A gas detection method, device, equipment and medium for fire alarm

Abstract

The application relates to the field of fire warning, in particular to a gas detection method, device and equipment for fire warning and a medium, the method comprises the following steps: comparing a detected smoke concentration with a preset smoke concentration, when the detected smoke concentration is higher than the preset smoke concentration, determining a wind force simulation diagram corresponding to a to-be-detected area according to environmental features and a regional model; identifying a detection position of a detection device from a regional image, and determining a wind force influence value corresponding to the detection position according to the detection position and the wind force simulation diagram; determining a final smoke concentration based on the detected smoke concentration and the wind force influence value, and determining a first weight of the to-be-detected area according to a concentration difference between the final smoke concentration and a preset smoke concentration limit value; identifying an abnormal feature in the regional image, and determining a second weight of the to-be-detected area based on the abnormal feature; and generating a first fire warning signal based on the first weight and the second weight. The application can improve the accuracy of fire warning.

Description

Technical Field

[0001] This application relates to the field of fire early warning, and in particular to a gas detection method, device, equipment and medium for fire alarm. Background Technology

[0002] A fire is a disaster caused by uncontrolled combustion in time or space. Because fires are generally uncontrollable and prone to occur, they are often defined as one of the most frequent and widespread major disasters threatening public safety and social development. Once a fire occurs, it may have a greater impact on the safety of people's lives and property.

[0003] In related technologies, smoke detectors are typically installed in the detection area to detect the concentration of smoke in the air, and the presence of fire hazards in the detection area is determined based on the concentration of smoke in the air. However, when there is wind in the detection area, the air in the detection area may move, which may reduce the concentration of smoke in the detection area. If the presence of fire in the detection area is determined based on the diluted smoke concentration, the accuracy of fire alarms may be reduced. Summary of the Invention

[0004] To improve the accuracy of fire alarms, this application provides a gas detection method, apparatus, equipment, and medium for fire alarms.

[0005] Firstly, this application provides a gas detection method for fire alarms, employing the following technical solution:

[0006] A gas detection method for fire alarm, comprising:

[0007] Obtain the smoke concentration within the detection area;

[0008] The detected smoke concentration is compared with a preset smoke concentration. When the detected smoke concentration is higher than the preset smoke concentration, the environmental features and area model of the area to be detected are obtained. The environmental features include wind direction and wind speed.

[0009] Based on the environmental characteristics and the regional model, a wind simulation map corresponding to the area to be detected is determined;

[0010] Acquire an area image within the area to be detected, identify the detection position of the detection device from the area image, and determine the wind force influence value corresponding to the detection position based on the detection position and the wind force simulation diagram;

[0011] The final smoke concentration is determined based on the detected smoke concentration and the wind force influence value, and the first weight of the area to be detected is determined based on the concentration difference between the final smoke concentration and the preset smoke concentration limit.

[0012] Identify abnormal features in the region image and determine a second weight for the region to be detected based on the abnormal features;

[0013] The target weight of the area to be detected is determined based on the first weight and the second weight. When the target weight is higher than the preset standard weight, a first fire alarm signal is generated.

[0014] By adopting the above technical solution, when the detected smoke concentration in the detection area is higher than the preset smoke concentration, the wind force simulation diagram determined by the wind direction and wind speed in the detection area facilitates the determination of the corresponding wind force influence value at different locations in the detection area. The wind force influence value helps to reduce the impact of air flow on smoke concentration measurement. Since there is flowing air in the detection area, the flowing air may dilute the gas in the detection area, which may lead to a large difference between the detected smoke concentration and the actual smoke concentration in the detection area. Therefore, the accuracy of determining whether a fire alarm is needed in the detection area by detecting smoke concentration is low. The wind force influence value determined by the wind force simulation diagram can restore the actual smoke concentration in the detection area before gas dilution. Judging whether a fire alarm is needed in the detection area by the restored smoke concentration helps to improve the accuracy of fire alarm. Furthermore, judging whether a fire alarm is needed in the detection area by abnormal features in the detection area facilitates further improvement in the accuracy of the judgment result.

[0015] In one possible implementation, after determining the final smoke concentration based on the detected smoke concentration and the wind influence value, the method further includes:

[0016] Acquire the detection electrical signal;

[0017] Based on the detected electrical signal, multiple light scattering values ​​corresponding to the area to be detected are determined;

[0018] Based on the correspondence between each light scattering value and the smoke particle type, the smoke particle type corresponding to each light scattering value is determined;

[0019] Based on the smoke particle type corresponding to each light scattering value, the number of each smoke particle type is counted, and the proportion of each smoke particle type is determined based on the number of each smoke particle type.

[0020] The hazard level is determined based on the proportion of smoke particle types, and the alarm level is determined based on the hazard level.

[0021] By adopting the above technical solution, during the detection of smoke concentration in the detection area, since different proportions of particles cause different harms to the human body, the types of particles contained in the smoke and the proportions between each type of particle are determined, and different alarm levels are determined according to the proportions of different smoke particle types, so as to remind relevant personnel to take early action and reduce casualties during the rescue process.

[0022] In one possible implementation, identifying anomalous features in the region image includes:

[0023] Identify the pixel values ​​in the region image, determine whether there is a bright region in the region image based on the pixel values, if there is, obtain the region infrared image corresponding to the bright region, and determine the distributed heat of the bright region based on the region infrared image, and when the distributed heat is higher than the preset standard heat, determine that the region image contains a first abnormal feature;

[0024] Determine whether a preset flammable material feature exists in the region image. When the region image contains a preset flammable material feature, determine that the region image contains a second abnormal feature.

[0025] A thermal change map of the region image is obtained within a first preset time period. When the thermal change value of the region image within the preset time period is higher than a preset standard change value, it is determined that the region image contains a third abnormal feature.

[0026] By adopting the above technical solution, the presence of anomalies in the area to be detected can be determined by judging whether the area image contains a combustion point, flammable materials, or whether the temperature changes too rapidly within a preset time period. This improves the accuracy of judging whether a fire will occur in the area to be detected.

