616 results about "Fire spread" patented technology

The invention relates to the technical field of fire prevention and control, in particular to a BIM and AI algorithm-combined fire spreading path evaluation system, which comprises a multi-source data fusion module, a fire source positioning module, a spreading path prediction module, a risk evaluation module and an intelligent linkage module. A three-dimensional dynamic model is generated by fusing sensor data and BIM data, accurate fire source positioning and fire spreading path prediction are achieved, the regional risk level is quantified in combination with building information, and a control instruction is sent to fire fighting equipment to isolate a high-risk region and delay fire spreading. The fire source positioning precision, the fire behavior prediction reliability and the emergency response efficiency can be improved, and scientific decision support is provided for building fire prevention and control.

The invention discloses a forest-town junction region fire dynamic early warning method based on multi-source data assimilation, and the method comprises the following steps: inputting collected multi-source observation data into a fire risk prediction model for training, and outputting a fire risk grid map covering the whole forest-town junction region for monitoring a high-risk building group; constructing a fire spreading numerical model covering multi-material, multi-scale and multi-physical mechanism coupling; a fire propagation characteristic quantitative model is constructed, and the building heat influence is evaluated; and constructing a data assimilation and fire dynamic prediction model, and dynamically predicting and outputting fire spreading parameters and a spreading trend chart. According to the method, a forest-building-oriented complex scene is constructed, and propagation behaviors of flames under multiple mechanisms of convection, radiation and conduction are effectively described; through the modes of risk identification, dynamic simulation, data assimilation, visual early warning and the like, the precision, response speed and engineering applicability of forest-town boundary region fire prediction are remarkably improved.

The invention discloses an intelligent building fire identification and simulation early warning method and system, belongs to the technical field of building informatization and disaster prevention and control, and aims to solve the technical problems of how to realize fire early identification, fire intelligent prediction and evacuation path dynamic planning, improve fire identification accuracy and response speed, and improve the safety and reliability of a building. According to the technical scheme, the method comprises the steps of BIM modeling, wherein a high-precision three-dimensional space model is established based on building information modeling, and the high-precision three-dimensional space model is deeply coupled with an FDS fire numerical simulation engine; multi-modal data acquisition: performing data acquisition by adopting a visual, environmental and spatial multi-modal sensor, and performing feature fusion on the acquired data by using a multi-channel deep convolutional network to generate unified space-time fire characterization; a video-sensing-geometric data collaborative sensing network is constructed on the basis of space-time fire characterization, so that the recognition robustness in a complex environment is improved; intelligent identification and decision making; performing early warning control linkage; and post-disaster assessment feedback.

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 discloses a virtual reality fire drill and training method and system, and the method comprises the steps: building a three-dimensional fire scene based on a BIM model and fluid dynamics, resolving the fire spreading rate and the smoke concentration in real time, and generating a dynamic disaster evolution model in combination with explosive parameters; collecting the heart rate variability and the action track of the user through the wearable device, and calculating a physiological stress index and a device operation deviation degree; smoke suppression, explosion delay and fire behavior correction instructions are triggered based on fire behavior and physiological data association; a cooperative avoidance strategy is generated in combination with the path overlap ratio and the fire-fighting role and is fed back to the fire behavior correction module; aligning the spatio-temporal data to evaluate the contribution degree and the cooperative influence weight of the fire extinguishing operation on fire behavior inhibition, and outputting a multi-dimensional evaluation matrix; generating a three-dimensional defect thermodynamic diagram by using a space-time convolutional network, marking a high-risk area and feeding back the high-risk area to a disaster model, and realizing adaptive difficulty iteration; according to the invention, through multi-source data fusion and dynamic regulation and control, the drill authenticity and the emergency disposal efficiency are improved.

