824 results about "Fire safety" patented technology

The invention relates to the technical field of fire safety monitoring, in particular to a firework identification system and method based on multi-modal fusion perception, and the core of the scheme is a visible light, multispectral and temperature three-modal framework: feature extraction optimization of each modal, improved YOLOv8s for visible light branches, dynamic background modeling and flame color screening, and multi-modal fusion perception. False positive is rejected by a multispectral branch depending on a waveband ratio and an index, an error compensation algorithm is introduced into a thermopile branch, and finally, a final smoke and fire area and the confidence coefficient thereof are determined by associating a three-mode area through collaborative decision. According to the scheme, the complex environment adaptability and the recognition reliability can be improved, the false alarm risk is reduced, the extremely-early smoke and fire detection capability is enhanced, good real-time performance and deployment flexibility are achieved, and the method is suitable for various types of fire safety monitoring scenes.

The invention discloses an intelligent fire-fighting AI collaborative early warning system and method fusing GIS and multi-source data, and relates to the technical field of fire-fighting safety, and the system comprises a GIS space modeling module which is used for constructing a digital twinborn model through integrating a building BIM model, fire-fighting facility distribution, a population density thermodynamic diagram, sensing equipment layout and real-time environment data; the multi-source data fusion module is used for integrating sensing equipment data, real-time environment data, meteorological information, manually reported hidden dangers and a historical fire case library, and outputting the data after standardization processing; the AI collaborative early warning engine module is used for accessing standardized data, realizing building fire dynamic risk assessment and outputting graded warning information; the 3D simulation drilling platform is used for calling the digital twinborn model, receiving graded alarm information and supporting fire spreading simulation, emergency drilling and plan optimization; and the block chain evidence storage module is used for storing alarm information and drill records. According to the invention, risk assessment and accurate prediction of the fire hazard can be realized.

The invention, which relates to the technical field of fire safety, discloses a multi-modal intelligent identification method for fire-fighting hidden troubles based on a large model, comprising the following steps: S1, acquiring multi-source heterogeneous feature data through a sensor network deployed in a fire-fighting water pump room to obtain an initial feature set; s2, performing unified scale conversion on the initial feature set, calculating heterogeneous bridging parameters according to the environmental parameters and the equipment operation data, constructing a fusion feature vector, inputting the fusion feature vector into a preset neural network for feature weight adaptive adjustment, and outputting an adjusted weight vector; according to the fire-fighting hidden danger intelligent identification method based on the large-model multi-mode, intelligent closed loop from hidden danger identification to prevention and control decision making is realized, and the intelligent, dynamic and precise management level of a fire-fighting safety system is comprehensively improved.

The invention relates to the technical field of fire safety management, and discloses a fire safety management supervision platform system. The system comprises a building information acquisition module for acquiring building structure data and environment monitoring data of a target building in real time; the risk area division module is used for dividing a plurality of independent fire risk areas according to the building structure data and distributing area identifiers; the historical data indexing module is used for indexing a historical fire accident data set and a fire-fighting facility maintenance record set of each region according to the region identifier; the dynamic risk analysis module fuses the environment monitoring data and the historical fire accident data set to generate a real-time fire risk coefficient sequence; the fire-fighting resource scheduling module is used for generating a fire-fighting resource allocation scheme based on the real-time fire risk coefficient sequence and the facility maintenance record set; and the emergency response decision module generates a multi-stage fire emergency response strategy according to the resource allocation scheme. The system improves the timeliness and pertinence of fire safety management.

The invention discloses a building fire-fighting automatic verification and evacuation path verification system based on a rule engine, and relates to the technical field of building fire-fighting intellectualization. Comprising the steps that a rule generation module analyzes a fire-fighting standard text and generates an executable rule set; the model analysis module is used for extracting component attributes and a spatial topological relation from the building information model; the real-time sensing module collects environment state data. The rule engine module matches the component attributes with the executable rule set to generate a first verification result; spatial topology and real-time sensing data are fused, the dynamic passing weight of each path segment is calculated, and an evacuation path network model is constructed. The path verification module verifies the safety of a path from a preset point to an exit based on the model, and generates a path verification result. And the result generation module outputs fire-fighting compliance data. According to the invention, through the dynamic optimal evacuation path planning from the static fire-fighting standard examination of the building design to the occurrence of the disaster, the guarantee capability and the emergency response efficiency of the building fire-fighting safety are improved.

