63 results about "Alarm response" patented technology

The invention relates to the technical field of abnormal alarm, in particular to an intelligent alarm method and system for the abnormal state of a battery, and the method comprises the following steps: obtaining a current period log, calculating a residual vector, analyzing the change trend of a residual track included angle, extracting an abnormal tendency period, and judging whether temperature rise abnormity exists or not through the combination of a load grade and temperature rise deviation. And judging whether microcirculation characteristics are met or not, correcting an alarm level, and triggering multi-source state abnormity alarm. According to the method, the evolution trend of the battery state can be dynamically tracked and the formation process of the abnormal tendency can be accurately captured by constructing the state residual feature vector and combining with multi-cycle data analysis, and the false alarm rate is reduced and the real-time monitoring capability of the battery abnormal state is improved through refined load and temperature rise response judgment; by detecting the trend change, the temperature response offset and the microcirculation phenomenon in the periodic change of the battery, the alarm response can be adjusted in real time under different load conditions, and the accuracy and the reliability of an alarm mechanism are ensured.

The invention provides a water immersion and electric leakage monitoring method, device, system and equipment for power equipment, and relates to the technical field of power equipment safety monitoring. The method comprises the following steps: acquiring electrical monitoring data of a grounding wire of power equipment and water level monitoring data of an area where the power equipment is located; judging whether an electric leakage event occurs or not according to the electrical monitoring data; water immersion event judgment is conducted according to the water level monitoring data, when the water level monitoring data exceed a preset water level threshold value, visual review operation is triggered, and whether a water immersion event occurs or not is judged based on the result of the visual review operation; and determining different alarm levels according to a combination condition between the judgment result of the water immersion event and the judgment result of the electric leakage event, and executing alarm responses corresponding to the alarm levels. According to the method, the electrical monitoring data is obtained in a non-contact manner, and a dual verification mechanism of'water level threshold triggering + visual rechecking 'is established, so that the water immersion and electric leakage states of the electrical equipment can be quickly and accurately identified.

The invention relates to the technical field of health monitoring, in particular to a health state alarm response system based on multi-dimensional monitoring, which comprises a dynamic threshold module, a physiological monitoring module, an anomaly positioning module, an inducement output module, an anomaly intervention module and an early warning response module, according to the method, multi-dimensional original data of a user is collected, meanwhile, a timestamp alignment and scene label binding technology is adopted, an exclusive physiological index normal fluctuation interval library is constructed for different large classes of scenes, then the problem of misjudgment of a static threshold value is fundamentally solved, the cause of'abnormity 'is deeply and accurately positioned, and the accuracy of the abnormal condition is improved. The abnormity-scene-behavior-cause full-link association not only enables the user to clearly know the cause of the abnormity, but also provides data support for the medical personnel to formulate a targeted intervention scheme, and reasonably formulates the targeted intervention scheme based on the intervention list, thereby avoiding the ineffectiveness of general suggestions, enabling resources to be inclined to high-risk users, and improving the user experience. The complication occurrence rate is effectively reduced.

The invention relates to an AI analysis alarm platform and method for video monitoring, and relates to the related technical field of video analysis alarm, and the platform comprises a priori threshold determination module which is used for constructing a negative space based on absolute normal data as a preposed priori threshold according to a region operation and maintenance rule for a target monitoring region; the abnormal alarm management module is used for accessing monitoring stream data, triggering a preposed prior threshold, executing data entropy change judgment by taking a negative space as a baseline, and performing abnormal alarm management; comprising a direct alarm response sub-module; a directional alarm response sub-module; wherein the preposed prior threshold and depth discriminator is an embedded plug-in of the AI analysis alarm platform. The technical problem that in the prior art, abnormal recognition model training depends on positive samples and annotation data and is difficult to adapt to dynamic complex scenes, so that video analysis alarm accuracy and timeliness are poor is solved, and the technical effect of improving video monitoring analysis alarm accuracy and timeliness is achieved.