[0027] In one possible implementation, the method further includes:

[0028] When the detected smoke concentration is higher than the preset smoke concentration limit, a second fire alarm signal is generated.

[0029] By adopting the above technical solutions, the amount of data processing can be reduced, the rate of anomaly detection can be improved, and thus the damage caused by fire can be reduced.

[0030] In one possible implementation, when multiple detection devices are present, the method further includes:

[0031] The area to be detected is divided into multiple detection areas based on the detection position of each detection device.

[0032] The system obtains multiple actual smoke concentrations corresponding to each detection area within a second preset time period, and determines the smoke concentration change trend of each detection area within the second preset time period based on the multiple actual smoke concentrations corresponding to each detection area.

[0033] The fire movement trajectory is determined based on the smoke concentration change trend in each detection area.

[0034] Identify the abnormal features contained in each detection area, and based on the smoke concentration change trend and abnormal features corresponding to each detection area, as well as the fire movement trajectory, determine the peak time of the fire, and feed back the peak time of the fire to the terminal equipment of relevant personnel.

[0035] By adopting the above technical solution, since the detection equipment can only detect a limited area, multiple detection devices may be needed to detect the presence of a fire in a large area. Since changes in smoke concentration correspond to changes in fire intensity, using multiple detection devices to detect fire in the area can predict the fire trend by analyzing the smoke concentration changes in the area where each detection device is located. This improves the accuracy of determining the fire's movement path. Furthermore, the presence of abnormal features in the detection area often enhances the speed of fire development. Therefore, based on the predicted fire trend and the abnormal features in each detection area, the accuracy of determining the peak fire time can be improved.

[0036] In one possible implementation, the method further includes:

[0037] Determine the abnormal location of the abnormal features within each detection area, and determine the abnormal interval distance between adjacent detection areas based on the fire movement trajectory.

[0038] The adjustment time is determined based on the number of abnormal intervals.

[0039] Update the peak fire time based on the adjustment time.

[0040] By adopting the above technical solution, when the abnormal interval distance between adjacent detection areas is small, it may cause a linkage reaction between the abnormal features of adjacent detection areas, which may lead to a sudden increase in fire intensity. Therefore, updating the fire peak time by the number of abnormal interval distances can improve the accuracy of the prediction results. In addition, since the fire peak time is determined based on the smoke concentration change value and the abnormal features of each detection area, it indicates that the fire peak time is related to the number of detection areas. Therefore, updating the fire peak time by the number of abnormal interval distances can further improve the accuracy of the fire peak time prediction results.

[0041] In one possible implementation, the method further includes:

[0042] Identify the features of people in the area image and determine the location of the people with the identified features;

[0043] Based on the wind simulation diagram, the location of the personnel, and the movement trajectory of the fire, an escape route is determined.

[0044] By adopting the above technical solution, since the wind simulation map is related to the movement of the fire, it can accurately represent the actual situation in the area to be detected. Therefore, by formulating an escape route based on the wind simulation map and the fire movement trajectory, it is easier to help relevant personnel avoid the fire source and areas with high smoke concentration, thereby reducing the risk of injury and suffocation.

[0045] Secondly, this application provides a gas detection device for fire alarm, which adopts the following technical solution:

[0046] A gas detection device for fire alarm, comprising:

[0047] The smoke concentration acquisition module is used to acquire the smoke concentration in the area to be detected;

[0048] The execution module is used to compare the detected smoke concentration with the preset smoke concentration. When the detected smoke concentration is higher than the preset smoke concentration, the module acquires the environmental features and area model of the area to be detected. The environmental features include wind direction and wind speed.

[0049] The simulation map determination module is used to determine the wind force simulation map corresponding to the area to be detected based on the environmental characteristics and the area model;

[0050] The wind impact value determination module is used to acquire a regional image of the area to be detected, identify the detection position of the detection device from the regional image, and determine the wind impact value corresponding to the detection position based on the detection position and the wind simulation map.

[0051] The first weighting module is used to determine the final smoke concentration based on the detected smoke concentration and the wind force influence value, and to determine the first weight of the area to be detected based on the concentration difference between the final smoke concentration and the preset smoke concentration limit.

[0052] A second weighting module is used to identify abnormal features in the region image and determine the second weight of the region to be detected based on the abnormal features;

[0053] The first early warning module is used to determine the target weight of the area to be detected based on the first weight and the second weight, and generate a first fire alarm signal when the target weight is higher than the preset standard weight.

[0054] By adopting the above technical solution, when the detected smoke concentration in the detection area is higher than the preset smoke concentration, the wind force simulation diagram determined by the wind direction and wind speed in the detection area facilitates the determination of the corresponding wind force influence value at different locations in the detection area. The wind force influence value helps to reduce the impact of air flow on smoke concentration measurement. Since there is flowing air in the detection area, the flowing air may dilute the gas in the detection area, which may lead to a large difference between the detected smoke concentration and the actual smoke concentration in the detection area. Therefore, the accuracy of determining whether a fire alarm is needed in the detection area by detecting smoke concentration is low. The wind force influence value determined by the wind force simulation diagram can restore the actual smoke concentration in the detection area before gas dilution. Judging whether a fire alarm is needed in the detection area by the restored smoke concentration helps to improve the accuracy of fire alarm. Furthermore, judging whether a fire alarm is needed in the detection area by abnormal features in the detection area facilitates further improvement in the accuracy of the judgment result.

[0055] In one possible implementation, the device further includes:

[0056] The electrical signal acquisition module is used to acquire the detection electrical signal;

[0057] The light scattering value determination module is used to determine multiple light scattering values ​​corresponding to the area to be detected based on the detection electrical signal;

[0058] The particle type determination module is used to determine the smoke particle type corresponding to each light scattering value based on each light scattering value and the correspondence between scattering values ​​and smoke particle types;

[0059] The module for determining the proportion of smoke particle types is used to count the number of each smoke particle type according to the smoke particle type corresponding to each light scattering value, and to determine the proportion of smoke particle types based on the number of each smoke particle type.

[0060] The alarm level determination module is used to determine the hazard level based on the proportion of smoke particle types, and to determine the alarm level based on the hazard level.

