518 results about "Flame detection" patented technology

The invention discloses a forest fire hidden danger identification method and device for a power transmission line based on a multi-modal large model, and the method comprises the steps: constructing a forest fire hidden danger identification model for a smog or flame-containing image outputted by a conventional target detection model, and enabling the model to guide a dialogue set through the combination with forest fire hidden danger identification, thereby achieving the recognition of the forest fire hidden danger. The dialogue context and the image visual features are fused, so that the deep fusion of the text semantics and the firework image features is realized; and finally, inputting the deeply fused features into a large language model, so that a forest fire hidden danger output dialogue of the power transmission line can be obtained by utilizing the deep semantic understanding capability of the large language model, and then a forest fire hidden danger recognition result of the power transmission line is obtained. Therefore, according to the invention, the judgment of whether the smoke and fire can damage the power transmission line is realized, the technology upgrade from smoke and fire existence detection to equipment threat research and judgment is completed, and on the basis, the problems of resource waste and untimely crisis response caused by reporting all smoke and fire information in the traditional technology can be avoided.

The invention discloses a virtual fire extinguishing training system and method based on deep learning flame recognition. The virtual fire extinguishing training system comprises a flame image acquisition module, a deep learning flame recognition module, a fire scene generation module, a fire extinguishing equipment simulation module and a scene customization module. And the flame image acquisition module is used for acquiring flame images and video data in different environments in real time through a high-definition camera, an infrared thermal imager, a panoramic camera and a sensor network. According to the invention, feature extraction and model training are carried out on mass flame images by using a deep learning flame recognition algorithm, accurate recognition of multi-dimensional information such as flame form, color, dynamic features and the like is realized, the flame detection capability in a complex environment is remarkably improved, and meanwhile, the system combines a physical engine and a scene generation module, so that the system is more accurate and reliable. The three-dimensional fire scene can be dynamically generated according to the real-time recognition result, the effects of fire spreading, smoke diffusion and the like are achieved, the constraint of a preset scene is eliminated, and training is more flexible and authentic.

The invention provides a combustible gas leakage protection system, which is characterized in that a control module of the combustible gas leakage protection system judges whether the concentration of combustible gas is lower than a first concentration threshold value or not when receiving concentration information detected by a concentration detection module, and generates a first control instruction when the concentration of the combustible gas is not lower than the first concentration threshold value. The control module further generates a second control instruction when the combustible gas concentration is not lower than a second concentration threshold value and the flame detection module detects that no open fire exists, and generates a third control instruction when the combustible gas concentration is not lower than the second concentration threshold value and the open fire exists. And the protection module executes different protection actions according to different control instructions of the control module. According to the application, the response scheme is divided into three grades, and corresponding protection strategies are implemented according to the detection signals of different grades, so that the response sensitivity and accuracy when the combustible gas leaks can be remarkably improved.

The invention discloses a forest fire fighting robot path planning method and system based on ground-air cooperation, and the method comprises the steps: carrying out the air scanning of a disaster area through employing an unmanned plane to carry a laser radar and infrared and visible light cameras, and obtaining the space information and fire intensity of a fire point in real time; the unmanned aerial vehicle is in communication connection with the wind power fire extinguishing robot, shares the three-dimensional point cloud model and performs environment proofreading and positioning; an improved A * algorithm is used for path planning, and a path planning mathematical model with the minimum disaster degree as the target is constructed; through fusion of a global satellite navigation system and an inertial navigation system, the working path of the wind power fire extinguishing robot is dynamically updated and planned; after a target fire point is reached, the wind power fire extinguishing robot identifies a fire source, calculates a safe fire extinguishing distance by using a flame detection model result, and dynamically adjusts an air duct angle according to a flame state to perform fire extinguishing operation. Through cooperative work between the unmanned aerial vehicle and the fire extinguishing robot, the efficiency and the intelligent degree of fire extinguishing operation are improved.

The invention discloses a gas-phase combustion model construction method based on a dynamic self-adaptive grid, which comprises the following steps: establishing a steady-state flame control equation set according to the property of target fuel, and obtaining laminar flame velocities and laminar flame thicknesses under different conditions; establishing an unsteady-state reactive Navier-Stokes equation set, performing spatial filtering on each variable in the equation set, and constructing a sub-lattice scale turbulence model; coupling a thickened flame model and a disturbance factor model in the filtered equation set; limiting the encrypted area of the self-adaptive grid near a flame surface through a flame detection function; and solving the equation set to obtain a variable of a next time step, updating a disturbance factor and the number of layers of the adaptive grid, and re-dividing the adaptive grid of the layered block structure to realize dynamic tracking of the flame position and real-time adjustment of the grid resolution. According to the method, the disturbance factor and the grid encryption layer number can be adjusted in real time based on the laminar flame speed and the flame thickness in the current state, and the combustion modeling precision and the calculation efficiency are improved.

