32242results about "Fire rescue" patented technology

The invention provides an intelligent fire-fighting equipment self-inspection and fault early warning system based on an AI algorithm. The intelligent fire-fighting equipment self-inspection and fault early warning system comprises a sensing layer used for integrating a multi-source heterogeneous sensing unit; the edge layer is used for deploying intelligent preprocessing nodes; the transmission layer is used for constructing a safe and reliable transmission channel; the platform layer is used for establishing an intelligent analysis center; the application layer is used for providing intelligent decision service; and the five layers of architectures work cooperatively. According to the invention, full-dimension monitoring of fire-fighting equipment is realized through a multi-physics field cooperative sensing framework of a sensing layer, and the fault detection capability is remarkably improved. The multi-source heterogeneous sensing unit integrated in the sensing layer can capture various physical quantity information such as acoustics, vibration and thermal fields at the same time, information of different physical fields is complementarily enhanced through a cross-domain feature complementation enhancement mechanism, and more comprehensive equipment state features are obtained. In particular, the sensor self-adaptive excitation technology dynamically adjusts the excitation energy of the sensor according to the environmental interference degree, and ensures that high-quality signals can be obtained under different working conditions.

The invention discloses a remote monitoring and intelligent management and control system for fire-fighting equipment, and belongs to the technical field of fire-fighting early warning, and the system specifically comprises the steps: deploying a multi-parameter sensor array, and enabling each sensor node to form a redundant monitoring network through a honeycomb topological structure; carrying out real-time fusion analysis on the sensor network data through an edge computing gateway, and triggering an abnormal region positioning module when detecting that any monitoring parameter exceeds a preset dynamic threshold value; the abnormal region positioning module constructs a three-dimensional thermodynamic diagram model based on the parameter gradient change of adjacent sensor nodes, and dynamically calculates the diffusion direction and the potential risk level of an abnormal region; the mobile inspection robot cluster receives the coordinates and risk parameters of the abnormal area, a multi-stage response path is automatically generated based on a building digital twin model updated in real time, a primary path quickly approaches along a preset main road, and a secondary path is dynamically adjusted according to field obstacle distribution; and the tail end path adopts a contact type detection module to recheck the abnormal area.

The invention discloses an energy storage power station fire safety monitoring system based on a big data Internet of Things, and relates to the technical field of fire safety monitoring. A multi-dimensional sensor network is adopted to monitor parameters in real time, a multi-dimensional parameter model under normal working conditions is established based on a multivariable Gaussian distribution model, and the real-time monitoring of the parameters is realized. In the early stage of thermal runaway, abnormity is recognized through the Mahalanobis distance, an early warning signal can be triggered immediately when the abnormity occurs, the defects that in a traditional method, the monitoring means is single, and response lags behind are overcome, fire early warning is more accurate and timely, and the concentration of harmful gas is monitored in real time in combination with a gas detection module; sensor data and gas concentration data are fused through Bayesian inference, the fire risk is evaluated more comprehensively, the comprehensiveness of fire risk evaluation is remarkably improved, a fire area is positioned through a fire source positioning algorithm, and the fire extinguishing range is adjusted in real time according to the fire risk level and the dynamic change of fire source diffusion.

The invention discloses a forest fire detection and disappearance method and system, and relates to the technical field of forest fire prevention and data processing, and the method comprises the steps: carrying out the fire inspection of a planned forest region through a plurality of inspection unmanned planes, and transmitting an image and airborne sensor data back to a command center in real time; identifying a fire behavior by using an artificial intelligence method, and performing fire behavior judgment and fire hazard grade division; the command center screens fire points according to the thermal images and updates the positions of the fire points in real time; the fire scene spreading trend is judged according to the returned data, and a basis is provided for the dispatching task of throwing the fire extinguishing bombs by the fire extinguishing unmanned aerial vehicle; using an MAPPO multi-agent reinforcement learning algorithm to train an optimal dynamic fire point collaborative disappearance regulation strategy; and after the open fire is extinguished, the inspection unmanned aerial vehicle continues to inspect to identify a re-ignition point or a smoke point, and secondary large-area fire is prevented. According to the method, efficient collaborative fire extinguishing, dynamic environment adaptation and resource optimization configuration can be achieved, and robustness is kept when part of intelligent agents fail.

