Alarm information automatic analysis method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides an alarm information automatic analysis method and device, electronic equipment and a storage medium, and belongs to the technical field of industrial control. The method comprises the following steps: receiving alarm triggering information uploaded by alarm equipment, and extracting an alarm triggering point location, an alarm triggering type and an alarm triggering state in the alarm triggering information; calculating an alarm triggering deviation based on the alarm triggering type of the alarm triggering information and the alarm triggering state; rule matching is carried out on the alarm triggering point position and the alarm triggering deviation and prefabricated alarm point positions and prefabricated alarm deviations of a plurality of pieces of prefabricated alarm information in an alarm knowledge database, and the fitting degree of the alarm triggering information and the prefabricated alarm information is calculated; and obtaining matched alarm reason information according to the fitting degree, and outputting the matched alarm reason information. According to the embodiment of the invention, the alarm information can be automatically analyzed, the processing period of the alarm information is shortened, and the production efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of industrial control technology, and in particular to an automatic analysis method and device for alarm information, an electronic device, and a storage medium. Background Art

[0002] In modern industrial production, with the widespread application of automation equipment and complex systems, alarm systems play a vital role in monitoring and maintaining the stability and safety of production lines. However, the current alarm processing method mainly relies on the experience and judgment of operators, which seriously affects production efficiency and safety. In practical applications, when an alarm occurs, operators need to analyze, process and verify the alarm based on their personal experience. This process, especially when facing complex systems and equipment, often takes a long time to finally solve the problem, which in turn affects production efficiency and the normal operation of equipment. There are differences in the skill level, experience accumulation and judgment ability of different operators, resulting in different processing methods and results for the same alarm. This method not only affects the efficiency and accuracy of problem solving, but also increases the dependence of enterprises on highly skilled employees, making it difficult to achieve standardization of processing methods. For new employees or inexperienced operators, the processing of complex alarms often requires more time and guidance, which not only increases training costs, but also limits the effective transfer of knowledge and experience, affecting the overall operational efficiency of the enterprise. In order to meet these challenges, companies urgently need to develop an intelligent alarm processing system to automatically and accurately analyze alarm information, quickly identify the cause of the problem, and provide effective solutions, thereby reducing reliance on personal experience and shortening the processing cycle. Summary of the invention

[0003] The main purpose of the embodiments of the present application is to propose an automatic analysis method and device for alarm information, an electronic device and a storage medium, aiming to improve the processing efficiency of alarm information.

[0004] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present application proposes a method for automatically analyzing alarm information, the method comprising: Receive alarm trigger information uploaded by the alarm device, and extract the alarm trigger point, alarm trigger type and alarm trigger status in the alarm trigger information; Calculating an alarm trigger deviation based on the alarm trigger type of the alarm trigger information and the alarm trigger state; Perform rule matching on the alarm trigger point and the alarm trigger deviation with prefabricated alarm points and prefabricated alarm deviations of a plurality of prefabricated alarm information in the alarm knowledge database, and calculate the degree of fit between the alarm trigger information and the prefabricated alarm information; The matching alarm reason information is obtained according to the fit degree, and the matching alarm reason information is output.

[0005] In some embodiments, the step of calculating the alarm trigger deviation based on the alarm trigger type and the alarm trigger state of the alarm trigger information specifically includes: If the alarm trigger type of the alarm trigger information is an over-limit alarm, the alarm upper limit value and the alarm lower limit value of the alarm trigger point are obtained, and the alarm trigger deviation is calculated according to the alarm upper limit value, the alarm lower limit value and the alarm trigger state; If the alarm trigger type of the alarm trigger information is a fluctuation alarm, the normal operating state of the alarm trigger point is obtained, and the alarm trigger deviation is calculated according to the standard deviation of the normal operating state and the alarm trigger state.

[0006] In some embodiments, the step of calculating the alarm trigger deviation according to the alarm upper limit value, the alarm lower limit value and the alarm trigger state specifically includes: Calculate the difference between the alarm trigger state and the alarm upper limit value to obtain an alarm upper limit deviation value; Calculate the difference between the alarm trigger state and the alarm lower limit value to obtain the alarm lower limit deviation value; If the alarm upper limit deviation value is less than the alarm lower limit deviation value, the alarm trigger deviation is determined to be an over-upper limit deviation; If the alarm lower limit deviation value is less than the alarm upper limit deviation value, it is determined that the alarm trigger deviation is an over-lower limit deviation.

