A Flame Recognition Method for Infrared Thermal Imaging Detectors

Abstract

The present invention discloses a flame recognition method for an infrared thermal imaging detector, which relates to the technical field of infrared thermal imaging and is used to improve the accuracy of fire recognition. The method includes: obtaining a visualized thermal image generated by an infrared thermal imaging detection component, analyzing temperature anomalies based on the thermal image, locating temperature anomaly points, obtaining the included angle between the observation direction vector and the reflection direction vector of the component according to the location and judgment time of the temperature anomaly points, determining whether the temperature anomaly points are specular reflections, marking the temperature anomaly points that do not conform to specular reflections as suspicious fire monitoring points, identifying combustibles at the suspicious fire monitoring points, analyzing the combustion risk of the combustibles at the suspicious fire monitoring points according to the ignition point data and oxygen data of the combustibles, analyzing the possibility that the suspicious fire monitoring points are flames according to the image data of the suspicious fire monitoring points, and analyzing whether a fire has occurred at the suspicious fire monitoring points based on the combustion risk of the combustibles at the suspicious fire monitoring points and the possibility that the suspicious fire monitoring points are flames.

Description

Technical Field

[0001] The present invention relates to the field of infrared thermal imaging technology, and particularly to a flame recognition method for an infrared thermal imaging detector. Background Art

[0002] An infrared thermal imaging detector is a device that receives the infrared radiation energy emitted by an object, converts it into an electrical signal, and finally generates a visible thermal image. It can capture the temperature distribution on the surface of an object and display the temperature difference in different colors, so as to achieve target detection and recognition. Since the infrared thermal imaging detector is sensitive to high-temperature sources, infrared radiation generated by other high-temperature objects (such as sunlight, industrial equipment, etc.) in outdoor or industrial environments may be misjudged as flames, resulting in a relatively high false alarm rate.

[0003] Most of the existing infrared thermal imaging detectors for flame recognition identify the flame targets in the image by training a large number of labeled data, and cannot first combine the reflection data to exclude the temperature anomalies caused by reflection, and then analyze the fire risk through the ignition point data of combustibles at the temperature anomaly points and the flame possibility, resulting in a reduction in the accuracy of fire recognition.

[0004] To solve the above problems, the present invention provides a flame recognition method for an infrared thermal imaging detector. Summary of the Invention

[0005] The present invention provides a flame recognition method for an infrared thermal imaging detector, which is used to solve the technical problem that the prior art cannot first combine the reflection data to exclude the temperature anomalies caused by reflection, and then analyze the fire risk through the ignition point data of combustibles at the temperature anomaly points and the flame possibility, resulting in a reduction in the accuracy of fire recognition.

[0006] A flame recognition method for an infrared thermal imaging detector provided in the first aspect of the present invention includes:

[0007] S1. Obtain the visualized thermal image generated by the infrared thermal imaging detection component, analyze the temperature anomaly according to the thermal image, and locate the temperature anomaly point;

[0008] S2. Obtain the normal vector of the reflecting surface according to the location and judgment time of the temperature anomaly point, obtain the incident angle and the reflection direction vector according to the position data of the sun, obtain the observation direction vector of the component according to the position data of the infrared thermal imaging detection component, and judge whether the temperature anomaly point is a reflection according to the comparison result between the included angle of the observation direction vector of the component and the reflection direction vector and the half field of view angle of the component, and mark the temperature anomaly point that does not conform to the reflection as a suspicious fire monitoring point;

[0009] S3. Identify the combustibles at the suspicious fire monitoring points, and analyze the combustion risk of the combustibles at the suspicious fire monitoring points according to the ignition point data of the combustibles and the oxygen data;

[0010] S4. Analyze the possibility that the suspicious fire monitoring point is a flame based on the analysis of the image data of the suspicious fire monitoring point;

[0011] S5. Analyze whether a fire has occurred at the suspicious fire monitoring point based on the combustion risk of the combustibles at the suspicious fire monitoring point and the possibility that the suspicious fire monitoring point is a flame.

[0012] Specifically, the S1 includes the following specific steps:

[0013] Obtain the visualized thermal image generated by the infrared thermal imaging detection component, perform grayscale processing on the thermal image, calculate the average gray value of the set area, compare the average gray value of the set area with the pixel threshold converted through the mapping relationship from the set temperature threshold. When the average gray value of the set area is less than the gray threshold, it is judged that the temperature of the set area is normal. When the average gray value of the set area is greater than or equal to the gray threshold, it is judged that the temperature of the set area is abnormal, and obtain the positioning of the temperature abnormal point.

