386 results about "Fire smoke" patented technology

The invention discloses a tunnel fire non-equilibrium control-smoke exhaust automatic adjustment control system and method, and belongs to the field of frequency conversion fan technology and tunnel fire control-smoke exhaust ventilation. The system comprises a data acquisition module, a data transmission module, a data processing and control algorithm module, a fan driving module and an emergency disposal module. The system dynamically and automatically controls the operation state of the smoke exhaust fan according to real-time fire smoke in the tunnel, and the exhaust air rate is reasonably adjusted. The abnormal environment parameters of the tunnel ceiling are collected through the sensing equipment, so that the approximate position of a fire in the tunnel and the real-time dynamic state of fire smoke spreading are obtained. And parameters such as the smoke front spreading speed and the smoke exhaust efficiency of the fan at the smoke exhaust port are obtained by applying an algorithm program to automatically control the start, stop and operation frequency of the fan. The interlocking arrangement of the emergency disposal module ensures that the other combinations are started under the condition that the exhaust air rate of one set of smoke exhaust port-smoke exhaust fan combination of the system is insufficient, fire smoke spreading is effectively controlled, and it is generally ensured that smoke is efficiently exhausted while the fire smoke is controlled within a safe range by the system.

The invention relates to the technical field of tunnel fire smoke exhaust, and discloses a tunnel fire smoke exhaust method and system, and the method comprises the steps: receiving a fire signal, and recognizing the fire position information; dividing the tunnel into three functional areas including a fire disaster area, an upstream evacuation area and a downstream evacuation area according to the fire position information; calculating control parameters required for forming an air pressure isolation belt; the control instruction is sent to smoke exhaust equipment, the fire disaster area is kept in a negative pressure state, and upstream and downstream evacuation areas are kept in a positive pressure state; data are collected in real time, control parameters are dynamically adjusted, and the air pressure difference between the fire disaster area and the evacuation area is maintained. According to the method, safety evacuation passages on the two sides of the tunnel are guaranteed through regional differential air pressure control strategies; continuously optimizing control parameters by adopting a model predictive control method; and a multi-objective optimization algorithm is adopted, so that the system operation cost is reduced while efficient smoke discharge is realized.

The invention discloses an expressway tunnel abnormal event recognition method based on multi-scale polarization fusion, relates to the technical field of intelligent recognition of road traffic videos, and is used for solving the problem of robust recognition of trailing collision, fire smoke and abnormal static behaviors in an expressway tunnel scene. The method comprises the following steps: acquiring polarization angle and polarization degree information of each pixel point in a vehicle driving process; then, the image is divided into a plurality of partitions according to longitudinal illumination changes, a time sequence locking window is established in each partition, and the difference between traffic flow reflection characteristics and background interference is extracted; and identifying a smoke area by constructing a disturbance graph and a direction texture graph, calibrating a trailing collision risk, and judging an abnormal static behavior. And finally, an event atlas is generated, full-process identification closed loop and response cooperation are ensured through structure fingerprints and version numbers, and a high-robustness identification means is provided for fire, trailing and abnormal static targets in a tunnel scene.

The invention relates to the technical field of image recognition, in particular to a fire behavior recognition method and system based on video monitoring. The technical problem that the early warning reliability of a video monitoring system on fire smoke is insufficient is solved. The method comprises the following steps: acquiring a monitoring video stream of a monitoring area and time sequence data acquired by a sensor in the monitoring area; determining an evaluation value of the to-be-detected area based on the image feature and the morphological change of the to-be-detected area; determining a confidence factor based on the form change trend of the to-be-detected region and the change trend of the time series data; determining a smoke authenticity value based on the evaluation value and the confidence factor; and adjusting an alarm threshold value of the smoke alarm based on the smoke authenticity value. The method is used for fire smoke early warning and monitoring scenes.