The invention discloses a coal mine goaf fire monitoring method and system based on multi-source data fusion, and relates to the technical field of coal mine goaf fire monitoring, and the method comprises the steps: collecting the concentration, concentration and air pressure of each wireless sensing node in a coal mine goaf in real time; according to the concentration of each node, a dual-parameter dynamic coupling gradient field traceability algorithm of fusion / gas expansion and chemical reaction mechanism is adopted to calculate a fire source coordinate; performing anomaly detection according to the concentration of each node, and positioning an air leakage point by adopting a three-dimensional oxygen concentration gradient field positioning algorithm and combining air pressure compensation for an oxygen concentration anomaly point; based on goaf point cloud data, a goaf three-dimensional grid model is constructed, and a fire source spreading path, an air leakage channel and gas concentration distribution are dynamically and visually displayed in combination with multi-source monitoring data and fire source and air leakage point positioning results. The goaf fire prevention and control system can achieve all-around prevention and control of goaf fire.

The invention belongs to the technical field of forest disaster monitoring and early warning, and particularly discloses and provides a forest fire spreading prediction method based on multi-dimensional features, which comprises the following steps: dividing a target area into grid units, collecting an infrared thermal imaging data sequence through an unmanned aerial vehicle, dynamically evaluating fire intensity indexes of the grid units, and predicting the fire intensity indexes of the grid units. Identifying each fire spreading path, evaluating the spatial proximity of each grid unit relative to the path, marking a fire occurrence area, and determining the path intersection density in each grid unit; fusing the fire intensity index, the path space proximity and the path intersection density, calculating to obtain a comprehensive fire spreading risk index of each grid unit, and generating a forest fire spreading danger level zoning map based on the index; according to the method, the fire spreading risk of each grid unit is comprehensively evaluated by fusing the fire intensity index, the path space proximity and the path intersection density, and refined and three-dimensional evaluation of the risk of the unburned area is realized.

The invention discloses a subway tunnel fire behavior spreading prediction method, which comprises the steps of 1, fire source type digital modeling, 2, fire scene initialization, 3, dynamic fire source loading and ignition triggering, 4, fire behavior spreading multi-physics field coupling calculation, 5, ventilation system dynamic response, 6, visual risk thermodynamic diagram generation, and 7, fire behavior spreading prediction. Step 7, carrying out real-time early warning on the safety margin; the method has the beneficial effects that a total factor modeling capability is realized, multi-dimensional parameter input from fire source characteristics to a tunnel environment is supported, a scene range covering a typical subway fire disaster is expanded, solving is realized through a multi-physics field simultaneous equation, a fire spreading error is reduced, smoke diffusion simulation precision is improved, and a dynamic ventilation adjustment and safety early warning mechanism is realized. And more buffer time is provided for emergency response.

The invention relates to the technical field of forest fire monitoring and power grid safety prevention and control, and discloses a fire scene spreading time sequence reconstruction method based on Doppler weather radar mountain fire echoes, which comprises the following steps: acquiring original data of the Doppler weather radar mountain fire echoes and carrying out quality control processing to obtain radar echo data; performing automatic segmentation of a smoke plume area on radar echo data by adopting an optimized Otsu-Unet network model, and extracting a centroid coordinate of a mountain fire echo area; a Kalman filtering algorithm is used and combined with external three-dimensional wind field data to predict a future motion trend of centroid coordinates of a forest fire echo region so as to reconstruct a continuous fire scene spreading time sequence voxel sequence; performing 3DTiles slicing processing on the fire scene spreading time sequence voxel sequence, and performing real-time rendering display on a power grid monitoring platform by using a WebGL technology; and obtaining an external expansion boundary of fire scene spreading based on the fire scene spreading time sequence voxel sequence, and calculating the distance between the external expansion boundary and the power transmission line GIS data in real time. The fire prevention and control capability of the power transmission line of the power grid is improved.

The invention discloses a scene preprocessing method for fire simulation, and relates to the technical field of building fire simulation, and the method comprises the steps: calculating a three-dimensional thermal weight through employing a fire propagation dynamics model, and generating a fire dangerous region thermal diagram; through a tensor field generation algorithm, fire behavior main diffusion direction and each axial anisotropic parameter are extracted, and fire behavior grid parameters are generated; through a hybrid grid generator, performing hexahedron dominant grid construction and increasing the grid density of a fire behavior dangerous area to obtain a fire behavior optimization hybrid grid; performing Reynolds number verification and boundary layer matching on the fire behavior optimization hybrid grid through a fire behavior feature adaptive algorithm, and performing iterative correction to generate a fire simulation correction grid; according to the invention, through the hybrid grid generator, the self-adaptive distribution of the grid density of the fire hazard area and the smooth connection of the transition area are realized, so that the grid distribution of the fire hazard area is accurately matched with the fire spreading characteristics.