The invention relates to the technical field of fire safety, in particular to a fire simulation early warning system based on intelligent fire protection multi-source data fusion, which comprises a sensor health degree dynamic evaluation module, an intelligent sensor health degree dynamic evaluation module and a fire simulation early warning module, establishing a two-dimensional feature library of the state of the sensor and environmental interference; and based on the feature library data, a fuzzy comprehensive evaluation method is adopted. By filtering unreliable data of the sensor, distinguishing multi-source contradictory data, dynamically adjusting weights according to fire behavior stages, iteratively updating data credibility and optimizing parameters in a closed-loop mode, the problems of false alarm and missing alarm in the prior art are effectively solved, and the accuracy and practicability of the intelligent fire-fighting early warning system are improved.

The invention discloses an intelligent layering and guiding device for highway tunnel fire smoke and a control method, and relates to the technical field of tunnel fire safety, a smoke flow Froude number is introduced as a direct control target, the parameter represents the ratio of smoke flow inertia force to buoyancy force, the numerical value directly determines the stability of a layering interface, and the layering interface can be directly controlled. The Froude number of each subarea of the tunnel is calculated in real time through a sensing network and is compared with a critical value calibrated through an experiment, when a real-time value is lower than the critical value, it is indicated that inertia force is relatively insufficient, the buoyancy effect is dominant, and instability and entrainment are likely to happen to an interface between a smoke layer and lower cold air, and then according to a control algorithm, the smoke layer and the lower cold air are controlled. The micro jet fan applies directional inertia force to a smoke layer by adjusting the angle and the speed, the intelligent induction smoke outlet optimizes local pressure difference and flow by adjusting the opening degree and assists in maintaining flowing, the smoke flowing state is actively locked in a stable layered flow interval, and mixing and sedimentation caused by flow state instability are prevented.

The invention relates to the technical field of security control systems, in particular to an escape door linkage method and system based on fire signals, and the method comprises the following steps: S1, obtaining local control suggestions corresponding to all microcontrollers; s2, based on all the obtained local control suggestions, generating a final global control instruction through linkage analysis; s3, the final global control instruction is sent to a door body driving motor so as to control a door body to execute corresponding opening and closing actions; wherein the local control suggestion comprises the target opening angle, the movement speed and the driving torque. According to the invention, the reliability of fire security and protection can be improved.

The invention discloses a multi-terminal linkage control method and system for a fire alarm scene, and relates to the technical field of energy storage system fire safety, and the method comprises the steps: configuring a composite cluster-level detector for each cluster of batteries of a target energy storage system, and collecting cluster-level external environment data; the method comprises the following steps: acquiring internal state data of a battery pack through a BMS, and uploading the two types of data to an edge calculation unit; the edge calculation unit performs fire risk assessment on the data and determines fire risk assessment parameters of the battery cluster; and determining a battery cluster fire extinguishing decision result, and finally performing multi-end linkage fire extinguishing control on the fire extinguishing device through the result. The technical problems that a traditional fire detection and fire extinguishing control scheme is slow in response, high in false alarm and missing alarm rate and incapable of giving consideration to internal and external states when dealing with thermal runaway of the energy storage system are solved, and the technical effects of early-stage accurate early warning and rapid linkage fire extinguishing and effective improvement of the fire safety level of the energy storage system are achieved.

The invention belongs to the technical field of fire-fighting facility control and management, and discloses a fire-fighting facility full-life-cycle intelligent operation and maintenance management control system. Comprising the following steps: acquiring real-time field state data; in a non-fire state, executing an active excitation and response test to obtain dynamic response data; processing the field state data and the dynamic response data by adopting an end-to-end multi-task learning framework, and outputting a structured diagnosis result containing the health states of the pump set, the valve and the pipe network; establishing an initial health baseline of each key device, and dynamically generating a self-adaptive alarm threshold value; a quantitative risk level is generated in combination with the fire safety level, and an operation and maintenance strategy instruction containing pilot operation and maintenance parameters is generated; main and standby equipment switching and strong health detection are automatically executed, and the fire protection function is preferentially guaranteed when a fire alarm or a manual forcing instruction is received; and executing grading alarm according to the quantitative risk grade. And intelligent operation and maintenance management control of the whole life cycle of fire-fighting equipment is realized.