The invention belongs to the technical field of tunnel catastrophe, and particularly relates to an intelligent feedback type tunnel catastrophe monitoring method, which comprises the following steps of: 1, deploying a tunnel monitoring system; a temperature sensor, a smoke sensor, an air velocity sensor and a gas concentration sensor are arranged in the tunnel; the temperature sensor is used for monitoring temperature changes in the tunnel. According to the intelligent feedback type tunnel catastrophe monitoring method, the safety and the emergency response capability of the tunnel are effectively improved through real-time data monitoring and analysis and an automatic control mechanism. Firstly, through temperature, smoke, gas concentration and air velocity sensors, the system can detect and identify potential catastrophe risks in a tunnel in time, such as fire, smoke diffusion and harmful gas leakage. Once an abnormality occurs, the system performs catastrophe prediction through an algorithm model, and performs accurate evaluation on a fire propagation path and smoke diffusion in combination with a simulation analysis result, thereby providing reliable data support for quick response.

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

The invention relates to the technical field of smoke particle detection, in particular to a fire smoke particle detection method and system for intelligent fire fighting, and the method comprises the steps: obtaining the fire smoke particle concentration and temperature of each position in each time window, acquiring a fire smoke particle abnormal fluctuation coefficient and a temperature rise saliency value of each position in each time window, further acquiring a smoke particle diffusion saliency of each position in each time window, and predicting the smoke particle diffusion saliency of an adjacent position of each position at the current moment. Obtaining a smoke particle state influence coefficient of each position at the current moment; and predicting the fire smoke concentration data of each position at the current moment, and optimizing the smoothing coefficient of the prediction algorithm according to the smoke particle state influence coefficient of each position at the current moment in the prediction process so as to obtain the fire smoke particle concentration through the predicted value. According to the invention, the accuracy of fire smoke particle concentration distribution detection can be improved.

The invention relates to the technical field of intelligent sensors, in particular to an intelligent fire-fighting fire smoke particle detection method, which comprises the following steps: acquiring multiple frames of target images of a target area, and determining whether the smoke area in each frame of target image is a fire smoke area according to the gray value of the smoke area in each frame of target image; determining the actual brightness of each sub-region in the fire smoke region under the condition that the fire smoke region is the fire smoke region; determining the global concentration of the fire smoke area according to the original brightness, the actual brightness of each sub-area and the number of pixels, and determining the instantaneous acceleration of the smoke concentration based on the global concentration of the fire smoke area in the target image of the current frame and the global concentration of the fire smoke area in the target image of the previous frame; and determining a fire risk grade by using the instantaneous speed increase of the smoke concentration and triggering an alarm of the corresponding grade. Therefore, the accuracy and reliability of the detection result of the fire smoke particles are improved.

The invention provides a fire smoke target detection method based on improved YOLOv11. The method comprises the following steps: constructing a fire smoke image data set; a CIB module is added to C3K2 in a YOLOv11 model, an inverted residual structure and depth separable convolution are used for improvement, and a fire smoke target detection model is constructed based on the improvement; selecting a data enhancement mode, and setting training parameters; training a fire smoke target detection model based on the improved YOLOv11; and testing the trained fire smoke target detection model based on the improved YOLOv11 to obtain a test result. The invention further provides a fire smoke target detection system based on the improved YOLOv11. On the basis of original YOLOv11, a CIB module is introduced into a core structure C3K2, an inverted residual structure and depth separable convolution are utilized, and the feature expression ability is kept while the calculated amount is reduced.

The invention relates to the technical field of intelligent fire protection of a thermal power plant, and discloses an intelligent fire smoke detection method and system for intelligent fire protection of the thermal power plant, and the method comprises the steps: collecting a video stream of a fire protection monitoring region through video monitoring disposed in the fire protection monitoring region of the thermal power plant, and extracting a video frame in the video stream; performing spatial texture feature extraction and time change feature extraction on the video frames to obtain a fire smoke spatial texture feature map and a fire smoke time change feature map; performing feature fusion on the fire smoke space texture feature map and the fire smoke time change feature map to obtain fire smoke fusion features; identifying the fire smoke fusion feature through a pre-trained fire smoke identification model to determine a fire smoke identification result and identification confidence of the fire-fighting monitoring area; and acquiring sensor data acquired by a fire-fighting sensor deployed in the fire-fighting monitoring area, and determining a fire smoke detection result of the fire-fighting monitoring area based on the fire smoke identification result, the identification confidence and the sensor data.