[0007] In some embodiments, the step of obtaining matching alarm reason information according to the fit degree and outputting the matching alarm reason information specifically includes: Compare the fit of the prefabricated alarm information with a preset fit threshold, obtain matching alarm cause information, and output the matching alarm cause information; If the fitting degrees of the prefabricated alarm information are all less than a preset fitting degree threshold, the corresponding prefabricated alarm information is output in order from high to low according to the fitting degrees.

[0008] In some embodiments, the matching alarm cause information includes prefabricated alarm points, prefabricated alarm deviations, prefabricated fault analysis, prefabricated fault points, prefabricated fault causes, prefabricated fault consequences, prefabricated interference measures, and prefabricated operation suggestions.

[0009] In some embodiments, the step of performing rule matching on the alarm triggering point and the alarm triggering deviation with prefabricated alarm points and prefabricated alarm deviations of a plurality of prefabricated alarm information in the alarm knowledge database, and calculating the degree of fit between the alarm triggering information and the prefabricated alarm information specifically includes: Calculating the cosine similarity between the alarm trigger point and the prefabricated alarm point to obtain the alarm point fitting degree; Based on the alarm triggering deviation and the prefabricated alarm deviation, obtaining an alarm deviation fitting degree; The fitting degree of the alarm point and the fitting degree of the alarm deviation are weighted averaged to obtain the fitting degree of the prefabricated alarm information.

[0010] In some embodiments, the step of outputting the matching alarm reason information further includes: If the matching alarm reason information includes a prefabricated fault point, the prefabricated fault point and the fault triggering state when the alarm is triggered are obtained, and the fault triggering state of the prefabricated fault point is displayed.

[0011] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application proposes an automatic analysis device for alarm information, the device comprising: An alarm receiving module is used to receive the alarm trigger information uploaded by the alarm device, and extract the alarm trigger point, alarm trigger type and alarm trigger status in the alarm trigger information; A deviation calculation module, used for calculating the alarm trigger deviation based on the alarm trigger type and the alarm trigger state of the alarm trigger information; A fitting calculation module, used for matching the alarm trigger point and the alarm trigger deviation with the prefabricated alarm points and prefabricated alarm deviations of a plurality of prefabricated alarm information in the alarm knowledge database, and calculating the fitting degree between the alarm trigger information and the prefabricated alarm information; The alarm output module is used to obtain matching alarm reason information according to the matching degree and output the matching alarm reason information.

[0012] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned automatic analysis method of alarm information when executing the computer program.

[0013] To achieve the above-mentioned purpose, the fourth aspect of the embodiments of the present application proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned automatic analysis method of alarm information is implemented.

[0014] The automatic alarm information analysis method and device, electronic device and storage medium proposed in the present application receive alarm trigger information, calculate the alarm trigger deviation through the alarm trigger information, match the alarm trigger deviation and the alarm trigger point with the prefabricated alarm information in the alarm knowledge database, and thus obtain the matching alarm information in the alarm knowledge database. Through the automatic analysis of the alarm information, the fault problem can be quickly identified and an effective solution can be provided, thereby reducing the reliance on personal experience and shortening the processing cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flow chart of the method for automatic analysis of alarm information provided by an embodiment of the present application; Figure 2 yes Figure 1 Flow chart of step S102 in FIG. Figure 3 yes Figure 1 Flow chart of step S103 in FIG. Figure 4 for Figure 1 Flow chart of step S104 in FIG. Figure 5 It is a structural diagram of the alarm information automatic analysis device provided in an embodiment of the present application; Figure 6 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0017] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0019] In modern industrial production, the widespread application of automation equipment and systems has made alarm processing an important part of ensuring production safety and stability. However, the current alarm processing method still mainly relies on the experience and judgment of operators, facing multiple challenges, which seriously affects production efficiency and consistency of alarm processing. First, the long processing cycle is a significant problem; when an alarm occurs, operators need to spend a lot of time analyzing, processing and verifying, especially in complex system and equipment environments. This manual processing method often delays the time to solve the problem. Secondly, the processing relies on personal experience, so different operators may adopt different processing methods when facing the same alarm due to differences in skill levels and experience, resulting in fluctuations in problem solving efficiency and accuracy. Insufficient experience or misjudgment of operators may directly affect production safety and equipment maintenance. In addition, the inefficiency of remote monitoring further increases the complexity of alarm processing. In the scenario of multi-site remote monitoring, operators cannot arrive at the site in time to check and deal with problems, resulting in delays in alarm processing. In this case, the alarm information cannot be responded to and processed quickly, increasing the risk of system operation. Difficulties in knowledge transfer are also a common problem in the industry. Faced with complex alarm scenarios, new employees or inexperienced personnel may find it difficult to make correct judgments in a timely manner, which prolongs the processing time and increases the difficulty of training and experience transfer.

