20 results about "Industrial fire" patented technology

The invention provides an industrial fire-fighting emergency method based on visual edge calculation. The method comprises the following steps: synchronously acquiring visual data, thermal data and gas data at the edge end of a factory; processing and feature extraction are respectively carried out on the collected data to obtain visual features, thermal features and gas features, after the visual features, the thermal features and the gas features are fused to obtain multi-modal fusion features, whether a fire happens or not is predicted, and if yes, a fire prediction picture is generated; presetting a time sequence analysis model, generating a fire emergency task flow according to a result output by the time sequence analysis model, dividing the priority of the fire emergency task flow, and submitting the fire emergency task flow to a workflow engine to distribute the fire emergency task flow to a corresponding execution unit; and on the basis of the steps S11 to S14, collecting multi-modal data of different factories, and pre-training corresponding fire emergency models. According to the invention, by synchronously collecting and fusing the multi-modal data of the treatment plant area, the corresponding industrial fire-fighting emergency scheme of the plant area is generated, and the fire-fighting emergency response time is remarkably shortened.

The utility model relates to the technical field of fire fighting equipment, and discloses a heat preservation type outdoor industrial fire hydrant which comprises a fire hydrant body, a fixing plate is fixedly connected to the side wall of the fire hydrant body, a heat preservation assembly is arranged on the side wall of the fixing plate, a protection assembly is arranged on the side wall of the fire hydrant body, and a positioning assembly is arranged on the side wall of the fire hydrant body. The heat preservation assembly comprises a connecting rod, the side wall of the connecting rod is fixedly connected to the side wall of the fixing plate, a first heat preservation plate and a second heat preservation plate are arranged on the side wall of the fire hydrant body, and the bottom of the first heat preservation plate and the bottom of the second heat preservation plate are fixedly connected with connecting blocks. According to the fire hydrant, the fire hydrant body is wrapped by the first heat preservation plate and the second heat preservation plate, heat preservation is enhanced through the internal heat preservation layer, heat loss is reduced, the problem that use of the fire hydrant is affected by icing of water in the cold environment is solved, and during use, the box cover is pulled to be separated, the second heat preservation plate is pushed to enable the clamping block to enter the sleeve, fixation of the first heat preservation plate is relieved, and the first heat preservation plate topples over to be exposed out of the fire hydrant body.

A method for preventing damage caused by a fire includes extinguishing the fire by applying a fireproof composition to the fire. The fireproof composition is constituted as an aqueous composition comprising at least one sugar and magnesium chloride (MgCl2). The fire can be a forest, domestic, or industrial fire. The composition can also be applied to protect a product against fire.

The invention relates to the technical field of fire safety monitoring, and discloses a fire-fighting equipment fault prediction method based on deep learning. According to the method, multi-source operation data of a fire fighting system and an alarm / linkage system are collected, an equipment topological graph is constructed, and a two-channel neural network model fusing time sequence convolution and graph convolution is established. Adaptivity and information propagation efficiency of a topological structure are enhanced through spectrum gap optimization and a greedy topology reconnection mechanism, and flexible alignment and stable fusion of time sequence features and structural features are realized by introducing a multi-modal mixed comparison consistency fusion mechanism. The method can identify the potential fault of the fire-fighting equipment in advance under a complex working condition, realizes accurate prediction and graded alarm, improves the reliability, robustness and intelligent operation and maintenance capability of the system, and is suitable for the field of operation safety monitoring of building fire-fighting systems and industrial fire-fighting equipment.

The utility model relates to the technical field of water mist sprayers, in particular to an industrial fire-fighting water mist sprayer which comprises a threaded sleeve, a sprayer body is arranged on the threaded sleeve in a communicated mode, a plurality of mounting holes are formed in the sprayer body, nozzles are arranged in the mounting holes, the nozzles are fixed through a fixing mechanism, and the fixing mechanism is arranged on the threaded sleeve. Elastic sleeves are fixedly connected into the multiple nozzles, cavities are formed in the multiple elastic sleeves, and the cavities are adjusted through an adjusting mechanism. According to the utility model, the inner diameter of the spray hole can be adjusted, and blocked objects can be discharged, so that the spray head can be conveniently maintained.