[0061] In one possible implementation, determining the second weighting module's function in identifying anomalous features in the region image specifically involves:

[0062] Identify the pixel values ​​in the region image, determine whether there is a bright region in the region image based on the pixel values, if there is, obtain the region infrared image corresponding to the bright region, and determine the distributed heat of the bright region based on the region infrared image, and when the distributed heat is higher than the preset standard heat, determine that the region image contains a first abnormal feature;

[0063] Determine whether a preset flammable material feature exists in the region image. When the region image contains a preset flammable material feature, determine that the region image contains a second abnormal feature.

[0064] A thermal change map of the region image is obtained within a first preset time period. When the thermal change value of the region image within the preset time period is higher than a preset standard change value, it is determined that the region image contains a third abnormal feature.

[0065] In one possible implementation, the device further includes:

[0066] The second early warning module is used to generate a second fire alarm signal when the detected smoke concentration is higher than the preset smoke concentration limit.

[0067] In one possible implementation, when multiple detection devices are present, the apparatus further includes:

[0068] The region division module is used to divide the area to be detected into multiple detection regions based on the detection position of each detection device.

[0069] The trend determination module is used to obtain multiple actual smoke concentrations corresponding to each detection area within a second preset time period, and determine the smoke concentration change trend of each detection area within the second preset time period based on the multiple actual smoke concentrations corresponding to each detection area.

[0070] The trajectory determination module is used to determine the movement trajectory of the fire based on the smoke concentration change trend corresponding to each detection area.

[0071] The module for determining the peak fire time is used to identify the abnormal features contained in each detection area, and based on the smoke concentration change trend and abnormal features corresponding to each detection area, as well as the fire movement trajectory, determine the peak fire time, and feed back the peak fire time to the terminal devices of relevant personnel.

[0072] In one possible implementation, the device further includes:

[0073] The abnormal interval distance determination module is used to determine the abnormal location of abnormal features in each detection area, and to determine the abnormal interval distance between adjacent detection areas based on the fire movement trajectory.

[0074] The module for determining adjustment time is used to determine the adjustment time based on the number of abnormal interval distances;

[0075] Update the peak fire time, which is used to update the peak fire time according to the adjustment time.

[0076] In one possible implementation, the device further includes:

[0077] A personnel location determination module is used to identify personnel features in the area image and determine the personnel location based on those features;

[0078] The escape route determination module is used to determine the escape route based on the wind simulation map, the personnel location, and the fire movement trajectory.

[0079] Thirdly, this application provides an electronic device that adopts the following technical solution:

[0080] An electronic device comprising:

[0081] At least one processor;

[0082] Memory;

[0083] At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: execute the gas detection method described above for fire alarm.

[0084] Fourthly, this application provides a computer-readable storage medium, which adopts the following technical solution:

[0085] A computer-readable storage medium includes: a computer program stored thereon that can be loaded by a processor and executed by the gas detection method described above for fire alarm.

[0086] In summary, this application includes at least one of the following beneficial technical effects:

[0087] The wind force simulation map, determined by the wind direction and speed within the detection area, facilitates the determination of wind force impact values ​​at different locations within the detection area. This wind force impact value helps reduce the influence of airflow on smoke concentration measurement. Since flowing air may dilute the gas within the detection area, the wind force impact value determined by the wind force simulation map can reconstruct the actual smoke concentration in the detection area before gas dilution. Using the reconstructed smoke concentration to determine whether a fire alarm is needed in the detection area helps improve the accuracy of fire alarm detection. Furthermore, using abnormal features within the detection area to determine whether a fire alarm is needed further improves the accuracy of the judgment results.

[0088] Since different proportions of particles cause different levels of harm to the human body, it is necessary to determine the types of particles contained in the smoke and the proportions between each type of particle, and to determine different alarm levels based on the different proportions of smoke particle types, so as to remind relevant personnel to take early action and thus reduce casualties during rescue operations. Attached Figure Description

[0089] Figure 1 This is a schematic flowchart of a gas detection method for fire alarm in an embodiment of this application;

[0090] Figure 2 This is a flowchart illustrating a method for determining the peak time of a fire in an embodiment of this application;

[0091] Figure 3 This is an example diagram of an abnormal interval distance in an embodiment of this application;

[0092] Figure 4 This is a structural example diagram of a gas detection device for fire alarm in an embodiment of this application;

[0093] Figure 5 This is a structural example diagram of an electronic device in an embodiment of this application. Detailed Implementation

[0094] The following is in conjunction with the appendix Figure 1-5 This application will be described in further detail.

[0095] After reading this specification, those skilled in the art may make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0096] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0097] Specifically, this application provides a gas detection method for fire alarm, executed by an electronic device. This electronic device can be a server or a terminal device. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and this application does not impose any limitations on this.

[0098] refer to Figure 1 , Figure 1This is a flowchart illustrating a gas detection method for fire alarm in an embodiment of this application. The method includes steps S110-S170, wherein:

[0099] Step S110: Obtain the smoke concentration in the detection area.

[0100] Specifically, the area to be detected is the area where gas detection is required to check for potential fire hazards. This area can be a factory, apartment, classroom, etc., and is not specifically limited in this embodiment. The detected smoke concentration is the smoke concentration within the area to be detected. The smoke concentration within the area to be detected can be 0. When the detected smoke concentration within the area to be detected is 0, it indicates that there is no smoke in the area. The detected smoke concentration can be collected by a detection device installed within the area to be detected and then uploaded to an electronic device. This detection device can be a photoelectric detector, an ionization detector, a thermal velocity sensor, or a gas sensor, etc. The specific detection device is not specifically limited in this embodiment, as long as it can obtain the smoke concentration within the area to be detected.

[0101] Step S120: Compare the detected smoke concentration with the preset smoke concentration. When the detected smoke concentration is higher than the preset smoke concentration, obtain the environmental features and area model of the area to be detected. The environmental features include wind direction and wind speed.