The invention relates to the technical field of tunnel fire smoke accident data processing, and discloses a tunnel fire smoke intelligent control method and an emergency disposal system, and the system comprises a tunnel fire smoke accident identification module, a tunnel fire smoke accident rescue information analysis module, and a tunnel fire smoke accident rescue information feedback module. The tunnel fire smoke accident occurrence type is accurately analyzed by scientifically presetting tunnel fire smoke accident occurrence type image parameters in combination with a deep learning intelligent algorithm and standard tunnel field real-time image data, and the occurrence reason type of the tunnel fire smoke accident is accurately evaluated and generated based on the deep learning intelligent algorithm. And according to the tunnel fire smoke accident occurrence type analysis parameters, the tunnel fire smoke accident rescue scheme is scientifically judged in combination with the intelligent search algorithm and the tunnel fire smoke accident rescue scheme parameters, and personalized customization of the tunnel fire smoke accident specific rescue scheme is achieved.

The invention discloses fire smoke alarm equipment based on a satellite positioning function, and belongs to the technical field of fire smoke alarm systems. Comprising a smoke alarm and a base, and double interchangeable collecting cylinders are arranged in the smoke alarm. The first collecting cylinder is used for a high-dust environment, and 80% of coarse dust is pre-separated through a large aperture and a settling table. The second collecting cylinder is used for high-humidity environment, small aperture and chimney effect condensation prevention, and the ventilation rate is larger than or equal to 96%. A smoke channel is integrated in an inner cavity of the upper connecting disc, an annular spraying array is arranged on the outer ring of the lower connecting disc, and the integration of detection, positioning and fire extinguishing is achieved. The satellite baseband chip and the infrared maze share an antenna guiding assembly, NMEA coordinates are frozen when smoke exceeds a threshold value, the NMEA coordinates are directly sent to a platform through NB-IoT, the positioning error is smaller than or equal to 2 m, and a platform map is a second-level flash point. The drawer type smoke detection module can be disassembled quickly in 5s, double silica gel sealing and pulse water spraying hole cooling are adopted, and long-term maintenance-free under high-temperature, high-dust and high-humidity conditions is ensured.

The invention discloses a forest fire smoke particle adsorption degree prediction method, system and device and a medium, and belongs to the field of power systems, and the method comprises the steps: obtaining forest fire data of a to-be-predicted overhead transmission line under a forest fire condition in a preset time period; inputting the forest fire data into a simulation calculation model, so that the simulation calculation model constructs a simulation model corresponding to the overhead transmission line to be predicted according to the forest fire data, determining a corresponding relation between coordinate data of each smoke particle and each simulation area according to the simulation model, and calculating the number and quality of the smoke particles in each simulation area, and outputting an adsorption degree prediction result corresponding to the target simulation area, the simulation model comprising a plurality of simulation areas, and each simulation area being obtained by division according to the space field intensity of the to-be-predicted overhead transmission line, so that through implementation of the method, the adsorption degree of the smoke particles in the overhead transmission line can be accurately predicted, and the prediction accuracy of the adsorption degree of the smoke particles in the overhead transmission line is improved. And the safety of the power system is improved.

The invention relates to the technical field of warehouse environment risk monitoring, in particular to a warehouse environment risk monitoring method and system, and the method comprises the following steps: obtaining a scheduling table and current operation time of forklift drivers or inspectors in a target warehouse, collecting a task load factor of a current task type and the temperature and noise level of an operation area, and obtaining a task load factor of a current task type; and calculating to obtain a scene fatigue risk value. According to the invention, by analyzing the scheduling data and real-time task load and environmental pressure indexes of the forklift driver and the inspector, the comprehensive influence of the personnel operation state and the environmental condition on the fatigue risk is quantitatively evaluated, so that the risk evaluation basis is more comprehensive and specific, and the oneness of risk judgment is avoided; according to the method, a warehouse layout map and cargo distribution information are obtained in real time, and multi-source risk factors are associated into specific warehouse grid units in combination with readings of fire smoke and toxic gas sensors in the warehouse, so that fusion of finer space granularity and more comprehensive risk information is realized.