[0014] Specifically, the S2 includes the following specific steps:

[0015] S21. Obtain the positioning and judgment time of the temperature abnormal point, identify the reflecting surface corresponding to the temperature abnormal point, obtain the reflectivity, azimuth angle and tilt angle of the reflecting surface, and obtain the normal vector of the reflecting surface according to the azimuth angle and tilt angle of the reflecting surface;

[0016] S22. Obtain the position data of the sun, where the position data of the sun includes the solar altitude angle and the solar azimuth angle, obtain the solar incident direction vector according to the solar altitude angle and the solar azimuth angle, and obtain the incident angle and the reflected direction vector according to the normal vector of the reflecting surface and the solar incident direction vector;

[0017] S23. Obtain the position data of the infrared thermal imaging detection component, where the position data of the infrared thermal imaging detection component includes the azimuth angle, pitch angle and field of view angle of the component, and obtain the component observation direction vector according to the azimuth angle and pitch angle of the component;

[0018] S24. Obtain the included angle between the component observation direction vector and the reflected direction vector, and judge whether the reflected light can enter the infrared thermal imaging detection component according to the comparison result between the included angle and the half field of view angle of the component. If the included angle is less than or equal to the half field of view angle of the component, it is judged that the reflected light can enter the infrared thermal imaging detection component, and perform the operation of step S25. If the included angle is greater than the half field of view angle of the component, it is judged that the reflected light cannot enter the infrared thermal imaging detection component, and perform the operation of step S3;

[0019] S25. Obtain the reflection intensity according to the incident angle and the reflectivity of the reflecting surface, and obtain the theoretical temperature rise according to the reflection intensity.

[0020] S26. Determine whether the temperature anomaly point is a reflection based on the theoretical temperature rise and the actual temperature rise of the temperature anomaly point. If the theoretical temperature rise is greater than or equal to the actual temperature rise, determine that the temperature anomaly point is a reflection point. If the theoretical temperature rise is less than the actual temperature rise, determine that the temperature anomaly point does not conform to a reflection, and mark the temperature anomaly point that does not conform to a reflection as a suspicious fire monitoring point.

[0021] Specifically, the S3 includes the following specific steps:

[0022] Identify the combustibles at the suspicious fire monitoring point, obtain the ignition point of the combustibles, the minimum oxygen concentration threshold for combustion, the temperature of the current suspicious fire monitoring point, and the oxygen concentration at the current suspicious fire monitoring point, and analyze the combustion risk of the combustibles at the suspicious fire monitoring point.

[0023] Specifically, the S4 includes the following specific steps:

[0024] Obtain the image of the suspicious fire monitoring point after grayscale processing, extract the characteristic data of the suspicious flame area, where the characteristic data of the suspicious flame area includes the flame area growth rate, circularity, and rectangularity, and analyze the possibility that the suspicious fire monitoring point is a flame based on the flame area growth rate, circularity, and rectangularity.

[0025] Specifically, the S5 includes the following specific steps:

[0026] Obtain the fire occurrence risk based on the combustion risk of the combustibles at the suspicious fire monitoring point and the possibility that the suspicious fire monitoring point is a flame. Analyze whether a fire occurs at the suspicious fire monitoring point based on the comparison result between the fire occurrence risk and the preset fire occurrence risk threshold. If the fire occurrence risk is less than the preset fire occurrence risk threshold, determine that no fire has occurred, and the indicator light is always on in green. If the fire occurrence risk is greater than or equal to the preset fire occurrence risk threshold, determine that a fire has occurred, and the indicator light is always on in red.

[0027] A flame recognition system for an infrared thermal imaging detector provided in the second aspect of the present invention is used to implement a flame recognition method for an infrared thermal imaging detector, and includes: a temperature anomaly positioning module, configured to obtain a visual thermal image generated by an infrared thermal imaging detection component, analyze the temperature anomaly according to the thermal image, and locate the temperature anomaly point;

[0028] A reflection analysis module, configured to obtain the normal vector of the reflection surface according to the positioning and judgment time of the temperature anomaly point, obtain the incident angle and the reflection direction vector according to the position data of the sun, obtain the component observation direction vector according to the position data of the infrared thermal imaging detection component, and obtain the included angle between the component observation direction vector and the reflection direction vector;

[0029] A suspicious fire monitoring point analysis module, configured to determine whether the temperature anomaly point is a specular reflection based on the comparison result between the included angle of the component observation direction vector and the reflection direction vector and the half field of view angle of the component, and mark the temperature anomaly points that do not conform to specular reflection as suspicious fire monitoring points;

[0030] A combustion risk analysis module, configured to identify combustibles at the suspicious fire monitoring points and analyze the combustion risk of the combustibles at the suspicious fire monitoring points based on the ignition point data and oxygen data of the combustibles;

[0031] A flame possibility analysis module, configured to analyze the possibility that the suspicious fire monitoring point is a flame based on the image data of the suspicious fire monitoring point;

[0032] A fire recognition module, configured to analyze whether a fire has occurred at the suspicious fire monitoring point based on the combustion risk of the combustibles at the suspicious fire monitoring point and the possibility that the suspicious fire monitoring point is a flame.