The invention discloses a safety and disinfection integrated system based on AI analysis linkage control electromagnetic valves, and relates to the technical field of intelligent fire fighting, and the safety and disinfection integrated system comprises a flame detection camera, a network input and output module, a safety and disinfection integrated machine, an execution module and an acousto-optic alarm bell. According to the security and disinfection integrated system for linkage control of the electromagnetic valve based on AI analysis, the advanced AI visual recognition technology and an electromagnetic valve linkage control mechanism are deeply fused, the efficiency and the precision degree of fire safety management are greatly improved, flame characteristics are precisely recognized by means of a deep learning model, and the safety and disinfection effect is improved. The limitation that traditional fire behavior detection is easily influenced by environmental factors is broken through, the accuracy and reliability of fire behavior recognition are greatly enhanced, the system supports multi-modal data fusion, the confidence coefficient of fire behavior judgment is further improved, adjacent electromagnetic valves can be automatically started according to the position of a fire behavior in the linkage control link, an effective fire extinguishing isolation belt is constructed, and the fire extinguishing efficiency is improved. And fire spreading is effectively restrained.

The invention discloses a quantitative decision-making method for an electric vehicle fire safety three-level evaluation system. The quantitative decision-making method comprises the following steps: step 1, constructing a three-level evaluation index system; 2, performing quantitative scoring on the three-level indexes by the plurality of large language models to obtain an expert comprehensive scoring vector of each large language model; 3, calculating a subjective weight vector W (x) of each level of index according to the expert comprehensive scoring vector, and if the consistency ratio CR does not meet the consistency requirement, iteratively correcting W (x) by adopting a power method to obtain an initial weight vector system W; 4, introducing a fire news collection agent to generate a vehicle type subtraction item delta G and an accident cause amplification coefficient (1 + delta), and obtaining a subjective weight vector system W'after dynamic correction; and step 5, calculating a comprehensive score Sfinal, dividing fire risk grades, and generating a visual report. According to the invention, a three-level index system is constructed and a fire news collection agent is introduced, so that the timeliness and adaptability of the system are significantly improved.

The invention relates to the technical field of fire safety monitoring and early warning, in particular to a fire risk dynamic assessment and early warning method based on deep reinforcement learning, comprising the following steps: acquiring multi-source sensing data of a target area; a dynamically updated fire risk assessment state space is constructed based on multi-source sensing data, and a real-time state in the state space is processed and a risk assessment decision is generated through a deep reinforcement learning agent optimized based on an accumulated award function weighted by an accuracy award, a false alarm punishment and a missing alarm punishment; the deep reinforcement learning agent adopts a deep deterministic strategy gradient network structure; mapping the continuous output of the risk assessment decision into a discrete dynamic fire risk level; and triggering an early warning signal matched with the dynamic fire risk level according to the dynamic fire risk level. Through multi-source data standardization, dynamic state space, reinforcement learning optimization and grading early warning binding, accurate dynamic evaluation, reliable early warning and efficient emergency response are realized.

The invention provides a building fireproof detection data processing system and method based on multi-source data fusion, and belongs to the technical field of building fireproof detection data processing, and the system comprises a source data collection module which collects dynamic video image data, fire-fighting sensing parameters and fire-fighting equipment state monitoring data in a building in real time; the data intelligent analysis module is used for performing feature extraction on the dynamic video image data by adopting an AI algorithm to obtain video features, and judging whether a fire occurs in the building or not to obtain a video analysis result; the multi-source data fusion and decision module is used for fusing the video analysis result, the fire-fighting sensing parameters and the fire-fighting equipment state monitoring data analysis result to obtain a final building fire safety detection result, and fusing video features to generate fire scene features; and the fire report sending module is used for generating a fire scene report based on the fire scene characteristics and the final building fire safety detection result so as to provide powerful guarantee for building fire safety.

Provided is a battery module and battery rack having enhanced fire safety features. The battery module includes a swelling / pressure sensor that detects swelling of a battery cell. An output signal of the sensor is used to halt operation of a battery rack / battery system containing the battery module and prevent charging and discharging of the battery module. In an embodiment, the battery module uses an AC-to-AC power supply to provide AC frequency power for balancing battery cells of the battery module. In an embodiment, the battery rack includes an internal water fire suppression system that provides battery cooling in the event of a battery cell fire to prevent the spread and / or reigniting of the fire.