[0102] Specifically, the preset smoke concentration is the lowest value at which the human body can perceive smoke. That is, when the smoke concentration in the detection area is lower than the preset smoke concentration, the relevant personnel in the detection area will find it difficult to detect the smoke. Since the human body's perception ability is related to the temperature, humidity, and area of ​​the detection area, the preset smoke concentration of the detection area can be determined based on the temperature, humidity, and area of ​​the detection area, from the correspondence between regional features and smoke concentration. The regional features include regional temperature, regional humidity, and regional area. The type of regional features is not specifically limited in this application embodiment. The correspondence between regional features and smoke concentration includes smoke concentrations corresponding to different regional features. The specific content of the correspondence is not specifically limited in this application implementation and can be added and modified by relevant technical personnel.

[0103] When the detected smoke concentration is higher than the preset smoke concentration, it means that relevant personnel in the detection area can perceive the smoke. However, the detected smoke concentration may not yet be high enough to warrant a fire warning. Reasons for a low detected smoke concentration include:

[0104] Reason 1: The amount of smoke in the area to be detected is less than the preset amount of smoke;

[0105] Reason 2: The amount of smoke in the area to be detected is not less than the preset amount of smoke, but the smoke in the area to be detected is diluted by the flowing air. In this embodiment of the application, the preset amount of smoke is not specifically limited, but can be set by relevant technical personnel according to the area of ​​the area to be detected.

[0106] When the low smoke concentration is due to smoke dilution by flowing air, the actual smoke concentration in the detection area can be determined by restoring the smoke concentration before dilution. Wind direction and speed within the detection area can be collected by wind data acquisition equipment installed within the area and uploaded to electronic equipment. The area model is a spatially consistent model with the area to be monitored. When obtaining the area model corresponding to the detection area, the area model can be determined from the model storage space by the name or number of the detection area. The model storage space contains area models corresponding to different detection areas, which can be added, deleted, or modified by relevant technical personnel.

[0107] Step S130: Based on environmental characteristics and regional models, determine the wind simulation map corresponding to the area to be detected.

[0108] Specifically, the wind simulation map is used to simulate the wind direction and flow path within the area to be detected. Based on the area model, the indoor structure of the area to be detected can be determined. By importing the wind direction and wind speed contained in the environmental features into the area model, discretizing the continuous physical domain into a grid, and then solving the fluid motion equations, the flow path of air in the area to be detected under the influence of wind direction and wind speed can be simulated. The generated wind simulation map can predict the flow value corresponding to each location of the wind field within the area to be detected.

[0109] Step S140: Obtain an area image within the area to be detected, identify the detection location of the detection device from the area image, and determine the wind force influence value corresponding to the detection location based on the detection location and the wind force simulation diagram.

[0110] Specifically, the area image to be detected can be acquired by an image acquisition device located within the area and then uploaded to an electronic device. The content contained in the area image is not specifically limited in this embodiment, as long as the area image contains a detection device. When determining the detection position of the detection device in the area image, the area image can be imported into a preset coordinate system to determine the three-dimensional coordinates of the detection device in the area image. Based on the three-dimensional coordinates of the detection device, the wind force influence value corresponding to the current coordinate position is determined from the wind force simulation image. Each point in the wind force simulation image corresponds to a wind force influence value, which is the dilution effect of flowing air on the smoke concentration at the corresponding location within the area to be detected. For example, when there is no air flow within the area to be detected, the smoke concentration detectable at the detection device is 'a'; when there is air flow within the area to be detected, the smoke concentration detectable at the detection device is 'b'. In this case, 'b' is determined as the wind force influence value at the detection device. The wind force influence value corresponding to each point in the wind force simulation image can be determined from historical experimental data, and is not specifically limited in this embodiment.

[0111] Step S150: Determine the final smoke concentration based on the detected smoke concentration and wind influence value, and determine the first weight of the area to be detected based on the concentration difference between the final smoke concentration and the preset smoke concentration limit.

[0112] Specifically, the final smoke concentration is the smoke concentration before dilution by flowing air. For example, if the detected smoke concentration is a1 and the wind influence value is a2, then the final smoke concentration is a1 + a2. A preset smoke concentration limit is set higher than the preset smoke concentration limit. Once the detected smoke concentration in the detection area exceeds the preset smoke concentration limit, it indicates a higher probability of a fire occurring in the detection area. At this time, relevant personnel in the detection area can clearly perceive the smoke in the environment. Different concentration differences correspond to different first weights. Based on the concentration difference, the first weight corresponding to the concentration difference can be determined from the correspondence between the concentration difference and the weight. Specifically, the correspondence between the concentration difference and the weight can be as follows: when the concentration difference is 0-5 mg / m³, the corresponding first weight is 20%; when the concentration difference is 6-10 mg / m³, the corresponding first weight is 30%; and when the concentration difference is greater than 10 mg / m³, the corresponding first weight is 50%. The specific correspondence between the concentration difference and the weight is not specifically limited in this embodiment and can be added and modified by relevant technical personnel.

[0113] Step S160: Identify abnormal features in the region image and determine the second weight of the region to be detected based on the abnormal features.

[0114] Specifically, abnormal features are those that may indicate a fire. The more abnormal features there are in the area to be detected, the greater the corresponding second weight, meaning the greater the probability of a fire occurring in the area to be detected.

[0115] The process of identifying abnormal features in a region image includes: identifying pixel values ​​in the region image; determining whether a bright area exists in the region image based on the pixel values; if so, acquiring the infrared image of the region corresponding to the bright area and determining the distributed heat of the bright area based on the infrared image; determining that the region image contains a first abnormal feature when the distributed heat is higher than a preset standard heat; determining whether a preset flammable material feature exists in the region image; determining that the region image contains a second abnormal feature when the region image contains a preset flammable material feature; and acquiring a thermal change map of the region image within a first preset time period; determining that the region image contains a third abnormal feature when the thermal change value of the region image within the preset time period is higher than a preset standard change value.