[0020] Based on this, the embodiments of the present application provide a method and device for automatic analysis of alarm information, an electronic device and a storage medium, aiming to improve the efficiency and accuracy of alarm analysis. The method and device for automatic analysis of alarm information, an electronic device and a storage medium provided in the embodiments of the present application are specifically described through the following embodiments. First, the method for automatic analysis of alarm information in the embodiments of the present application is described.

[0021] The automatic analysis method of alarm information provided in the embodiment of the present application relates to the field of industrial control technology. The automatic analysis method of alarm information provided in the embodiment of the present application can be applied to a terminal, can be applied to a server side, or can be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or can be configured as a server cluster or a distributed system composed of multiple physical servers, or can be configured as 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, and big data and artificial intelligence platforms; the software can realize the application of the automatic analysis method of alarm information, etc., but is not limited to the above forms.

[0022] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0023] It should be noted that in each specific implementation of the present application, when it is necessary to perform relevant processing based on data related to user identity or characteristics such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of these data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0024] Figure 1 is an optional flowchart of the method for automatically analyzing alarm information provided in an embodiment of the present application. Figure 1 The method may include but is not limited to steps S101 to S104.

[0025] Step S101, receiving alarm trigger information uploaded by an alarm device, and extracting the alarm trigger point, alarm trigger type and alarm trigger status in the alarm trigger information; Step S102, calculating an alarm trigger deviation based on the alarm trigger type and the alarm trigger state of the alarm trigger information; Step S103, matching the alarm trigger point and the alarm trigger deviation with prefabricated alarm points and prefabricated alarm deviations of a plurality of prefabricated alarm information in an alarm knowledge database, and calculating the degree of fit between the alarm trigger information and the prefabricated alarm information; Step S104, obtaining matching alarm reason information according to the degree of fit, and outputting the matching alarm reason information.

[0026] Steps S101 to S104 shown in the embodiment of the present application realize intelligent analysis of alarm processing through automatic extraction of alarm information, calculation of deviation, database matching and fitting output, and help operators quickly judge and handle alarm situations.

