136 results about "Alarm analysis" patented technology

The invention relates to an intelligent monitoring alarm method and system for a motor controller, and the method comprises the steps: obtaining an internal circuit signal and a body vibration signal of the motor controller, carrying out the combined noise analysis, and generating a dynamic noise baseline; performing component fault identification based on the dynamic noise baseline and the internal circuit signal to obtain a fault precursor current feature; performing component impact response separation based on the dynamic noise baseline and the body vibration signal to obtain hidden fault vibration characteristics; performing component association mapping on the fault precursor current feature and the hidden fault vibration feature to obtain an internal fault component identifier; and performing alarm analysis based on the fault component identifier, the fault precursor current feature and the hidden fault vibration feature to obtain a graded alarm decision. According to the invention, early fault features can be captured more sensitively, and false alarms and missing alarms are reduced.

The invention relates to the technical field of large model agent application, and discloses a hierarchical management alarm analysis and prediction implementation method based on a large model agent, and the method comprises the steps: obtaining historical alarm logs and real-time operation parameters of a target system, and constructing a hierarchical management feature library; designing an alarm grading evaluation framework and determining a multi-source data acquisition scheme; collecting multi-dimensional alarm data, and carrying out alarm grade judgment and abnormal mode recognition through a large model agent; and transmitting an analysis and prediction result to a management decision module to optimize a grading strategy. According to the invention, through multi-modal data fusion, dynamic weight distribution and intelligent analysis, the problems of single data processing and rigid grade division in traditional alarm management are solved, accurate classification and prediction of alarms are realized, and the operation and maintenance efficiency and reliability of the system are improved.

The invention provides a remote control method and device for a security system, equipment and a storage medium, and the method comprises the steps: carrying out the feature extraction of security data of a fire alarm host, and obtaining a fire alarm scene vector; a preset linkage strategy library is matched according to the fire alarm scene vector, and a PTZ positioning instruction is obtained; controlling a camera to collect an alarm image based on the PTZ positioning instruction; based on a preset fire alarm analysis model, generating an alarm confirmation report according to the alarm condition image and the fire alarm scene vector; and notifying a plurality of preset user terminals to perform remote interaction according to the alarm confirmation report, and performing start-stop control on the fire-fighting equipment.

The invention relates to a power plant temperature control system safety protection device and system. The power plant temperature control system safety protection device comprises a redundant temperature acquisition module, a temperature control safety processing module, an actuator control protection module, an intelligent strategy recovery module and a communication and alarm module. Through multi-point temperature data acquisition, abnormal trend intelligent identification and local linkage control, the device realizes quick response and protection control of temperature control abnormity of a key area of a boiler thermodynamic system. The system supports data interconnection with a DCS platform and an alarm analysis platform, has local independent operation and remote centralized management capabilities, and is suitable for temperature control safety protection of high heat load areas such as boilers of coal-fired power plants.

The invention discloses an alarm information research and judgment noise reduction method. According to the method, multiple pieces of alarm information with internal relation are combined into a structured alarm cluster through deep mining and by utilizing context association information between alarm events, so that redundant information is greatly compressed, and the alarm signal-to-noise ratio is improved. And multi-dimensional and comprehensive evaluation is carried out on the alarm cluster by fusing three mechanisms of information entropy analysis, customization rule evaluation and semantic evaluation of a large model, so that high threat alarms can be identified more accurately. Wherein the information entropy analysis helps to identify potential unknown threats by quantifying the uncertainty of the alarm, and the large model semantic evaluation can deeply analyze the alarm content, so that the accuracy and efficiency of alarm analysis are improved.