[0116] Specifically, the color value of each pixel in the region image can be detected to identify the pixel values ​​contained in the region image. Abnormal pixels are identified by comparing the pixel values ​​corresponding to each pixel in the region image. Abnormal pixels are those with pixel values ​​higher than a preset pixel value. The preset pixel value is not specifically limited in this embodiment. When abnormal pixels exist in the region image, it is determined that the region image contains a bright area. Based on the location information corresponding to the abnormal pixels, the bright area is determined from the region image. Then, based on the location information corresponding to the bright area, the region infrared image corresponding to the bright area is determined from the infrared image corresponding to the region to be detected. The infrared image corresponding to the region to be detected can be acquired by an infrared acquisition device set in the region to be detected and uploaded to an electronic device. The region infrared image contains the thermal value corresponding to each pixel in the bright area. Since the bright area may be a fire point or a lighting device, it is necessary to compare the thermal value corresponding to the bright area with the preset standard heat value to determine whether there is a first abnormal feature in the region to be detected. The preset standard heat value is not specifically limited in this embodiment and can be set by relevant technical personnel.

[0117] Flammable materials refer to substances that are easily combustible under certain conditions. Common flammable materials include liquid flammable materials, such as gasoline, diesel, and alcohol; and solid flammable materials, such as wood, paper, cloth, plastic, rubber, and foam. The preset flammable material features are characteristic identifiers that can characterize flammable materials. In this application embodiment, no specific limitation is made, and they can be added and modified by technicians. When determining whether a region image contains a second abnormal feature, the region image can be imported into a trained flammable material feature recognition model for feature recognition. If the recognition result is the preset flammable material feature, then the region image contains a second abnormal feature. The training process of the flammable material feature involves iteratively training the feature recognition model using a large number of images containing flammable material features and sample images with corresponding manual labels until the output result of the feature recognition model is consistent with the manual label.

[0118] By analyzing the thermal change map of the area to be tested, it is easy to determine the thermal changes of the area to be tested within a preset time period. The thermal change map can be obtained directly or uploaded by relevant personnel. The specific acquisition method is not specifically limited in this application embodiment. The first preset time period can be 2 minutes or 5 minutes. It is not specifically limited in this application embodiment, as long as it can be used to determine whether there are abnormal thermal changes in the area to be tested.

[0119] Step S170: Determine the target weight of the area to be detected based on the first weight and the second weight. When the target weight is higher than the preset standard weight, generate the first fire alarm signal.

[0120] Specifically, the preset standard weight can be 95% or 98%. The specific weight is not limited in this embodiment and can be set by relevant technical personnel. The fire alarm signal can establish communication with the broadcasting equipment in the area to be detected through electronic equipment, and the broadcasting equipment will broadcast the alarm to remind relevant personnel to evacuate in time; it can also be fed back to the terminal equipment of relevant rescue personnel to remind them to carry out emergency rescue.

[0121] In this embodiment of the application, when the smoke concentration detected in the detection area is higher than the preset smoke concentration, the wind force simulation diagram determined by the wind direction and wind speed in the detection area facilitates the determination of the wind force influence value corresponding to different locations in the detection area. The wind force influence value helps to reduce the impact of air flow on the smoke concentration measurement. Since there is flowing air in the detection area, the flowing air may dilute the gas in the detection area, which may cause a large difference between the detected smoke concentration and the actual smoke concentration in the detection area. Therefore, the accuracy of determining whether the detection area needs a fire alarm by detecting the smoke concentration is low. The wind force influence value determined by the wind force simulation diagram can restore the actual smoke concentration in the detection area before gas dilution. Judging whether the detection area needs a fire alarm by the restored smoke concentration helps to improve the accuracy of fire alarm. Furthermore, judging whether the detection area needs a fire alarm by abnormal features in the detection area further improves the accuracy of the judgment result.

[0122] Furthermore, when the smoke concentration in the detection area is uniform, different types of particles contained in the smoke have different effects on relevant personnel. Therefore, the method also includes:

[0123] Acquire detection electrical signals; determine multiple light scattering values ​​corresponding to the area to be detected based on the detection electrical signals; determine the smoke particle type corresponding to each light scattering value based on the correspondence between each light scattering value and the smoke particle type; count the number of each smoke particle type based on the number of each smoke particle type, and determine the proportion of each smoke particle type based on the number of each smoke particle type; determine the hazard level based on the proportion of smoke particle types, and determine the alarm level based on the hazard level.

[0124] Specifically, the detection electrical signal is measured by a photoelectric detection device installed in the area to be detected and then uploaded to an electronic device. Since a photoelectric detector is a device that converts light energy into electrical energy, when light from the area to be detected shines on the photoelectric detection device, the device generates a photoelectric effect, converting light energy into electronic energy and outputting it. The output signal of the photoelectric detection device can be an electrical signal in the form of current, voltage, or impedance. The electrical signal output by the photoelectric detection device can measure the light scattering value when light passes through smoke particles in the area to be detected. Different types of smoke particles correspond to different light scattering values. By processing multiple light scattering values, the number of smoke particles corresponding to the same light scattering value can be determined. The smoke particle type ratio is the ratio of the number of different smoke particle types. For example, if there are three types of smoke particles, A, B, and C, and the corresponding numbers for the three types are 100, 800, and 300 respectively, then the smoke particle type ratio is 1:8:3.

[0125] Different proportions of smoke particle types correspond to different hazard levels. In this embodiment, the relationship between the proportion of smoke particle types and the hazard level is not specifically limited. The higher the hazard level, the higher the alarm level. Different alarm levels are determined according to different proportions of smoke particle types to remind relevant personnel to prepare for response in advance, thereby reducing casualties during rescue operations.

[0126] Furthermore, when the detected smoke concentration is higher than a preset smoke concentration, the method also includes:

[0127] When the detected smoke concentration exceeds the preset smoke concentration limit, a second fire alarm signal is generated.

[0128] Specifically, when the detected smoke concentration is higher than the preset smoke concentration, it indicates that relevant personnel in the detection area can perceive the smoke. If the detected smoke concentration value is also higher than the preset smoke concentration limit at the same time, it indicates that the smoke concentration in the detection area has reached a level requiring fire warning. By directly generating a second fire alarm signal, the amount of data processing is reduced, the anomaly detection rate is improved, and the harm caused by the fire is reduced. The processing method of the generated second fire alarm signal can be referred to the embodiment section corresponding to step S170 above, and will not be repeated here.