[0027] Specifically, in the process of automatic analysis of alarm information, it is first necessary to receive the alarm trigger information uploaded by the alarm device, so as to obtain the original alarm data and perform preliminary analysis. The alarm trigger information includes the alarm trigger point, alarm trigger type and alarm trigger status. Among them, the alarm trigger point refers to the location or device where the alarm event occurs, such as the location of a sensor or a specific component of a machine has a problem. Extracting the alarm point helps to quickly locate the fault later; the alarm trigger type defines the nature of the alarm, such as equipment overtemperature, overpressure, vibration abnormality, etc. Different trigger types represent different faults or abnormal phenomena. The alarm trigger status describes the real-time status information of the alarm, usually including the alarm value, duration, frequency, etc. Through this step, the system can extract structured information from multiple data sources, laying the foundation for subsequent analysis. Next, it is necessary to calculate the alarm trigger deviation based on the alarm trigger type and alarm trigger status. The alarm trigger deviation includes the deviation type of the alarm trigger, such as whether the value is high or low when the alarm is triggered. Of course, it is not limited to the deviation of the alarm trigger. By calculating the direction and deviation of the alarm trigger deviation vector, the system can preliminarily judge the severity and possible causes of the alarm. If the deviation is large, it may mean that the equipment has a serious fault or needs emergency treatment; if the deviation is small, it may be a regular warning or a temporary abnormality, and it can also help the system provide accurate data basis for the next step of rule matching and alarm fitting. Then, the system will use the pre-established alarm knowledge base for rule-based matching. The knowledge base usually contains a large amount of historical alarm data, equipment models and failure mode information. The alarm knowledge database stores information such as historical equipment operation data, known alarm modes, fault causes and treatment plans. The prefabricated alarm information includes the trigger point and deviation data of each alarm type. The system compares the currently extracted alarm trigger point and deviation with the prefabricated alarm information already in the database. The system will match one by one according to the rule set (such as fault model, equipment characteristics) and calculate the similarity between the current alarm information and the historical alarm information. The degree of fit is the degree of match between the current alarm information and the prefabricated alarm information in the database. The higher the degree of fit, the closer the current alarm event is to a certain known failure mode. The calculation of the degree of fit can be based on multiple parameters, such as the similarity of the trigger point, trigger type and deviation, and the final result can be obtained through weighted algorithms. Finally, based on the fit analysis of the previous step, the system outputs the most matching alarm information, including possible fault causes and treatment suggestions. Through this output, the system can help operators quickly determine the severity of the problem, shorten the problem diagnosis time, and improve the efficiency of alarm processing. For inexperienced operators, the suggestions provided by the system can be used as a reference for decision-making, thereby reducing operational errors. Through the four steps of receiving alarm information, calculating deviations, matching with the knowledge database, and outputting alarm information, the automatic analysis and processing of alarm information is effectively realized.This method can not only improve the efficiency of alarm processing and reduce human errors, but also gradually improve the intelligence level of the system through continuous accumulation of data and rule optimization.

[0028] See also Figure 2 In some embodiments, step S102 may include but is not limited to steps S1021 to S1022: Step S1021, if the alarm trigger type of the alarm trigger information is an over-limit alarm, obtaining the alarm upper limit value and the alarm lower limit value of the alarm trigger point, and calculating the alarm trigger deviation according to the alarm upper limit value, the alarm lower limit value and the alarm trigger state; Step S1022: if the alarm trigger type of the alarm trigger information is a fluctuation alarm, the normal operating state of the alarm trigger point is obtained, and the alarm trigger deviation is calculated according to the standard deviation of the normal operating state and the alarm trigger state; Specifically, when the alarm trigger type is an over-limit alarm, that is, the monitoring parameter exceeds the upper or lower limit range set by the device or system, the system needs to calculate the alarm trigger deviation through the set threshold. First, the system extracts the upper and lower limit values ​​of the alarm point from the configuration data of the device or system. These values ​​are usually pre-set according to the normal operating range or safe operating range of the device. For example, the alarm upper limit value of a temperature sensor is 100℃ and the lower limit value is 50℃, which defines the safe temperature range of the device. Based on the current alarm trigger state, that is, the actual measured value, the system compares it with the upper or lower limit value. If the actual measured value exceeds the upper limit, the deviation is the difference between the actual value and the upper limit value; if the actual value is lower than the lower limit, the deviation is the difference between the lower limit value and the actual value. The larger the deviation, the more serious the over-limit. For example, if the actual temperature reaches 120℃ and the upper limit value is 100℃, the deviation is 20℃. In this way, the system can accurately calculate the deviation of the over-limit alarm and evaluate the severity of the alarm accordingly. This method is mainly used to detect parameters with clear upper and lower limit thresholds, such as temperature, pressure, voltage, etc. When the alarm trigger type is a fluctuation alarm, that is, the fluctuation of the parameter value in a short period of time exceeds the normal fluctuation range, the system will calculate the alarm trigger deviation based on the fluctuation of the parameter. The system first needs to obtain the normal operating state of the alarm trigger point. This state can usually be defined by historical data or long-term equipment operation records. The normal state reflects the stable value or normal fluctuation range of the equipment or system under ideal conditions. The trigger deviation of the fluctuation alarm is evaluated by calculating the standard deviation between the actual trigger state and the normal operating state. The standard deviation is a statistical indicator used to measure the fluctuation range of the value. If the current fluctuation range is far beyond the normal standard deviation range, the system will calculate the corresponding deviation value. This means that the more severe the fluctuation, the greater the deviation, and the system will judge the degree of abnormal fluctuation based on this. By calculating the standard deviation, it can be determined that the fluctuation of the current parameter exceeds the normal fluctuation range. This calculation method is suitable for systems or equipment that are sensitive to fluctuations, such as vibration sensors, flow monitoring systems, etc. By combining the alarm type and the specific calculation method, the system can provide more accurate alarm trigger deviation calculation results, thereby providing an accurate data basis for subsequent alarm analysis and processing.