The invention relates to a motor abnormal sound intelligent identification method based on time-frequency characteristics and hearing adaptation, and belongs to the technical field of motor fault detection. The method comprises the steps that motor operation sound signals are collected in real time through a multi-azimuth sound signal collection array, and signal preprocessing and dynamic framing processing are carried out; a time-frequency spectrum is generated through short-time sliding window time-frequency conversion, a normal operation sound auditory baseline is established in combination with an auditory perception adaptive dynamic weighting technology, and hierarchical weighting processing is performed on the time-frequency spectrum to generate fused time-frequency weighted features; a time-frequency weighted feature enhanced residual network model is constructed, and abnormal feature extraction and recognition are realized through a cross-dimension fusion mechanism, a fault feature transfer learning mechanism and a fault feature attention mechanism; and a working condition dynamic adaptive reasoning mechanism and a hierarchical linkage alarm system are adopted to complete state recognition and alarm response. The method effectively improves the accuracy and real-time performance of motor abnormal sound recognition, and is suitable for motor state monitoring in a complex industrial environment.

The invention provides a tunnel safety monitoring and early warning management method and system, and relates to the technical field of tunnel safety, and the method comprises the steps: carrying out the multi-mode data collection of a tunnel environment through a plurality of intelligent monitoring terminals connected to an RS485 bus, and carrying out the environment abnormality alarm triggering analysis; when any intelligent monitoring terminal detects an alarm event, the alarm event is broadcasted to other terminals through an RS485 bus, and other terminals receiving the alarm event autonomously analyze a diffusion probability map, calculate an emergency evacuation route and control an escape indicating device to display an evacuation direction; communication authority differentiation scheduling based on the RS485 bus is executed, and alarm event situation awareness based on multi-modal data dynamic updating is completed. The technical problems that in the prior art, tunnel safety monitoring and early warning management often adopts a centralized control mode, information transmission and processing are lagged, the alarm response time is long, and effective emergency disposal cannot be carried out in time are solved.

The invention discloses a multi-source data fire-fighting facility risk level assessment and early warning decision-making method, and particularly relates to the technical field of intelligent fire-fighting alarm devices and public safety, and the method comprises the steps: S1, collecting the state of a fire-fighting facility and environment dynamic data in real time, S2, calculating the static health degree index of the facility through an uncertainty reasoning model and a topological relation, and S3, calculating the risk level of the fire-fighting facility according to the static health degree index. The method comprises the steps of S1, generating an environment dynamic risk degree index through an adaptive evaluation model, S4, fusing the two indexes through a nonlinear coupling function to generate a comprehensive risk level and a visual map, and S5, matching, verifying and deducing a recommendation decision scheme with a utility score based on risk information. And a grading early warning signal is generated so as to drive a corresponding alarm device to execute early warning. According to the method, the defects of static facility assessment and dynamic environment risk separation are overcome, accurate risk quantification and prospective early warning are realized, and the intelligent level and execution reliability of alarm response are remarkably improved through an alarm decision closed loop and a self-optimization mechanism.

This utility model relates to an intelligent intrusion prevention security system, comprising a security sensing device, an alarm response device, and a security host. The security sensing device includes a fixed infrared communication sensing device mounted on the fixed end of the opening / closing mechanism and a mobile infrared communication sensing device mounted on the moving end of the opening / closing mechanism. When the opening / closing mechanism is closed, the mobile infrared communication sensing device cooperates with the fixed infrared communication sensing device for real-time two-way encrypted communication. The fixed infrared communication sensing device is connected to the security host, and its communication status with the mobile infrared communication sensing device is fed back to the security host by responding to a true random mathematical problem. The security host is connected to the alarm response device, and is used to monitor the operating status of the alarm response device and the feedback information from the fixed infrared communication sensing device in real time, and can control the opening and closing of the alarm response device. The purpose of this utility model is to provide an intelligent intrusion prevention security system that can achieve efficient and rapid security response, providing comprehensive and intelligent security protection.

This invention relates to the field of power electronics technology, specifically to a method and system for monitoring the insulation of DC charging piles. The method includes the following steps: real-time monitoring of branch voltage deviation from the busbar; adjusting measurement compensation parameters; correcting the measured value of branch insulation resistance; identifying leakage current drift; locating the leakage branch and triggering relay control; sending alarm information; and generating a charging pile monitoring record. In this invention, the consistency of branch voltage measurement is improved by combining branch voltage deviation trends with voltage compensation parameters. Observational errors are corrected by comparing insulation resistance fluctuations, optimizing measurement accuracy. Current deviation compensation under no-load conditions eliminates sensor zero-point drift interference. Leakage branch identification is achieved by combining current jump amplitude and voltage direction, enhancing location accuracy. Relay control and event information linkage are used to form a closed loop between alarm response and equipment status recording, improving the real-time performance and completeness of system monitoring.