The invention relates to the technical field of dust combustion, and provides a dust explosion combustion experiment device in order to solve the problems that an existing dust explosion combustion experiment device is insufficient in parameter control precision, and an experiment multi-focus single variable lacks a dust removing mechanism and a safety protection measure, and the dust explosion combustion experiment device comprises an experiment table which is provided with a power chamber and an equipment chamber; one side of the experiment table is hinged with an access door, two sides of the top of the experiment table are provided with conveying main pipes extending to the equipment chamber, a power supply assembly is arranged in the electric power chamber; the protective shell assembly comprises an outer shell and an inner shell; a plurality of exhaust pipes are arranged at the top of the inner shell; the dust generation assembly comprises a plurality of dust storage tanks and an air compressor; the ignition control assembly comprises a pulse igniter, a flame detection feedback circuit and an ignition head; the environment adjusting assembly comprises a box body, an oxygen tank and a humidifier, wherein the oxygen tank and the humidifier are arranged in the box body. The device has the advantages that the dust concentration is accurately regulated and controlled, the environmental parameters are dynamically coupled and controlled, dust residues are rapidly removed, and the experiment safety is high.

The invention discloses a safety and disinfection integrated system based on AI analysis linkage control electromagnetic valves, and relates to the technical field of intelligent fire fighting, and the safety and disinfection integrated system comprises a flame detection camera, a network input and output module, a safety and disinfection integrated machine, an execution module and an acousto-optic alarm bell. According to the security and disinfection integrated system for linkage control of the electromagnetic valve based on AI analysis, the advanced AI visual recognition technology and an electromagnetic valve linkage control mechanism are deeply fused, the efficiency and the precision degree of fire safety management are greatly improved, flame characteristics are precisely recognized by means of a deep learning model, and the safety and disinfection effect is improved. The limitation that traditional fire behavior detection is easily influenced by environmental factors is broken through, the accuracy and reliability of fire behavior recognition are greatly enhanced, the system supports multi-modal data fusion, the confidence coefficient of fire behavior judgment is further improved, adjacent electromagnetic valves can be automatically started according to the position of a fire behavior in the linkage control link, an effective fire extinguishing isolation belt is constructed, and the fire extinguishing efficiency is improved. And fire spreading is effectively restrained.

The invention discloses an integrated pulverized coal burner. A burner head comprises a cooling water jacket, a cooling water partition plate, a fuel gas nozzle, an ignition oxygen nozzle and a pulverized coal nozzle. The burner body comprises a cooling water outer pipe, a cooling water partition pipe, a cooling water inner pipe, a pulverized coal sleeve, an ignition oxygen sleeve, a fuel gas sleeve, an ignition gun mounting pipe and a flame detection pipe; a fuel gas channel is formed between the ignition gun mounting pipe and the fuel gas sleeve, an ignition oxygen channel is formed between the fuel gas sleeve and the ignition oxygen sleeve, a pulverized coal channel is formed between the ignition oxygen sleeve and the pulverized coal sleeve, and a process oxygen channel is formed between the pulverized coal sleeve and the cooling water inner pipe. A cooling water outlet cavity is formed between the cooling water outer pipe and the cooling water partition pipe, and a cooling water inlet cavity is formed between the cooling water inner pipe and the cooling water partition pipe. Various key functions such as flame detection, an ignition gun, start-up fuel gas, start-up oxygen, process pulverized coal and process oxygen are integrated into single equipment, and the device has the advantages that the cost is saved, and the efficiency is improved.