[0029] In some embodiments, step S1021 specifically includes: Calculate the difference between the alarm trigger state and the alarm upper limit value to obtain an alarm upper limit deviation value; Calculate the difference between the alarm trigger state and the alarm lower limit value to obtain the alarm lower limit deviation value; If the alarm upper limit deviation value is less than the alarm lower limit deviation value, the alarm trigger deviation is determined to be an over-upper limit deviation; If the alarm lower limit deviation value is less than the alarm upper limit deviation value, it is determined that the alarm trigger deviation is an over-lower limit deviation.

[0030] Specifically, in the transmission of over-limit information, it is generally not specifically marked whether it exceeds the upper limit or the lower limit, but only the value of the alarm trigger state can be transmitted. Therefore, it is necessary to judge the current over-limit state according to the value of the alarm trigger state and calculate the deviation value at the same time. According to the current alarm trigger state, the alarm upper limit value and the alarm lower limit value, the absolute value is calculated to obtain the alarm upper limit deviation value and the alarm lower limit deviation value. By comparing the alarm upper limit deviation value and the alarm lower limit deviation value, if the alarm upper limit deviation value is less than the alarm lower limit deviation value, the system will determine that the alarm trigger deviation is an over-upper limit deviation. This indicates that the current state exceeds the safe operation upper limit of the equipment and measures need to be taken immediately. On the contrary, if the alarm lower limit deviation value is less than the alarm upper limit deviation value, the alarm trigger deviation is determined to be an over-lower limit deviation. This indicates that the current state is lower than the safe operation lower limit of the equipment, and appropriate treatment measures are also needed. By dividing the over-limit alarm into an over-upper limit deviation and an over-lower limit deviation, the system can identify the problem more accurately and match the corresponding treatment strategy for different situations. By refining the difference calculation and judgment process in step S1021, the system can effectively distinguish different types of over-limit alarms and provide an accurate basis for subsequent processing. This structured alarm analysis method not only improves the intelligence of the system, but also enables efficient and reliable alarm management in complex industrial environments.

[0031] See also Figure 4 In some embodiments, step S104 may include but is not limited to steps S1041 to S1042: Step S1041, comparing the fit of the prefabricated alarm information with a preset fit threshold, obtaining matching alarm cause information, and outputting the matching alarm cause information; Step S1042, if the fitting degrees of the prefabricated alarm information are all less than a preset fitting degree threshold, the corresponding prefabricated alarm information is output in order according to the fitting degree from high to low; Specifically, the calculated fit of the prefabricated alarm information is first compared with the preset fit threshold, which is usually set by industry standards, equipment characteristics or empirical values. If the fit of the prefabricated alarm information is greater than or equal to the preset fit threshold, the system will consider the alarm information to be matching alarm cause information, which usually includes possible fault causes and processing suggestions. The system will present these matching alarm cause information to the operator in a visual manner, such as popping up a warning or generating a report on the monitoring interface. The output content should include the alarm type, trigger point, fit value and corresponding processing suggestions. If it is detected that the fit of all prefabricated alarm information is lower than the preset fit threshold, it means that no known fault mode can fully match the current alarm trigger information. This situation usually indicates that the current alarm may be a new fault or an unrecorded abnormal situation. The system sorts all prefabricated alarm information below the fit threshold from high to low according to the fit. Although this information may not be completely matched, it may still contain relevant prompts or suggestions for the problem. After sorting, the system will output these prefabricated alarm information in sequence to help operators obtain possible fault clues, although the reliability of these clues is relatively low. In this way, the operator can check and troubleshoot one by one according to the current situation. By setting the fit threshold, the system can ensure that the output alarm information has a high relevance, thereby improving the accuracy of fault diagnosis. By refining the matching and sorting output process in step S104, the system can effectively analyze and display the alarm information, which not only improves the efficiency and accuracy of fault identification, but also provides flexible decision support for operators, especially in the face of complex industrial environments and changing fault conditions.