The invention discloses a fire simulation method, device, equipment and medium for a new energy vehicle roll-on and roll-off place, and the method comprises the steps: building an accurate fire risk simulation evaluation model, setting a roll-on and roll-off place vehicle mixed transportation and partition transportation fire scene model, and carrying out the simulation of a new energy vehicle on the basis of temperature distribution, thermal radiation intensity and other key data. According to the method, the fire spreading condition of the electric vehicle under different transportation strategies is simulated, then the effectiveness of the transportation strategies is evaluated, the roll-on-roll-off ship transportation strategies are formulated according to the vehicle power mode, a scientific basis is provided for formulating reasonable roll-on-roll-off site transportation strategies and emergency response measures, and therefore the safety of the new energy vehicle roll-on-roll-off site is improved.

The invention provides an intelligent building fire safety early warning system based on intelligent fire protection, and relates to the field of fire safety, and the system comprises a distributed data collection module which is used for achieving data real-time collection and network disconnection local processing through heterogeneous sensor networking and dual-mode communication; the edge processing module is used for carrying out edge processing on the output standardized environment data flow by adopting a fire behavior triple verification model and a dynamic weight algorithm, and carrying out cross-node model sharing in combination with a federated learning framework so as to obtain a fire risk score and a fire source positioning coordinate; the decision execution module is used for dynamically planning an evacuation path; the feedback module is used for performing real-time rendering fluid dynamics fire spreading simulation on the evacuation path and generating multi-terminal early warning; and the dynamic evacuation optimization module simulates and optimizes the exit position and the path planning through fluid dynamics to obtain the optimized path planning. The method and the device are used for overcoming the defects of cloud processing delay and failure during network disconnection in the prior art.

The invention provides a chemical industrial park fire spreading prediction method and system. The method comprises the following steps: dividing a grid chart structure of a target chemical industrial park space structure into a plurality of function partition sub-graphs; determining a fire propagation flux of a shared node in an overlapping region between every two adjacent function zone sub-graphs, converting each function zone sub-graph into a macro-scale sub-graph, and determining a fire propagation macro-situation of the target chemical industrial park; according to the fire propagation flux and the fire propagation macroscopic situation, determining a fire front edge envelope line of each area, thereby constructing a fire propagation prediction model of the target chemical industry park, inputting fire initial environment data into the fire propagation prediction model, and outputting a fire propagation prediction result. And automatically triggering a fire alarm signal of the target park according to a fire spreading prediction result. By adopting the scheme of the application, the fire spreading of the target chemical industrial park can be predicted by combining the dynamic fire interaction among the areas in the target chemical industrial park.

The invention relates to the technical field of data management, in particular to a digital twinning-based smart park visual management method, which comprises the following steps of S1, acquiring real-time data through a multi-source sensor, formulating a uniform data format specification and an interface protocol, performing data access conversion, and outputting uniform data; s2, an integrated three-dimensional digital twinborn model is established according to the unified data, and a simulation engine and an event linkage rule engine are introduced for real-time deduction. During use, by establishing the park integrated three-dimensional digital twinborn model, when an emergency situation such as a fire alarm occurs, real-time deduction can be carried out; the method comprises the following steps: automatically deducing simulation animations of entrance guard opening and personnel evacuation in a digital twin interface, synchronously turning off ventilation systems of related floors at the same time to form a linkage reaction, further predicting the fire spreading direction and time through a simulation engine, and intuitively presenting a future change trend through a visual means, so as to improve the fire spreading effect. And the cognition and response speed of a manager to potential risks and resource demand changes can be improved.