[0033] A computer device provided in the third aspect of the present invention includes a memory and a processor. A computer program is stored in the memory. When the computer program is executed by the processor, the processor is caused to execute the steps of a method for flame recognition for an infrared thermal imaging detector as described in any one of the above.

[0034] A computer-readable storage medium provided in the fourth aspect of the present invention has a computer program stored thereon. When the computer program is executed, the steps of a method for flame recognition for an infrared thermal imaging detector as described in any one of the above are implemented.

[0035] A computer program product provided in the fifth aspect of the present invention. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer is caused to execute the steps of a method for flame recognition for an infrared thermal imaging detector as described in any one of the above.

[0036] It can be seen from the above technical solutions that the present invention has the following advantages:

[0037] The present invention analyzes temperature anomalies based on the thermal images generated by an infrared thermal imaging detection component, locates the temperature anomaly points, obtains the angle between the observation direction vector and the reflection direction vector of the component to determine whether the temperature anomaly points are caused by reflection, marks the temperature anomaly points that do not conform to reflection as suspicious fire monitoring points, identifies the combustibles at the suspicious fire monitoring points, analyzes the combustion risk of the combustibles at the suspicious fire monitoring points according to the ignition point data and oxygen data of the combustibles, analyzes the possibility that the suspicious fire monitoring points are flames according to the image data of the suspicious fire monitoring points, and analyzes whether a fire occurs at the suspicious fire monitoring points according to the combustion risk of the combustibles at the suspicious fire monitoring points and the possibility that the suspicious fire monitoring points are flames, thereby improving the accuracy of fire identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following-described drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0039] Figure 1 It is a schematic flowchart of the steps of a method for flame recognition for an infrared thermal imaging detector provided by the present invention;

[0040] Figure 2 It is a schematic flowchart of the steps of step S2 of a method for flame recognition for an infrared thermal imaging detector provided by the present invention;

[0041] Figure 3 It is a schematic structural framework diagram of a system for flame recognition for an infrared thermal imaging detector provided by the present invention;

[0042] Figure 4 It is a schematic structural framework diagram of a computer device provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] The embodiments of the present invention provide a method for flame recognition for an infrared thermal imaging detector, which is used to solve the technical problem that the prior art cannot first combine reflection data to exclude temperature anomalies caused by reflection, and then analyze the fire risk through the ignition point data of combustibles at the temperature anomaly points and the possibility of flames, resulting in a reduction in the accuracy of fire identification.

[0044] In order to make the object, features, and advantages of the present invention more obvious and understandable, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the following described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0045] Please refer to Figure 1 , Figure 1 which is a schematic flow chart of the steps of a flame recognition method for an infrared thermal imaging detector provided by the present invention.

[0046] A flame recognition method for an infrared thermal imaging detector provided by the present invention includes:

[0047] S1. Obtain the visualized thermal image generated by the infrared thermal imaging detection component, analyze the temperature anomaly according to the thermal image, and locate the temperature anomaly point;

[0048] In this embodiment, S1 includes the following specific steps:

[0049] Obtain the visualized thermal image generated by the infrared thermal imaging detection component. Infrared thermal imaging technology is a technology that detects the infrared ray signals of the thermal radiation of an object and converts them into images or graphics that can be distinguished by the human vision. The surface of the object emits infrared radiation according to its temperature. The infrared thermal imaging fire detector captures the radiation signals through a vanadium oxide uncooled infrared focal plane imaging detection component, and then converts the received infrared light signals into electrical signals. After the electrical signals are processed, a thermal image that can be recognized by the human vision is generated, showing the temperature distribution of the object. The vanadium oxide uncooled infrared focal plane imaging detection component forms an image through infrared rays with a response band of 8-14 μm, which can reduce the interference factors of non-contact temperature measurement;