[0032] In some embodiments, the matching alarm reason information includes prefabricated alarm points, prefabricated alarm deviations, prefabricated fault analysis, prefabricated fault points, prefabricated fault causes, prefabricated fault consequences, prefabricated interference measures, and prefabricated operation suggestions.

[0033] Specifically, the matching alarm cause information is the alarm-related fault information obtained from the alarm knowledge database. The matching alarm cause information includes multiple key elements, which can help operators quickly understand the nature of the alarm and take appropriate treatment measures. The prefabricated alarm point indicates the specific location that needs to be monitored in the equipment or system, such as sensors, valves or other key components. By indicating the alarm point, the operator can quickly locate the area where the fault occurs, which is convenient for inspection and processing. The prefabricated alarm deviation indicates the deviation direction and deviation value between the current state and the set normal operating range, which is usually a specific value that exceeds the upper or lower limit. By providing the deviation value, the system can quantify the severity of the fault and help operators assess the urgency of the problem. Prefabricated fault analysis conducts a detailed analysis of the causes of possible faults, including fault modes and their effects. By analyzing the potential causes of the fault, the operator can have a deeper understanding of the mechanism behind the fault and take more effective measures. The prefabricated fault point is similar to the prefabricated alarm point, but focuses on the specific location where the fault occurs. It is usually determined after the fault analysis. By clarifying the source of the fault, it is convenient for operators to conduct targeted inspections and repairs. Prefabricated fault causes list possible causes of alarms, which may include factors such as equipment damage, operating errors or external interference. By identifying the causes of faults, operators can conduct targeted investigations to reduce the risk of repeated faults. Prefabricated fault consequences describe the possible consequences of failures if they are not handled in a timely manner, including equipment damage, production stagnation or safety hazards, thereby emphasizing the severity of the fault, increasing the vigilance of operators, and prompting them to take timely measures. Prefabricated interference measures are emergency measures that should be taken when a fault occurs to reduce the impact on the production process, provide specific operational suggestions, help operators quickly respond to emergencies, and reduce losses and risks. Prefabricated operational suggestions provide specific operational steps or suggestions based on fault analysis and evaluation results to help operators solve problems. Through clear operational suggestions, they reduce reliance on personal experience and improve the efficiency and accuracy of fault handling. Rich matching alarm cause information provides strong support for fault management in industrial production. Through detailed fault analysis and operational suggestions, the system can help operators make quick and accurate decisions in complex environments, thereby improving production efficiency, reducing risks, and ensuring safety.

[0034] See also Figure 3 In some embodiments, step S103 may include but is not limited to steps S1031 to S1033: Step S1031, calculating the cosine similarity between the alarm trigger point and the prefabricated alarm point to obtain the alarm point fitting degree; Step S1032, obtaining an alarm deviation fitting degree based on the alarm triggering deviation and the prefabricated alarm deviation; Step S1033: performing weighted average of the alarm point fitting degree and the alarm deviation fitting degree to obtain the fitting degree of the prefabricated alarm information.

[0035] Specifically, in the process of calculating the fit of the prefabricated alarm information and the alarm trigger information, it is necessary to calculate the fit of the alarm point and the fit of the alarm deviation respectively. In the process of calculating the fit of the alarm point, the cosine similarity can be used for calculation. In the alarm information, the alarm point is generally constructed in the form of a combination of letters and numbers. Therefore, the alarm trigger point and the prefabricated alarm point are regarded as vectors respectively, and the dot product and its modulus between the two vectors are calculated. The cosine similarity value obtained is the fit of the alarm point, which quantifies the similarity between the alarm trigger point and the prefabricated alarm point. The fit of the alarm deviation measures the similarity between the alarm trigger deviation and the prefabricated alarm deviation. In the calculation process, the alarm trigger deviation and the prefabricated alarm deviation need to be regarded as two different vectors respectively. For example, the deviation exceeding the upper limit is a positive direction vector, and the deviation exceeding the lower limit is a negative direction vector. The error between the two vectors is calculated and normalized to obtain the fit of the alarm deviation. Finally, by combining the fit of the alarm point and the fit of the alarm deviation, the overall matching of the alarm information can be comprehensively evaluated. Through calculation, the system can more accurately evaluate the matching degree between the alarm trigger information and the pre-set alarm information, ensuring the pertinence and effectiveness of the alarm processing. By setting weights, the system can flexibly adjust according to the actual situation and improve the intelligent level of fault processing.