The invention discloses a fire smoke detection method based on an improved YOLOv8 network, and the method comprises the steps: carrying out the data preprocessing, and building a data set: building the data set through employing a fire smoke image, and enabling the data set to comprise two kinds of scene cities and forests; comprising annotation fire disasters and smog of two target categories, large targets and small targets of the fire disasters and the smog, and interference images without the fire disasters and the smog; establishing a target detection network which comprises a feature extraction network, a feature fusion network and a detection head; the feature extraction network generates a multi-scale primary feature map; the feature fusion network optimizes semantic and spatial information of the multi-scale primary feature map through cross-scale connection, and outputs an enhanced feature pyramid; the detection head executes fractional-scale dense prediction based on the pyramid, and outputs a detection result through non-maximum suppression; and sending the test set sample to a target detection network, and performing category classification and position regression on test data to obtain a final detection result.

The invention relates to a UHPC-based fabricated fire-fighting smoke exhaust fan room structure and a construction method thereof, the room structure comprises a main body structure, and the main body structure is prefabricated by adopting an ultra-high performance concrete UHPC material; a fan is arranged in the internal space of the main body structure; the main body structure is provided with a machine room enclosure bulkhead cylinder body and an end cover side wall. Wherein the machine room enclosure bulkhead cylinder body is provided with a bottom plate, a first side wall and a second side wall, the first side wall and the second side wall are connected with the bottom plate and vertically arranged in parallel, and a first opening end and a second opening end which are oppositely arranged are arranged at the two ends of the machine room enclosure bulkhead cylinder body in the horizontal direction respectively; the end cover side wall is provided with a first end cover and a second end cover which are respectively arranged at the first opening end and the second opening end; the first end cover and the second end cover are each provided with a smoke suction and exhaust port, and the smoke suction and exhaust ports are used for being connected with a ventilation pipeline. The UHPC shell is adopted, the advantages of being high in strength and good in fire resistance are achieved, the prefabricated assembly type structure is adopted, construction is convenient, and efficiency is high.

The invention discloses an intelligent temperature control axial flow type fire-fighting smoke exhaust fan, and belongs to the technical field of smoke exhaust fans. Blades of an impeller of the smoke exhaust fan comprise a connecting piece, a rotating piece and a connecting shaft, two sets of symmetrical thermal deformation metal pieces are arranged between the connecting piece and the rotating piece, the characteristic that the thermal deformation metal pieces contract or extend along with the temperature is utilized, the rotating piece is driven to deform bidirectionally so as to adjust the angle of the blades, intelligent temperature control is achieved, and the air volume of the impeller can be automatically adjusted. A heat dissipation and self-cleaning integrated component is further arranged on the machine shell, the functions of oscillation of cleaning liquid, heat dissipation and self-cleaning can be achieved, the smoke exhaust fan can be self-cleaned while heat dissipation is conducted on the whole smoke exhaust fan, a large amount of dust is prevented from standing and precipitating on blades, and the heat absorption and dissipation capacity of the whole smoke exhaust fan can be enhanced. Intelligent adjustment is achieved through mechanical structure linkage, complex electric control is not needed, and the smoke exhaust efficiency, operation stability and maintenance convenience are improved.

The invention relates to an assembly type integrated fire-fighting smoke exhaust fan room structure which comprises a machine room enclosure bulkhead cylinder body which is provided with a bottom plate, a first side wall and a second side wall, the first side wall and the second side wall are connected with the bottom plate and vertically arranged in parallel, and the two ends of the machine room enclosure bulkhead cylinder body in the horizontal direction are provided with a first opening end and a second opening end which are oppositely arranged correspondingly; the end cover side wall is provided with a first end cover and a second end cover which are respectively arranged at the first opening end and the second opening end; smoke suction and exhaust ports are formed in the first end cover and the second end cover and are used for being connected with a ventilation pipeline; the machine room access door is arranged on the first side wall or the second side wall and can be opened and closed; the fan is arranged in an internal space formed by the machine room enclosure bulkhead cylinder body, the first end cover and the second end cover; the machine room enclosure bulkhead cylinder body, the first end cover, the second end cover and the machine room access door are all of a prefabricated concrete structure. The fabricated integrated design is adopted, the cost is low, the self weight is light, fireproof performance is achieved, and the advantages of being stable, reusable, attractive and the like are achieved.