The invention discloses an alarm analysis method, device and equipment, and the method comprises the steps: determining a target DAG matched with a target alarm analysis scene from a preset directed acyclic graph DAG; the DAG comprises a plurality of rule judgment nodes; the rule judgment nodes comprise at least one natural language rule judgment node, and each natural language rule judgment node is used for calling a large language model based on a preset prompt text to perform binary classification judgment on the input alarm data; inputting the alarm data into the target DAG, and generating a node hit track of the alarm data; the node hit track is used for recording a rule judgment node triggered by the alarm data and a corresponding judgment result; and obtaining an alarm analysis result based on the node hit trajectory. According to the invention, the automatic, interpretable and traceable research and judgment process of the alarm can be realized, and the accuracy, interpretability and maintenance convenience of alarm analysis are improved.

The invention provides a multi-source log fusion driven database monitoring method and system, and relates to the technical field of computers.The method comprises the steps that format analysis processing is conducted on multi-source heterogeneous logs of a to-be-monitored database on the basis of a dynamic analysis template library, and initial database logs are obtained; performing data preprocessing on the initial database log based on a rule engine to obtain a database log; and performing streaming processing on the database log to obtain a log event stream, and sending the log event stream to the server side, so that the server side detects the log event stream based on the log anomaly detection model and the associated alarm analysis engine, and generates a monitoring analysis result of the to-be-monitored database. By means of the mode, the technical bottleneck that heterogeneous database logs are difficult to analyze is broken through, the problem that the terminal is poor in database log format compatibility can be solved, invalid data transmission between the terminal and the server side is effectively reduced, and the database monitoring effect is improved.

The invention discloses a direct current B code wave recording alarm analysis device and method based on an FPGA, and relates to the technical field of power system automation and signal analysis, and the device comprises an FPGA collection module which is used for collecting a TTL level signal of a direct current B code in real time at a preset sampling frequency, recording a high-precision timestamp of each sampling point, and carrying out the subsequent pulse parameter calculation; the pulse width measurement module is connected with the FPGA acquisition module, is used for calculating the pulse width of the current pulse based on the rising edge timestamp and the falling edge timestamp of the signal, triggering a wave recording module, and is used for starting wave recording operation when the pulse width is detected to exceed a preset threshold range or abnormity occurs for a plurality of times continuously; collecting complete waveform data before and after the fault; the DC B code wave recording alarm analysis device and method based on the FPGA improve the intelligent level, response speed and fault visualization capability of a B code monitoring system, and are especially suitable for high-reliability monitoring and management scenes of key synchronization signals in a DC system.

The invention relates to an intelligent alarm analysis method and device, and a medium. The method comprises the following steps: receiving aggregated alarm data; matching alarm rules in the aggregated alarm data with strong rules in an intelligent rule base; if the strong rule is hit, performing attack judgment based on the strong rule; if the strong rule is not hit, preliminarily analyzing the aggregated alarm data; based on a preliminary analysis result, issuing a traffic acquisition task to acquire associated traffic data; analyzing the associated flow data by using an AI alarm analysis model, and outputting an attack judgment result; generating a security event report based on the attack judgment result; combining the security event report with the corresponding aggregated alarm data and the attack judgment result into a security event; and outputting the security event to a security event early warning notification module. By constructing an automatic and multi-level analysis decision system, various problems confronted by traditional manual analysis are effectively solved.

The invention provides an intelligent alarm analysis and diagnosis method and device based on an AI algorithm, and the method comprises the steps: obtaining historical alarm data, and generating an intelligent alarm analysis and diagnosis large model according to the historical alarm data and historical disposal data; acquiring all real-time alarm data in a preset time window, inputting all the real-time alarm data into the intelligent alarm analysis and diagnosis large model, and associating all the real-time alarm data into a plurality of combined alarm records through an alarm association engine, according to the type confidence degree distribution of each combined alarm record by the trend classification model and the component probability distribution of each combined alarm record by the component positioning model, the fault type and the specific fault position are obtained; and generating an alarm disposal suggestion for each combined alarm record according to the fault type and the specific fault position by the matching disposal rule, and then distributing the alarm disposal suggestion. According to the invention, the problems of difficult alarm problem tracing, difficult problem root cause positioning and long fault recovery time are solved.