The invention relates to the technical field of computer vision, and discloses a flame recognition and fire extinguishing system for indoor fire fighting, comprising: a binocular infrared imaging module for acquiring a thermal imaging image; the monocular visible light imaging module is used for acquiring a visible light image; the infrared stereoscopic vision module is used for carrying out processing and feature extraction on the thermal imaging images, carrying out feature aggregation to obtain an aggregated feature map, carrying out parallax optimization on the aggregated feature map, and carrying out calculation according to a parallax optimization result to obtain depth information of the thermal imaging images at different visual angles; the multi-mode stereoscopic vision fusion module is used for fusing the thermal imaging image with the depth information and the visible light image; the flame identification and fire behavior prediction module is used for performing flame detection according to the fused image, predicting a bounding box, confidence and a category label of the flame in the fused image, and predicting a future diffusion position of the flame, a diffusion scale of the flame and a diffusion trend of the flame; and the self-adaptive water gun spraying control module controls the water gun to execute spraying operation.

The invention relates to the technical field of image processing, in particular to a flame detection method based on a multi-modal fusion image, which comprises the following steps: acquiring a visible light near-infrared thermal infrared image and matching positions, extracting multi-channel difference to generate a feature set, combining adjacent blocks to judge a direction and a brightness trend, and identifying a temperature rise gathering area. And combining the three types of images to confirm flame characteristics and position a detection result. According to the invention, by collecting visible light, near-infrared and thermal infrared images, cross-modal accurate alignment is realized by using interpolation, and the fusion effect is optimized. The flame area is accurately extracted according to the pixel deviation characteristics, and false alarm and missing alarm are reduced. The positioning precision is improved by combining block boundary tracking and temperature change analysis, and a flame target is effectively recognized in a complex environment. The multi-mode complementation enhances the adaptability of the system, and ensures that the system has high stability and robustness in a dynamic interference environment.

The invention relates to a coal mine flame pseudo fire interference suppression method based on time sequence consistency analysis, and belongs to the technical field of coal mine safety monitoring. According to the method, aiming at the problem of high false alarm rate of a flame detection system caused by false fire source interference such as electric welding sparks and mechanical friction in a mine environment, the flame identification accuracy is improved through time sequence consistency analysis. According to the technical scheme, the method comprises the following steps: acquiring an infrared spectrum flame saliency probability graph of continuous image frames in an underground coal mine; extracting a flame candidate region by adopting Otsu adaptive threshold segmentation in combination with morphological optimization and hole filling; and performing time sequence consistency analysis on the continuous frame candidate regions, and calculating the spatial overlapping degree, the morphological stability and the infrared thermal intensity change trend of adjacent frames. According to the method, the false fire false alarm rate is remarkably reduced, the robustness to complex backgrounds and dynamic illumination is enhanced, the method can be independently integrated to an existing infrared flame detection system or used in cooperation with a deep learning model, and the reliability of mine fire monitoring is improved.

This invention discloses a method and system for detecting wall radiation information through flame penetration. The method determines the radiation wavelength range, and within this range, establishes a wall radiation intensity detection model and a flame radiation intensity detection model, showing the distribution of wall radiation intensity and flame radiation intensity with radiation wavelength. It also obtains the radiation wavelength λ when the wall radiation intensity equals the flame radiation intensity. eq The peak wavelength λ when the wall radiation intensity is at its maximum. max When the radiation wavelength λ eq Less than the peak wavelength λ max At that time, the wavelength for detecting wall radiation information is the peak wavelength λ. max When the radiation wavelength λ eq Greater than the peak wavelength λ max At that time, the wavelength for detecting wall radiation information is the radiation wavelength λ. eq The wall radiation information is detected according to the detection wavelength determined above. The present invention finds a suitable band range for wall radiation detection by accurately quantifying wall radiation and flame radiation, and can obtain wall radiation information by penetrating the flame.

The invention discloses an infrared and ultraviolet flame detector with multiple safety redundancy and an anti-explosion control method, and relates to the technical field of flame detection, and the anti-explosion control method comprises the steps: S1, obtaining the multi-source fire data of a target object through a signal obtaining module; s2, analyzing the multi-source fire data through a dynamic coupling adjustment module; s3, performing time domain association verification on the first monitoring data through a time domain continuity verification module, and generating second monitoring data; and S4, the grading execution module sends an alarm signal according to the second monitoring data and adopts grading execution processing. Through ultraviolet polarization degree and dielectric constant dual-threshold triggering, interference of the metal reflective layer is stripped, so that the smoldering detection rate of a covered scene is increased from less than or equal to 60% to more than or equal to 95%; and moreover, the smoldering authenticity is subjected to cross validation through the bidirectional verification module, so that the problem of missing report of a traditional flame detector caused by a covering effect of'reflective interference 'on'smoldering monitoring' is avoided.