The utility model discloses a fire-fighting smoke exhaust pipeline, and relates to the technical field of fire-fighting equipment. The pipeline body comprises a fan, a ventilation pipe and a filter device, a through groove is formed in the inner wall of the ventilation pipe and divides the ventilation pipe into a first ventilation pipe and a second ventilation pipe, the fan is arranged in the first ventilation pipe, the filter device is arranged between the first ventilation pipe and the second ventilation pipe, and the filter device comprises an annular filter screen, a brush roller, a rotating roller and a motor; the annular filter screen is wound on the brush roller and the rotating roller, the annular filter screen can effectively filter impurities in the smoke, the fan provides strong power, and it is ensured that the smoke is rapidly discharged. Through cooperation of the brush roller and the cleaning brush, automatic cleaning of the filter screen is achieved, blockage is reduced, long-term stable operation is guaranteed, through combination of the heat insulation ring and the rock wool board, high temperature is effectively blocked, the pipeline and peripheral equipment are protected, the protective net protects the fan, the service life of the pipeline is prolonged through the high-temperature-resistant coating, and the reliability of a fire fighting system is improved.

The invention discloses a fire smoke exhaust system and method for a rail transit tunnel, and relates to the technical field of rail transit safety. The fire smoke exhaust system of the rail transit tunnel comprises a draught fan and a smoke exhaust pipeline, the smoke exhaust pipeline is arranged on the draught fan, one end of the smoke exhaust pipeline communicates with the draught fan, the other end of the smoke exhaust pipeline is used for communicating with an ascending tunnel and a descending tunnel, and the smoke exhaust pipeline comprises a first pipeline, a second pipeline, a third pipeline and a fourth pipeline; a first air valve of the air valve assembly is arranged in the first pipeline, a second air valve of the air valve assembly is arranged in the second pipeline, a third air valve of the air valve assembly is arranged in the third pipeline, and a fourth air valve of the air valve assembly is arranged in the fourth pipeline. On the premise that a smoke exhaust well in the middle of the tunnel is not arranged, fire smoke in the tunnel can be exhausted out of an inlet or an outlet of an upstream tunnel or out of an inlet or an outlet of a downstream tunnel through different airflow organization methods, meanwhile, it is guaranteed that people and smoke are separated in the tunnel, and safe evacuation of people is guaranteed.

The invention relates to the technical field of smoke detection and alarm, and discloses a fire smoke detection and alarm device and a use method thereof, the fire smoke detection and alarm device comprises an alarm shell, and the top of the alarm shell is fixedly connected with a fixed base. A second gear rotates to drive a rotating shaft to rotate, the rotating shaft rotates to drive a moving block rotationally connected to a reciprocating threaded groove to slide up and down along the reciprocating threaded groove, and the moving block slides up and down to drive an annular brush to slide up and down along the outer wall of a dustproof net cylinder; through the arrangement, bristles on the inner side of the annular brush can remove sundries attached to the outer wall of the dustproof net cylinder, on one hand, the annular brush can scrape water drops attached to the surface of the dustproof net cylinder, and on the other hand, the annular brush can remove catkins and other sundries on the surface of the dustproof net cylinder; the air holes in the dustproof net cylinder are prevented from being blocked by sundries meeting water, so that the sundries are prevented from hindering smoke collection of the alarm device.