The invention provides fire extinguishing spraying equipment which comprises a stator and a rotor arranged outside the stator, a water flow channel is designed in the stator, a connector capable of rotating around the stator is movably connected to the lower end of the stator, a nozzle is connected to the connector, and the connector or the nozzle is in transmission connection with the rotor. And the rotor can drive the nozzle to rotate in a rotating state. Spraying equipment is designed to be of a rotatable positioning water outlet structure, original fixed blasting type fire extinguishing spraying is innovated and upgraded, more accurate fire extinguishing is achieved, the spraying equipment is improved, the fire spreading risk is reduced, the fire prevention and extinguishing capacity of a defense area is greatly improved through application of the technology, and the device is simple in structure, good in durability and high in practicability. And the practicability and the chemical degree are high.

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 relates to the technical field of radar fire source positioning, in particular to a light quantum radar fire source identifying and positioning method and system for a fire extinguishing robot. Acquiring radar point cloud data, temperature time sequence data and smoke concentration time sequence data of a fire scene; comparing the radar point cloud data with preset radar point cloud data, identifying smoke data points, analyzing motion characteristics of the smoke data points to determine a smoke diffusion path, and analyzing changes of temperature and smoke concentration time sequence data to determine a fire spreading path; comparing the two and combining temperature and smoke concentration change characteristics, identifying a real fire behavior evolution trend, and screening suspected fire source positions; and at each suspected fire source position, the initial power and the resolution of the light quantum radar are adaptively and intelligently adjusted according to indexes such as the area to be measured, the environmental complexity and the smoke concentration, fire source identification and positioning are carried out with the optimal performance, and the accuracy and the stability are improved. The range is dynamically reduced, radar parameters are adaptively adjusted, and accurate positioning of a fire source is facilitated.

The invention relates to an emergency evacuation path generation method, system and device under multi-target conflict and a medium. The method comprises the following steps: acquiring video monitoring data and environment sensing data of a target building, and performing fire disaster detection according to the video monitoring data to obtain a fire detection result; in response to the fire detection result that the fire disaster exists, performing fire evolution prediction according to the environment sensing data based on the environment topological graph of the target building to obtain fire evolution parameters; performing risk assessment and latest passable time marking on each space unit node in the environment topological graph according to the fire evolution parameters to obtain a risk graph layer; and in response to the obtained positions of the to-be-evacuated persons, generating an exclusive emergency evacuation path of each to-be-evacuated person in combination with the environment topological graph and the risk map layer. According to the method, fire detection and fire spreading deduction are carried out through continuous video image frames, time sequence judgment is carried out on traffic effectiveness, and path design is prevented from lagging behind risk change.

The invention discloses a fire behavior prediction method and system based on an unmanned aerial vehicle image, and a storage medium, and relates to a fire monitoring and early warning technology. According to the method, the unmanned aerial vehicle is used for carrying multispectral, visible light and infrared cameras to obtain target area image data, and target data are matched for unit areas of non-fire areas in combination with meteorological station meteorological data and database geographic data; dynamically adjusting weight coefficients of temperature, humidity, wind speed, wind direction and terrain, and calculating a unit area spreading coefficient; constructing the fire point information, the spreading coefficient and the position coordinates into model input data, and inputting the model input data into a trained LSTM model to predict a fire spreading trend; the defects of a traditional fire monitoring and predicting technology are effectively overcome, information can be obtained more comprehensively and timely through multi-source data collection and fusion, the accuracy and timeliness of fire prediction are remarkably improved through combination of dynamic weight adjustment and an advanced model, and powerful support is provided for fire prevention and control and rescue decision making.

The invention relates to the technical field of virtual training, in particular to a firefighter search, rescue and escape virtual training method and system, and the system comprises a virtual scene dynamic construction module which abstracts a room and a corridor intersection into nodes according to a planar graph of a building, abstracts a door and a channel into edges with geometric distance weights, and carries out the virtual scene dynamic construction module; and responding to a fire spreading or structure collapse event in the virtual training, adjusting the weight of a corresponding edge to be infinite, obtaining a shortest path, and establishing a reference rescue path set. According to the method, through dynamic analysis of building plan structure information, rooms and corridor intersections are abstracted as nodes, doors and channels are abstracted as edges with geometric weights, the accessibility of the edges is adjusted in real time after fire spreading or structure collapse occurs, impassable conditions are introduced during path calculation, and the path calculation accuracy is improved. And the real-time adaptability and rescue simulation precision of the path generation process are improved.