The invention relates to the technical field of monitoring and early warning, in particular to a fire hydrant monitoring intelligent early warning system based on an anomaly analysis technology, which comprises a flow velocity anomaly identification module, a node collaborative pressure difference detection module, a pressure difference trend independence judgment module, a node degradation feature extraction module and a risk level generation module. According to the method, through correlation judgment of flow velocity deviation and control signals, no-signal recognition of abnormal water taking behaviors and a cooperative analysis mechanism of pressure change of adjacent nodes, a hydraulic disturbance area under non-manual control can be accurately recognized, and through analysis of spatial independence of a pressure response trend, a water flow disturbance area under non-manual control can be accurately recognized. The function degradation level of the device is extracted according to historical data of on-off time delay and response performance, the quantitative evaluation capability of the node function state is enhanced, the capability of finely dividing the risk level is achieved when risk early warning is given out, the risk identification accuracy is improved, and the active discovery capability of early fault hidden dangers is enhanced.

The invention relates to the technical field of fire control management, in particular to a fire rescue intelligent management method and system based on a multi-mode AI large model. The method comprises the following steps: acquiring real-time environment monitoring data of a fire scene; carrying out environmental parameter analysis on the fire scene real-time environmental monitoring data, and carrying out gas change trend prediction to generate a scene gas parameter change trend; acquiring a fire scene thermal imaging image; performing temperature distribution visual identification and continuous frame temperature change rate calculation according to the fire scene thermal imaging image so as to generate a fire source area temperature change rate; performing multi-time ignition trend prediction according to the temperature change rate of the fire source area and the on-site gas parameter change trend so as to generate a multi-time ignition trend prediction map; and identifying a to-be-rescued area point based on the fire scene thermal imaging image. According to the invention, real-time and accurate distribution of on-site fire rescue resources is realized, and the rescue management efficiency and safety are improved.

The invention discloses a battery cluster level fire-fighting linkage control method and system based on a BMS, and the method comprises the steps: carrying out the thermal runaway prediction through a multi-source feature fusion network according to the real-time voltage, temperature and gas concentration data of a battery cluster, and outputting a thermal runaway prediction level; on the basis of the thermal runaway prediction level, a dynamic priority mapping algorithm is utilized, and a control instruction set containing execution priority and spatial positioning is output according to the battery cluster topological structure; according to the control instruction set, a dual-channel redundant signal verification mechanism is adopted to execute a fire-fighting action, and a real-time action feedback signal is output; and on the basis of the real-time action feedback signal and the residual state data of the battery cluster, updating the parameter weight of the multi-source feature fusion network through a reinforcement learning model so as to be used for fire-fighting linkage control in the next period, and forming a closed-loop control link. According to the embodiment of the invention, battery cluster-level fire-fighting linkage control can be realized, so that the safety protection capability of a battery system is improved.

The invention discloses a safety control method based on a knowledge graph, and belongs to the field of safety control, and the method comprises the following steps: crawling various types of data according to keywords through a crawler program to construct a fireproof database; carrying out semantic analysis on data in the fireproof database by using a natural language processing technology, and carrying out data processing on the fireproof database after semantic analysis through word vector modeling and entity relationship extraction; constructing an internal large-scale language model by using the processed fireproof database, and performing hierarchical clustering on the internal large-scale language model by adopting a Leiden technology; establishing a multi-dimensional mapping model based on historic building spatial features, cultural relic features and disaster-inducing factors in a hierarchical clustering result, and constructing a multi-modal dynamic association fireproof knowledge graph by using a knowledge graph technology based on the multi-dimensional mapping model; and dynamically selecting a search mode based on a user query keyword, and generating a security control result according to the query keyword based on the search mode.