The invention relates to an improved CycleGAN-based forest fire smoke image generation method and system, and belongs to the crossing field of a forest fire safety technology, a deep learning technology and a computer vision identification technology. According to the method, the potential distribution rule of fog can be learned under the condition that there is no paired foggy image-fogless image, and the foggy image corresponding to the input fogless image is synthesized and output. A CycleGAN framework is adopted in the model, a double-branch generator is used for synthesizing a foggy image, a physical formula of an atmospheric scattering model, a dense residual module and a double-path attention module are introduced, and training schemes of feature reconstruction loss, confrontation loss and feature matching loss are optimized. The pixel-pixel corresponding paired images with strong physical constraints are generated, and the precision of the generated images is improved. The method for generating the non-paired image of the forest fire smoke image provides an effective solution for solving the problem that a high-quality paired data set in an image defogging task in recent years is difficult to obtain.

The embodiment of the invention provides a smoke shielding false alarm intelligent identification system and method, and is applied to the technical field of intelligent fire detection, and the method comprises the steps: synchronously collecting an imaging picture, radiant heat response data and a wind field state parameter of a suspected shielding region; the method comprises the following steps: identifying and identifying an abnormal shielding area in a picture; further analyzing the motion characteristics of the region along with the change of the wind field and the dynamic process of the thermal inertia change of the region; the core is to judge whether a time sequence lag relationship meeting a smoke diffusion physical rule exists between the two, so as to identify whether the shielding object is combustion smoke or not. And if the physical mechanism is not met, the alarm is inhibited, so that real fire smoke and non-fire interferents such as dust and steam are effectively distinguished, and the fire false alarm rate in a complex ventilation environment is remarkably reduced.

The middle shaft-free ventilation system comprises a right-line tunnel, a left-line tunnel and a middle tunnel, an air feeder is arranged in an air feeder room, the air feeder room takes air through the middle tunnel, and the air is fed to the right-line tunnel or the left-line tunnel through an air feeding opening in an outlet of the air feeder room; the right-line tunnel top air duct and the left-line tunnel top air duct are provided with ordinary exhaust outlets in the upstream of the air supply outlets in the driving direction, the right-line tunnel top air duct and the left-line tunnel top air duct communicate with each other through a plurality of parallel air ducts arranged at intervals, and a fire smoke exhaust air port is formed in the communicating position of the right-line tunnel top air duct and the left-line tunnel top air duct. The right line tunnel top air duct and the left line tunnel top air duct are each divided into a plurality of sections, a relay fan and a blocking plate are arranged at each section, and each relay fan is arranged in an independently-excavated relay ventilation duct. A ventilation shaft does not need to be arranged in the middle of the tunnel, the efficient ventilation and safe smoke exhaust functions are achieved, and the reliability, economical efficiency and emergency response capacity of tunnel operation are remarkably improved.

The invention discloses a forest fire smoke monitoring method and related device based on false detection feedback and model self-evolution, and the method comprises the steps: obtaining a video stream of a monitoring region, carrying out the preprocessing, inputting a target detection model and a scene understanding model, and judging whether a candidate alarm event is generated or not through consistency analysis; when a candidate alarm event is generated, a work order is generated for manual judgment, a real alarm executes a disposal process, and a false alarm is stored in a database; screening high-value false detection samples based on an information entropy priority strategy, storing the samples into a dynamic memory bank, selecting the samples to form an incremental training set, performing incremental training on a pre-training teacher model, and introducing low-rank constraint stability parameters; migrating the discrimination ability of the teacher model to the student model through knowledge distillation, wherein alignment of a channel dimension and a multi-scale space dimension is carried out; and redeploying the updated student model to execute target detection. The invention aims to solve the problems that the current monitoring system depends on manpower, the coverage capability is limited, the response is slow and the cost is high, and the traditional method is high in false alarm rate, easy to leak and misjudge, difficult in large-scale network edge deployment, limited in light-weight model discrimination capability, lack of linkage between alarm processing and model updating and the like, and more accurate and efficient forest fire smoke monitoring is realized.

A fire smoke-detection method and detector based on particle shape characteristics for detecting particles in an optical dark chamber. An optical path angle between one blue light and one infrared light and a photoelectric conversion module is an acute angle, while an optical path angle between another blue light and the photoelectric conversion module is an obtuse angle. The detection method includes: starting a light source combination, calculating a change value between a current scattered light optical power and a background value of each light source, when the change value exceeds a set threshold, continuously starting the light source combination and constructing a space vector from the recorded change values, and using a classifier to classify a plurality of space vectors to obtain a plurality of classification results with categories including fire smoke and interfering aerosols; and counting the classification results to obtain the correct classification result.