The present application relates to the technical field of power transmission line operation safety monitoring, and discloses an intelligent monitoring system for preventing high-falling in power transmission line operation, which comprises a data acquisition end, an edge computing module, a cloud platform and an alarm response module; the data acquisition end constructs a multi-source perception network of "person-equipment-environment" by means of an intelligent safety helmet, a safety belt and auxiliary equipment, and accurately collects position, posture, stress and environmental parameters; the edge computing module preloads a dangerous action recognition model trained specially, and realizes real-time screening of abnormal data; the cloud platform deeply analyzes data in combination with a machine learning algorithm, and visualizes the operation scene by means of digital twin technology; and the alarm response module is provided with three thresholds, and realizes multi-end collaborative response and event whole-process tracing. The present application solves the problems of existing passive protection, single monitoring and lagging response, realizes accurate identification of high-falling risk, real-time early warning and collaborative disposal, and significantly improves the safety and management efficiency of power transmission line operation.

The invention discloses a combined train obstacle detection system and method, and belongs to the technical field of train operation safety, the detection system comprises an active detection module, a passive detection module, a processor module and a communication module, the active detection module comprises a distance detection assembly and a form detection assembly; the distance detection assembly and the form detection assembly are arranged at the head position of the train and are respectively used for detecting form information and distance information of an object; the passive detection module comprises a pressure detection assembly arranged at the bottom of the train and used for detecting pressure information when the train makes contact with an obstacle. The processor module is in communication connection with the distance detection assembly, the shape detection assembly and the pressure detection assembly, and judges and generates different signals according to detected information; and the communication module transmits the information received by the processor module and the generated signal to a cab and a train control center. According to the combined train obstacle detection system, early warning response and alarm response of different levels of obstacles can be achieved.

The invention belongs to the field of dynamic alarm strategy communication, and particularly relates to a dynamic alarm strategy communication method supporting protocol hot plug, which comprises the following steps: S1, constructing a protocol hot plug system; and S2, a dynamic alarm strategy of the alarm system. According to the invention, through a visual alarm response strategy editor, alarm triggers / monitoring systems, alarm display of alarm response terminals, voice broadcast, acousto-optic feedback, relay control and the like are set for different alarm types; according to the method and the system, the alarm parameters can be dynamically configured, alarms with different priorities can be adaptively adjusted by adopting different prompt modes and processing flows, the unified alarm information is converted into a target protocol format, and in addition, the communication protocols can be subjected to hot plugging by loading / unloading the communication protocol implementation module during operation, so that the communication protocols are diversified.

The invention belongs to the technical field of security and protection monitoring, and relates to an air-ground cooperative intelligent alarm response and unmanned aerial vehicle patrol evidence obtaining system, which comprises a channel feature sensing module used for generating space channel feature data; the cooperative resonance construction module is used for constructing a stable air-ground coupling resonance system; the system disturbance monitoring module is used for identifying disturbance and generating an abnormal alarm by monitoring the change of an energy supplementary value; the target feature inversion module analyzes signal distortion, inverts the position, volume and dynamic information of the intrusion target, and generates a spatial analysis portrait of the intrusion target; the visual tracking locking module is used for driving the unmanned aerial vehicle to perform visual locking on the target and acquiring locking video evidence; the comprehensive evidence obtaining report module associates and binds the video evidence, the analysis portrait and the alarm timestamp, and outputs an air-ground collaborative evidence obtaining report; the problems that an existing security and protection system is slow in response, high in false alarm rate and lack of visual front non-visual detection positioning capacity are solved.

Methods and systems for providing context for alarms and resolving alarms using a virtual agent are described. Inputs including imaging, patient information, and aural, visual, and mechanical patient inputs are analyzed to provide context for an alarm. Based on the context, the methods and systems may identify a patient action that may resolve the alarm. A virtual agent may interact with the patient to identify and resolve the alarm without additional caregiver input.

The application discloses a kind of unified processing and alarm method of production field area personnel behavior monitoring data, it is related to industrial safety monitoring and information processing technical field, including acquisition production field area personnel behavior monitoring data, abnormal signal and behavior are classified and priority identification in layers, and alarm object and push path are determined in combination with business rules, responsible subject, equipment state and network condition.The stability and closed-loop management capability in the alarm transmission process are enhanced by load balancing, integrity check, encrypted transmission, abnormal retry, timeout monitoring and sequence check, so as to effectively improve the production field area personnel behavior monitoring data processing efficiency, abnormal behavior alarm response efficiency and overall safety management level.