The invention discloses a battery thermal runaway detection system based on an early warning function, and relates to the technical field of battery thermal runaway, and the system comprises a supervision center which is used for carrying out the real-time supervision of the data information of a plurality of batteries, carrying out the early warning of the time data of the battery thermal runaway, and facilitating the timely issuing of warning information and notification announcements, and a monitoring device which is used for monitoring the data information of a plurality of batteries. The monitoring device is used for collecting thermal runaway parameters of each detection node of a plurality of batteries, the thermal runaway parameters comprise battery voltage, temperature, current and pressure, and the protection device is used for carrying out delayed protection operation on the monitoring device. The battery thermal runaway detection system based on the early warning function establishes a thermal runaway early warning model by fusing multi-parameter data of heat, force, electricity and the like and historical data of a thermal runaway phenomenon and by utilizing various learning algorithms, monitors battery parameters and sets simple judgment standards and threshold values such as a non-working state current threshold value and the like, so that the battery thermal runaway early warning model is established. Early detection of battery thermal runaway is realized, and monitoring and early warning effects are achieved.

The invention discloses an electric vehicle parking lot fire prevention and control system based on multi-source information fusion. A sensing layer captures the environment state of an electric vehicle parking lot and the operation parameters of a vehicle battery in real time through a multi-mode sensor network; the network layer adopts an intelligent fusion network architecture to realize communication between the sensing layer and the data processing layer; the data processing layer is used for performing fusion analysis on the environment state and the operation parameters, judging a fire risk level and generating a dynamic control instruction; the data processing layer is composed of a multi-dimensional analysis engine, and a hierarchical progressive intelligent analysis architecture is adopted to realize multi-level research and judgment of fire risks; and the application layer receives the dynamic control instruction generated by the data processing layer, and realizes full-process closed-loop management of fire prevention and control through a multi-mode terminal device. The method not only improves the fire prevention and control precision of the electric vehicle parking lot, but also has good interpretability, and can be directly applied to a fire prevention and control system of the electric vehicle parking lot.

The invention discloses a BMS-based multifunctional integrated monitoring and fire control method and system, and the method comprises the steps: synchronously collecting the temperature, combustible gas concentration and dynamic environment monitoring data in a container through a BMU battery box management unit of a BMS, and generating a space-time correlated container environment state matrix; based on the environment state matrix, extracting temperature anomaly features, gas concentration gradient features and dynamic environment fluctuation features through a multi-modal feature fusion model, and constructing a multi-dimensional risk feature vector; inputting the multi-dimensional risk feature vector into a fire-fighting early warning optimization algorithm to generate a graded fire-fighting early warning signal; and according to the graded fire-fighting early warning signal, an active fire-fighting intervention strategy is triggered through a BMU unit of the BMS, a fire extinguishing device, a ventilation system and a power cut-off module are dynamically controlled, and a fire-fighting response path is synchronously optimized to be matched with the current risk grade. According to the embodiment of the invention, graded fire-fighting early warning can be realized, and the accuracy and timeliness of fire early warning are improved.

The invention discloses an AFIS intelligent fire-fighting monitoring system based on the Internet of Things technology, and relates to the technical field of fire-fighting safety, and the AFIS intelligent fire-fighting monitoring system comprises a front-end module, a central monitoring module, a data analysis module, an early warning module and a fault diagnosis module. The front-end module is used for monitoring fire-related environment data and fire-fighting equipment states through a plurality of sensor nodes; installing and deploying various types of sensor nodes in the key area; the collected original data is subjected to primary processing, including data cleaning, denoising, standardization and the like, so that the accuracy and reliability of the data are ensured; according to the invention, through integration of various sensor nodes, real-time monitoring of environment parameters of a key area and the state of fire-fighting equipment is realized, so that the fire prevention and response efficiency is obviously improved, the system can wirelessly transmit data by using the Internet of Things technology, the complexity of installation and maintenance is reduced, and the monitoring range is expanded.