The invention provides an intelligent launching pad management system based on AI visual auxiliary supervision. The system carries out target identification through a YOLO model, carries out behavior sequence analysis in combination with an LSTM model, and carries out cross-modal dynamic feature fusion through spatio-temporal feature alignment, time sequence and spatial feature enhancement and a graph convolution network and graph attention mechanism to generate globally optimized feature representation. And further utilizing a knowledge reasoning engine to combine with the case database and the equipment knowledge graph to generate an intelligent emergency processing scheme. And finally, generating a preliminary potential safety hazard analysis report based on a Transform technology, and performing semantic calibration in combination with the central control module and the domain knowledge base to generate an accurate and normalized alarm analysis report. The system also has the functions of adaptive algorithm optimization, multi-modal data fusion processing and real-time alarm and feedback, realizes the intelligent and automatic management of the launching pad, improves the safety supervision efficiency and fault processing capability, and effectively improves the intelligent level of the safety management of the launching pad.

The invention discloses a root cause alarm analysis method and system based on time sequence association and multi-modal fusion, and the method comprises the steps: taking digital twin dynamic threshold cleaning as a core, fusing multi-source data time sequence alignment verification, and forming a multi-source data set of time sequence alignment and preliminary restoration through exception handling and cross-system time consistency verification; a cleaning threshold is optimized in combination with a working condition to filter noise, a label confidence weighting method is fused, confidence is given to a label through twin simulation, and a multi-modal data set with a multi-dimensional label is constructed. A learning model is constructed and trained, exclusive feature extraction branches are designed for multi-source data, a twin working condition adaptation enhancement module is introduced to strengthen core modal extraction, and the proportion of abnormal modals in fusion is reduced by means of a dynamic attention filtering mechanism. Based on the model and a twinning system, root cause penetration type positioning is completed through dynamic sequencing of root cause confidence in combination with a twinning reduction time sequence. And the root cause analysis efficiency and accuracy are improved.

The invention discloses a monitoring, alarming and early warning method and system based on numerical analysis and coupling analysis. The method comprises the following steps: acquiring monitoring data of each industry based on urban safety development evaluation from a plurality of data sources and preprocessing the monitoring data; calculating the preprocessed monitoring data by using an alarm logic formula based on static numerical analysis and dynamic numerical analysis, and determining whether to give an alarm or not according to a calculation result; according to an alarm logic formula, determining an association relationship and an interaction factor of multi-source alarm, and according to the association relationship and the interaction factor, performing association coupling early warning analysis and spatial coupling early warning analysis on each monitoring data; through the preset big data analysis model, urban safety event prediction and early warning prompt are carried out based on the coupling early warning analysis result, and through an alarm analysis mechanism and an early warning analysis mechanism which are widely applied and fully verified, the alarm accuracy and the early warning effectiveness in a cross-industry, cross-organization and cross-region monitoring scene are effectively improved.

The invention belongs to the field of information network security. The invention specifically discloses an agent-based logic vulnerability detection method, system and device, and a medium. The method comprises the following steps: capturing service system request response data through network traffic, identifying an HTTP protocol through a port and protocol features, filtering non-HTTP request data, extracting and analyzing the request data, standardizing extracted parameters, continuously collecting and analyzing through an API analysis agent, improving the semantic analysis capability of a large model, perfecting a logic relation graph, and improving the semantic analysis efficiency of the large model. A complete vulnerability life cycle data link is constructed through a vulnerability analysis agent, the system logic vulnerability mining efficiency and coverage are improved, and automatic logic vulnerability alarm and disposal can be realized and the risk disposal real-time performance is improved by accessing the agent to a network security protection product, an alarm analysis platform and other systems.