[0129] Furthermore, when the area to be detected contains multiple detection devices, the method also includes steps Sa1, Sa2, Sa3, and Sa4, as follows: Figure 2 As shown, where:

[0130] Step Sa1: Divide the area to be detected into multiple detection areas based on the detection position of each detection device.

[0131] Specifically, each detection device has a limited working range. For example, the working range of a household photoelectric detection device may be between 25 and 40 square meters. Therefore, when the area to be detected is large, it may be necessary to install multiple detection devices. The method for determining the detection position of the detection device can be referred to the embodiment corresponding to step S140 above, which will not be elaborated here.

[0132] Step Sa2: Obtain multiple actual smoke concentrations corresponding to each detection area within the second preset time period, and determine the smoke concentration change trend of each detection area within the second preset time period based on the multiple actual smoke concentrations corresponding to each detection area.

[0133] Specifically, the second preset time period can be 5 minutes or 10 minutes, and this embodiment does not impose a specific limitation. It can be set by relevant technical personnel. The actual smoke concentration corresponding to the detection area is the smoke concentration after reduction and dilution. Since the airflow path in the detection area has different degrees of influence in different detection areas, that is, the wind force influence value is different in different detection areas, the actual smoke concentration corresponding to different detection areas is also different. By analyzing the multiple actual smoke concentrations corresponding to each detection area within the second preset time period, the smoke concentration change trend of each detection area within the second preset time period can be determined.

[0134] Step Sa3: Determine the fire movement trajectory based on the smoke concentration change trend corresponding to each detection area.

[0135] Specifically, since the development of a fire is related to the smoke concentration, the larger the fire, the greater the corresponding smoke concentration. Therefore, when the smoke concentration in a certain detection area decreases from high to low, it indicates that the fire has subsided in that area. For example, consider four adjacent detection areas: Detection Area 1, Detection Area 2, Detection Area 3, and Detection Area 4. The smoke concentration in Detection Area 1 changes from high to low within a second preset time period; the smoke concentration in Detection Area 2 changes from high to low; the smoke concentration in Detection Area 3 changes from low to high; and the smoke concentration in Detection Area 4 changes from low to high. Furthermore, the temperature in Detection Area 1 is lower than that in Detection Area 2, and the temperature in Detection Area 3 is higher than that in Detection Area 4. Therefore, the fire's movement path can be determined as Detection Area 1, Detection Area 2, Detection Area 3, and Detection Area 4.

[0136] Step Sa4: Determine the abnormal features contained in each detection area, and based on the smoke concentration change trend and abnormal features corresponding to each detection area, as well as the fire movement trajectory, determine the peak time of the fire, and feed back the peak time of the fire to the terminal equipment of relevant personnel.

[0137] Specifically, the method for determining the abnormal features contained in each detection area can be referred to the embodiment corresponding to step S160 above, and will not be repeated here.

[0138] Based on the trend of smoke concentration changes within the second preset time period and the area of ​​each detection zone, the development speed of the fire in the detection zone can be determined. Since the second anomalous feature contained in the anomalous features is a flammable substance, the earlier the detection zone reaches the peak fire time when the second anomalous feature exists in the detection zone, the earlier the peak fire time is reached. After determining the initial peak fire time based on the development speed, the target advance time corresponding to the anomalous features contained in the detection zone is determined based on the correspondence between the number of anomalous features and the advance time. The peak fire time can be determined based on the target advance time and the initial peak fire time.

[0139] To further improve the accuracy of determining the peak fire time, the method also includes:

[0140] Determine the location of anomalous features within each detection area, and determine the anomalous interval distance between adjacent detection areas based on the fire movement trajectory; determine the adjustment time based on the number of anomalous interval distances; update the peak fire time based on the adjustment time.

[0141] Specifically, the abnormal location of the abnormal feature within the detection area is determined, that is, the abnormal location of the second abnormal feature within the detection area is determined. The specific method for determining the abnormal location can be referred to the embodiment corresponding to step S160 above, and will not be elaborated here. The abnormal interval distance is the interval distance between the second abnormal features in adjacent detection areas. If there is an abnormal interval distance between connected detection areas, it indicates that the second abnormal features of the two adjacent detection areas may be ignited simultaneously. This may further intensify the fire development, that is, the peak fire time may be further advanced. Figure 3 As shown, there are abnormal intervals between detection areas 1 and 2, and also between detection areas 3 and 4. A higher number of abnormal intervals indicates that the detected area reaches its peak fire intensity earlier. The correspondence between the number of abnormal intervals and the adjustment time includes the adjustment time corresponding to different numbers of abnormal intervals. The specific correspondence between the number of abnormal intervals and the adjustment time can be determined from historical experimental data, and is not specifically limited in this embodiment. Updating the peak fire intensity time by the number of abnormal intervals facilitates further improvement in the accuracy of the peak fire intensity time prediction results.

[0142] Furthermore, to help personnel avoid sources of fire and areas with high smoke concentrations, thereby reducing the risk of injury and suffocation, the method also includes:

[0143] Identify human characteristics in the area image and determine the location of the human characteristics; determine the escape route based on the wind simulation map, the location of the human and the movement trajectory of the fire.

[0144] Specifically, the personnel features can be facial features. The specific personnel features are not limited in this embodiment, as long as they can identify the personnel in the area image. When identifying personnel features in the area image, the area image can be imported into a facial feature recognition model to obtain the personnel features contained in the area image. The image containing personnel features is then imported into a preset coordinate system to determine the coordinates of each personnel feature, thereby determining the position of each person within the detection area. Since the wind simulation map is related to the movement of the fire and can accurately represent the actual situation within the detection area, a safe zone can be determined using the wind simulation map and the fire movement trajectory. Connecting the location corresponding to the safe zone with the personnel location determines the escape route. After generating the escape route, communication can be established between electronic devices and broadcasting equipment within the detection area, and the broadcasting equipment will announce the escape route to help relevant personnel avoid fire sources and areas with high smoke concentrations.