The invention relates to the technical field of artificial intelligence rescue, and discloses an unmanned aerial vehicle and robot dog rescue emergency system and method, and the system comprises an unmanned aerial vehicle cluster module which is used for air data collection, communication guarantee and emergency material distribution; the robot dog cluster module is used for ground environment detection, sample collection and special task execution; the communication cooperation module is used for ensuring information intercommunication and task cooperation between air-ground equipment; the central control module provides task instructions for the unmanned aerial vehicle cluster and the robot dog cluster; the human-computer interaction interface module is used for realizing effective communication between rescue workers and the system; the modules work cooperatively, multi-source data acquisition, three-dimensional scene reconstruction, semantic segmentation, risk assessment, fire spreading prediction and decision support information generation of a disaster site are realized, and a reliable basis is provided for rescue command decision.

The invention relates to the technical field of communication machine room safety protection, and discloses a communication machine room intelligent fire monitoring and fire extinguishing system based on edge computing, which comprises a fire parameter acquisition module, a temperature characteristic analysis module, a smoke dynamic detection module, a multi-source fusion judgment module, a regulation and control parameter generation module and the like. The fire parameter acquisition module acquires parameters such as temperature gradient, smoke concentration and equipment current, judges fire risk and triggers cooperative monitoring; the temperature characteristic analysis module extracts temperature distribution characteristics and quantitatively evaluates hot spot abnormity; the smoke dynamic detection module analyzes the smoke diffusion trend; the multi-source fusion judgment module is combined with multiple parameters to generate a fire extinguishing or optimizing signal; and the regulation and control parameter generation module is matched with the strategy to generate injection and ventilation parameters. The system also corrects a risk index through an equipment coupling analysis module, and forms closed-loop control by using a dynamic feedback execution module. According to the system, multi-source data fusion monitoring and intelligent fire extinguishing are realized, and the fire prevention and control accuracy of the communication machine room is improved.

The invention belongs to the technical field of fire safety, and discloses a fire-fighting equipment detection early warning method and system based on a visual camera, and the method comprises the following steps: obtaining multi-focal-length image frames of a fixed spray head and a fire extinguisher edge region, judging the continuous change of gray scale in the continuous image frames, and carrying out the detection early warning of the fire-fighting equipment based on the visual camera. Comparing the gray level distribution difference under the long focus and the short focus, identifying the dynamic trajectory of the contour line angular point of the fire-fighting equipment association structure, analyzing the delay of the function action response, marking as an abnormal region, and generating a fire-fighting equipment collaborative early warning information set; according to the invention, by extracting and analyzing the multi-focal-length image frames of the edge areas of important facilities such as a fixed spray head and a fire extinguisher, fine changes of the fire-fighting facilities under differentiated focal lengths can be captured, working states and potential faults of the fire-fighting facilities can be judged, functional abnormalities caused by equipment aging or damage can be recognized in advance, early warning can be carried out in real time, and the safety of the fire-fighting facilities can be improved. And a higher guarantee level is brought to fire safety.

An electrified fire fighting vehicle includes a chassis, a front axle coupled to the chassis, a rear axle coupled to the chassis, a water pump, an energy storage system, an engine, an electric motor coupled to the engine and the energy storage system, and a power divider positioned between the electric motor, the water pump, and the rear axle. The power divider facilitates selectively driving the water pump and the rear axle with the engine and the electric motor.

A control method for fire-fighting false alarm of an energy storage system comprises the following steps of: calculating a fluctuation period, a derivative and a probability density function by using fast Fourier transform and the like by acquiring data streams such as current, voltage, power and heat energy of the energy storage system, determining a system state and predicting a related trend. And predicting power by using an autoregressive moving average algorithm and a support vector machine, and setting a threshold value according to a probability density function to judge abnormity. For heat energy data, through derivative calculation and signal analysis, states are identified and early warning is carried out in combination with models such as a deep convolutional adversarial neural network and a support vector machine. The normal range of monitoring data is determined by means of the long-short-term memory neural network, the change trend and physical quantity relation of abnormal data are analyzed and predicted through a cubic exponential smoothing method and Gaussian process regression, potential risks are judged through weighted fusion and a self-adaptive Simpson algorithm, fire-fighting false alarms are effectively reduced, fire risks are accurately recognized, and the safety of an energy storage system is guaranteed.

