56 results about "Flame" patented technology

The invention discloses an explosion-proof and intrinsic safety type combined feeder switch state monitoring method based on big data, and relates to the technical field of industrial electrical equipment state monitoring and fault diagnosis, and the method is realized based on a three-level architecture constructed by an edge computing node, a region computing node and a cloud platform. Comprising the following steps: S1, collecting multi-source sensing data of a feeder switch in real time by an edge computing node, and performing feature extraction and fusion calculation on the multi-source sensing data; according to the method for monitoring the state of the explosion-proof and intrinsic safety type combined feeder switch based on the big data, the contradiction between the real-time performance and the accuracy in multi-source heterogeneous data fusion processing is effectively solved, abnormity can be found in the first time, early warning can be triggered, and the reliability of a diagnosis conclusion is improved; and the accuracy and foresight of fault diagnosis are ensured. According to the grading processing mechanism, computing resources are reasonably distributed, the network transmission load is greatly reduced, and the system can stably operate in a complex industrial environment.

The invention discloses a lightweight class attention mechanism fused improved YOLOv7 flame detection method and system. The method comprises the following steps: acquiring flame and non-flame images, preprocessing the flame and non-flame images, constructing a flame detection data set based on the preprocessed flame and non-flame images, and labeling and dividing the flame detection data set; the original YOLOv7 network model is optimized, and an improved YOLOv7 network model is obtained; training the improved YOLOv7 network model by using the training set, and adjusting model hyper-parameters by using the verification set in the training process to obtain a flame detection model; evaluating the performance of the flame detection model by using the test set; and deploying the flame detection model in a monitoring camera of the power distribution station, and carrying out real-time monitoring and alarming on flames in the power distribution station by using the model. The technical problem that in the prior art, light weight and detection precision of a model are mutually balanced, and actual application requirements are not easy to meet can be solved.

A flame stability discrimination method based on a variational auto-encoder comprises the following steps: acquiring a real-time flame image, and preprocessing the flame image; based on the preprocessed flame image, geometric parameters and physical parameters of the flame are extracted; performing data fusion processing on the flame parameters, and calculating frequency parameters of flame flicker; preliminarily sorting flame stable and unstable sample databases; importing a flame stable and unstable sample database into a variational automatic encoder, realizing data dimension reduction and classification effects, and outputting potential probability distribution; and establishing a category center distance index, namely a flame stability index, by using a Gaussian hybrid clustering model based on the potential probability distribution so as to monitor a stable state and an unstable state of the flame, and carrying out real-time adjustment on combustion in the unstable state. The flame stability is accurately represented according to the flame image, the flame image area can be tracked and displayed when combustion is unstable, and the real-time performance, accuracy and reliability of flame monitoring are effectively improved.

The invention relates to the technical field of computer rendering, and discloses a dynamic effect processing method and device, electronic equipment and a program product, and the dynamic effect processing method provided by the invention simulates a flame effect in a virtual scene through combustion bitmaps of multiple cycles, and avoids uncertainty of a diffusion range caused by simulation of flame diffusion through particles. Meanwhile, as the combustion bitmap is used for simulating diffusion, flame diffusion simulation can be carried out without calculating the track and the drop point of each particle through a CPU, and the CPU pressure caused by the fact that a large number of particles in a particle system need to be simulated in the related technology is solved. In the rendering process, a map does not need to be added for each particle, the corresponding position in the virtual scene is directly rendered according to the combustion bitmap, the rendering process and the simulated flame diffusion process are separated, the occurrence of a large number of particles is reduced, and the load of the GPU can be reduced.

The utility model discloses a mining flame-proof and intrinsic safety type intelligent controller, which comprises an intelligent controller body, the intelligent controller body comprises a flame-proof cavity and an intrinsic safety cavity, the flame-proof cavity comprises a horn mouth, a switching power supply, an intrinsic safety power supply, an industrial personal computer and an isolation plate, the intrinsic safety power supply is connected with the isolation plate, and the intrinsic safety power supply is connected with the industrial personal computer. The switching power supply is connected with the horn mouth, the industrial personal computer and the intrinsic safety power supply; the intrinsic safety cavity comprises a display screen, a key board, a wireless receiver and an information acquisition board, and the key board, the display screen and the wireless receiver are all connected with the information acquisition board. According to the utility model, through the arrangement of a series of elements, all signals of the intelligent controller body are processed in the explosion-proof cavity and then are output to the intrinsic safety cavity through the through-wall terminal, so that the effect of multi-signal isolation output is realized, the signal transmission stability of the intelligent controller body is very reliable, the operation is convenient and fast, and the cost is low. And an extra explosion-proof carrier is not needed, so that the use cost is reduced.