The invention discloses a rapid fire smoke diffusion simulation method based on a grid Boltzmann technology, and relates to the technical field of fire safety simulation. Comprising the following steps: carrying out three-dimensional modeling inside and outside a semiconductor large-scale industrial factory building, gridding the three-dimensional modeling inside and outside the semiconductor large-scale factory building, dividing a calculation space by adopting a Boltzmann LBMD3Q19 model, setting a fire point, calculating a smoke substance proportion by adopting an incomplete combustion chemical reaction equation, and calculating combustion heat release according to the incomplete combustion chemical reaction equation. Calculating a high-temperature thermal plume region formed by chemical reaction heat release, calculating a microscopic particle collision process, calculating a microscopic particle migration process, processing boundary conditions, counting macroscopic quantity, and iteratively calculating flue gas concentration; according to the method, microscopic and macroscopic advantage complementation of the two can be realized, the resolving efficiency is improved, seamless coupling of flame chemistry-turbulence-heat transfer is completed, and a new method is provided for solving the problem of fire smoke spreading of complex plants.

The present invention relates to a centrifugal fire smoke exhaust fan, belonging to the technical field of centrifugal fans. The centrifugal fire smoke exhaust fan includes a base and a fan, and further includes: an air inlet pipe, a filtering mechanism; a spraying mechanism; a mixing mechanism; a water removal mechanism. Through the combined use of the filtering mechanism and the spraying mechanism, when the centrifugal fire fan works, the filtering mechanism filters the flue gas entering the air inlet pipe, so that the dust particles in the flue gas are blocked. When the spraying mechanism works, clean water will flow through the heat exchange pipes in the filtering mechanism, so that the clean water absorbs the temperature of the flue gas, thereby reducing the probability of the impeller being corroded. The clean water after absorbing the temperature of the flue gas will be sprayed into the flue gas through the spraying mechanism. At this time, because the clean water has a temperature, the atomization efficiency of the clean water can be higher, so that the atomized clean water can more comprehensively absorb the polluting gases in the flue gas, further reducing the probability of the impeller being corroded and protecting the environment well.

The present application relates to a kind of fire smoke flow intelligent monitoring early warning device and early warning method, early warning device includes base, swivel seat, monitoring head, main control module, thermal imaging module, laser module and alarm module, swivel seat is horizontally rotated by drive mechanism one and is arranged on base, monitoring head is vertically rotated by drive mechanism two and is arranged on swivel seat, laser module and thermal imaging module are arranged on monitoring head, thermal imaging module is connected with main control module, main control module is used to calculate the movement direction of smoke, main control module is connected with drive mechanism one, drive mechanism two, laser module and alarm module, for according to the movement direction of smoke control drive mechanism one and drive mechanism two action, make laser module towards the movement track of smoke.The present application has higher identification efficiency, judgment accuracy and response speed, can provide key early warning for firemen before fire outbreak, so as to gain crucial emergency decision and evacuation time.

The present application relates to the technical field of smoke alarm, in particular to a kind of intelligent fire-fighting smoke sensing alarm method and system based on Internet of Things, comprising the following steps: installing spectrum analysis sensor in the key area of building, capture spectrum signal, according to preset time interval collection smoke spectrum data, and be transmitted to cloud platform by Internet of Things network node, unified data format, generate spectrum dataset.In the present application, by capturing and analyzing the spectral characteristic curve of smoke, different types of smoke can be distinguished, efficient differentiation between fire smoke and non-fire smoke is achieved, false alarm phenomenon is reduced, combined with real-time environmental data, dynamically adjust the sensitivity of the sensor and the alarm threshold, still can maintain high reliability in complex and variable environment, at the same time, it can trigger multiple device response synchronously, quickly start fire sprinkler, smoke exhaust equipment and other mechanisms, and real-time fire alarm signal is transmitted to relevant departments, shorten the response time, optimize the linkage effect of fire emergency handling.