The invention provides a concrete prefabricated energy storage cabin which comprises a cabin body and a cabin door which are made of a concrete composite material, so that the energy storage cabin has high compressive strength and high fire resistance rating, and a plurality of energy storage cabins can also be transversely arranged without spacing or stacked in the height direction, so that the occupied area is effectively reduced; an energy storage box provided with a basin-shaped box body and a cover plate is arranged in the cabin body, the cover plate covers the basin-shaped box body to form a closed energy storage cavity for accommodating a battery module, and the basin-shaped box body and the cover plate are also made of a concrete composite material, so that high temperature generated by thermal runaway of a battery in a single energy storage box can be effectively limited in the energy storage box; as the oxygen content in the energy storage box is relatively low, the flame can be automatically extinguished after the battery with relatively light thermal runaway degree is on fire; and for a battery fire with a heavy thermal runaway degree, a long time can be provided for fire fighting and extinguishment, and flames can be extinguished in time in the energy storage box.

The invention discloses an energy storage cabinet intelligent fire extinguishing system and method suitable for a distributed architecture. The energy storage cabinet intelligent fire extinguishing system suitable for the distributed architecture comprises an environment sensing flame smoke detection module, an environment temperature and key position monitoring module, a control module and a fire extinguishing execution module. When detection or / and monitoring data of the environment sensing flame smoke detection module or / and the environment temperature and key position monitoring module reaches a preset threshold value or is abnormal, the control module sends a control instruction to the fire extinguishing execution module; and the fire extinguishing execution module executes fire extinguishing action. According to the energy storage cabinet intelligent fire extinguishing system suitable for the distributed architecture, the safety and reliability of the energy storage cabinet can be improved, and resource waste and potential economic loss caused by false alarm are reduced.

The invention relates to the technical field of data processing and identification, in particular to an intelligent fire fighting equipment fault identification method and system, and the method comprises the steps: carrying out the execution according to a set first period: generating simulation data through a constructed digital twinborn model; acquiring operation data of real equipment through a sensor network; comparing a deviation value between the simulation data and the real equipment data; when the deviation value exceeds a preset threshold value, triggering a causal inference engine; calibrating digital twin model parameters and adjusting equipment operation parameters; the prior art mainly depends on fixed threshold alarm, early progressive faults of equipment are difficult to capture, and response lags behind; according to the scheme, digital twin simulation and active flaw detection are combined, and deep insight of the health state of the equipment is formed by periodically injecting micro-amplitude disturbance signals into the equipment and analyzing the dynamic response characteristics of the equipment; according to the invention, tiny degradation of equipment performance can be captured in a fault incubation period, so that maintenance intervention is triggered in advance, and the advancement and accuracy of fault early warning are remarkably improved.

The invention relates to the technical field of unmanned aerial vehicle assistance, and discloses an unmanned aerial vehicle assisted fire scene real-time monitoring and commanding method, which comprises the following steps: acquiring fire disaster situation data of a fire scene in real time through equipment such as a high-definition camera and a red thermal imager of an unmanned aerial vehicle, and outputting the fire disaster situation data to a commanding center; analyzing the fire behavior development direction, the fire source position and the smoke concentration of the fire disaster situation data; evaluating a fire scene scale and a dangerous area according to an analysis result, forming a rescue scheme according to an evaluation result, and commanding firefighters and a fire extinguishing unmanned aerial vehicle based on the rescue scheme; dynamically adjusting a rescue scheme according to the fire disaster situation data of the fire scene collected by the unmanned aerial vehicle in real time; when the fire is extinguished, the blind fire area is continuously monitored, and if abnormity occurs, an alarm is given out immediately; the unmanned aerial vehicle serves as an air base station for communication. According to the invention, instant and comprehensive fire scene information is provided for a command center, and rapid decision making is facilitated.

