2314 results about "Smoke Emission" patented technology

A device, and method for its use, which may be worn by a firefighter for detecting the source of a fire in a smoke-filled or noisy environment, the device having directional infrared sensors for detecting the direction of maximum or minimum intensity of infrared radiation in two or more directions relative to the wearer and reporting at least the direction of maximum or minimum intensity to the wearer by a tactile indicator contacting the skin of the wearer.

A system and apparatus for automatic smoke evacuation using an RF sensor. The system and apparatus utilizes an RF sensor for automatic activation of an evacuator that evacuates smoke and / or debris during the use of any electrosurgical instrument or surgical instrument that is capable of generating smoke and / or debris and capable of producing a radiofrequency during its operation. Exemplary embodiments of the system and apparatus for automatic smoke evacuation include both wired and wireless embodiments.

The invention relates to the technical field of environment early warning, and discloses a holographic sensing multi-mode environment early warning control method and system, and the method comprises the steps: obtaining an original multi-mode signal, and constructing a multi-mode fire signal matrix; performing matrix decomposition operation of combustion dynamics constraint and flue gas diffusion constraint on the multi-modal fire signal matrix to obtain a fire basic characteristic matrix and a spatio-temporal evolution coefficient matrix; performing feature fusion on the fire basic feature matrix and the spatio-temporal evolution coefficient matrix to obtain a comprehensive fire feature vector; according to the method, multi-dimensional fire feature information such as temperature, smoke, gas, acoustics and infrared can be captured at the same time, the comprehensiveness and reliability of fire detection are improved, and the method is suitable for popularization and application. And the three-dimensional space coordinates of the fire source can be accurately determined.

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 application provides a kind of super-long chemical pipeline conveying system, comprising: centralized liquid supply system equipment;Several chemical distribution plates;Several transparent PVC boxes, and hollow double-layer pipes;For connecting centralized liquid supply system equipment, chemical distribution plate and transparent PVC box;Hollow double-layer pipe includes transparent PVC pipe and PFA hose, transparent PVC pipe is contained in transparent PVC direct head, PFA hose is contained in transparent PVC pipe, PFA hose diameter is 1-1.5 inch, transparent PVC box is internally provided with by letting box, by letting box includes several adapters, locking nuts and electronic valves, electronic valve is electrically connected with PLC and smoke sensor;Transparent PVC box bottom surface is also provided with several reagent boxes, and reagent box contains reagent that can react with dangerous chemicals to generate smoke.The application can realize super-long chemical transportation turning to prevent pipeline rupture, and prevent chemical leakage.

The invention discloses an artificial intelligence-based equipment security and protection monitoring method, equipment and a medium, and relates to the technical field of equipment security and protection monitoring, and the method comprises the steps: constructing a deep learning optical flow estimation model based on image frame sequences, carrying out the optical flow motion vector calculation of adjacent image frames through employing the model, and extracting the motion characteristics of smoke diffusion; textural features are extracted from the image frames, normalization and time alignment are carried out on the textural features and smoke diffusion characterization features, and a space-time joint feature vector sequence is constructed; performing smoke event classification prediction on the sequence through a time sequence classification model containing an attention mechanism to obtain an event type and confidence; and triggering a security response according to the smoke event type and the confidence coefficient. According to the invention, the dynamic characteristics of smoke diffusion are effectively extracted, and the detection precision is improved; the capturing capability of time sequence continuity and space consistency in the smoke diffusion process is enhanced through spatio-temporal joint modeling, and missing report and false report are reduced.

The invention discloses an intelligent fire prevention and control and operation and maintenance optimization method and system for an electric power supply network, and the method comprises the steps: collecting temperature, humidity and smoke concentration data in real time through a sensor network, generating a comprehensive environment index data flow, and obtaining a fire initial signal through abnormality judgment; calling a medium selection model, and outputting an optimal environment-friendly insulating medium and release parameters thereof by querying an environment-friendly medium and insulating characteristic parameter library and performing matching calculation based on the equipment type; utilizing a response speed optimization algorithm to generate an accurate release instruction sequence containing a release path, a dose and a time sequence; controlling the medium atomization device to synchronously release the medium according to the instruction; and collecting equipment protection and power supply continuity data, performing risk assessment to generate an efficiency index, and updating the prevention and control strategy library to optimize a subsequent decision. Through intelligent decision making and closed-loop optimization, power supply continuity and equipment safety are guaranteed to the maximum extent while rapid and accurate fire extinguishing is achieved, and transformation from post-disaster disposal to operation and maintenance level prevention and control is completed.