The utility model relates to the technical field of coal transportation, and discloses a coal overflow and scattering detection alarm device, the end part of one side of a rotating support plate is connected with a connecting seat and is detachably connected with a baffle plate, and the edge part of a linkage shaft is connected with a trigger rotating rod at the position on the inner side of a back shell; a coal blocking microswitch is installed at the position, corresponding to the trigger rotating rod, in the back shell, and through the shaft seat, the rotating supporting plate, the baffle, the linkage shaft, the trigger rotating rod and the coal blocking microswitch, when the coal piling phenomenon occurs in the discharging hopper, the piled coal is used for driving the baffle to overturn upwards, the rotating supporting plate and the linkage shaft are driven to deflect synchronously, and the coal blocking phenomenon is avoided. The linkage shaft drives the triggering rotating rod to deflect, the triggering block at the end of the triggering rotating rod can make contact with the coal blocking microswitch to act, a coal blocking signal is sent to a central controller, alarm response is carried out, meanwhile, the belt conveying motor is closed, continuous coal conveying is stopped, the material blocking situation is detected and responded in time, and larger losses are prevented from being further caused.

Methods and systems for providing context for alarms and resolving alarms using a virtual agent are described. Inputs including imaging, patient information, and aural, visual, and mechanical patient inputs are analyzed to provide context for an alarm. Based on the context, the methods and systems may identify a patient action that may resolve the alarm. A virtual agent may interact with the patient to identify and resolve the alarm without additional caregiver input.

The application provides a fire-fighting alarm response system and method, comprising: in response to an alarm communication, extracting an alarm element based on a preset inquiry rule, and generating a pre-alarm work order including the alarm element; and processing the alarm element by using a preset determination model; specifically: constructing a fire alarm dialogue model with Transform as a basic architecture, regarding the alarm question and answer as a sequence generation question, reasoning the fire situation that should be inquired next in a self-recurrence manner according to the obtained fire situation, until the model considers that enough information has been obtained to judge the fire grade; the above steps are executed for multiple times, the understanding of the fire scene situation is gradually deepened, and the real-time fire grade evaluation is generated on this basis. The system deviation existing in the strategy learning method of the Markov decision process and reinforcement learning in the existing alarm automatic alarm response or type system is solved, and the defect that the response result deviates from the actual operator's behavior to a certain extent is solved.

The invention provides a cast-in-place pile offset real-time monitoring system, a using method and a monitoring method. The real-time monitoring system comprises at least one monitoring host and two reference targets. The monitoring host comprises a laser sensing module, the laser sensing module comprises two laser sensing units, the laser emitting directions of the two laser sensing units are perpendicular to each other, and each laser sensing unit corresponds to one standard target and is used for detecting the reference distance between the cast-in-place pile and the standard target; the data processing module is used for calculating an offset distance and an offset direction according to the two reference distances, and generating an alarm signal when the offset distance is greater than a set distance or the reference distance abnormally jumps; the alarm response module is used for making an alarm response according to the alarm signal; and the wireless transmission module is used for uploading the alarm signal to a processing center. The monitoring system provided by the invention can accurately detect the offset of the cast-in-place pile and make an alarm response.

The invention belongs to the technical field of nuclear power production, and provides an alarm analysis system for a nuclear power plant, which comprises an analysis module, and a response module and a display module connected with the analysis module, wherein the response module is configured to adopt a regulation-based alarm response, automatically call a matched response operation according to an alarm signal, and provide decision analysis for the analysis module in combination with the called response operation and the display module; the analysis module is configured to analyze the alarm signal, generate single alarm point performance evaluation data and alarm triggering indexes, analyze time characteristics in the generated alarm triggering indexes, identify whether response delay or abnormity exists or not, and optimize and identify alarm points; and the display module is configured to adopt a configurable alarm window additionally provided with font paragraphs, set different alarm window font formats for different alarm areas, and meet the display requirements of different areas and different types of alarm information.

This invention belongs to the field of smoke and fire alarm technology, specifically relating to a smoke and fire alarm processing method, system, and terminal based on IoT-based smart fire protection. This invention calculates the overall offset time to correct the real-time collected smoke and fire alarm signals based on an alarm response time sequence formed from historical smoke and fire alarm datasets. Based on a set of alarm data nodes determined in the corrected signal, a comprehensive fitting value is calculated as a reference benchmark for subsequent corrections. Therefore, through macroscopic correction of historical data and iterative optimization of recent data, dynamic and adaptive precision calibration of the alarm response time is achieved, overcoming the insufficient accuracy problem caused by using fixed offset values ​​for correction, thereby improving the accuracy of the timestamp of the starting point of the fire alarm event signal characteristics.