A remotely-triggered wildfire defense spraying system installed on property with a building, and adapted for spraying the building and property with an environmentally-clean water-based liquid fire inhibitor for defending against wildfire by inhibiting fire ignition and flame spread caused by hot flying wildfire embers created during a wildfire storm. The wildfire defense spraying system includes: a storage tank containing environmentally-clean liquid fire inhibitor comprising an alkali metal salt of a nonpolymeric carboxylic acid, and triethyl citrate (TEC) dissolved in water according to a prespecified formulation, wherein the environmentally-clean water-based liquid fire inhibitor remains stable without the formation of solids at expected operating temperatures, and for immediate spraying on property. A fluid pumping loop having a hydraulic pump system is connected to spray heads and the storage tank, and is operably controlled by a remote control switch. When the hydraulic pump system is remotely activated by a remotely generated trigger signal (e.g. from a mobile smartphone or remote wildfire detection system), the hydraulic pump system pumps environmentally-clean water-based liquid fire inhibitor from the storage tank and through the spray heads to produce a spray pattern of environmentally-clean water-based liquid fire inhibitor covering the combustible surfaces on the property. As water molecules in the sprayed environmentally-clean water-based liquid fire inhibitor evaporate to the environment, fire-inhibiting alkali metal salt crystalline coatings form on the sprayed combustible surfaces, inhibiting fire ignition and flame spread in the presence of wildfire embers.

The invention relates to the technical field of fire-fighting monitoring, in particular to a fire-fighting water system fault detection and early warning method and system based on the fire-fighting Internet of Things, and the method comprises the steps: 1, periodically collecting pressure data through pressure sensors disposed at a fire-fighting water pump outlet, a pipe network main pipe branch point and the most unfavorable tail end; 2, according to the current valve opening degree, the pump state and historical normal working condition data, theoretical pressure expected values and dynamic allowable deviation zones of all nodes are generated; 3, when actually measured pressure deviates from a theoretical pressure expected value and exceeds a dynamic allowable deviation band, marking abnormal nodes, reversely constructing a fault propagation tree along the topological model, and allocating weight factors for associated nodes according to fault types; and 4, triggering graded early warning based on the number of the abnormal nodes, the fault propagation path and the weight factor accumulated value. And the system can automatically take measures when a fault occurs through an equipment linkage function, so that the efficient operation of the fire fighting water system is guaranteed, and the efficiency and safety of fire emergency response are improved.

The invention discloses a scheduling information management method and system based on fire fighting of a fire fighting truck, and relates to the technical field of intelligent fire fighting scheduling, and the method comprises the steps: receiving fire alarm information, and collecting real-time fire scene data based on a preliminary fire behavior evaluation result; combining the collected real-time fire scene data with historical fire data, and analyzing a fire spreading trend through an AI fire prediction model; according to the fire behavior spreading trend and the equipment state of the fire fighting truck, dynamically allocating fire fighting truck resources, and planning an optimal driving route; the driving state of the fire fighting truck is monitored in real time, dynamic adjustment is performed based on road conditions and equipment information, and task allocation of the fire fighting truck is updated according to the real-time fire scene situation; in the fire extinguishing process, resources are dispatched in real time for supply according to the material consumption condition of the fire fighting truck. By monitoring the material consumption condition of the fire fighting truck in real time, the supply resources are intelligently dispatched, and the continuity and high efficiency of the fire extinguishing action are ensured.

An intelligent safety supervision system applied to a ship is provided. An image acquisition module is configured to acquires high-definition images in real time. An automatic recognition module is configured to obtains ship dynamic and static data. A ship server to-performs feature recognition on the ship dynamic and static data to obtain a data processing result, to-transmits the ship dynamic and static data and the data processing result, and receives alarm indication information. An alarm module outputs an alarm. A ship client displays the data processing result, and determines whether to transmit the alarm indication information according to the data processing result. A communication module receives and transmits the ship dynamic and static data and the data processing result. A shore-side supervision system includes a ship safety supervision big data analysis platform for performing secondary feature recognition on the ship dynamic and static data, so as to obtain a secondary data processing result.