The invention relates to the technical field of data analysis, and particularly provides a keyword-based alarm analysis method and device, a medium and equipment, and the method can comprise the steps: obtaining the occurrence frequency of a keyword in a to-be-processed data stream in a preset time period; obtaining an abnormal parameter of the keyword based on the average frequency of the keyword in the corresponding historical preset time period and a pre-constructed target model; wherein the target model is a distribution class model based on probability statistics; and determining whether alarm information is generated or not according to the abnormal parameters and the occurrence frequency. According to some embodiments of the invention, accurate and automatic monitoring of keyword abnormity can be realized, false alarm and missing alarm of alarm are effectively reduced, and alarm precision is improved.

The invention discloses an alarm confirmation method and device and a storage medium, and the method comprises the steps: obtaining a to-be-confirmed alarm which has been notified to an operation and maintenance system which comprises at least one of a business system, a technical system and an infrastructure system; and matching the to-be-confirmed alarm with confirmation rules to determine whether the to-be-confirmed alarm needs to establish an order, the confirmation rules including an order establishment confirmation rule and an order non-establishment confirmation rule. According to the technical scheme, the problems that in the prior art, alarm information is not accurate, frequent manual confirmation is needed, the alarm analysis workload is increased, and the application range is narrow are at least solved.

The application discloses a video alarm method, device and equipment and a computer readable storage medium. The method comprises the following steps: detecting a first video image by using a first alarm target detection model to obtain a detection result; obtaining a first feature group, wherein the first feature group at least comprises a time feature value, a position feature value and a model feature value corresponding to a first target; matching the same type of feature values in the first feature group and a second feature group to obtain a matching result, wherein the second feature group at least comprises one or more feature values selected from the time feature value, the position feature value and the model feature value corresponding to a second target by a person; determining an alarm analysis result of the first target according to the matching result between the first feature group and a feature group corresponding to at least one false alarm target; and outputting alarm information corresponding to the first target when it is determined according to the alarm analysis result that the first target needs to be alarmed. The application reduces the false alarm rate of video alarm.

The invention discloses an alarm integration method applied to a signal centralized monitoring system, and the method comprises the steps: carrying out the classification of an alarm integration model based on a business mechanism for a large number of common invalid alarms on site; pre-defined alarm integration rules are written for the alarm integration model, and the signal centralized monitoring system carries out alarm integration according to the pre-defined alarm integration rules in a default mode; the alarm analysis module performs alarm analysis according to the collected data, and enters a short-time cache queue after an alarm occurs; when the alarm in the cache accords with a predefined alarm integration rule, sending the alarm after alarm integration for prompting; and displaying the alarm after alarm integration on a real-time alarm interface and a historical alarm interface. The real fault source of the equipment can be quickly and accurately identified, the safety risk of railway operation is reduced, and the operation and maintenance efficiency is improved.

The invention relates to an alarm information processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: receiving a plurality of original alarm events of a target system; aggregating the plurality of original alarm events based on the alarm time to obtain an aggregated alarm event; performing alarm text semantic analysis on each aggregated alarm event to obtain an alarm object related to the aggregated alarm event and at least one alarm index item corresponding to the alarm object; obtaining historical value data of each alarm index item, and performing association relationship mining on a change condition of the historical value data to obtain an index value association relationship between the alarm index items; determining an alarm causal relationship between the aggregated alarm events according to the index value association relationship; and merging the aggregated alarm events according to the alarm causal relationship to obtain a target alarm event corresponding to the target system. By adopting the method, the alarm analysis efficiency and accuracy can be improved.

The invention provides an event analysis method and related equipment, relates to the field of artificial intelligence, and is used for automatically analyzing a reason for an alarm event during safety alarm analysis so as to help a program to understand an analysis result and facilitate operation and maintenance personnel to locate the reason for system abnormality. In the method, a first device obtains a plurality of system events; the first device analyzes the plurality of system events through a language model to obtain an analysis result, the analysis result comprises whether each system event needs to be alarmed or a reason for alarming the system event needing to be alarmed, a plurality of strategies are configured in the language model, and the system events need to be alarmed. The multiple strategies are used for generating multiple cue words of the language model.

