167 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 method comprises the following steps: constructing an intelligent research and judgment model, carrying out environment modeling on the intelligent research and judgment model, constructing a network attack path according to the intelligent research and judgment model, and identifying a network attack by using a known signature of the network attack or a rule-based detection technology; classifying and marking the data of the network security equipment by using an SVM classification algorithm, training an intelligent study and judgment model, establishing a threat identification strategy of the network attack, and identifying the features of the network attack; performing context learning and state prediction by using the intelligent study and judgment model, and optimizing a threat identification strategy of network attacks; a data field of a normal HTTP request is slightly disturbed, an adversarial sample is generated by using a threat of a known network attack, adversarial training is performed in combination with a forged HTTP request, and a deceptive network attack is identified. According to the method, cross validation and correlation analysis of high-quality and multi-source threat intelligence are realized, and the attack defense capability is improved.

The invention discloses an intelligent alarm analysis method for an operation and maintenance scene, a computer device and a medium. The intelligent alarm analysis method for the operation and maintenance scene comprises the following steps: analyzing alarm information to obtain target information; determining a plurality of processing strategies associated with the target information from a preset knowledge base, and obtaining a plurality of association indexes of the target information and each processing strategy; based on a plurality of relevance indexes and a preset weight of each relevance index, calculating a relevance score of the target information and each processing strategy; the relevance scores are ranked from high to low, if the highest relevance score is larger than a preset threshold value, the processing strategy corresponding to the highest relevance score serves as a target strategy, and alarm information is automatically processed based on the target strategy; and if the highest relevance score is not greater than a preset threshold value, pushing the alarm information to the operation and maintenance personnel, receiving a processing strategy of the operation and maintenance personnel, and updating the processing strategy to a preset knowledge base. According to the method, the alarm information can be quickly and effectively processed.

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 belongs to the field of power distribution cabinet supervision, relates to a data analysis technology, is used for solving the problem that the maintenance necessity and maintenance influence factors of an outdoor power distribution cabinet cannot be analyzed according to electrical monitoring data in the prior art, and particularly relates to an outdoor power distribution cabinet operation safety linkage supervision control system. Comprising an electrical monitoring module, an alarm analysis module, an operation and maintenance management module, a maintenance analysis module and a database, the electrical monitoring module, the alarm analysis module, the operation and maintenance management module and the maintenance analysis module are sequentially in communication connection, and the alarm analysis module, the operation and maintenance management module and the maintenance analysis module are all in communication connection with the database; according to the method, operation and maintenance management analysis can be carried out on the outdoor power distribution cabinet, the distribution condition of the electrical coefficients of the outdoor power distribution cabinet in the analysis period is analyzed to obtain the operation and maintenance coefficients, and the operation and maintenance necessity of the outdoor power distribution cabinet is fed back through the operation and maintenance coefficients, so that the outdoor power distribution cabinet can be maintained in time, and the fault probability of the outdoor power distribution cabinet is reduced.

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 fault analysis method, device and equipment for power distribution equipment and a storage medium, and the method comprises the steps: obtaining historical alarm data and geographical environment data of the power distribution equipment, and determining an environment interference change trend based on the historical alarm data and the geographical environment data; wherein the environment interference change trend is used for representing a dynamic influence trend of each geographical environment factor on power distribution equipment alarm generation; performing feature extraction on the historical alarm data by adopting a convolutional neural network according to the environmental interference change trend to obtain comprehensive feature representation; training the convolutional neural network by adopting comprehensive feature representation to obtain a trained fault prediction model; acquiring real-time alarm data, inputting the real-time alarm data into the fault prediction model, and outputting a preliminary fault reason; performing time sequence analysis on the preliminary fault reason by adopting a long short-term memory network to obtain a fault diagnosis result; according to the invention, the accuracy of fault reason identification and the intelligent level of alarm analysis can be improved, and reliable operation of a power system is ensured.

The invention discloses an interpretable correlation analysis method for alarm noise reduction, and relates to the field of network security and alarm analysis. The problems that a traditional alarm event interpretation and analysis method is insufficient in consideration of dimensionality and insufficient in interpretability are solved. According to the method, the space-time similarity and the semantic similarity are combined, the natural language processing capacity of large language reasoning is utilized, a novel alarm noise reduction and correlation analysis method is constructed, the false alarm rate can be reduced, efficient, accurate and interpretable alarm analysis support is provided, the complex attack detection capacity is improved, and the network security automatic early warning capacity is enhanced. The method is mainly applied to network security alarm analysis.

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.