[0050] Perform grayscale processing on the thermal image and calculate the average grayscale of the set area. In specific implementation, the calculation of the average grayscale of the set area can select the following formula: , where is the average grayscale of the set area, is the length of the set area, is the width of the set area, is the pixel value of the coordinate point (i, j), is the total pixel value of the set area;

[0051] Compare the average grayscale of the set area with the pixel threshold converted through the mapping relationship of the set temperature threshold. In specific implementation, the calculation of converting the set temperature threshold into a pixel threshold through the mapping relationship can select the following formula: , where is the pixel threshold converted from the set temperature threshold through the mapping relationship, is the set temperature threshold, is the total temperature measurement span of the infrared thermal imaging fire detector. In this embodiment, the temperature measurement range of the infrared thermal imaging fire detector is -20°C to 550°C. Therefore, the total temperature measurement span is 570°C, and the pixel range of the 8-bit grayscale image is (0, 255). Multiplying the above formula by 256 is used to uniformly map the set temperature threshold to the complete 256-pixel value interval;

[0052] When the average grayscale of the set area is less than the grayscale threshold, it is judged that the temperature of the set area is normal. When the average grayscale of the set area is greater than or equal to the grayscale threshold, it is judged that the temperature of the set area is abnormal, and the positioning of the temperature abnormal point is obtained. In specific implementation, obtaining the positioning of the temperature abnormal point includes the distance and angle between the temperature abnormal point and the center point of the set area. The calculation of obtaining the distance between the temperature abnormal point and the center point of the set area can select the following formula: , where is the distance between the temperature abnormal point and the center point of the set area, is the abscissa of the coordinate point (i, j), is the abscissa of the center point of the set area, is the abscissa of the image moment of the temperature abnormal area, is the ordinate of the coordinate point (i, j), is the ordinate of the center point of the set area, is the ordinate of the image moment of the temperature abnormal area. The calculation of obtaining the angle can select the following formula: , where is the angle between the temperature abnormal point and the center point of the set area. The above formula calculates the distance and angle between the temperature abnormal point and the center point of the area through the image moment, improving the accuracy of the positioning of the temperature abnormal point. In this embodiment, the average grayscale of the set area is calculated and compared with the pixel threshold converted from the set temperature threshold through the mapping relationship, subtracting the calculation amount of the non-key area while ensuring the coverage of the key monitoring range, and improving the efficiency of the temperature abnormal judgment.

[0053] Exemplarily, in order to prevent coal spontaneous combustion and monitor equipment anomalies, a certain coal loading and unloading terminal installed ten infrared thermal imaging fire detectors with a field of view of 90.0° * 62.5° to comprehensively and continuously monitor the terminal conveyor belt, obtain the visual thermal images generated by the infrared thermal imaging fire detectors, perform grayscale processing on the thermal images, and obtain the average grayscale of the temperature fluctuation area. Since the conveyor belt transports coal, combined with the characteristics of coal spontaneous combustion and safety standards, the set temperature threshold can be set to 70 - 80 °C, and it can also be adjusted up and down by 5 °C in combination with the high-temperature and high-humidity environment. For example, when the set temperature threshold is set to 80 °C, the corresponding pixel threshold is 80 °C / 570 °C × 256 ≈ 36. Obtain the distance and angle between the temperature anomaly point and the center point of the area where the average grayscale is greater than or equal to 36, and locate the temperature anomaly point.

[0054] S2. Obtain the normal vector of the reflection surface according to the positioning and judgment time of the temperature anomaly point, obtain the incident angle and the reflected direction vector according to the position data of the sun, obtain the observation direction vector of the component according to the position data of the infrared thermal imaging detection component, and judge whether the temperature anomaly point is a specular reflection according to the comparison result between the included angle between the observation direction vector of the component and the reflected direction vector and the half field of view angle of the component. Mark the temperature anomaly points that do not conform to specular reflection as suspicious fire monitoring points;

[0055] Please refer to Figure 2 , Figure 2 which is a schematic flow chart of step S2 of a flame recognition method for an infrared thermal imaging detector provided by the present invention.