This invention provides a method, apparatus, device, and readable storage medium for vehicle dynamic projection alarms, relating to the field of vehicle technology. The method includes acquiring first, second, and third information; obtaining fourth information containing expected trajectory data and extended area trajectory data; obtaining fifth information; obtaining sixth information corresponding to interactive evaluation indicators; and determining the optimal dynamic projection alarm scheme. This invention constructs a multi-source information-driven dynamic projection alarm process, introducing key steps such as path prediction, human-vehicle interaction simulation, and interactive behavior evaluation. Combined with mathematical modeling and optimization strategies, it transforms multi-dimensional evaluation indicators into composite optimization objectives, forming a complete dynamic alarm scheme optimization problem under design constraints and operational scenario limitations. This method can improve the real-time performance and accuracy of alarm responses while ensuring pedestrian safety and driving comfort, and enhance the stability and practicality of vehicles in complex traffic environments.

The invention relates to the technical field of intelligent traffic operation and maintenance, in particular to an operation and maintenance management system and method for vehicle-road cloud integrated equipment. The method comprises the following steps: acquiring basic information of the vehicle-road cloud integrated equipment; equipment operation data are collected in real time through an equipment communication interface, an equipment visual monitoring map is constructed in combination with a geographic information system, and equipment distribution and operation states are displayed; carrying out intelligent alarm and hierarchical response, and analyzing the collected operation data in real time by presetting an equipment operation threshold value; after the alarm information is received, generating an operation and maintenance task; performing statistical analysis on the equipment operation data, the alarm data and the operation and maintenance records; the system comprises an equipment asset filing module, an equipment state monitoring module, an intelligent alarm response module, an operation and maintenance task closed-loop module and an operation and maintenance strategy optimization module. The equipment state can be automatically identified, potential faults can be predicted, timely maintenance suggestions can be provided, the operation and maintenance cost can be greatly reduced, and the reliability and safety of the system can be improved.

The invention discloses a collapse source alarm method and system, and relates to the technical field of disaster early warning, and the method comprises the following steps: obtaining acceleration data, pressure data, angle data and gas data; processing the collected acceleration data, including amplitude calculation and FFT (Fast Fourier Transform), obtaining an amplitude and a result array through FFT, the result array including the vibration frequency; respectively carrying out threshold comparison on the amplitude and the change rate thereof, the pressure data and the change rate thereof, the angle data and the change rate thereof, the gas data and the change rate thereof, and the frequency; generating an alarm state according to a comparison result; and the light module and the sound module execute corresponding warning actions according to different warning states. The method has the advantages that the multi-dimensional data real-time processing capability is improved, an intelligent multi-stage early warning mechanism is realized, and the alarm response efficiency is optimized.

The invention discloses a wide-range gamma critical detector and a detection method, and the detector comprises a composite probe which carries out the region and critical radiation detection and self-inspection under the control of a signal processing system, and outputs a region signal and a critical signal corresponding to the region and critical gamma dose rate of an environment where the composite probe is located; the signal processing system is used for providing corresponding working voltage and self-checking control for the composite probe, performing data conversion and counting acquisition on the regional signal and the critical signal, and outputting a regional radiation detection result and a critical radiation detection result; and identifying and judging the critical radiation detection result based on a preset alarm threshold value, and selecting to output a corresponding alarm signal when the critical radiation detection result exceeds the alarm threshold value. According to the invention, the composite probe is utilized to detect the regional and critical radiation in the environment at the same time, the measurement range is widened, two alarm signals are selectively output according to the preset alarm threshold, the missing report rate and the false alarm rate of critical alarm are greatly reduced, the reliability and the stability are enhanced, and the alarm response speed is extremely high.