An operation and maintenance alarm method and apparatus, and a storage medium and an electronic device. The method comprises: acquiring an operation and maintenance data set to be processed, and by means of a target algorithm, performing data cleaning processing on operation and maintenance data in the operation and maintenance data set to be processed, so as to obtain a processed operation and maintenance data set (S101); performing a stability test on a time sequence of the operation and maintenance data in the processed operation and maintenance data set, so as to obtain a test result, and determining a first operation and maintenance data set from the processed operation and maintenance data set on the basis of the test result (S102); performing feature extraction processing on the first operation and maintenance data set by means of a principal component analysis method, so as to obtain a plurality of operation and maintenance data features, and performing feature selection processing on the plurality of operation and maintenance data features by means of a K-means clustering algorithm, so as to obtain a target operation and maintenance data set (S103); and performing alarm analysis on the basis of the target operation and maintenance data set, so as to obtain an alarm analysis result (S104). The technical problem in the prior art of the accuracy of an operation and maintenance alarm being relatively low due to the fact that the accuracy of data pre-processing performed on the basis of a fixed rule is low is solved.

The invention relates to the technical field of meteorological and traffic data processing, and discloses a distributed meteorological data transmission and processing method for regional meteorological alarm, which comprises the following steps: acquiring distributed meteorological data of a target region, constructing a meteorological alarm analysis reference feature set, and predicting meteorological information of each position coordinate in the target region in a target time period; according to the path information of the target highway and the predicted meteorological information, regional meteorological alarm information is generated, then a highway traffic flow prediction database is utilized, the maximum traffic flow value and the maximum driving speed of the regional alarm range in the corresponding regional alarm time period are considered, and a speed limiting setting strategy is generated; dynamic speed limiting setting of different unit periods is executed in different sections of the target expressway, and the traffic flow and the vehicle running speed in different sections of the expressway are regulated and controlled by utilizing reasonable setting of the speed limiting, so that the running safety and the passing efficiency of the running vehicle in the corresponding meteorological environment of the expressway are 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 discloses an alarm method and system of a video conference system, a medium, equipment and a program product. The alarm method applied to a server comprises the following steps: in response to receiving first alarm information sent by a first edge node, determining whether to push the first alarm information according to a global alarm rule corresponding to a video conference system, the first edge node being any one of at least one edge node, and the global alarm rule corresponding to the video conference system; the first alarm information is generated by the first edge node based on a local alarm rule and index data of the first conference terminal, and the local alarm rule comprises alarm triggering conditions corresponding to each conference terminal in the first conference terminal; and if it is determined that the first alarm information is pushed, pushing the first alarm information to an alarm analysis system. The local and global analysis combined mode not only considers the special condition of each conference terminal, but also can grasp the operation state of the conference terminal on the whole, thereby effectively avoiding the problems of false alarm and missed alarm caused by the adoption of a global alarm threshold, and improving the alarm accuracy.

The invention relates to the field of computer science and technology, in particular to a data uploading fault monitoring system based on intelligent early warning, which comprises a target data acquisition module, an early warning feature extraction module, an alarm rule setting module, a linkage alarm module, a network construction module, an alarm analysis module and a management database, the system carries out data acquisition by defining an early warning target, extracts each early warning feature of the early warning target data, determines alarm points according to historical early warning target data of each device, obtains an association relationship between the alarm points of each device, constructs a single alarm point rule and a linkage alarm rule, and generates alarm content. According to the method, the alarm features and the inherent features of the early-warning target are subjected to correlation analysis, the alarm early-warning network is constructed, the risk condition of the specified early-warning target is further evaluated, the essence and the influence range of the alarm event can be known more comprehensively, and thus the cause of the fault and the possible consequence can be judged more accurately.

The invention discloses a low-level alarm management method and device. The method comprises the following steps: receiving a low-level alarm, and respectively storing a first alarm caused by a network element fault, a second alarm caused by a user behavior and a third alarm caused by network management equipment upgrading into corresponding databases; detecting the alarm flow written into the first database in real time, and analyzing the alarm in the first database when the alarm flow meets a preset condition; periodically utilizing the time sequence prediction model to analyze the alarms in the second database, and analyzing the alarms in the second database when the predicted number of the second alarms is not matched with the actual number of the second alarms; analyzing alarms in a third database in response to the alarm analysis instruction; and corresponding early warning notifications are generated based on analysis results of different alarms. The technical problems that a related alarm management scheme focuses on responding to high-grade alarms, and the analysis and early warning capability on low-grade alarms is insufficient are solved.

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.