The invention provides a granary safety intelligent early warning method and device, relates to the field of data processing and early warning, and solves the technical problems that the existing granary operation risk detection is not accurate enough, and the conditions of incomplete identification, false alarm or missing alarm are easy to occur. The method comprises the following steps: collecting multi-source time sequence data in a granary, and constructing environmental safety time sequence characteristics based on oxygen concentration time sequence data, toxic gas concentration time sequence data and smoke state time sequence data; based on the temperature and humidity time sequence data and the grain pile temperature time sequence data, risk trend time sequence characteristics are extracted; constructing a risk time sequence based on the environmental safety time sequence characteristics, the risk trend time sequence characteristics and the personnel access information time sequence data; carrying out fusion modeling on the risk sequential sequence through Transform, and identifying a risk level; and when the risk level reaches a preset threshold value, the system controls the bin gate access control to execute opening or closing operation, and synchronously triggers linkage early warning treatment. The method is used in the granary operation safety early warning process.

The present disclosure relates to a battery tray and a power battery pack. The battery tray includes a tray body. The tray body includes a base plate and a side beam, and the side beam is disposed around the base plate and defines, together with the base plate, an accommodating space for battery cells. The base plate is formed therein with an air passage, and the base plate is provided with several inlet vents and at least one exhaust vent. The inlet vent is configured to introduce a flame, smoke or gas discharged from the battery cell into the air passage, and the exhaust vent is configured to discharge the flame, smoke or gas inside the air passage.

The invention provides a capsule used as an aerosol generating substrate, the capsule contains fuming materials propylene glycol and glycerol, a capsule skin comprises a colloidal substance, the colloidal substance is at least one of animal glue, vegetable glue, starch and a starch modifier, and only one layer of capsule skin is provided. The invention also discloses an aerosol generating product using the capsule, and uniform and sufficient smoke release can be obtained at a lower heating temperature, so that the aerosol product can further reduce the energy consumption, reduce the release of harmful substances and improve the feeling of a smoker.

The invention relates to the technical field of motor manufacturing equipment. The invention discloses a slot insulation paper cutting device which comprises a base, a slot insulation paper laser cutting module, a smoke purifier, a paper feeding and pushing module and a tension paper feeding module are integrated on the base, the slot insulation paper laser cutting module is arranged on the downstream of the tension paper feeding module, and the smoke purifier is arranged above the slot insulation paper laser cutting module; the tension paper feeding module is used for providing stable conveying of slot insulation paper; the groove insulation paper laser cutting module is used for carrying out laser cutting and printing processing on groove insulation paper; the paper feeding and pushing module is used for pushing the groove insulation paper from the tension paper feeding module to the groove insulation paper laser cutting module; the smoke purifier is used for collecting smoke generated in the cutting process. The method has the beneficial effects that 1, high-precision laser cutting and dynamic compensation are achieved, specifically, a special laser cutting module for slot insulation paper is adopted, the cutting focal length of a laser head is adjusted through a hand-cranking wheel, a cutting path is preset according to the slot type unfolding shape of the skewed slot stator, the cutting path is dynamically adjusted, the technology that cutting printing is not cut through is supported, the burr problem of cutting of a traditional cutter is avoided, and the production efficiency is improved; in combination with the tension control of a servo motor paper feeding servo motor and a tension paper feeding module, the cutting precision is ensured to be + / -0.05 mm; 2, an environment-friendly smoke purification system is adopted, a smoke purifier is integrated at the top of equipment, harmful smoke generated in the laser cutting process is collected in real time, the workshop environment is improved, and the environment-friendly requirement is met;

The invention relates to the technical field of highway tunnel smoke exhaust systems, and discloses a bypass type smoke exhaust system suitable for extra-long and large municipal and highway tunnels, the bypass type smoke exhaust system comprises a ground, the upper side of the ground is fixedly connected with a tunnel body, and the left side of the interior of the tunnel body is fixedly connected with a connecting assembly; the connecting assembly is used for monitoring parameters such as smoke concentration and temperature in a tunnel in real time, a fixing box is fixedly connected to the left side of the upper portion of the ground, a partition plate is fixedly connected to the interior of the fixing box, a sealing ring is fixedly connected to the front side of the partition plate, and the sealing ring is fixedly connected to the front side of the interior of the fixing box; and a fixing frame is slidably connected to the interior of the sealing ring, and a filter screen is fixedly connected to the upper side of the interior of the fixing frame. Flue gas is effectively humidified and settled in the discharging process, the treatment effect of the smoke is further improved, the system can be adjusted in real time, and it is ensured that quick response is achieved when a fire disaster happens, and spraying of water mist is controlled.