The application discloses a gas water heater and a control method thereof, which comprises the following steps: S1, obtaining an ignition command; S2, detecting and storing a flame current initial value I0; S3, discharging and igniting an igniter, opening a gas valve, detecting a flame current value I1 in real time, and obtaining a difference value AI=I1-I0; S4, judging whether the opening time AT is less than a first set time Tset1, if yes, executing step S5, and executing step S6; S5, judging whether the difference value AI is greater than a first current set value Iset1, if yes, outputting a flame signal, judging whether the difference value AI is less than a second current set value Iset2, if yes, outputting no flame signal; S6, judging whether the difference value AI is greater than a third current set value Iset3, if yes, outputting the flame signal, judging whether the difference value AI is less than a fourth current set value Iset4, if yes, outputting no flame signal; wherein, Iset1=Iset2+I 回差1 , Iset3=Iset4+I 回差2 ; Iset3 is greater than Iset1; and Iset4 is greater than Iset2. The application can adapt to the change of environment to judge the presence or absence of the flame signal.

The embodiments of the present application disclose a method, device, electronic device, and storage medium for searching for stuck functions; the method comprises: obtaining each function included in a stuck flame graph, and the cumulative sampling times of each function in the stuck flame graph; obtaining a normal flame graph at a historical moment; for each function included in the stuck flame graph, comparing the cumulative sampling times of the function included in the stuck flame graph with the cumulative sampling times of the same function in the normal flame graph to obtain a comparison result; based on the comparison result, screening out preliminary screening functions from all functions included in the stuck flame graph; and selecting K stuck functions from the preliminary screening functions based on the type and type priority of the function. The method can first screen out preliminary screening functions from the stuck flame graph; and then select K stuck functions from the preliminary screening functions based on the type and type priority of the function, thereby improving the problem of high cost in flame graph screening and analysis in the prior art.

The invention relates to the technical field of art burning, and discloses an art burning control method and system, a storage medium and electronic equipment, and the method comprises the steps: responding to a target time sequence formula selected by a user, and according to the start-stop time sequence and the working time length of each type of target art burning device contained in the target time sequence formula, controlling the target art burning device according to the start-stop time sequence and the working time length of each type of target art burning device; each type of target art burning device is controlled to carry out ignition or flameout operation; inputting current meteorological parameters collected in real time into the optimized RBF neural network to obtain predicted PID control parameters; and based on the predicted PID control parameters, adjusting the opening degree of an electric adjusting valve of each type of target art burning device so as to enable the flame height and the burning posture to adapt to environmental changes. The problems of manual control, fixed time sequence and difficulty in dynamic adjustment of existing art fire can be solved, dynamic adjustment of the time sequence of art fire and self-adaption of flame to environment change are realized, and the flexibility and effect of art fire control are improved.

The invention provides a flame detection method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a data sequence of operation parameters of a gas turbine based on a set sliding window in response to a received flame detection instruction; for the data sequence of any operation parameter, acquiring a change rate sequence and a change rate threshold value corresponding to the data sequence, and determining a flame state sequence based on the change rate sequence and the change rate threshold value; and performing flame detection on the gas turbine based on the flame state sequence corresponding to the data sequence of each operation parameter. A data sequence is dynamically intercepted through a sliding window, and the running state of the gas turbine can be tracked in real time; in combination with change rate analysis and threshold judgment, parameter fluctuation characteristics can be accurately extracted, and the sensitivity and noise immunity of flame state recognition are improved; flame detection is carried out comprehensively through multiple operation parameters, the false alarm rate can be reduced, and safe and efficient operation of the gas turbine is guaranteed.

The utility model discloses a storage type flame-retardant data line, which comprises an upper storage shell and a lower storage shell which are fixed with each other, the left and right sides of the upper storage shell and the lower storage shell are respectively provided with a line outlet groove, the upper storage shell and the lower storage shell are respectively provided with a flame-retardant cavity, a line placing part is arranged between the upper storage shell and the lower storage shell, and the line placing part is provided with a wire outlet groove. A line placing part is arranged on the upper storage shell, a data line is wound on the line placing part, a rotating mechanism capable of driving the line placing part to rotate is arranged in the flame-retardant cavity, a locking mechanism capable of locking and unlocking the line placing part is arranged in the flame-retardant cavity, and the outer skin of the upper storage shell, the outer skin of the lower storage shell and the outer skin of the data line are all made of TPE materials. A user can conveniently pull out the data line and automatically recycle the data line, and the flame retardant effect of the data line can be enhanced.