The embodiment of the utility model provides an exhaust assembly and a generator noise reduction structure, and relates to the technical field of generator noise reduction. The exhaust assembly and the generator noise reduction structure comprise square steel pipes and iron sheets, a plurality of square steel pipes are assembled to form a box-shaped frame, the iron sheets are installed on the outer side of the box-shaped frame, the box-shaped frame and the iron sheets are assembled to form a machine room for wrapping a generator, an exhaust pipe of the generator is connected with a silencer, and one end of the silencer is connected with a pipeline. The square steel pipes and the iron sheets are welded, the structure of the machine room is enlarged and thickened, the durability during carrying is enhanced, the overall strength of the machine room is ensured, and in consideration of convenience in operation and heat dissipation, the front door plate and the rear door plate are arranged on the two sides of the machine room, so that a unit and related equipment can be conveniently operated by the door; thickened noise-reduction fireproof cotton special for industrial fire prevention is designed in the machine room, mechanical noise is restrained to a great extent, a secondary anechoic chamber is transformed for a mechanical noise channel, and it is ensured that the mechanical noise is eliminated to the maximum extent.

The utility model relates to the technical field of air pipes, in particular to an industrial fire-resistant air pipe with a reinforced structure, which comprises a shell, the shell comprises a pipeline, and the surface of the pipeline is fixedly connected with a flange; and a reinforcing mechanism is arranged on the surface of the pipeline. The first reinforcing sleeve and the second reinforcing sleeve are arranged on the surface of the pipeline in a sleeving mode, the connecting rod is inserted into the inner side of the first inserting groove, the connecting rod and the first inserting groove can be locked through the cooperation of the inserting rod and the second inserting groove, and then the first reinforcing sleeve and the second reinforcing sleeve are fixed to the pipeline; through fixing of the first reinforcing sleeve and the second reinforcing sleeve, connection between the flanges can be reinforced, so that connection between the flanges is not prone to loosening and can be tighter and firmer, the stability of connection between pipelines can be improved, the quality of pipeline connection can be improved, and industrial gas can be better conveyed through the pipelines.

The invention discloses an industrial fire early prevention and control early warning system based on multi-sensor fusion, which belongs to the technical field of industrial safety monitoring and comprises a data acquisition module, a false alarm judgment module, a risk partition module, a fire identification module and a prevention and control optimization module. The data acquisition module acquires fire data through a layered distributed multi-sensor network; the false alarm discrimination module screens effective fire data based on a dynamic false alarm discrimination rule; the risk partitioning module is used for generating a risk thermodynamic diagram and completing sub-region division and risk label distribution; the fire identification module predicts a fire occurrence probability and identifies a fire development stage; the prevention and control optimization module matches a prevention and control strategy based on a fire development stage and a risk label, plans an optimal path for the AGV in combination with a dynamic cost map to execute a prevention and control task, and feeds back an execution result to the data acquisition module to realize dynamic correction; according to the invention, the false alarm rate is reduced, and the reliability and high efficiency of early prevention and control and early warning of industrial fire are improved.

The application relates to the technical field of fire safety monitoring, and discloses a fire-fighting equipment fault prediction method based on deep learning. The method collects multi-source operation data of a fire-fighting system and an alarm / interlocking system, constructs an equipment topology graph, and establishes a dual-channel neural network model integrating time series convolution and graph convolution. The adaptability and information propagation efficiency of the topology structure are enhanced through spectral gap optimization and a greedy topology reconnection mechanism, and a multi-modal mixed contrast consistency fusion mechanism is introduced to realize flexible alignment and stable fusion of time series features and structure features. The method can identify potential faults of fire-fighting equipment in advance under complex working conditions, realize accurate prediction and graded alarm, improve the reliability, robustness and intelligent operation and maintenance capability of the system, and is suitable for operation safety monitoring of building fire-fighting systems and industrial fire-fighting equipment.

The application discloses a structured lightweight fire smoke detection method for a petrochemical plant area, and comprises the following steps: acquiring image data; inputting the image data into an IFS-DETR model to obtain a detection result, wherein the IFS-DETR model is obtained by training a training set, and the training set comprises preprocessed industrial fire smoke images and corresponding boundary boxes and class labels; and sending alarm information based on the detection result to realize the structured lightweight fire smoke detection for the petrochemical plant area. The application reduces the complexity of the network, improves the detection effect of the fire smoke, and increases the real-time detection performance of the network. By introducing a feature fusion network based on an alignment mechanism, the detection performance of the network on small targets and prominent targets is effectively improved, and the network precision is improved.