[0145] The above embodiments describe a gas detection method for fire alarm from the perspective of process flow. The following embodiments describe a gas detection device for fire alarm from the perspective of virtual module or virtual unit. For details, please refer to the following embodiments.

[0146] This application provides a gas detection device for fire alarm, such as... Figure 4 As shown, the device may specifically include a smoke concentration acquisition module 410, an execution module 420, a simulation diagram determination module 430, a wind force influence value determination module 440, a first weight determination module 450, a second weight determination module 460, and a first early warning module 470, wherein:

[0147] The smoke concentration acquisition module 410 is used to acquire the smoke concentration in the area to be detected;

[0148] The execution module 420 is used to compare the detected smoke concentration with the preset smoke concentration. When the detected smoke concentration is higher than the preset smoke concentration, it acquires the environmental features and area model of the area to be detected. The environmental features include wind direction and wind speed.

[0149] The simulation map module 430 is used to determine the wind simulation map corresponding to the area to be detected based on environmental characteristics and the regional model.

[0150] The wind impact value determination module 440 is used to acquire regional images within the area to be detected, identify the detection location of the detection device from the regional images, and determine the wind impact value corresponding to the detection location based on the detection location and the wind simulation diagram.

[0151] The first weight module 450 is used to determine the final smoke concentration based on the detected smoke concentration and the wind influence value, and to determine the first weight of the area to be detected based on the concentration difference between the final smoke concentration and the preset smoke concentration limit.

[0152] The second weight module 460 is used to identify abnormal features in the region image and determine the second weight of the region to be detected based on the abnormal features.

[0153] The first early warning module 470 is used to determine the target weight of the area to be detected based on the first weight and the second weight. When the target weight is higher than the preset standard weight, a first fire alarm signal is generated.

[0154] In one possible implementation, the device further includes:

[0155] The electrical signal acquisition module is used to acquire the detection electrical signal;

[0156] The light scattering value determination module is used to determine multiple light scattering values ​​corresponding to the area to be detected based on the detection electrical signal.

[0157] The particle type determination module is used to determine the smoke particle type corresponding to each light scattering value based on each light scattering value and the correspondence between scattering values ​​and smoke particle types;

[0158] The module for determining the proportion of smoke particle types is used to count the number of each smoke particle type based on the smoke particle type corresponding to each light scattering value, and to determine the proportion of smoke particle types based on the number of each smoke particle type.

[0159] The alarm level determination module is used to determine the hazard level based on the proportion of smoke particle types, and then determine the alarm level based on the hazard level.

[0160] In one possible implementation, when determining the anomalous features in the region image, the second weighting module 460 is specifically used for:

[0161] Identify the pixel values ​​in the region image, determine whether there is a bright region in the region image based on the pixel values, if there is, obtain the infrared image of the region corresponding to the bright region, and determine the heat distribution of the bright region based on the infrared image of the region. When the heat distribution is higher than the preset standard heat, it is determined that the region image contains the first abnormal feature.

[0162] Determine whether there are preset flammable material features in the region image. When the region image contains preset flammable material features, determine that the region image contains a second abnormal feature.

[0163] Obtain the thermal change map of the region image within a first preset time period. When the thermal change value of the region image within the preset time period is higher than the preset standard change value, it is determined that the region image contains a third abnormal feature.

[0164] In one possible implementation, the device further includes:

[0165] The second early warning module is used to generate a second fire alarm signal when the detected smoke concentration is higher than the preset smoke concentration limit.

[0166] In one possible implementation, when multiple detection devices are present, the apparatus further includes:

[0167] The region division module is used to divide the area to be detected into multiple detection regions based on the detection position of each detection device.

[0168] The trend determination module is used to obtain multiple actual smoke concentrations corresponding to each detection area within a second preset time period, and to determine the smoke concentration change trend of each detection area within the second preset time period based on the multiple actual smoke concentrations corresponding to each detection area.

[0169] The trajectory determination module is used to determine the movement trajectory of the fire based on the smoke concentration change trend corresponding to each detection area.

[0170] The module for determining the peak fire time is used to identify the abnormal features contained in each detection area, and based on the smoke concentration change trend and abnormal features corresponding to each detection area, as well as the fire movement trajectory, determine the peak fire time and feed it back to the terminal equipment of relevant personnel.

[0171] In one possible implementation, the device further includes:

[0172] The module for determining abnormal interval distance is used to determine the abnormal location of abnormal features in each detection area and to determine the abnormal interval distance between adjacent detection areas based on the fire movement trajectory.

[0173] The module for determining adjustment time is used to determine the adjustment time based on the number of abnormal interval distances;

[0174] Update peak fire time, used to update the peak fire time based on the adjustment time.

[0175] In one possible implementation, the device further includes:

[0176] The personnel location determination module is used to identify personnel features in a region image and determine the personnel location based on those features.

[0177] The escape route determination module is used to determine escape routes based on wind simulation diagrams, personnel locations, and the movement trajectory of the fire.

[0178] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0179] This application provides an electronic device, such as... Figure 5 As shown, Figure 5 The illustrated electronic device 500 includes a processor 501 and a memory 503. The processor 501 and the memory 503 are connected, for example, via a bus 502. Optionally, the electronic device 500 may also include a transceiver 504. It should be noted that in practical applications, the transceiver 504 is not limited to one type, and the structure of this electronic device 500 does not constitute a limitation on the embodiments of this application.

[0180] Processor 501 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 501 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0181] Bus 502 may include a pathway for transmitting information between the aforementioned components. Bus 502 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 502 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0182] The memory 503 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0183] The memory 503 is used to store application code that executes the solution of this application, and its execution is controlled by the processor 501. The processor 501 is used to execute the application code stored in the memory 503 to implement the content shown in the foregoing method embodiments.

[0184] Electronic devices include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Servers can also be included. Figure 5 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0185] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments.