The application discloses a kind of based on deep learning's cable over fire maximum temperature fast nondestructive prediction method, it is related to bridge post-fire safety evaluation technical field.The method obtains the apparent image data of cable anticorrosion-fire protection system at different temperatures by various fire tests, and constructs special data set after shunt pretreatment;Innovatively, a double-branch weight sharing prediction model based on ConvNeXt-Tiny is constructed, the state characteristics of cable flame-retardant sealant layer and anticorrosion layer are extracted by two parallel branches respectively, deep representation learning is carried out by feature fusion and shared backbone network, and finally high-precision parallel prediction of double temperature parameters is realized by two ordered classification prediction heads;Using transfer learning strategy and hybrid loss function for training, the prediction accuracy and generalization ability are significantly improved;Finally, a visual window is developed to realize the fast nondestructive evaluation of cable over fire temperature without disassembly and sensor.The method provides reliable technical support for post-fire safety performance evaluation of bridge cable.

The invention belongs to the technical field of fire safety management, and particularly relates to an intelligent early warning method and system for fire safety management, and the method comprises the steps: obtaining multi-source fire sensor data; training a basic multi-modal fusion model according to the multi-source fire-fighting sensor data to obtain fire risk probability data, and meanwhile, generating sequential aligned continuous video frames through basic inter-frame feature matching; according to continuous video frames, space-time joint features are extracted by using a basic space-time convolutional network, local feature maps of flames and smog are generated in combination with a lightweight backbone network, a fire source key area is positioned, and a fire spreading direction and a fire spreading speed are analyzed to obtain a risk change trend; and based on the risk change trend, identifying a fire risk level through a lightweight classification model, carrying out risk scoring on the safety degree, and generating a thermodynamic diagram to mark a high-risk area. Therefore, the problems of insufficient multi-source data fusion depth, weak video analysis time sequence coherence, lack of visualization ability and the like in the prior art are solved.

The invention discloses a building fire safety management and control method based on a digital twinborn technology, and the method comprises the steps: constructing sensor-middle platform-model bidirectional mapping, and reconstructing a dynamic scene through employing a neural radiation field technology; fusing the cross-domain desensitization data based on federal transfer learning, and constructing a building total-factor dynamic digital mirror image; through a spectrum analysis algorithm, a fire source is positioned in real time, and a flame spreading track is predicted; performing fire simulation in linkage with a total-factor dynamic digital mirror image, and optimizing a fire-fighting resource scheduling path through a multi-target particle swarm optimization algorithm; a multi-target rescue scheme is generated, an asynchronous block chain is used for evidence storage of a fire-fighting decision instruction, a rescue key area is plotted, and an optimal evacuation route is planned; and converging federal node data to quantify the data contribution degree, reproducing a historical fire behavior and deducing a new scene to carry out iterative optimization. According to the method, the problems of data sensing fragmentation, difficulty in cross-domain fusion, fire prediction lag, underscientific resource scheduling, slow drill scheme iteration and the like in traditional management and control are solved.

The invention discloses an evacuation path dynamic planning method and system based on an HPSO-IGWO algorithm, and relates to the technical field of fire safety and emergency evacuation. The system mainly comprises a fire information acquisition module, a data processing coordination module, a path planning module and an evacuation indication module. The fire information acquisition module acquires information such as the position, smoke concentration and temperature of a fire through a sensor, and transmits the acquired data to the data processing coordination module; the data processing coordination module sends the data to the path planning module, so that the evacuation path is planned and optimized by using an HPSO-IGWO algorithm, the path is dynamically adjusted according to the real-time condition of the fire, and the safety and optimality of the evacuation path are ensured; and finally, the path planning module sends the planned evacuation path information to each LED evacuation indicator through the wireless sensor network, and the indicators display the evacuation direction in real time according to the information sent by the server to guide people to evacuate along the planned path.

The invention relates to the technical field of fire safety, and discloses a heptafluoropropane fire detection tube fire extinguishing system with an internet of things intelligent monitoring function. The cross-modal physical field sensing module is used for collecting internal physical field data and external environment field data of a protected area in real time; the fire detection tube health assessment and adaptive scanning control module is used for receiving the internal physical field data to execute health state assessment; the cross-modal correlation interference discrimination module is used for receiving internal physical field data and external environment field data; the fire process evolution analysis and time-space association confirmation module is used for receiving data of potential fire events; a precise fire extinguishing strategy generation module; a precise targeted response execution module; and a remote situation awareness and monitoring interaction module. Through the combination of multi-source data verification, health state self-evaluation and accurate response, the problems that a traditional system is weak in anti-interference capacity and prone to false alarm and waste of a fire extinguishing agent are effectively solved, and the accuracy of fire detection and the high efficiency of fire extinguishing response are remarkably improved.