This invention relates to an intelligent method for identifying abnormal motor noises based on time-frequency features and auditory adaptation, belonging to the field of motor fault detection technology. The method includes: real-time acquisition of motor operating sound signals through a multi-directional acoustic signal acquisition array, followed by signal preprocessing and dynamic framing; generation of a time-frequency spectrum using short-time sliding window time-frequency conversion, establishing an auditory baseline for normal operation sound using auditory perception adaptation dynamic weighting technology, and performing hierarchical weighting processing on the time-frequency spectrum to generate fused time-frequency weighted features; construction of a time-frequency weighted feature-enhanced residual network model, achieving abnormal feature extraction and identification through cross-dimensional fusion mechanisms, fault feature transfer learning mechanisms, and fault feature attention mechanisms; and completion of status identification and alarm response using a dynamic adaptation inference mechanism and a hierarchical linkage alarm system. This invention effectively improves the accuracy and real-time performance of motor abnormal noise identification and is suitable for motor status monitoring in complex industrial environments.

The invention relates to the technical field of fire safety monitoring, in particular to an alarm system and method for identifying smoke and flames. The method comprises the following steps: receiving video data collected by field acquisition equipment in real time; the collected video data are preprocessed; smoke and flame features are extracted from the preprocessed video data; constructing a recognition model based on deep learning; setting multi-level alarm threshold values, and triggering alarms with different intensities in combination with scene risk levels; recording the information of the whole alarm process in detail; the system comprises a video acquisition module, a video preprocessing module, a feature extraction module, an identification module, an alarm module and a storage module. According to the method, multi-dimensional feature extraction can be carried out on smoke flame detection, core features of smoke flames are highlighted, the problems of false alarm and missing alarm of a single threshold value are avoided on the basis of multi-level alarm threshold values of scene risk levels, alarm response is more accurate, and therefore the safety and reliability of fire early warning are greatly improved.

A digital recoverable temperature sensing cable temperature monitoring system and method belong to the technical field of cable intelligent operation inspection, and comprise a temperature acquisition module, a signal transmission module, a data analysis module, a logic judgment module, a monitoring management module and a data storage module. The temperature acquisition module, the signal transmission module and the power supply are all arranged on the temperature sensing cable, and the data analysis module, the logic judgment module, the monitoring management module and the data storage module are remotely arranged on the monitoring host; the invention aims to provide a digital recoverable temperature sensing cable temperature monitoring system and method, so as to overcome the defects of an existing cable temperature monitoring system in the aspects of temperature measurement precision, alarm response, automatic recovery capability, operation and maintenance efficiency and the like. Real-time, continuous and distributed monitoring is performed on the temperature along the cable, automatic resetting is performed when the temperature is recovered to a safe range after temperature abnormity alarm, and the intelligent level and the operation efficiency of the system are improved.

The invention provides a thermal detection system and method for a PFC power supply module, and relates to the technical field of thermal detection alarm, and the method comprises the steps: obtaining the temperature distribution information and dynamic heat flow data of the PFC power supply module during operation; determining a heat accumulation track in the key heat source area according to the temperature distribution information, and determining a heat flow trend of the operation temperature of the PFC power supply module during temperature diffusion according to the heat accumulation track and the adjusted qualitative heat early warning strategy; performing multi-path thermal conductance matching on the calibrated temperature deviation to obtain an alarm response index of the PFC power supply module during cooperative heat dissipation operation, and determining a thermal out-of-limit boundary on a temperature detection point in the PFC power supply module according to the alarm response index and the dynamic heat flow data; and according to the heat flow trend and the heat out-of-limit boundary, performing graded alarm on the PFC power supply module during dynamic heat balance synchronous detection. According to the invention, the thermal state can be accurately monitored and early warned when the PFC power supply module is dynamically operated, so that the accuracy of thermal detection alarm is improved.

The invention relates to the field of network security, in particular to an alarm method and device, equipment, a medium and a product, and the method comprises the steps: obtaining a to-be-classified original alarm; inputting the original alarm into the micro-service architecture to obtain an alarm type of the original alarm, and executing a corresponding alarm response according to the alarm type; the micro-service architecture is constructed based on a plurality of research and judgment services according to a preset research and judgment link; the research and judgment service is used for carrying out corresponding alarm type research and judgment, and if the research and judgment service determines that the initial alarm type of the original alarm is not the first alarm type, the next research and judgment service determined by the preset research and judgment link is used for carrying out alarm type research and judgment on the original alarm. According to the method and the device, after the to-be-classified initial alarms are obtained, the alarm types are researched and judged sequentially according to the multiple research and judgment services for classifying the alarm types with corresponding functions based on the micro-service architecture constructed by the multiple research and judgment services according to the preset research and judgment link, so that the initial alarms are classified quickly and accurately.