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 intelligent sensors, and particularly discloses a smoke sensor monitoring sensing method and system. The system comprises a multi-source environment sensing module, a feature extraction and fusion module, a dynamic threshold decision module and an execution control module, a comprehensive environment state vector is constructed by fusing multi-dimensional environment data, and an alarm threshold is dynamically adjusted based on a deep reinforcement learning model, so that accurate fire identification and hierarchical control are realized, and the system is suitable for popularization and application. And the monitoring reliability, the environmental adaptability and the agriculture and forestry equipment operation efficiency are effectively improved.

The utility model relates to a cold fuming smoking tank which comprises a smoking insecticide and a tank body, the smoking insecticide is arranged at the bottom of an inner cavity of the tank body, a cigarette lighting hole is formed in the middle of the smoking insecticide, a reaction chamber is arranged on the upper side of the smoking insecticide in the inner cavity of the tank body, a spring is arranged in the reaction chamber, and the upper end of the spring is matched with the top of the tank body. The lower end of the spring is matched with the upper end of the smoking insecticide, and a tank smoke outlet is formed in the top of the tank. During field use, the smoke lighting hole in the middle of the smoke insecticide is heated, smoke formed by the smoke insecticide firstly enters the reaction chamber, and the reaction chamber plays a role in gathering and pressurizing the smoke, so that the smoke has a certain initial speed when being discharged from the smoke outlet of the tank body, and the smoke can quickly climb to the top of the space; the mushroom cloud-shaped volatile smoke is formed, the whole roof can be gradually dispersed with the smoke, and then the smoke naturally sinks, so that insect killing is achieved.

The invention relates to the technical field of fire prevention, and discloses a high-and-low-voltage power distribution room fire prevention early warning system based on potassium ion aerosol fire extinguishing, which comprises a smoke fire detection module used for detecting fire related data inside and outside a high-and-low-voltage power distribution room; the fire related data comprises smoke data and temperature data; the comprehensive evaluation module is used for judging whether an adopted evaluation model is a temperature evaluation model or a smoke evaluation model according to the fire related data; the fireproof grade classification module is used for grading fireproof grades in the high and low voltage power distribution room according to the screened evaluation model; the fire prevention measure implementation module is used for starting the potassium ion aerial fog fire extinguishing equipment in the corresponding fire prevention subareas to extinguish fire according to different grades; the electrical characteristic monitoring module is used for monitoring the load current and arc signal intensity of electrical equipment in the high-low voltage power distribution room and the temperature change rate of key nodes in real time; according to the invention, multi-dimensional accurate monitoring and graded prevention and control of the fire risk of the high and low voltage power distribution room are realized.

The invention belongs to the technical field of fire safety management, and particularly relates to an intelligent early warning method and system for fire safety management, and the method comprises the steps: obtaining multi-source fire sensor data; training a basic multi-modal fusion model according to the multi-source fire-fighting sensor data to obtain fire risk probability data, and meanwhile, generating sequential aligned continuous video frames through basic inter-frame feature matching; according to continuous video frames, space-time joint features are extracted by using a basic space-time convolutional network, local feature maps of flames and smog are generated in combination with a lightweight backbone network, a fire source key area is positioned, and a fire spreading direction and a fire spreading speed are analyzed to obtain a risk change trend; and based on the risk change trend, identifying a fire risk level through a lightweight classification model, carrying out risk scoring on the safety degree, and generating a thermodynamic diagram to mark a high-risk area. Therefore, the problems of insufficient multi-source data fusion depth, weak video analysis time sequence coherence, lack of visualization ability and the like in the prior art are solved.

The invention discloses an edge flame and smoke intelligent identification method based on deep learning, and the method comprises the steps: collecting continuous video frames, carrying out the normalization, correction and noise reduction, and generating a preprocessing video sequence; constructing a background static reference frame, and carrying out pixel difference on the background static reference frame and the current frame to generate geometric refraction potential field codes; performing refraction phase mapping on the geometric refraction potential field code to form a refraction phase disturbance tensor; inputting an improved SlowFast model, dynamically adjusting three-branch sampling, and outputting a preliminary candidate region; extracting refraction, phase and energy evolution sequences, constructing a coupling sequence and correcting an identification result; and calculating a risk level, marking a high-risk area, and outputting fire early warning at edge equipment. According to the invention, through constructing the refraction potential field features and the phase disturbance features and combining the improved multi-branch SlowFast deep learning model, rapid, accurate and stable edge side intelligent identification and early warning of flames and smog are realized.