The invention discloses an early warning method and system for intelligently detecting fire scene waste heat reburning based on AR glasses, and relates to the technical field of fire safety intelligent monitoring. The early warning method comprises the following steps: scanning a conical area in front of a visual field in real time based on AR glasses, capturing temperature matrix data and collecting environmental parameter data, and identifying afterheat hot spots in the visual field and associated article types based on a YOLOv8s model; based on edge AI comprehensive temperature matrix data and environmental parameter data, risk indexes of residual heat hot spots are calculated in real time and visualized into low, medium and high risks; locking and analyzing the temperature change of the medium-high risk article, dynamically correcting the safety coefficient in combination with an article material database, and visualizing the detailed information, the real-time temperature and the risk index of the article; and spraying and cooling the high-risk target based on the guidance of AR glasses, and judging whether the risk is relieved or not according to the temperature attenuation rate and the risk index. By implementing the technical scheme provided by the invention, the fire scene afterheat after-combustion hidden danger can be quickly, comprehensively and intuitively detected.

The invention relates to the technical field of fire safety, in particular to a fire operation whole-course acousto-optic identification monitoring and early warning system, which comprises front-end data acquisition equipment and rear-end data processing equipment in two-way communication with the front-end data acquisition equipment, the front-end data acquisition equipment comprises a visual information acquisition device and a sound information acquisition device and is used for acquiring a visual light source signal and a voiceprint signal of a fire operation site, encrypting the visual light source signal and the voiceprint signal and transmitting the signals to the rear-end data processing equipment; the rear-end data processing equipment comprises a feature extraction and analysis module and a platform early warning module; the feature extraction and analysis module is used for carrying out feature extraction on the received visual light source signal and voiceprint signal and carrying out fire operation danger signal identification based on extracted feature parameters; and the platform early warning module is used for determining the current risk level and carrying out risk early warning based on the fire operation danger signal identification result, so that pre-identification and timely alarm of the danger signal in the fire operation process are realized.

The invention discloses a fire-fighting equipment intelligent monitor cooperating with a safety management platform and a predictive maintenance method, and relates to the technical field of fire-fighting safety management and internet-of-things crossing, the monitor is configured to be installed on fire-fighting equipment and is in communication connection with a central safety management platform, and the monitor comprises a sensor module, a data processing module and a data processing module, the data acquisition module is used for acquiring real-time state data of the fire-fighting equipment; the main control module is electrically connected with the sensor module and is used for processing the real-time state data; and the communication module is electrically connected with the main control module and is used for sending the processed real-time state data to the central safety management platform through a wireless network, and the conversion from regular maintenance to on-demand maintenance is realized by establishing an automatic and non-tampering electronic inspection record and a predictive maintenance model based on data trend analysis.

The invention discloses a fire intelligent identification and grading early warning method and system based on multi-modal fusion, and belongs to the technical field of fire safety monitoring. The method comprises the steps that time sequence sensor data and image data of a monitoring area are collected in real time and preprocessed; inputting the preprocessed time sequence sensor data into a time sequence prediction model, determining a time sequence fire probability value, and comparing the time sequence fire probability value with a dynamically optimized primary judgment threshold value; when the time sequence fire probability value is greater than or equal to the primary judgment threshold value, inputting the preprocessed image data into an image recognition model, and determining an image fire probability value; carrying out weighted fusion on the time sequence fire probability value and the image fire probability value by adopting a self-adaptive dynamic weight fusion strategy to obtain a comprehensive fire probability value, and comparing the comprehensive fire probability value with a dynamically optimized optimal fusion threshold value; and according to a comparison result, determining a corresponding early warning strategy from preset multi-stage fire early warning strategies and executing the corresponding early warning strategy.

The invention provides an electric window control method and system based on fire-fighting linkage, and relates to the technical field of building fire-fighting, firstly, a fire-fighting linkage basic information set of a building fire-fighting system is obtained, and the fire-fighting linkage basic information set comprises information such as a building structure, fire-fighting facility layout, an electric window installation position and real-time fire-fighting monitoring data; performing multi-dimensional state analysis on the fire-fighting linkage basic information set to obtain a building fire-fighting risk state and electric window equipment linkage state information, matching a fire-fighting linkage rule based on an analysis result to generate an electric window control strategy set, sorting the strategy set according to control priority parameters to obtain an electric window control instruction set, and performing electric window control on the electric window control instruction set. And finally, the electric window control instruction set is sent to an electric window executing mechanism, opening, closing or adjusting operation is executed, and executing state information is returned, so that precise linkage of the electric window and a fire fighting system is achieved, and the building fire fighting safety performance is improved.