The invention discloses an infrared flame detection method and system based on deep learning, and the method comprises the following steps: obtaining infrared flame image sets in different scenes, and marking the infrared flame image sets; performing Mosaic data enhancement on the marked infrared flame image set to obtain an enhanced image set; improving the YOLOv8 model, and training the improved model based on the enhanced image set to obtain a flame detection model; and detecting and positioning flame by using the flame detection model to obtain an ignition position. On the basis of improving the recognition accuracy and the feature extraction performance, the infrared flame image target can be rapidly and accurately detected and positioned, and finally, after the target flame is detected, the fire water monitor device is used for extinguishing the fire in the target area.

The invention discloses a liquid rocket engine combustion tail flame detection device and method, the device comprises an air inlet pipe, an exhaust pipe, a gas chamber packaging pipe and an intelligent controller, a plurality of detection devices such as a temperature sensor and a spectrum analyzer are arranged in the gas chamber packaging pipe along the airflow direction, and the detection devices are connected with the intelligent controller to form a data transmission channel; the detection method comprises the steps that the device is initialized, and all devices are calibrated and debugged; after the engine is started, tail flame parameters are detected in real time and transmitted to the intelligent controller; the controller performs preprocessing and deep analysis on the data; comparing an analysis result with a preset normal parameter range to judge the working state of the tail flame; and if normal, the data are backed up periodically, and the long-term trend of the performance of the tail flame can also be predicted. According to the method, the tail flame parameters can be comprehensively and accurately detected in real time, intelligent analysis and abnormal early warning are achieved, and the safety and reliability of an engine are improved.

The embodiment of the invention provides a flame detection method and device based on image recognition, electronic equipment and a medium, and relates to the technical field of computer vision. The method comprises the steps of obtaining a target video; performing video frame extraction on the target video to obtain at least two target video frames; according to the color feature of each target video frame and a preset target flame color rule, performing flame color region detection on each target video frame to obtain a flame color region; performing moving area detection on any two adjacent target video frames to obtain a moving area of each target video frame; wherein the adjacent target video frames are used for representing the adjacent video frames in the time sequence; and performing overlapped region screening on the flame color region and the moving region of each target video frame to obtain a target flame region. According to the embodiment of the invention, the accuracy and reliability of flame detection can be improved.

The utility model discloses an oxyhydrogen burner for SOEC, which comprises a cylindrical steam generating device, and the outer wall of the steam generating device is connected with a pure water inlet pipeline and a steam outlet pipeline; a cylinder is sleeved with the steam generating device, the bottom of the cylinder is close to the bottom of the steam generating device, the lowest end of the cylinder is connected with an outlet pipeline, and the outlet pipeline protrudes out of the lower end of the steam generating device. The outer wall of the cylinder body is connected with a flame detection opening; a hydrogen inlet pipeline and an oxygen inlet pipeline are inserted above the outer wall of the barrel; a flame holder, a catalytic grating and a premixing device are arranged in the barrel. Fuel and air can be evenly mixed, combustion is sufficient, and the heat utilization rate is increased.

A flame detection system is disclosed. The flame detection system includes: an image capture unit configured to capture an image of a field of view (FOV); a flame detector configured to capture a first set of spectral band data and a second set of spectral band data; and a processor configured to classify the one or more images and the first set of spectral band data, assign a weight to each of the second set of spectral band data, receive a flame count for each of the second set of spectral band data, determine a weighted count for each of the flame counts, and determine a weighted count for each of the flame counts. A number of weighted counts exceeding its respective threshold is determined, and a flame is determined to be present within the FOV when the number is greater than or equal to a number threshold, and a flame is determined to be absent within the FOV when the number is less than the number threshold.

The invention discloses a flame detection method based on a visual large model. The method comprises the following steps: extracting a multi-scale context semantic enhancement feature map through a feature extractor in combination with a context aggregation module; the fire source positioning accuracy is improved by fusing multi-scale information through cross-layer feature two-way convolution transmission by using a two-way feature interaction module; sensing geometric features of a fire source through a dynamic adaptive point representation module, and screening samples to suppress interference in combination with density clustering and spatial constraint; a multi-task loss function containing classification, regression (generalized IoU and center distance IoU loss), multi-scale supervision and spatial constraint is constructed, and a model is trained in combination with an AdamW optimizer and a dynamic attenuation learning rate strategy. According to the method, small-scale fire source features can be effectively captured, complex background false detection is reduced, the detection precision on multiple data sets is superior to that of a traditional method, and the method is suitable for real-time monitoring and fire early warning of scenes such as hydraulic power plants.

