9 results about "Active fire" patented technology

The invention provides a perfluorohexanone active fire extinguishing system applied to an energy storage power station, and belongs to the technical field of active fire extinguishing systems, the perfluorohexanone active fire extinguishing system comprises a multi-mode composite detection array composed of a thermal imaging sensor, an air pressure sensor, a visible light camera and an ultraviolet light sensor, the multi-mode composite detection array is configured to collect temperature field data, air pressure data, visible light video streams and ultraviolet spectrum data in the energy storage battery cabin by a preset timestamp synchronization mechanism, and output four-mode original data streams to the thermal runaway micro-hotspot recognition engine and the like; early discovery, accurate positioning, fine release, true suppression and self-evolution full-closed-loop active fire extinguishing of the energy storage power station in the high-altitude extreme environment are achieved, and the safety, economical efficiency and long-term maintainability of the energy storage power station are remarkably improved.

The application discloses a kind of wild fire smoke cluster and its boundary vector automatic identification method, system, storage medium and electronic equipment, belong to satellite remote sensing and disaster monitoring technical field.Method includes: obtaining satellite active fire point, fire event and UVAI data;Fire source area is positioned based on fire event geographic location and initial plume pixel is marked;The spatially continuous smoke cluster connected domain is identified by iterative region growing algorithm;According to the specific distribution form of connected domain pixel in satellite pixel matrix, the accurate closed boundary vector is automatically generated using matching geometric algorithm;Finally, using multiple criteria, the spatial isolated independent smoke cluster is screened out.The application avoids the defects that traditional image method is easily disturbed by environment from physical principle, realizes fully automated processing without training data, and can output vector boundary that can be directly used for diffusion and emission evaluation, significantly improves the accuracy, automation degree and application value of wild fire smoke cluster monitoring.

This invention discloses a fire-resistant, flame-retardant, and highly weather-resistant integrated marine furniture system, comprising a three-layer architecture: a basic layer, an intelligent layer, and an application layer. The basic layer consists of prefabricated functional units and quick-connect interfaces for rapid installation. The intelligent layer includes an intelligent fire prevention unit and an adaptive environment unit. The intelligent fire prevention unit automatically triggers targeted aerosol fire suppression based on dual-condition logic using temperature and smoke sensors and safety control nodes deployed in key locations, enabling early autonomous fire suppression. The adaptive environment unit learns user habits through sensors and, upon user confirmation, solidifies "context-operation" rules, achieving personalized automatic environmental adjustment. The application layer provides various interactive terminals. This system represents an upgrade from passive alarm to active fire prevention, and from manual operation to intelligent adaptation, significantly improving the safety and comfort of ship cabins.

The invention relates to an intelligent control system for active monitoring and active fire extinguishing. The MCU of the host is used for setting a condition threshold value and acquiring data, storing and recording the data, transmitting the data through a 4G or 5G network or a Wi-Fi network or an RS485 communication line, a serial server or a router and a server, and monitoring real-time temperature data through a mobile phone APP or a computer APP; an early warning temperature alarm, a cloud server, a mobile phone APP or a computer APP, a TCP / IP protocol, an enterprise central control system or an FAS and a fire alarm system, and a short message or a mailbox or an APP acousto-optic notification designated principal and a fire protection unit. The mobile phone or the computer with network signals can be used for setting the early warning temperature of a monitored area, actively starting the fire extinguishing temperature, actively starting the fire extinguishing mode, monitoring the interval time of data transmission, monitoring the early warning temperature state, notifying the fire extinguishing starting state, and notifying the position of a fault area or an area where fire extinguishing is started.

The invention discloses a wildfire puff and boundary vector automatic identification method and system thereof, a storage medium and electronic equipment, and belongs to the technical field of satellite remote sensing and disaster monitoring. The method comprises the following steps: acquiring satellite active fire points, fire events and UVAI data; positioning a fire source area based on the geographic position of the fire event and marking an initial smoke plume pixel; identifying a smoke puff connected domain with continuous space through an iterative region growing algorithm; automatically generating an accurate closed boundary vector by adopting a matched geometric algorithm according to the specific distribution pattern of the connected domain pixels in the satellite pixel matrix; and finally, screening out the independent puff with isolated space by utilizing multiple criteria. According to the method, the defect that a traditional image method is easily interfered by the environment is avoided from the physical principle, full-automatic processing without training data is achieved, the vector boundary which can be directly used for diffusion and emission evaluation can be output, and the accuracy, the automation degree and the application value of wildfire puff monitoring are remarkably improved.