The invention particularly relates to a control method applying an unmanned aerial vehicle and based on multi-modal characteristics of a fire source, and relates to the technical field of fire safety. Acquiring multi-modal data of a fire source in real time; comprehensively estimating the heat power of the fire source; correcting combustion intensity; and quantitative calculation of fire extinguishing agent demand. An infrared imaging sensor, a visible light camera and a gas sensor array are integrated, a multi-mode fire source sensing system is constructed, the sensing limitation that a traditional fire extinguishing system only depends on single temperature or image is broken through, fire source temperature distribution, flame forms and combustion gas concentration changes can be comprehensively captured, and complete data support is provided for fire behavior judgment; the thermal power of a fire source is estimated in a fusion manner, a fuel type is combined to calibrate a correction coefficient, a differential quantitative calculation model is established according to liquid and solid fire extinguishing agents, fire disasters of different fuels such as wood, gasoline and plastic are adapted, and economy and fire extinguishing reliability are both considered.

The invention relates to the technical field of fire risk assessment, in particular to a fire risk assessment method and device for an energy storage power station, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining the structure information and equipment information of the energy storage power station, and constructing a three-dimensional simulation model; a three-dimensional simulation model is used for conducting simulation analysis through multiple physical fields, and disaster diffusion trends under various emergencies are obtained; the method comprises the following steps: simulating an emergency response plan in a multi-physics field simulation process based on disaster diffusion trends under various emergencies, fire-fighting equipment deployed by an energy storage power station and the corresponding emergency response plan, and performing fire-fighting risk assessment on a simulation result to obtain an assessment result. Modeling is carried out by utilizing physical characteristics and fire dynamics, so that the fire extinguishing design efficiency and accuracy are improved, the design cost and time investment are remarkably reduced, and a powerful guarantee is provided for the fire safety of the energy storage power station.

The invention discloses a building fire protection transformation method, device and equipment and a medium. The method comprises the steps of obtaining building information corresponding to a to-be-transformed building, wherein the building information comprises a building category and a building age of the to-be-transformed building; determining an index set and a weight set of fire fighting capability assessment corresponding to the to-be-transformed building based on the building category, wherein the weight set comprises a weight coefficient corresponding to each index in the index set; determining a fire protection risk corresponding to the to-be-transformed building and a risk evaluation value corresponding to the fire protection risk based on the index set and the weight set, and determining a fire protection transformation strategy corresponding to the to-be-transformed building based on the fire protection risk and the risk evaluation value; and if the overall fire safety performance of the building under the fire-fighting reconstruction strategy passes the assessment of a preset fire safety algorithm, performing fire-fighting reconstruction on the to-be-reconstructed building based on the fire-fighting reconstruction strategy. According to the method, the quality and safety of fire-fighting transformation can be improved, the fire-fighting risk after transformation is effectively reduced, and the safety of personnel and property in a building is guaranteed.

A battery pack includes a pack case including a plurality of module mounting areas divided by partition walls, battery modules each including a sensor member for transmitting a danger signal when a thermal event occurs, the battery modules being respectively located in the plurality of module mounting areas, and a fire extinguishing unit configured to receive the danger signal and supply fire extinguishing water to the module mounting area in which a target battery module transmitting the danger signal among the battery modules is located.

The invention relates to the technical field of electrochemical energy storage power stations, in particular to a fire safety assessment method and system for an electrochemical energy storage power station, and the method comprises the following steps: S1, collecting battery cluster operation data, environment data and spatial topology data, and carrying out the fusion to generate a power station multi-dimensional safety data asset set containing a spatial association relationship; s2, identifying a risk source battery cluster based on the data asset set, and calculating a dynamic heat spreading risk index of the risk source battery cluster to a surrounding battery cluster; and S3, judging the highest risk propagation path according to the risk index, and generating a physical isolation strategy which comprises starting a nearby fire-fighting device and adjusting the ventilation direction to form a negative pressure isolation area. According to the method, accurate identification, quantitative evaluation and active intervention of the fire risk of the electrochemical energy storage power station are realized by constructing the multi-dimensional safety data asset set of the power station, fusing thermal radiation and ventilation coupling modeling and generating a dynamic isolation strategy based on a high-risk propagation path.