The invention provides an alarm analysis method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring alarm information, wherein the alarm information comprises alarm time period information, alarm range information and alarm scene information; generating alarm query data corresponding to the plurality of alarm associated data sources according to the alarm time period information and the alarm range information, and sending the corresponding alarm query data to each alarm associated data source; when a query result returned by any alarm association data source based on the corresponding alarm query data is received, determining an association degree corresponding to at least one received query result according to the alarm scene information; calculating the confidence coefficient of the analysis result according to the correlation degree; and when the analysis result confidence is greater than a preset confidence threshold, analyzing the alarm root cause corresponding to the alarm information according to the at least one query result. According to the method, the alarm analysis efficiency can be improved.

The invention relates to the technical field of network security, in particular to a network security protection system and method. The system comprises an original flow data acquisition module, a metadata generation module, a data storage management module, a data feature extraction module, a feature vector anomaly detection module, a threat alarm analysis module and a threat alarm response execution module which are connected in sequence. According to the method, through full-flow capture and deep metadata analysis, a complete and uniform network behavior view is constructed, and the threat discovery and perception capability is remarkably improved. Unsupervised anomaly detection is carried out by using a deep learning model such as an auto-encoder, a normal network behavior mode can be adaptively learned, unknown threats and variant attacks are effectively identified, and the false alarm rate is reduced. The risk assessment is performed by fusing the multi-source data, and the response instruction is automatically generated and executed based on the assessment result, so that the closed-loop automatic disposal of the security event is realized, the response time is greatly shortened, and the dependence on manual intervention is reduced.

The invention relates to an alarm analysis method and device and computer equipment. The method comprises the following steps: acquiring attack alarm information, wherein the attack alarm information represents that an attack is suspected to be detected; the attack alarm information is analyzed, the confidence coefficient of the attack alarm information is obtained, a first alarm judgment result of the attack alarm information is obtained, the first alarm judgment result is one of multiple alarm judgment results, and each alarm judgment result corresponds to a rechecking strategy; determining a target review strategy from review strategies corresponding to the multiple alarm judgment results based on the confidence; analyzing the attack alarm information by using the target recheck strategy to obtain a second alarm judgment result of the attack alarm information; and determining an alarm analysis result of the attack alarm information based on the first alarm judgment result and the second alarm judgment result. By adopting the method, the accuracy of alarm analysis can be improved.

The present application discloses a data alarm analysis method and device, which includes: obtaining alarm information from a database at preset intervals; determining whether there are important keywords in the alarm information; if there are no important keywords in the alarm information, respectively calculating the similarity between the alarm information and the non-important keywords corresponding to each piece of knowledge in the knowledge base; determining each target knowledge from each piece of knowledge based on the similarity; wherein the similarity of the non-important keywords corresponding to the target knowledge is greater than a preset threshold; if there are important keywords in the alarm information; searching the knowledge base for each target knowledge with the same important keywords; and outputting access links corresponding to each target knowledge. Thus, instead of manually searching the knowledge base for content associated with the alarm information, the corresponding knowledge content is automatically searched from the knowledge base based on the keywords in the alarm information, thereby effectively improving the efficiency of the search.

The application provides a data processing method, a big data processing platform, an electronic device and a storage medium, pre-processes obtained index data; determines a target open source event processing model matched with the index data from each open source event processing model pre-set according to data characteristics of the pre-processed index data and model characteristics of each open source event processing model pre-set; and performs alarm analysis processing on the index data by using a target CEP alarm analysis rule pre-set on the target open source event processing model to obtain corresponding alarm information. The application can solve the problems that there is no mature and efficient rule to process the monitored data when data is abnormal or a system fails, and corresponding alarm information is generated in time for an operation and maintenance personnel to perform corresponding emergency processing according to the alarm information, and that data formats are quite different and affect the operation performance of a production system.