The invention discloses a dual-band flame detection method and system based on visible light and near-infrared images. The dual-band flame detection method comprises the following steps: collecting a dual-band flame image, carrying out joint calibration on a visible light camera and infrared imaging equipment, and obtaining internal and external parameters of the visible light camera and the infrared imaging equipment; performing horizontal alignment on the collected visible light image and the infrared image by using distortion correction and epipolar correction; marking the visible light image and the near-infrared image after horizontal alignment, and constructing a dual-band flame data set; constructing a dual-band flame detection model based on visible light and near-infrared images; and training a dual-band flame detection model by using the dual-band flame data set, and monitoring flame information in the scene in real time by the trained dual-band flame detection model. Compared with an existing flame detection model, the detection precision is higher, and the anti-interference capability is higher.

The invention belongs to the technical field of boiler maintenance, and particularly relates to a boiler four-pipe foreign matter blockage early warning method and system. The method comprises the steps of obtaining boiler four-tube foreign matter blockage historical data; collecting boiler four-tube real-time state data of a reheater, an induced draft fan and a flame detection cooling fan; a fault mode-influence-risk mapping relation is established by adopting FMEA based on historical data, and a risk assessment framework is formed; generating an initial risk level; training a machine learning algorithm model by adopting historical data and generating a blockage probability; and dynamically adjusting the initial risk level according to the blockage probability, generating a final risk level and outputting a corresponding maintenance strategy. The system comprises a data acquisition module, an equipment monitoring module, a risk division module, a risk assessment module, a jam prediction module and a decision module. According to the scheme, the FMEA and the machine learning algorithm are fused, early warning, accurate risk assessment and dynamic maintenance decision making of boiler foreign matter blockage are achieved, and boiler operation safety and maintenance efficiency are improved.

The invention belongs to the technical field of fire detection, and particularly relates to a YOLOv8-based lightweight flame detection method and system, and the method comprises the steps: obtaining a to-be-detected flame image; constructing a YOLOv8 backbone network on the basis of the alternately arranged convolutional layers and a Ghost Bottleneck Hybrid module with different synchronization lengths, and extracting multi-scale features of the obtained flame image on the basis of the constructed backbone network; a YOLOv8 neck network of a lightweight Slim-Neck architecture is adopted, and multi-scale features of the obtained flame images of different levels are fused; and according to the obtained fused flame image multi-scale features and the YOLOv8 head network, carrying out classified detection on flames in the flame image, and completing YOLOv8-based lightweight flame detection.

The invention relates to the technical field of fire detection and early warning, in particular to an intelligent ultraviolet flame detection and early warning system and method suitable for complex industrial scenes. Comprising distributed multispectral ultraviolet detection nodes and a central processing early warning unit. The nodes carry out signal acquisition and preliminary identification through a multispectral sensor, local processing and high-precision time synchronization; and the central unit fuses multi-node data, performs three-dimensional flame positioning by using a TDOA algorithm, performs machine learning recognition and false alarm elimination, and performs trajectory tracking by using a Kalman filter so as to realize graded early warning linkage. According to the intelligent ultraviolet flame detection and early warning system and method suitable for the complex industrial scene, the problems that in the prior art, the false alarm rate is high, flame positioning is not accurate, trajectory tracking is missing, cooperative monitoring is limited and the like are solved or at least relieved, false alarms are effectively reduced, and the positioning precision, the tracking capacity and the early warning reliability are improved.

According to the flame detection method, system and equipment and the storage medium provided by the invention, the situation and the position of the flame can be judged in advance by detecting the site through ultraviolet rays and judging whether the flame appears or not, the flame can be detected under the condition that the flame is not developed into a large scale, the flame position can be subjected to multiple detections, and the flame detection efficiency is improved. According to the method, a plurality of detection results are combined to judge whether flames are evolved into flames or not, each technology performs detection and mutual complementary verification on the fire from different angles, misjudgment and missed judgment possibly generated by a single technology are reduced, the accuracy and reliability of fire detection are greatly improved, the generation of flames is quickly responded, and the detection efficiency is improved. And a user can take corresponding measures on the flame more quickly. The flame is detected in multiple detection modes, the position, spectrum, temperature and other multi-dimensional features of the flame are comprehensively considered, the real situation of the flame is more comprehensively known, and misjudgment possibly caused by single feature judgment is avoided.