The present application belongs to the technical field of digital computing or data processing equipment or method specially applied to specific application, discloses a method for analyzing the jet flow of a flame gun, establishes a mathematical model and a discrete method for the jet flow of the flame gun, and performs jet flow analysis based on the model; the calculation domain of the jet flow of the flame gun comprises a nozzle part and a jet flow part, the width of the calculation domain below the nozzle of the flame gun is set to 1.5 m, and the width above the nozzle is set to 0.5 m; in the boundary conditions of the calculation domain, the nozzle inlet is set as a velocity inlet, the nozzle pipe boundary is set as a wall surface, the ground is also set as a wall surface, and other boundaries are set as pressure outlets; the Reynolds average method is adopted to model the turbulent flow; the k-ε model is adopted to construct a turbulent flow model, and a two-layer wall surface model is introduced; the VOF model is adopted as a multiphase flow model; and the finite volume method is adopted to disperse the control equations. The present application solves the problem that the jet flow of the flame gun can be conveniently analyzed by constructing a jet flow model of the flame gun.

This application relates to the field of security monitoring technology, specifically to a method and system for alarming upon flame extinguishing. The method includes: collecting flame status information within a monitored area; determining whether the flame is extinguished based on the flame status information; if it is extinguished, accumulating the duration of flame extinguishing; and triggering an alarm operation and the linkage control operation of field equipment when the accumulated duration of extinguishing meets a preset trigger condition. This application mainly addresses the technical problems existing in current flame status monitoring technologies, such as high reliance on manual intervention, low flame identification accuracy, lack of a flame extinguishing duration accumulation mechanism, poor alarm strategy adaptability, delayed equipment linkage response, and insufficient reliability.

The utility model discloses a multi-shielding flame-retardant computer cable which comprises an outer sheath, a first flame-retardant layer, a first shielding layer, a second flame-retardant layer, a second shielding layer, a wrapping layer and a filling layer which are sequentially arranged from outside to inside, a drainage wire is arranged in the second flame-retardant layer, and a plurality of cable cores are arranged in the filling layer. The cable core comprises an inner sheath and a third shielding layer located in the inner sheath, two twisted wire cores are arranged in the third shielding layer, and each wire core sequentially comprises an insulating layer, a fireproof layer and a conductor from outside to inside. The computer cable is provided with the fireproof layer and a multi-layer flame-retardant layer structure, and the flame-retardant and fireproof performance of the cable is remarkably improved, so that in the case of a fire, the further spreading of the fire behavior can be delayed, and the integrity of the cable structure and the stable transmission of signals can be maintained. And a plurality of shielding layers are arranged, so that the influence of external electromagnetic interference on internal signals of the cable is effectively prevented, and the transmission quality and stability of the signals are improved.

The utility model discloses a high flame-retardant fireproof computer cable, which comprises a cable core and an outer sheath wrapped on the outer layer of the cable core, the cable core comprises a plurality of wire cores, and the structure of each wire core comprises a conductor, a first wrapping tape, a sub-shielding layer, a second wrapping tape, a fireproof layer, an insulating layer and a tensile unit. The cable is reasonable in structural design, and has the following beneficial effects: the tensile unit is arranged between the sub-shielding layer and the second wrapping tape, so that the capability of resisting external force of the cable is improved, and the service life of the cable is prolonged; and meanwhile, the fireproof layer and the outer sheath are arranged in the cable for resisting fire, so that the fireproof performance of the cable is improved, and the cable can normally operate for more than 1.5 hours under the flame condition of 950-1000 DEG C.

The invention discloses a fire mode recognition system based on big data, and relates to the technical field of big data. A distributed deployment urban flame monitoring sensor network and a target area are set through a data acquisition module, and environment parameter data and flame image data corresponding to the target area are acquired; processing the environment parameter data through a physical parameter processing unit to obtain flame image data corresponding to the target area, and sending the flame image data to the flame image data; processing the flame image data in real time to obtain flame identification data in real time; setting a flame state database based on big data, and performing real-time identification on flame identification data according to the flame state database to obtain a flame evaluation model; evaluating a flame trend in real time according to the flame evaluation model, and further obtaining a flame grade; generating a grade alarm signal according to the flame grade; processing the grade alarm signal and generating an alarm signal to be checked; and the management module receives and processes the to-be-checked alarm signal.