An aerosol generating device may include a cartridge configured to store an aerosol generating material, a main body to which the cartridge is detachably coupled, a first heater configured to heat a cigarette inserted into the aerosol generating device, a second heater configured to heat an aerosol generating material, and a processor configured to individually control the first heater and the second heater so that the aerosol generating device operates in one of a smokeless mode in which visible smoke is not generated and a smoke mode in which visible smoke is generated.

The invention discloses an aerosol generating product which comprises an aerosol generating substrate section, an air inlet is formed in a pipe body corresponding to the aerosol generating substrate section or the sealed end of the pipe body, the air inlet is formed in a heat conduction material, the heat conduction material covers a part of the overall surface of the aerosol generating material, and the air inlet can enable air to flow into the pipe from the outside of the pipe. Not only can the suction resistance be reduced, but also the heat transfer efficiency can be improved, thereby improving the smoke concentration of the first port.

The invention relates to the technical field of high polymer materials, and particularly discloses a B1-grade low-smoke halogen-free flame-retardant polyethylene cable material and an extrusion molding process thereof. The invention discloses a B1-grade low-smoke halogen-free flame-retardant polyethylene cable material. The cable material is prepared from the following raw material components in parts by weight: 50 to 70 parts of linear low-density polyethylene, 50 to 70 parts of ethylene-vinyl acetate copolymer, 40 to 60 parts of nanoscale magnesium hydroxide, 5 to 8 parts of microencapsulated red phosphorus, 10 to 15 parts of intumescent flame retardant, 3 to 5 parts of zinc borate and 2 to 4 parts of carbon nanotubes. According to the cable material, the ethylene-vinyl acetate copolymer can improve the dispersing performance of the inorganic filler, the composite flame retardant composed of the nanoscale magnesium hydroxide, the microencapsulated red phosphorus and the intumescent flame retardant is utilized, and the synergistic effect of the zinc borate and the carbon nanotubes is matched, so that the obtained cable material has better flame retardance, and the release of smoke is less.

The invention relates to the technical field of energy storage fire fighting, and discloses an energy storage three-level fire fighting response system and method based on temperature and smoke linkage, and the energy storage three-level fire fighting response method based on temperature and smoke linkage comprises the steps: collecting the operation data of an energy storage system in real time, respectively establishing and updating corresponding gas concentration base lines, temperature base lines and smoke base lines for different operation conditions; calculating a threatened gas index, temperature trend energy and a smoke abnormity index, and calculating a gas information modulation factor; calculating a comprehensive risk amount; performing three-level response judgment and executing an action; the risk attenuation rate is calculated, and self-correction is carried out; according to the method, continuous coverage of thermal runaway of the energy storage system from an early symptom to emergency disposal is realized through linkage fusion of temperature, smoke and threatened gas, risks can be identified in advance in a window period in which traditional temperature and smoke information is not obvious, a unified comprehensive risk quantity is taken as a judgment basis, missing report and false report of a single sensing quantity threshold value are reduced, and the safety of thermal runaway of the energy storage system is improved. And the timeliness and consistency of early warning are improved.

The invention relates to the technical field of fire detection, in particular to a smog alarm method based on a smog particle motion trail, which comprises the following steps: constructing a three-dimensional flow field distribution diagram of smog particles, and aiming at the sectional area change and curvature change of a current channel at a branch path, taking the predicted smog particle position as a center to obtain a smog particle motion trail distribution diagram; associating the flow velocity data of each branch path to obtain a flow velocity gradient sequence of each branch path; on the basis of the flow velocity gradient sequence of each branch path, when the flow velocity gradient exceeds a flow velocity threshold value, the smoke particle position in each branch path is updated; performing trajectory fitting on the smoke particles, and configuring concentration intensity indexes and updating time of the smoke particles in different branch paths according to concentration gradients corresponding to the motion trajectory sequences on the branch paths; and configuring a classification label of each branch path, and carrying out graded early warning according to flow velocity differentiation. And the accuracy and timeliness of smoke alarm are improved.

The present application belongs to the field of smelting coal gas recovery, and particularly relates to an optimized control method and system for combustible gas recovery. The method divides the smelting process into N measurement time periods, and calculates the average secondary combustion coefficient of each time period in real time. Meanwhile, M target smelting time zones and their weights are set, and a dynamic target value sequence is established. Based on the initial fan speed, the measured coefficient is adjusted through multiple iterations of the furnace, and when the measured coefficient is greater than the target value, the speed is reduced in steps, and a thermal imager and a differential pressure instrument are introduced to monitor the smoke emission. A smoke emission rate statistics and tolerance threshold judgment mechanism is established to trigger speed backtracking adjustment, and finally the average secondary combustion coefficient of each time period is minimized to generate an optimal fan speed model. The present application maximizes the improvement of the calorific value of coal gas and the recovery of carbon monoxide under the premise of preventing smoke from the furnace mouth.