The invention relates to a multi-dimensional alarm analysis method and system based on an alarm platform, and relates to the field of water meter detection, and the method comprises the steps: responding to a water meter detection signal to collect a water meter metering value and historical metering data; calling a historical measurement value based on the historical measurement data; generating a reference metering interval based on the historical metering value and a reference deviation value; when the water meter metering value does not fall into the reference metering interval, current temperature and pressure parameters are collected; generating a metering deviation value based on the current temperature and pressure parameter; obtaining a water meter deviation value according to the water meter metering value and the metering deviation value; when the water meter deviation value does not fall into the reference metering interval, a water meter self-checking device is controlled to conduct metering self-checking through a self-checking method, and self-checking information is output; and when the self-inspection information is consistent with the abnormal information, reporting a water meter abnormal prompt, and discarding the water meter metering value acquired this time. The method has the effect of reducing the false alarm rate of the water meter.

The invention discloses an alarm correlation analysis method, device and equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: carrying out the feature extraction of target alarm data, and obtaining the multi-mode alarm feature information in the target alarm data; performing alarm data association analysis based on the target alarm data and the multi-modal alarm feature information through a preset alarm association model to generate alarm data association representation; performing clustering analysis on the alarm data association representation, and generating an alarm association group and an alarm attack chain identification result according to a clustering analysis result; and generating an alarm association analysis result based on the alarm association group and the alarm attack chain identification result. According to the technical scheme, the technical problem that in the prior art, a rule-based alarm correlation analysis method depends on manual definition and maintenance of rules, and consequently the efficiency and flexibility of alarm analysis are not high is solved.

The invention belongs to the technical field of power system network security and smart power grid data analysis, and discloses a smart power grid alarm analysis attack detection method, system and device and a medium, and the method comprises the steps: carrying out the preprocessing of multi-dimensional time series data; performing parameter initialization on the graph neural network model; inputting the processed multi-dimensional time sequence data into the initialized graph neural network model for training to obtain a prediction result of the current alarm; performing calculation and analysis by using a dual mahalanobis distance mechanism to obtain dual-dimension mahalanobis distance representation; distinguishing normal data from attack data according to a preset threshold value; performing integration processing based on the attack data, the prediction result and the actual alarm data; analyzing and positioning by using an attention mechanism to obtain an attack source of the smart grid; and optimizing parameters for the initialized graph neural network model and the attack source, and adjusting a Mahalanobis distance threshold to obtain a final detection threshold. The model can adapt to a complex power grid environment and high-dimensional alarm data.

The invention discloses an alarm analysis method, device and product applied to a distributed system. Comprising the following steps: acquiring at least one alarm data stored in a distributed system, and classifying the alarm data according to a node identifier of each execution node in the system to obtain an alarm data group corresponding to each execution node; for each alarm data group, dividing the alarm data into at least one alarm data subgroup according to reason codes contained in any two alarm data in the alarm data group; according to index data corresponding to at least one index in the operation and maintenance knowledge set and the alarm data subgroup, inputting the index data and the alarm data subgroup into a first target model to determine a first identifier of each reason code; and determining a target alarm group according to the first identifier in each alarm data of the same node identifier, and inputting the index data of the reason code of the first identifier in the target alarm group, the operation and maintenance knowledge, the repair suggestion and the alarm content template cue word into a second target model to obtain an alarm analysis report. And the interpretability of alarm analysis is improved.

This invention discloses a method for detecting the accuracy of an elevator intelligent identification device, comprising the following steps: S1, listening to the alarm signal interface to receive AI alarm and IO alarm signals respectively; S2, storing the alarm results in chronological order in a form; S3, automatically entering the analysis and processing unit after the alarm results are received; S4, the system POSTs the IO alarm records to the black-box image analysis unit, which then returns the analysis results to the system to form an IO alarm false alarm analysis report; S5, comparing and analyzing the IO alarm report and the AI ​​alarm report to form a missed alarm analysis report. This invention achieves fully automatic detection of the AI ​​alarm system, automatically generates detection results and reports, and realizes a standardized detection process for the AI ​​alarm system.