A wildfire defense spraying system installed on a property with combustible surfaces and adapted for spraying the property and combustible surfaces with an environmentally-clean water-based liquid fire inhibitor for defending against wildfire by inhibiting fire ignition and flame spread caused by hot flying wildfire embers created during a wildfire storm. The wildfire defense system includes: a storage tank containing an environmentally-clean liquid fire inhibitor comprising a majority amount of tripotassium citrate (TPC) and minor amount of triethyl citrate (TEC) dissolved in a major amount of water according to a prespecified formulation, wherein the environmentally-clean water-based liquid fire inhibitor remains stable without the formation of solids at expected operating temperatures, and ready for immediate spraying on combustible surfaces. A hydraulic pump system is connected to remote power control switch employed to supply electrical power to the hydraulic pump, and remotely activated. A plurality of spray heads is mounted about the property, in fluid communication with the storage tank, and supplied with environmentally-clean water-based liquid fire inhibitor by the hydraulic pump system. During operation, the spray heads spray liquid fire inhibitor from the storage tank forming a spray pattern that covers the property and combustible surfaces to be defended against wildfire embers. When the hydraulic pump system completes pumping and spraying the environmentally-clean water-based liquid fire inhibitor in the storage tank, the hydraulic pump system automatically shuts off, and as water molecules in the sprayed environmentally-clean water-based liquid fire inhibitor evaporate to the environment, thin potassium salt crystalline coatings form on the sprayed combustible property surfaces, inhibiting fire ignition and flame spread in the presence of wildfire.

The invention relates to the technical field of fire-fighting management, and discloses an intelligent fire-fighting service management system, which comprises a data acquisition unit used for acquiring three basic parameters, namely environment data, working condition data and battery data, of a fire-fighting object in an office building, and the system acquires the environment, working condition and battery data of a fire extinguisher through the data acquisition unit; the fusion unit generates a dynamic composite abnormal threshold value, and the adjustment unit executes a three-stage sampling frequency adjustment mechanism according to the threshold value, the battery health degree score and the data deviation degree, which means that the sampling frequency can be reduced to reduce the battery energy consumption when the state of the fire extinguisher is normal and the risk is relatively low, and when the risk is increased or the battery health degree is reduced, the battery energy consumption is reduced. The whole system realizes accurate management and regulation of the battery according to the actual working condition of the fire extinguisher, energy waste is avoided, the service life of the battery is prolonged, the cost of frequently replacing the battery is reduced, and the sustainability of intelligent fire control management is enhanced.

A forest fire retardant composition contains a retardant compound that includes a phosphate salt. The phosphate salt may include diammonium phosphate, diammonium orthophosphate, monoammonium phosphate, monoammonium orthophosphate, monosodium phosphate, disodium phosphate, disodium phosphate hydrate, sodium ammonium phosphate, sodium ammonium phosphate hydrate, sodium tripolyphosphate, trisodium phosphate, or dipotassium phosphate, and combinations thereof. The forest fire retardant composition may include an ammonium source. The composition may be in the form of a dry concentrate, a liquid concentrate, or a final diluted product. The final diluted product is effective in suppressing, retarding, and controlling forest fires while exhibiting corrosion resistance and low toxicity.

The invention relates to the technical field of fire extinguishing control, in particular to an unmanned aerial vehicle fire extinguishing control method and system. The method comprises the following steps: carrying out hot-flow wind field real-time data acquisition on a high-rise building fire scene through a sensor carried on an unmanned aerial vehicle, carrying out approaching hot-flow wind field intensity difference analysis, and then carrying out unmanned aerial vehicle flight attitude instability numerical value quantification to obtain flight attitude instability numerical value quantification data; time-varying attitude spraying strategy adjustment is carried out according to the flight attitude instability numerical value quantization data, and a time-varying attitude spraying adjustment strategy is obtained; building a fire extinguishing spraying control model for the time-varying attitude spraying adjustment strategy based on a strategy gradient algorithm to obtain a fire extinguishing spraying control model; and sending the fire extinguishing spraying control model to the terminal. The fire extinguishing control technology is optimized, so that the fire extinguishing control technology is more perfect.

A dual-molded silicone-polyamide composite article including a first molded piece that comprises a blend of polyamide and an ethylene-vinyl alcohol copolymer and a second molded piece that comprises a thermoset, hydrosilylation-cure silicone polymer. A portion of a surface of the second molded piece is autogenously bonded to a portion of a surface of the first molded piece.