The invention discloses an intelligent tunnel fire identification method and system based on multi-modal sensor fusion, particularly relates to the field of tunnel safety monitoring, and is used for solving the problems of fire detection delay, inaccurate positioning and low response efficiency in an ultra-long tunnel. Fusing and compressing into a global identification quantity delineated abnormal region; then, activating the monorail suspension device by taking the suspected area as a target, and generating a local recognition quantity by a second sensor; forming a corrected recognition set through time-space alignment and deviation correction; on the basis, a fire source positioning result set is extracted, temperature deviation intensity and a smoke propagation rate coefficient are analyzed through machine learning, and a fire development potential index is calculated; and finally, writing back a result to correct a trigger parameter and a travel path, and supporting subsequent fire reuse. The recognition precision is improved, the response time is shortened, and casualty and loss risks are reduced.

The invention discloses an aerosol generating product which comprises an aerosol generating matrix section, the aerosol generating matrix section comprises an aerosol generating capsule, the aerosol generating capsule comprises a core material, and the core material is paste, colloid or a solid-liquid mixture. The aerosol generating product is simple in structure, uniform, sufficient and continuous smoke release can be obtained at a lower heating temperature, and the smoking feeling is improved.

The invention discloses a fire-fighting detection early warning system, and relates to the technical field of fire-fighting early warning, and the system comprises a multi-source data obtaining module which comprises a gas monitoring unit, a smoke monitoring unit and a temperature obtaining unit, obtains the concentration of combustible gas, the granularity of smoke and the temperature data, carries out the preprocessing of the data, and integrates the data into a data set; the analysis and early warning module analyzes the data based on the data set, introduces a gradient compensation algorithm into the temperature acquisition unit, synchronously records the ambient temperatures of three different distances around, calculates a temperature gradient value, judges whether the temperature data exceeds the standard or not based on the gradient value, preliminarily obtains a judgment result from the temperature direction, and sends the judgment result to the early warning unit; and performing trend prediction on the multi-source data based on a time sequence analysis method. According to the method, the gradient compensation algorithm is introduced, the gradient value is calculated by using the three temperature monitoring points at different distances, local temperature anomaly can be accurately captured, the danger diffusion trend can be recognized earlier, local fluctuation and system risks can be distinguished, and time is won for early intervention.

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 invention relates to a smoke identification and classification early warning method, which comprises the following steps: carrying an infrared camera, an infrared spectrum sensor and a temperature and humidity sensor on an unmanned aerial vehicle, and carrying out a smoke inspection activity on a set target area; the method comprises the following steps: acquiring an infrared visual image, infrared spectrum data and environmental parameters of a target area by using an unmanned aerial vehicle, and preprocessing the acquired data; the infrared spectrum data comprises the concentration of CO2 and the concentration of CO, and the environmental parameters comprise the temperature, the humidity and the wind speed; multi-modal data fusion is carried out on the preprocessed data to construct a fusion feature vector, and a trained deep learning classification model is used to identify the smoke type according to the fusion feature vector; and determining an early warning level according to the identified smoke type, and dynamically realizing early warning triggering based on the early warning level and a set grading response rule. According to the method, accurate distinguishing and early warning decision making can be carried out on smoke in the urban comprehensive treatment complex environment.

The invention provides an intelligent electric energy metering box capable of being remotely regulated and controlled, and relates to the technical field of electric energy metering, the intelligent electric energy metering box comprises an embedded assembly, a box body and a fence mechanism, a mounting cavity is formed in the embedded assembly, the box body is embedded in the mounting cavity, the side edge of the box body is attached to the inner wall of the mounting cavity, the embedded assembly is used for being embedded in a wall, and the fence mechanism is arranged in the box body. The front end of the embedded assembly is provided with a fence mechanism, the fence mechanism is connected with the top area of the embedded assembly, and the fence mechanism is used for shielding and covering the front end area of the box body. When overheating or even open fire occurs in the box body, the inner box body can be remotely controlled to move, an approximately closed structure is formed in the inner side space, and the box body can be prevented from being damaged. And finally, oxygen input is blocked through the sealing effect, the fire extinguishing purpose is achieved, the protection effect can be provided for the internal smoke sensor in the process, meanwhile, external rainwater and dust can be prevented from entering the box body, and the protection effect on internal power equipment is enhanced.