The present invention discloses a method for automatically controlling a boiler burnout chamber fire, comprising the steps of: S1, obtaining a flame image of the boiler burnout chamber and transmitting it to a computer; S2, the computer analyzing and edge processing the obtained flame image; S3, calculating the ratio of flame pixels in the burnout chamber image to the total pixels in the image; and S4, transmitting a pixel digital quantity signal to a PLC controller, comparing the percentage of flame pixels to image pixels with a fire setting value of a host computer, and determining whether the burnout chamber has fire or not. The method of the present invention does not require manual operation, is simple and convenient to use, has high practical value, avoids coal waste, saves coal, and transmits the image to the computer for easy observation by the boiler operator, reducing the boiler operator's back-and-forth work and improving work efficiency.

A flame detection system is disclosed. The flame detection system includes at least one monitoring device including at least one primary flame detector configured to detect one or more infrared (IR) signals from a monitoring zone, and at least one secondary flame detector configured to detect one or more IR signals from a flame zone. Further, the one or more processors are communicatively coupled to the at least one monitoring device. The one or more processors are configured to receive the detected one or more IR signals from the monitoring zone and the flame zone; correlating the one or more IR signals from the monitoring zone with the one or more IR signals from the flame zone based at least on the time domain and the frequency domain of the detected one or more IR signals, and determining a flame condition within the monitoring zone based at least on the correlation.

The invention relates to a flame early warning method, computer equipment and a storage medium. According to the invention, the deep learning model comprising the forward prediction model and the backward prediction model is set, the trained deep learning model is used to output the prediction image, and the prediction image is compared with the real image, so that the real image is judged to deviate from the development direction of a normal flameless condition when the prediction image and the real image have deviation. Therefore, the occurrence of the flame is judged when the real image deviates from the development direction of the normal flame-free condition, early warning can be carried out before the occurrence of the flame is detected in time in the production process of the energy storage equipment, the occurrence rate of the flame is reduced, and the safety is improved.

Embodiments of the present application provide a flame detection method, apparatus, electronic device, and computer-readable storage medium. In this embodiment, the first flame band data and second flame band data required for flame detection are not obtained in a fixed gain mode, but rather are obtained through a dynamically adjusted gain mode. Compared to directly using flame band data in a fixed gain mode for flame detection, this method of using flame band data in a dynamically adjusted gain mode for flame detection avoids the problems of missing detection of close-range flames due to excessive gain amplitude in a fixed gain mode, and failing to identify distant flames due to excessive gain amplitude in a fixed gain mode. This allows flame detection using the method of this embodiment to take into account both close-range and long-range flame detection, effectively reducing the probability of missed detection, and thus improving the accuracy of flame detection.

This invention relates to the field of flame arresters, and discloses a flame arrester monitoring device and method. The monitoring device includes: a detection unit for detecting a blockage signal from the flame arrester; a processing unit for storing a pre-established relationship model between the blockage signal and the degree of blockage, and using the relationship model to calculate the degree of blockage of the flame arrester based on the blockage signal detected by the detection unit; and a display unit for displaying a signal indicating the degree of blockage of the flame arrester. The technical solution provided by this invention can improve the accuracy of monitoring the degree of blockage of flame arresters and enhance the operational safety of flame arresters and gas pipelines.

Flame mitigation devices meeting all applicable regulatory requirements are described. The system includes a mesh element affixed to a closure fitment that is specially designed to couple to a rounded bead or edges on a container neck. Tamper-evident and child resistant features can be incorporated at the interfaces of the closure fitment and a cap that is removably attachable to the closure, whereas the closure is effectively coupled to the container in a permanent a manner

To provide a system.SOLUTION: A social media management tool system includes: means for using a generative AI to automatically detect a slanderous comment on social media and process the same so as to be invisible from a person in question; means for reducing mental damage and time and effort for a manual check; means for automatically recording information on an aggressive user to assist with a legal action and evidence preservation; and means for incorporating a content correction function to avoid flame war.SELECTED DRAWING: Figure 1

The present application discloses a safety warning method for hot work and related products, which includes: obtaining target basic data; arranging m control balls in a target operation area according to the target basic data and a preset arrangement method; collecting target monitoring data of the target operation area; analyzing the target monitoring video to determine the start time of the flame in the flame area; intercepting multiple video frames of the flame area in the target monitoring video; inputting the multiple video frames into a target hot work recognition model to obtain at least one recognition result and at least one confidence level; when the target recognition result includes the presence of hot work, determining a first risk probability based on the flame area and the target confidence level; determining a second risk probability corresponding to the flame area based on the target sensor data; and controlling an alarm module to execute a target alarm operation when the first risk probability and the second risk probability meet preset conditions. The embodiments of the present application improve the safety of hot work.