[0036] In some embodiments, the step of outputting the matching alarm reason information further includes: If the matching alarm reason information includes a prefabricated fault point, the prefabricated fault point and the fault triggering state when the alarm is triggered are obtained, and the fault triggering state of the prefabricated fault point is displayed.

[0037] Specifically, when the matched alarm information contains information related to a prefabricated fault point, the point will be identified and its specific location will be obtained, and the operating status of the fault point at the time of the alarm will be read, including the operating status, parameter values ​​and status indications, etc., and the historical operating data of the fault point will be automatically captured to help analyze the cause of the fault. The real-time status information of the prefabricated fault point obtained is displayed to the operator, and the display content can be the name, location, status value, etc. of the fault point. By displaying the status of the fault point when the fault is triggered, it is convenient for the operator to quickly determine the problem and evaluate the severity of the fault, while helping the operator to narrow the scope of investigation and accurately locate the problem. When the matched alarm information is associated with the prefabricated fault point, the system can not only provide the alarm matching results, but also further display the status of the relevant points to help the operator better understand the fault behind the alarm. By directly displaying the trigger status of the prefabricated fault point, the operator does not need to search or check other locations, which will greatly improve the efficiency of fault handling.

[0038] See also Figure 5 The embodiment of the present application also provides an automatic analysis device for alarm information, the device comprising: The alarm receiving module 101 is used to receive the alarm trigger information uploaded by the alarm device, and extract the alarm trigger point, alarm trigger type and alarm trigger status in the alarm trigger information; Deviation calculation module 102, used for calculating alarm trigger deviation based on the alarm trigger type and the alarm trigger state of the alarm trigger information; A fitting calculation module 103 is used to match the alarm trigger point and the alarm trigger deviation with the prefabricated alarm points and prefabricated alarm deviations of a plurality of prefabricated alarm information in the alarm knowledge database, and calculate the fitting degree between the alarm trigger information and the prefabricated alarm information; The fitting calculation module 104 is used to obtain matching alarm reason information according to the matching degree and output the matching alarm reason information.

[0039] The specific implementation of the automatic alarm information analysis device is basically the same as the specific implementation of the automatic alarm information analysis method described above, and will not be repeated here.

[0040] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned alarm information automatic analysis method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0041] See also Figure 6 , Figure 6 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes: The processor 601 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory 602 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 602 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 602, and the processor 601 calls and executes the automatic analysis method of alarm information in the embodiment of this application; Input / output interface 603, used to implement information input and output; Communication interface 604, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.); A bus 605 that transmits information between various components of the device (e.g., processor 601, memory 602, input / output interface 603, and communication interface 604); The processor 601 , the memory 602 , the input / output interface 603 and the communication interface 604 are connected to each other in communication within the device via a bus 605 .

[0042] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned automatic analysis method of alarm information is implemented.

[0043] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0044] The embodiments of the present application provide an automatic alarm information analysis method, an automatic alarm information analysis device, an electronic device, and a storage medium, which calculate the degree of fit between the alarm trigger information and the prefabricated alarm information in the alarm knowledge database, thereby outputting highly matched alarm cause information to assist maintenance personnel in performing device maintenance.

[0045] The description of the embodiments of the present application is intended to more clearly illustrate the technical solutions of the embodiments of the present application and does not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0046] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0047] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0048] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0049] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0050] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0051] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0052] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0053] The preferred embodiments of the present application are described above with reference to the accompanying drawings, but the scope of the rights of the present application is not limited thereto. Any modification, equivalent substitution and improvement made by those skilled in the art without departing from the scope and essence of the present application should be within the scope of the rights of the present application.

Claims

1. A method for automatic analysis of alarm information, characterized in that: The method comprises: Receive alarm trigger information uploaded by the alarm device, and extract the alarm trigger point, alarm trigger type and alarm trigger status in the alarm trigger information; Calculating an alarm trigger deviation based on the alarm trigger type of the alarm trigger information and the alarm trigger state; Perform rule matching on the alarm trigger point and the alarm trigger deviation with prefabricated alarm points and prefabricated alarm deviations of a plurality of prefabricated alarm information in the alarm knowledge database, and calculate the degree of fit between the alarm trigger information and the prefabricated alarm information; The matching alarm reason information is obtained according to the fit degree, and the matching alarm reason information is output.

