also realize the deduplication and merging functions of abnormal data, avoiding the occurrence of rework problems. When multiple processing personnel receive abnormal data of the same event at the same time, the system can automatically merge these abnormal data into one task and assign it to one of the processing personnel for processing, thereby reducing the waste of repeated work by processing personnel and improving work efficiency.

However, it should be understood that the specific embodiments of the present invention are only for illustrative purposes, and various changes can be made without departing from the scope and spirit of the patent application of the present invention, and all should be included in the patent scope of the present invention. Therefore, the specific embodiments described in this specification are not used to limit the present invention, and the true scope and spirit of the present invention are disclosed in the following patent application scope.

100: Alarm system

110:Analysis module

120: Mission generation module

130:Task Assignment Module

140: Notification module

200: Personnel monitoring module

300: Mission monitoring module

P: Processing personnel

S: System

Claims (12)

An alarm system comprises: a parsing module, receiving abnormal data from a system, and parsing out keywords of the abnormal data based on natural language processing, thereby determining a category and a priority of the abnormal data according to the keywords; a task generation module, configured to store task data, and associate a task based on the task data and the keywords, wherein the task data is associated with the corresponding processing means when the system is in different abnormal states; a task assignment module, configured to determine the relevance of the multiple processing personnel to the task based on the attendance rules and task experience of the task and multiple processing personnel, and assign the task to at least one of the multiple processing personnel based on the relevance; and A notification module is configured to send a notification to at least one of the processing personnel based on the priority, wherein the notification includes the task; When the parsing module receives a plurality of the abnormal data and parses out a plurality of the keywords, the task generation module is configured to determine that the plurality of the abnormal data belongs to the same source based on the plurality of the keywords, and merge the abnormal data of the same source into the task. The alarm system as described in claim 1, wherein the analysis module determines the priority based on at least one of the severity, system type, weight, construction record, and online time of the abnormal data. The alarm system as described in claim 1 further includes a personnel monitoring module, which is configured to generate the attendance rules based on at least one of the shift of the processing personnel and whether the processing personnel is at work, and is configured to generate the task experience based on at least one of the system the processing personnel is responsible for, the assigned tasks and the task processing speed, and provide the attendance rules and the task experience to the task assignment module. The alarm system as described in claim 1 further includes a task monitoring module, which is configured to monitor a first information, wherein the first information includes at least one of the status of the task, the processing flow of the processing personnel, the processing method of the processing personnel, and the processing time of the processing personnel. The alarm system as described in claim 4, wherein the task monitoring module is configured to provide the first information to the task generation module so that the task generation module can further associate the task based on the first information. An alarm system as described in claim 4, wherein the task monitoring module is configured to provide the first information to the task assignment module so that the task assignment module further determines the relevance of the multiple processing personnel to the task based on the first information. An alarm method, comprising: a parsing step, receiving abnormal data from a system, and parsing the abnormal data based on a natural language processing to obtain a keyword, thereby determining a category and a priority of the abnormal data according to the keyword; a task generation step, storing a task data, and associating a task based on the task data and the keyword, wherein the task data is associated with the corresponding processing means when the system is in different abnormal states; a task assignment step, based on the attendance rules and task experience of the task and multiple processing personnel, determining the relevance of the multiple processing personnel to the task, and assigning the task to at least one of the multiple processing personnel based on the relevance; and A notification step is performed to send a notification to at least one of the processing personnel based on the priority, wherein the notification includes the task; When the parsing step receives a plurality of the abnormal data and parses out a plurality of the keywords, the task generation step determines that the plurality of the abnormal data belongs to the same source based on the plurality of the keywords, and merges the abnormal data of the same source into the task. The alarm method as described in claim 7, wherein the analysis step determines the priority based on at least one of the severity, system type, weight, construction record, and online time of the abnormal data. The alarm method as described in claim 7 further includes a personnel monitoring step, generating the attendance rule based on at least one of the shift of the processing personnel and whether the processing personnel is at work, and is configured to generate the task experience based on at least one of the system for which the processing personnel is responsible, the assigned tasks and the task processing speed, and provide the attendance rule and the task experience to the task assignment step, so that the task assignment step regenerates the task. The alarm method as described in claim 7 further includes a task monitoring step, which monitors a first information, and the first information includes at least one of the status of the task, the processing flow of the processing personnel, the processing method of the processing personnel, and the processing time of the processing personnel. As described in claim 10, the alarm method further provides the first information to the task generation step in the task monitoring module step, so that the task generation step further re-associates the task based on the first information. As described in claim 10, the alarm method further provides the first information to the task assignment step in the task monitoring module step, so that the task assignment step further re-determines the relevance of the multiple processing personnel to the task based on the first information.