The invention discloses an intelligent fire fighting system based on a neural network. The AGV fire fighting system comprises an AGV fire fighting truck, the AGV fire fighting truck comprises an AGV platform and a fire extinguishing device, the fire extinguishing device is fixedly connected to the top of the AGV platform, and the fire extinguishing device comprises a supporting column, a guide pipe and a rotating nozzle; and the fire source sensing system is used for detecting whether a fire source exists in the warehouse area and positioning the fire source. The data processing module is used for processing fire-fighting data, and the fire-fighting data comprises data of a smoke sensor, an infrared sensor and a visual sensor; the AGV execution system is used for sending a control command to the AGV fire fighting truck according to a preset threshold value; and the system module is used for sending the fire-fighting data to the AGV execution system and instructing the AGV execution system to execute a fire extinguishing program. According to the invention, the problems of incapability of accurately extinguishing fire and high risk of manual fire extinguishing in industrial fire fighting in related technologies are solved.

The invention discloses a thermal radiation simulation analysis method and system for an indoor fire of a chemical plant building, and belongs to the technical field of industrial fire safety, and the method comprises the following steps: building a model; highly layering; radiation calculation; danger grading; and performing visual display. According to the invention, highly layered discretization is carried out on an indoor space, a layered radiation calculation model is established, and a Unity 3D three-dimensional visualization platform is combined, so that the thermal radiation intensity distribution is superposed in a real building model in a cloud picture form, thereby dynamically displaying the change of a thermal radiation hazard area in a fire spreading process, and improving the fire hazard hazard effect. Scientific support is provided for evacuation path optimization, fireman safe operation area delimiting and emergency rescue decision making.

The invention relates to the technical field of industrial fire fighting and automation, in particular to a data center early fire detection positioning and fire extinguishing treatment method and system. The invention provides a data center early fire detection positioning and fire extinguishing treatment method. The method comprises the following steps: S1, early warning of an extremely early region; s2, robot autonomous linkage; s3, accurately confirming a fire source point; s4, penetrating type precise fire extinguishing is carried out; and S5, after-disaster environment recovery and system reset. The system aims at implementing efficient and accurate early-stage fire hazard advanced early warning, accurate positioning and non-intrusive fire extinguishing treatment on key facilities such as a data center and a server room.

The utility model discloses a wear-resistant and weather-resistant fire hose, and relates to the technical field of fire hoses. The bulge assemblies are uniformly and fixedly arranged on the outer side of the water hose main body; the protruding assembly comprises a wear-resisting soft block fixedly arranged on the outer side of the water hose body. The protruding assembly further comprises a connecting cavity formed outside the wear-resisting soft block and a wear-resisting hard block which is fixedly attached to the wear-resisting soft block by being arranged in the connecting cavity, and the wear-resisting hard block does not make contact with the outer side of the water hose body. The wear-resistant soft block has the advantages that the wear-resistant hard block is attached and externally connected to the wear-resistant soft block through the connecting cavity arranged on the wear-resistant soft block, so that the wear-resistant hard block can provide a better wear-resistant attaching surface on the premise of ensuring the flexibility and the impact resistance of the wear-resistant soft block; therefore, the fire hose can be suitable for field fire extinguishing or industrial fire rescue and urban fire rescue, and the use effect of the fire hose in various scenes is good. And the wear-resistant soft block and the covering layer are integrally manufactured, so that the strength during use can be improved, and the falling possibility is reduced.

The invention relates to the technical field of flame target detection, in particular to a threshold and angle self-adaptive infrared flame detection system and a control method, and the system comprises an infrared detection unit, a holder mechanism, a data processing unit and a fire alarm unit, the data processing unit divides each frame of real-time image into a to-be-identified area and a background area according to the temperature variation among the continuous multiple frames of real-time images of the monitoring area, and dynamically adjusts an abnormal temperature threshold according to the temperature of the background area near the to-be-identified area; extracting a suspected flame region from the to-be-identified region according to the abnormal temperature threshold value, preliminarily eliminating the influence of an interference heat source according to whether the displacement of the suspected flame region is continuous or not, calculating the position of the suspected flame region when the displacement of the suspected flame region is discontinuous, and judging whether the suspected flame region is a normal heat source of a fixed point location or not; therefore, interference of normal heat sources such as industrial fire to fire is eliminated, and the method is suitable for identification of flames which are long in distance, small in scale and unobvious in characteristics.