2. The method for automatic analysis of alarm information according to claim 1, characterized in that: The step of calculating the alarm trigger deviation based on the alarm trigger type and the alarm trigger state of the alarm trigger information specifically includes: If the alarm trigger type of the alarm trigger information is an over-limit alarm, the alarm upper limit value and the alarm lower limit value of the alarm trigger point are obtained, and the alarm trigger deviation is calculated according to the alarm upper limit value, the alarm lower limit value and the alarm trigger state; If the alarm trigger type of the alarm trigger information is a fluctuation alarm, the normal operating state of the alarm trigger point is obtained, and the alarm trigger deviation is calculated according to the standard deviation of the normal operating state and the alarm trigger state.

3. The method for automatic analysis of alarm information according to claim 2, characterized in that: The step of calculating the alarm trigger deviation according to the alarm upper limit value, the alarm lower limit value and the alarm trigger state specifically includes: Calculate the difference between the alarm trigger state and the alarm upper limit value to obtain an alarm upper limit deviation value; Calculate the difference between the alarm trigger state and the alarm lower limit value to obtain the alarm lower limit deviation value; If the alarm upper limit deviation value is less than the alarm lower limit deviation value, the alarm trigger deviation is determined to be an over-upper limit deviation; If the alarm lower limit deviation value is less than the alarm upper limit deviation value, it is determined that the alarm trigger deviation is an over-lower limit deviation.

4. The method for automatic analysis of alarm information according to claim 1, characterized in that: The step of obtaining matching alarm reason information according to the fit degree and outputting the matching alarm reason information specifically includes: Compare the fit of the prefabricated alarm information with a preset fit threshold, obtain matching alarm cause information, and output the matching alarm cause information; If the fitting degrees of the prefabricated alarm information are all less than a preset fitting degree threshold, the corresponding prefabricated alarm information is output in sequence according to the fitting degrees from high to low.

5. The method for automatic analysis of alarm information according to claim 1, characterized in that: The matching alarm reason information includes prefabricated alarm points, prefabricated alarm deviations, prefabricated fault analysis, prefabricated fault points, prefabricated fault causes, prefabricated fault consequences, prefabricated interference measures, and prefabricated operation suggestions.

6. The method for automatic analysis of alarm information according to claim 1, characterized in that: The step of matching the alarm trigger point and the alarm trigger deviation with the prefabricated alarm points and prefabricated alarm deviations of a plurality of prefabricated alarm information in the alarm knowledge database, and calculating the degree of fit between the alarm trigger information and the prefabricated alarm information specifically includes: Calculating the cosine similarity between the alarm trigger point and the prefabricated alarm point to obtain the alarm point fitting degree; Based on the alarm triggering deviation and the prefabricated alarm deviation, obtaining an alarm deviation fitting degree; The fitting degree of the alarm point and the fitting degree of the alarm deviation are weighted averaged to obtain the fitting degree of the prefabricated alarm information.

7. The method for automatic analysis of alarm information according to claim 1, characterized in that: The step of outputting the matching alarm reason information also includes: If the matching alarm reason information includes a prefabricated fault point, the prefabricated fault point and the fault triggering state when the alarm is triggered are obtained, and the fault triggering state of the prefabricated fault point is displayed.

8. An automatic alarm information analysis device, characterized in that: The device comprises: An alarm receiving module is used to receive the alarm trigger information uploaded by the alarm device, and extract the alarm trigger point, alarm trigger type and alarm trigger status in the alarm trigger information; A deviation calculation module, used for calculating the alarm trigger deviation based on the alarm trigger type and the alarm trigger state of the alarm trigger information; A fitting calculation module, used for matching the alarm trigger point and the alarm trigger deviation with the prefabricated alarm points and prefabricated alarm deviations of a plurality of prefabricated alarm information in the alarm knowledge database, and calculating the fitting degree between the alarm trigger information and the prefabricated alarm information; The alarm output module is used to obtain matching alarm reason information according to the matching degree and output the matching alarm reason information.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the automatic analysis method of alarm information according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for automatically analyzing alarm information according to any one of claims 1 to 7 is implemented.

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