The invention relates to the technical field of fire source detection, and discloses a fire source detection identification and alarm system and method for an intelligent fire-fighting robot, and the method comprises the steps: employing a deep learning target detection model, carrying out the high-precision identification of a fire source based on the data of a multi-modal sensor, extracting the initial three-dimensional position coordinates of the fire source, and providing basic data for subsequent tracking; besides, the fire source is dynamically tracked based on a Kalman filtering algorithm, the fire source spreading trend is predicted in combination with the motion state of the fire source, a fire behavior development prediction map is further constructed, and accurate pre-judgment of the fire behavior spreading range is achieved. And according to a fire source identification result and a fire behavior development prediction map, a fire alarm strategy is optimized, an alarm level, a personnel evacuation route and fire-fighting resource allocation are dynamically adjusted, and the intelligent degree of fire emergency response is improved. According to the technical scheme, the accuracy and real-time performance of fire monitoring can be effectively improved, the intelligent level of fire prevention and control and emergency disposal is improved, and casualties and property losses are reduced.

The invention relates to the technical field of fire spreading prediction, and discloses a fire spreading prediction method and system based on local real-time high-precision weather prediction, a terminal and a storage medium, and the method comprises the steps: obtaining fire observation data collected by a plurality of pieces of information collection equipment for a target region, preprocessing the fire observation data through an edge calculation layer to obtain target fire observation data; a lightweight 3D-Transform architecture is designed based on a big archaeological meteorological model, and the target fire observation data and historical fire scene case data are fused to generate a meteorological prediction result; and constructing a fire spread prediction network model, jointly inputting the meteorological prediction result, the terrain elevation and the fuel humidity, and outputting a fire spread probability graph and a spread velocity field in a future preset time. According to the method, the fire spreading prediction precision and speed are improved, and a high-precision and high-response full-chain solution is provided for forest fire emergency management.

The invention relates to a virtual simulation emergency drilling method and system under a mine fire dynamic catastrophe condition based on deep reinforcement learning, and belongs to the field of mine safety management. According to the method, a mine comprehensive database is constructed, environment, equipment, fire source and ventilation system data of a mine are collected, a mine structure model is generated by using a three-dimensional modeling technology, and a mine fire spreading process is simulated in real time through fire dynamics simulation, deep reinforcement learning optimization and a virtual reality technology. The drill personnel enter the fire disaster simulation environment through the virtual reality equipment to carry out emergency operation, and the system carries out real-time feedback according to the operation of the drill personnel and optimizes the fire disaster spreading simulation model. Parameters such as wind speed and wind quantity of the ventilation system and fire spreading are subjected to coupling calculation, so that the accuracy and dynamic response of fire simulation are ensured. According to the system, through cooperative work of a plurality of modules, intelligence, individuation and high efficiency of mine fire emergency drilling are realized, and the emergency response capability of drilling personnel is effectively improved.

The invention discloses a power distribution box suitable for a low-carbon smart power grid, and particularly relates to the technical field of power distribution boxes, the power distribution box comprises a box body, one side of the box body is rotatably connected with a box door, one side of the interior of the box body is fixedly provided with a PLC, one side of the interior of the box body is fixedly provided with a short circuit grounding indicator, and the other side of the interior of the box body is fixedly provided with a power supply. The PLC is electrically connected with the short-circuit grounding indicator, a miniature air compression pump is fixedly mounted on the bottom surface of the interior of the box body, and the miniature air compression pump is electrically connected with the PLC; after a fire behavior is detected, the system presses down the wire connection position through the second pneumatic push rod to achieve forced power failure, meanwhile, the first pneumatic push rod moves equipment into a closed cabin composed of the upper closing cover and the lower closing cover, and a puncture nail is triggered to puncture a fire extinguishing bag to extinguish fire; therefore, integrated operation of automatic power-off, moving-out, sealing isolation and active fire extinguishing of ignition equipment is achieved, fire spreading is effectively restrained, and safety is greatly improved.