This invention discloses a method, apparatus, device, and storage medium for determining exception stacks. The method includes: determining a flame graph corresponding to a preset task based on the stack of preset thread calls required to execute a preset task; constructing a task tree corresponding to the preset task based on the flame graph; determining an initial stack set based on the stacks corresponding to leaf nodes in the task tree and the stacks corresponding to non-leaf nodes whose stack time is greater than the average time; determining a target stack set based on the initial stack set; identifying the stack type of each target stack contained in the target stack set; and determining the exception stack in the target stack set based on the stack type of each target stack contained in the target stack set. This technical solution considers both non-business stack exceptions and business stack exceptions, enabling staff to promptly optimize the exception code corresponding to the exception stack when they learn that the exception stack is a business stack to resolve application exception issues and improve user experience.

The invention discloses a method, device and equipment for identifying flame, a readable medium and a program product, and belongs to the technical field of computers. The method for identifying the flame comprises the following steps: acquiring a target image frame; in response to determining that the target image is detected in the target image frame, determining a target bounding box with the target image from the target image frame; determining a target trajectory corresponding to the target bounding box; and determining a flame identification result of the target trajectory according to the position information and the time sequence information of the bounding box in the target trajectory. According to the invention, the problem of false detection in flame detection is reduced, and high-precision and high-accuracy flame detection in a monitoring scene is realized.

The utility model relates to the technical field of monitoring substations, in particular to a mining flame-proof and intrinsic safety type monitoring substation, which comprises a shell which is divided into a main intrinsic safety cavity and an uninterruptible power supply cavity by a partition plate. A network management machine with multiple data interfaces, a high-definition display screen in signal transmission with the network management machine, a digital signal acquisition unit, a looped network switch and an analog signal acquisition unit are fixedly arranged in the main intrinsic safety cavity; a transparent observation window is embedded in the shell and located above the high-definition display screen. The system has the advantages of long power supply time after power failure, strong anti-interference capability and good signal transmission effect, is internally provided with a database storage conversion system, is high in integration level and strong in universality, and simultaneously displays intuitively acquired information data.

Embodiments utilize captured data, such as gas data and / or flame / heat data, from sensors in an environment to generate a data-constructed image for use in predicting explosion likelihood within an environment. Some embodiments utilize gas and flame data to generate the data-constructed image that is processable via one or more model(s) to determine whether the environment includes one or more sub-regions at risk of explosion. Some embodiments receive a plurality of gas sensor data and a plurality of flame sensor data, generate a data-constructed image including a plurality of channels based at least in part on such data, and generate explosion prediction data by applying at least a portion of the data-constructed image to a prediction model.

The application discloses a flame detection method and system in a multi-source scene, first constructs a flame data set in a multi-source scene; secondly, a jump connection is designed to improve a pyramid feature dynamic extraction module in a PS-Net (progressive selection network), so that the detection capability of the model for small flame targets is improved; then, a flame feature attention mechanism is designed to improve a scale perception fusion module in the PS-Net, so that the inhibition capability of the model for similar shape feature interference is strengthened; subsequently, a decoder structure is designed to reduce the influence of similar color feature interference on the detection result; finally, a PS-Net+ model after training and testing is used for flame detection. The flame detection method in the multi-source scene of the application is helpful to realize high-precision detection of flame targets in a multi-source scene, and provides technical support for quickly and accurately finding flame targets in reality and timely solving safety hazards caused by the flame.

The invention relates to the technical field of visual monitoring, in particular to a lightweight flame detection method and system based on improved YOLOv11n, and the method comprises the steps: collecting and preprocessing a field flame image, constructing a flame detection data set based on the preprocessed flame image, and marking and dividing the flame detection data set; the original YOLOv11n network model is optimized, and an improved YOLOv11n network model is obtained; constructing an InerGIoU loss function, and replacing a CIoU loss function of the original YOLOv11n network model; training the improved YOLOv11n network model by using the training set, and adjusting model hyper-parameters by using the verification set in the training process to obtain a flame detection model; evaluating the performance of the flame detection model by using the test set; deploying the flame detection model to a land unmanned equipment system to realize all-weather monitoring of a field fire source; according to the method, the lightweight level of the YOLOv11n network model and the field flame detection precision are improved, and the actual application requirements of edge equipment are more easily met.