[0186] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0187] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A gas detection method for fire alarm, characterized in that, include: Obtain the smoke concentration within the detection area; The detected smoke concentration is compared with a preset smoke concentration. When the detected smoke concentration is higher than the preset smoke concentration, the environmental features and area model of the area to be detected are obtained. The environmental features include wind direction and wind speed. Based on the environmental characteristics and the regional model, a wind simulation map corresponding to the area to be detected is determined; Acquire an area image within the area to be detected, identify the detection position of the detection device from the area image, and determine the wind force influence value corresponding to the detection position based on the detection position and the wind force simulation diagram; The final smoke concentration is determined based on the detected smoke concentration and the wind force influence value, and the first weight of the area to be detected is determined based on the concentration difference between the final smoke concentration and the preset smoke concentration limit. Identify abnormal features in the region image and determine a second weight for the region to be detected based on the abnormal features; The target weight of the area to be detected is determined based on the first weight and the second weight. When the target weight is higher than the preset standard weight, a first fire alarm signal is generated. The process of determining the final smoke concentration based on the detected smoke concentration and the wind force influence value further includes: Acquire the detection electrical signal; Based on the detected electrical signal, multiple light scattering values ​​corresponding to the area to be detected are determined; Based on the correspondence between each light scattering value and the smoke particle type, the smoke particle type corresponding to each light scattering value is determined; Based on the smoke particle type corresponding to each light scattering value, the number of each smoke particle type is counted, and the proportion of each smoke particle type is determined based on the number of each smoke particle type. The hazard level is determined based on the proportion of smoke particle types, and the alarm level is determined based on the hazard level. The identification of abnormal features in the region image includes: Identify the pixel values ​​in the region image, determine whether there is a bright region in the region image based on the pixel values, if there is, obtain the region infrared image corresponding to the bright region, and determine the distributed heat of the bright region based on the region infrared image, and when the distributed heat is higher than the preset standard heat, determine that the region image contains a first abnormal feature; Determine whether a preset flammable material feature exists in the region image. When the region image contains a preset flammable material feature, determine that the region image contains a second abnormal feature. A thermal change map of the region image is obtained within a first preset time period. When the thermal change value of the region image within the preset time period is higher than a preset standard change value, it is determined that the region image contains a third abnormal feature.

2. The gas detection method for fire alarm according to claim 1, characterized in that, Also includes: When the detected smoke concentration is higher than the preset smoke concentration limit, a second fire alarm signal is generated.

3. The gas detection method for fire alarm according to claim 1, characterized in that, When multiple detection devices are present, the method further includes: The area to be detected is divided into multiple detection areas based on the detection position of each detection device. The system obtains multiple actual smoke concentrations corresponding to each detection area within a second preset time period, and determines the smoke concentration change trend of each detection area within the second preset time period based on the multiple actual smoke concentrations corresponding to each detection area. The fire movement trajectory is determined based on the smoke concentration change trend in each detection area. Identify the abnormal features contained in each detection area, and based on the smoke concentration change trend and abnormal features corresponding to each detection area, as well as the fire movement trajectory, determine the peak time of the fire, and feed back the peak time of the fire to the terminal equipment of relevant personnel.

4. A gas detection method for fire alarm according to claim 3, characterized in that, Also includes: Determine the abnormal location of the abnormal features within each detection area, and determine the abnormal interval distance between adjacent detection areas based on the fire movement trajectory. The adjustment time is determined based on the number of abnormal intervals. Update the peak fire time based on the adjustment time.

5. A gas detection method for fire alarm according to claim 4, characterized in that, Also includes: Identify the features of people in the area image and determine the location of the people with the identified features; Based on the wind simulation diagram, the location of the personnel, and the movement trajectory of the fire, an escape route is determined.

6. A gas detection device for fire alarm, characterized in that, A gas detection method for fire alarm according to any one of claims 1-5, comprising: The smoke concentration acquisition module is used to acquire the smoke concentration in the area to be detected; The execution module is used to compare the detected smoke concentration with the preset smoke concentration. When the detected smoke concentration is higher than the preset smoke concentration, the module acquires the environmental features and area model of the area to be detected. The environmental features include wind direction and wind speed. The simulation map determination module is used to determine the wind force simulation map corresponding to the area to be detected based on the environmental characteristics and the area model; The wind impact value determination module is used to acquire a regional image of the area to be detected, identify the detection position of the detection device from the regional image, and determine the wind impact value corresponding to the detection position based on the detection position and the wind simulation map. The first weighting module is used to determine the final smoke concentration based on the detected smoke concentration and the wind force influence value, and to determine the first weight of the area to be detected based on the concentration difference between the final smoke concentration and the preset smoke concentration limit. A second weighting module is used to identify abnormal features in the region image and determine the second weight of the region to be detected based on the abnormal features; The first early warning module is used to determine the target weight of the area to be detected based on the first weight and the second weight, and generate a first fire alarm signal when the target weight is higher than the preset standard weight. The electrical signal acquisition module is used to acquire the detection electrical signal; A light scattering value determination module is used to determine multiple light scattering values ​​corresponding to the area to be detected based on the detection electrical signal; The particle type determination module is used to determine the smoke particle type corresponding to each light scattering value based on each light scattering value and the correspondence between scattering values ​​and smoke particle types; The module for determining the proportion of smoke particle types is used to count the number of each smoke particle type according to the smoke particle type corresponding to each light scattering value, and to determine the proportion of smoke particle types based on the number of each smoke particle type. An alarm level determination module is used to determine the hazard level based on the proportion of smoke particle types, and to determine the alarm level based on the hazard level. When determining the second weighting module for identifying anomalous features in the region image, it is specifically used for: Identify the pixel values ​​in the region image, determine whether there is a bright region in the region image based on the pixel values, if there is, obtain the region infrared image corresponding to the bright region, and determine the distributed heat of the bright region based on the region infrared image, and when the distributed heat is higher than the preset standard heat, determine that the region image contains a first abnormal feature; Determine whether a preset flammable material feature exists in the region image. When the region image contains a preset flammable material feature, determine that the region image contains a second abnormal feature. A thermal change map of the region image is obtained within a first preset time period. When the thermal change value of the region image within the preset time period is higher than a preset standard change value, it is determined that the region image contains a third abnormal feature.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform a gas detection method for fire alarm according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, include: The computer program is stored and can be loaded by a processor and executed as described in any one of claims 1-5, which is a gas detection method for fire alarm.

Images