The invention relates to the technical field of wind power generation equipment, and discloses a fireproof cabin based on offshore wind power generation, which comprises a cabin shell, a fireproof separation mechanism, a ventilation mechanism and an air supply mechanism. The interior of the cabin is divided into a plurality of independent fireproof subareas by arranging the fireproof separation mechanism, so that fire is prevented from spreading in the cabin, the fire is controlled in a local area, and the situation that an initial small fire is developed into a whole-cabin catastrophic fire is avoided; the ventilation mechanism and the air supply mechanism convey air into the cabin together and exhaust the air through the air outlet pipe, and a positive pressure environment higher than the external environment air pressure is formed and maintained in the cabin. The positive pressure design can effectively prevent an external fire source from invading the cabin; as the positive pressure airflow can prevent external smoke and flame from entering, and meanwhile, oxygen flowing inwards is reduced, and internal fire diffusion is restrained. The active fire prevention capacity of the cabin can be improved, and the cabin is suitable for the offshore remote environment and the occasion where external rescue is difficult to arrive quickly.

The invention discloses a fire prevention and control linkage system for an urban rail transit vehicle. The fire prevention and control linkage system comprises a smoke and fire alarm linkage subsystem and a fire suppression subsystem. According to the characteristics of different areas such as a passenger area and an equipment area in a train, fire feature data are collected, fire hidden dangers are comprehensively researched and judged by combining an intelligent fire recognition model of a monitoring video, then linkage, alarm and control instructions are generated, a linkage signal triggers a broadcasting system to carry out subarea broadcasting, an alarm signal is uploaded to a TCMS and a control center, and the TCMS and the control center carry out subarea broadcasting. The control instruction is issued to the fire suppression subsystem; and the fire suppression subsystem receives instructions from the linkage subsystem and the TCMS and performs fire extinguishing or fire suppression operation on the target area. According to the invention, differentiated and intelligent identification of fire characteristics in different areas is realized, and a set of complete and active fire prevention and control system is constructed.

The invention relates to the technical field of fire-fighting monitoring, and discloses an artificial intelligence fire-fighting monitoring early warning and active fire extinguishing technology, which comprises a base, a wall body is fixedly installed on the base point, a ceiling is fixedly installed on the top of the wall body, an air pipe is installed on the top of the ceiling, a water pipe is installed below the air pipe, and a water outlet is installed below the water pipe. One end of the water pipe is connected with a water tank through a water pump. According to the artificial intelligence fire fighting monitoring early warning and active fire extinguishing technology, a spraying head is installed at one end of a water pipe, a plurality of water outlets are formed in the side face and the bottom of the spraying head at equal intervals, and water can be comprehensively sprayed to a fire source for fire extinguishing; water in the water tank can be kept at the safe water level, it is ensured that the spray header can extinguish fire in time, the camera, the smoke sensor and the like can monitor and collect environment data in real time, calculation can be conducted through artificial intelligence through the communication module, the early warning response capacity is improved, and reliability is improved.

This invention relates to the field of fire monitoring technology, and more specifically to a method for dynamic risk assessment of grassland fires. The method includes: acquiring multi-source data such as historical active fire points, satellite remote sensing, digital terrain, and grassland distribution data for the monitoring area; preprocessing active fire points in the grassland distribution data as positive samples with time attributes, generating fire impact areas through DBSCAN clustering, constructing negative samples with time distributions consistent with the positive samples from non-impact areas, merging them to form a total grassland fire sample and dividing it into training and testing sets. Based on the time attributes of the samples, remote sensing factors, tassel transformation components, and terrain factors within the time window before the assessment date are extracted as features. These features are input into an XGBoost model for training, and hyperparameters are optimized using grid search and five-fold cross-validation. Through iterative training and verification using multiple time windows, the time window with optimal accuracy is determined. Five typical dates in 2024 are selected, and the optimal model and window are used to conduct grassland fire risk assessment, outputting a fire occurrence probability grid; based on historical fire point clustering characteristics, a grading interval is determined, classifying the probability into five risk levels: extremely high, high, medium, low, and extremely low. This method can dynamically assess grassland fire risk on different dates in near real-time and visualize risk areas, providing support for disaster prevention and mitigation decision-making.