The invention discloses a fire early warning cooperative system composed of a thermal imaging double-spectrum intelligent ball, an intelligent analysis platform and a fire extinguishing unmanned aerial vehicle, which is applied to the technical field of fire early warning, and comprises the thermal imaging double-spectrum intelligent ball, an integrated visible light sensor and a thermal imaging sensor, and a double-spectrum fusion monitoring technology is adopted to carry out omnibearing and all-weather monitoring; the intelligent analysis platform simulates a fire spreading path based on a fire spreading prediction model of a fluid dynamics and machine learning algorithm, generates a three-dimensional fire danger thermodynamic diagram, and completes a whole-process response from regional early warning to command center decision making to unmanned aerial vehicle cluster task distribution through a multi-level early warning mechanism; the fire extinguishing unmanned aerial vehicle adopts a multi-model collaborative operation system to meet the fire extinguishing requirements of different fire scenes. According to the invention, in a complex and changeable fire scene, the fire hazard can be quickly and accurately identified, and the efficient disposal of fire extinguishing operation is realized.

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 belongs to the technical field of remote control, and particularly relates to an internet-of-things remote inspection system based on multi-modal fire-fighting sensing data, which comprises a multi-modal data acquisition module, a judgment module and a fire behavior trend prediction module, and is characterized in that the multi-modal data acquisition module is used for acquiring an RGB three-dimensional image, a smoke concentration matrix and a thermal value matrix of a monitoring area in real time; the judgment module carries out feature fusion on the multiple data sources and then judges whether a fire exists, and the fire behavior trend prediction module predicts the space change trend of flames and the boundary change trend of smoke and then carries out space fusion on the space change trend and the boundary change direction of the smoke to generate a fire behavior trend chart. Compared with the judgment that only the change trend of the simple flame area is used as the development trend of the fire, the judgment on the spreading trend of the fire is quicker, and the accuracy is higher.

The invention relates to the technical field of battery energy storage, in particular to a high-efficiency and high-power-density power supply which comprises a protection box, a mounting groove is formed in the protection box, and through use of a multi-stage heat dissipation assembly and an induction fire extinguishing assembly, in the working process of a power supply main body, when low-power operation is carried out, the power supply main body does not work; cooling can be achieved only through cooperation between a heat dissipation pump and a heat dissipation pipe, when high-power use is conducted and the temperature exceeds a set threshold value, a servo motor is driven to start to dissipate heat, air cooling and water cooling are matched with each other, the heat dissipation efficiency is greatly improved, the service life of the device is prolonged, and when a fire occurs in an extreme situation, an induction fire extinguishing assembly is used for extinguishing fire. The internal device is destructively driven, so that open fire is treated in the first time, the interior of the device is sealed, and the possibility that external oxygen enters the protection box is reduced and isolated, and the possibility that other injuries are caused by fire spreading when a fire breaks out is greatly reduced.

The invention provides a dangerous chemical fire accident tracing method based on RFID, and belongs to the technical field of fire tracing, and the method comprises the steps: configuring an RFID tag for each dangerous chemical container; based on a pre-deployed read-write network, information of each RFID tag is read and transmitted to a central data platform, and a dynamic information database of the dangerous chemicals is established; integrating the residual label information with a dynamic information database, tracing a position sequence and a state sequence of the dangerous chemicals before the fire occurs, and simulating a fire spreading path and an expansion trend of each path point on the spreading path according to the current fire situation and the residual label information of the dangerous chemicals; and comprehensively judging the cause of the fire accident and generating a traceability accident report. And the safety of dangerous chemical management is improved.

The invention relates to the technical field of fire safety and simulation training, and discloses a rule-driven fire-fighting real smoke and real fire training simulation system, which comprises a data acquisition and modeling module, a rule driving module, a rendering output module and a training evaluation module. The data acquisition and modeling module is used for acquiring initial fire data and constructing a reference model of smoke diffusion and fire spreading; the rule driving module simulates the non-synchronous evolution process of the fire through a particle simulation algorithm, a time coordination rule and a feedback loop algorithm; the rendering output module is used for integrating the environment rendering data and the multi-factor propulsion mode and generating a training effect evaluation index; and the evaluation optimization module judges whether the simulation precision of the reference model reaches a preset standard or not according to the training effect evaluation index until a simulation result meeting a precision requirement is obtained. According to the invention, the reality and accuracy of fire-fighting simulation training are improved.