The invention discloses a parameter calculation method for optimizing flow characteristics of a foam fire retardant material. The parameter calculation method comprises the following steps: establishing a theoretical calculation model of the foam fire retardant material; based on the theoretical calculation model, establishing an Ergun equation; adding unknown empirical parameters to the dimensionless number in the Ergun equation to obtain a dimensionless number calculation equation set; adding constraint conditions for the dimensionless number calculation equation set; based on the dimensionless number calculation equation set, solving an optimal solution of the unknown empirical parameters; and substituting the optimal solution of the unknown empirical parameter into the Ergun equation, and calculating a viscous resistance coefficient and an inertial resistance coefficient. According to the parameter calculation method for optimizing the flow characteristics of the foam fire retardant material, the problem that the flow characteristic parameters of the foam fire retardant material are difficult to accurately obtain in the prior art is solved, and the purposes of rapidly and accurately determining the flow characteristic parameters of the foam fire retardant material and providing important reference for industrial fire retardant type selection are achieved.

This invention discloses an early warning and prevention system for industrial fires based on multi-sensor fusion, belonging to the field of industrial safety monitoring technology. It includes: a data acquisition module, a false alarm discrimination module, a risk zoning module, a fire identification module, and a prevention and control optimization module. The data acquisition module acquires fire data through a hierarchical distributed multi-sensor network. The false alarm discrimination module filters valid fire data based on dynamic false alarm discrimination rules. The risk zoning module generates a risk heatmap and completes sub-region division and risk label allocation. The fire identification module predicts the probability of fire occurrence and identifies the fire development stage. The prevention and control optimization module matches prevention and control strategies based on the fire development stage and risk labels, combines a dynamic cost map to plan the optimal path for AGVs to execute prevention and control tasks, and feeds the execution results back to the data acquisition module for dynamic correction. This application reduces the false alarm rate and improves the reliability and efficiency of early warning and prevention of industrial fires.

The invention relates to the field of industrial fire fighting, and discloses an intelligent early warning fire extinguishing system and equipment based on electrical equipment. The system comprises a multi-mode sensing module, a data fusion and feature extraction module, a fire risk prediction module, a self-adaptive fire extinguishing control module, a digital twin modeling module, an intelligent alarm and linkage module and a model self-learning optimization module, the equipment comprises a protection shell, and a plurality of heat dissipation holes distributed in an array are formed in the protection shell. The fire extinguishing assembly is installed on the front side of the protection shell, the installation buckles are fixed to the left side and the right side of the protection shell correspondingly, the circuit board is installed in the protection shell, and the sensor set is arranged on the top of the circuit board. According to the invention, through a risk scoring mechanism of the convolution and the long-short-term memory network, in combination with multi-modal data input and time sequence modeling, trend prediction of the electrical fire is realized, and the problems of inaccurate early risk pre-judgment and response lag are solved.

The invention provides a method, a system, equipment and a medium for grading fire operation in an oil and gas production place, and the method comprises the steps: carrying out the assignment of a plurality of first-class influence factors of the risk of the industrial fire operation, and obtaining a first-class correction coefficient of each first-class influence factor, the multiple first-class influence factors comprise operation positions, operation types and whether the operation has a disposal process or not; assigning multiple second-class influence factors of the industrial fire operation risk to obtain a second-class correction coefficient of each second-class influence factor, the second-class influence factors including construction operation contractor classes, the number of construction operation contractor, associated operations and whether an operation unit is a major hazard source; obtaining a high-risk operation grading score based on the first-class correction coefficient and the second-class correction coefficient, and obtaining a fire operation grading result based on the high-risk operation grading score; the method can comprehensively and accurately evaluate the fire operation grading of the oil and gas production place, and carefully guides the industrial fire operation grading management of the oil and gas production place.

The invention discloses a structure-free superposed three-dimensional chemical water island layout structure and method, and relates to the technical field of water treatment.The structure comprises a raw water pretreatment unit, a boiler make-up water treatment unit, an industrial wastewater treatment unit, a fine treatment regeneration unit, a regeneration auxiliary unit and a comprehensive water pump unit which are annularly arranged in sequence; the raw water pretreatment unit comprises an industrial fire pool; the clarification tanks are uniformly arranged at the top of the industrial fire-fighting water tank, and the clarification tanks are connected with the industrial fire-fighting water tank through a plurality of mounting brackets; the stability detection mechanism is arranged between the clarification tank and the industrial fire-fighting water tank; and the turbulent flow assembly is arranged in the clarification tank. In the raw water pretreatment unit, through the three-dimensional superposition design of the industrial fire pool and the clarification tank, the efficient utilization of the vertical space is realized on the premise of not depending on the traditional civil engineering structure, and the energy consumption and the operation cost of the system are further reduced.