The invention discloses an RH refining furnace control method and related equipment, and relates to the technical field of steel smelting, the method comprises the following steps: obtaining in-furnace color image data of a target RH refining furnace; performing flame state recognition on the color image data in the furnace through a first preset model to obtain a flame detection result; performing material adding action recognition on the color image data in the furnace through a second preset model to obtain blanking event information; performing metallurgy stage feature extraction on the color image data in the furnace through a third preset model to obtain a refining state recognition result; and according to the flame detection result, the blanking event information and the refining state recognition result, interlocking control operation is triggered. Automatic judgment and interlocking control of key working conditions of the RH refining furnace are achieved through multi-model image recognition, the control precision and the system stability can be improved, and energy conservation, consumption reduction and refining quality improvement can be achieved.

The embodiment of the invention discloses an explosion source flame detection method and system, and the method comprises the steps: collecting a multi-mode signal of an explosion source flame, and the multi-mode signal comprises an acoustic vibration type signal and an optical type signal; preprocessing the acoustic vibration type signal and the optical type signal to generate an acoustic vibration feature set and an optical feature set; performing topology analysis on the acoustic vibration feature set by using a persistent coherence algorithm to identify a dynamic behavior mode of the explosion source flame, and obtaining a dynamic behavior mode identification result of the explosion source flame; the dynamic behavior pattern recognition result and the optical feature set are converted into a symbol sequence through a symbolic dynamics algorithm, a cross-modal symbol pattern is analyzed through a transition probability matrix, and comprehensive feature representation of the explosion flame is generated; and based on the comprehensive feature representation, judging whether an explosion source flame exists through a classification algorithm, and outputting a detection result. According to the invention, high-precision explosion source flame detection suitable for a complex environment is realized.

The present invention discloses a laser ignition device and a laser ignition control method. The laser ignition device includes: a control host; a laser emitting device electrically connected to the control host and, under control of the control host, emitting a laser toward a target to ignite the target; and a flame identification device electrically connected to the control host and configured to detect a flame and output a corresponding flame detection signal to the control host. The control host is configured to control the laser emitting device to emit or stop emitting the laser based on the flame detection signal. The present invention can solve the problem of high energy consumption in existing laser igniters.

The invention discloses an industrial ignition gun, and relates to the field of ignition devices, the industrial ignition gun comprises an ignition assembly, a fuel gas conveying assembly and a flame detection assembly, a combustion area is formed on the same side of the ignition assembly, the fuel gas conveying assembly and the flame detection assembly, the fuel gas conveying assembly is used for conveying combustible gas to the combustion area, and the flame detection assembly is used for detecting the combustible gas. The ignition assembly is used for generating point discharge in the combustion area so as to ignite the combustible gas and form a high-temperature flame area; the flame detection assembly is used for collecting ion current signals of the high-temperature flame area. The method has the advantages that the flame detection accuracy is improved, and the equipment operation safety is improved.

The invention discloses a battery pack with a flame detection function. The battery pack comprises a plurality of battery cells and an acquisition board, the acquisition board is connected with the plurality of battery cells and is integrated with a detection circuit; the acquisition board is provided with a flame sensor and a temperature sensor corresponding to the positions of each battery cell pole, and is provided with a safety valve sensor corresponding to the position of each battery cell safety valve; the detection circuit comprises a battery acquisition chip, and a plurality of acquisition channels of the battery acquisition chip are connected with a plurality of detection branches; each detection branch comprises a flame sensor and a safety valve sensor, and the flame sensor and the safety valve sensor are connected with a common resistor in parallel and then connected with a thermistor in series. Through the above arrangement, the detection efficiency and reliability of the battery pack are higher.

The invention relates to a motor vehicle (100) with a refrigerant circuit (102) operated with a CO2 refrigerant, wherein an outlet (104) is provided on the refrigerant circuit (102), characterized in that the outlet (104) a) is configured to flood the engine compartment (106) with CO2 upon detection of an incipient fire by means of a sensor (108) located in the engine compartment (106) for flame detection, and / or b) is configured to be connected to a fire extinguishing valve (110) or directly to a fire extinguishing hose (112) such that the CO2 refrigerant from the refrigerant circuit (102) can be discharged via the fire extinguishing valve (110) and / or the fire extinguishing hose (112) at a discharge point (118) located remote from the outlet. The invention also relates to a method for extinguishing an incipient fire in a motor vehicle (100).