[0056] In this embodiment, S2 includes the following specific steps:

[0057] S21. Obtain the positioning and judgment time of the temperature anomaly point, identify the reflection surface corresponding to the temperature anomaly point, obtain the reflectivity, azimuth angle, and tilt angle of the reflection surface. In specific implementation, the reflectivity of the reflection surface is directly measured using an infrared reflectivity measuring instrument, the azimuth angle can be obtained by measuring the projection direction of the normal line of the reflection surface on the horizontal plane with a compass (north is 0°, increasing clockwise), and the tilt angle can be obtained by measuring the angle between the reflection surface and the horizontal plane with an inclinometer (horizontal is 0°, vertical is 90°); obtain the normal vector of the reflection surface according to the azimuth angle and tilt angle of the reflection surface; in specific implementation, the normal vector of the reflection surface can be expressed as: , is the tilt angle of the reflection surface, is the azimuth angle of the reflection surface;

[0058] S22. Obtain the position data of the sun. The position data of the sun includes the solar altitude angle and the solar azimuth angle. In specific implementation, the calculation of the solar altitude angle can choose the following formula: , where is the solar altitude angle, is the local latitude, is the solar declination, is the hour angle. The solar declination and the hour angle can be obtained in real time through astronomical software or through existing calculation formulas. For example, the solar declination can be obtained through calculation, is the day of the year. For example, January 1st is 1. The hour angle can be obtained through calculation, is the true solar time, expressed in 24-hour format. During actual calculation, it needs to be corrected according to the equation of time difference between local time and true solar time;

[0059] The calculation of the solar azimuth angle can select the following formula: , where is the solar azimuth angle;

[0060] Obtain the solar incident direction vector based on the solar altitude angle and the solar azimuth angle. During specific implementation, the solar incident direction vector can be expressed as: ;

[0061] Obtain the incident angle and the reflected direction vector based on the normal vector of the reflecting surface and the solar incident direction vector; During specific implementation, the calculation of the incident angle can select the following formula: , where is the dot product between vectors;

[0062] The reflected direction vector can be obtained according to the law of reflection, specifically: ;

[0063] S23. Obtain the position data of the infrared thermal imaging detection component. The position data of the infrared thermal imaging detection component includes the azimuth angle, pitch angle, and field of view angle of the component. During specific implementation, the azimuth angle can be obtained by measuring the horizontal direction pointed by the thermal imager lens with a compass, and the pitch angle can be obtained by measuring the angle between the lens and the horizontal plane with an inclinometer;

[0064] Obtain the component observation direction vector based on the azimuth angle and pitch angle of the component; During specific implementation, the component observation direction vector can be expressed as: , is the pitch angle of the component, is the azimuth angle of the component;

[0065] S24. Obtain the included angle between the component observation direction vector and the reflected direction vector. During specific implementation, the comparison between the included angle and the field of view angle of the component can select the following formula: , where is the modulus of the vector. According to the comparison result between the included angle and the half field of view angle of the component, it is determined whether the reflected light can enter the infrared thermal imaging detection component. The half field of view angle is the maximum allowable deviation angle of the infrared thermal imaging detection component relative to the center line. If the included angle is less than or equal to the half field of view angle of the component, it is determined that the reflected light can enter the infrared thermal imaging detection component, and the operation of step S25 is performed. If the included angle is greater than the half field of view angle of the component, it is determined that the reflected light cannot enter the infrared thermal imaging detection component, and the operation of step S3 is performed;

[0066] S25. Obtain the reflection intensity according to the incident angle and the reflectivity of the reflection surface, and obtain the theoretical temperature rise according to the reflection intensity. In specific implementation, the calculation of the reflection intensity can select the following formula: , where is the reflection intensity, is the reflectivity of the reflection surface, is the solar irradiance, which can be measured by a solar irradiance meter or monitored by converting solar radiation into an electrical signal through the photovoltaic effect, is the area of the reflection surface actually irradiated by the sun. The calculation of the area of the reflection surface actually irradiated by the sun can select the following formula: , where is the area of the reflection surface actually irradiated by the sun, is the total area of the reflection surface, which can be measured by a laser rangefinder;

[0067] The calculation of the theoretical temperature rise can select the following formula: , where is the theoretical temperature rise, is a constant, approximately 5.67×10 -8 W / (m²·K 4 );

[0068] S26. Determine whether the temperature anomaly point is a reflection according to the theoretical temperature rise and the actual temperature rise of the temperature anomaly point. If the theoretical temperature rise is greater than or equal to the actual temperature rise, it is determined that the temperature anomaly point is a reflection point. If the theoretical temperature rise is less than the actual temperature rise, it is determined that the temperature anomaly point does not conform to the reflection, and the temperature anomaly point that does not conform to the reflection is marked as a suspicious fire monitoring point.

[0069] Exemplarily, a certain coal loading and unloading terminal locates a temperature anomaly point at 10:00 am. The azimuth angle of the reflection surface is 150°, the tilt angle is 30°, the azimuth angle of the infrared thermal imaging fire detector is 90°, the tilt angle is 0°, the solar altitude angle is 45°, and the solar azimuth angle is 120°. Then the normal vector of the reflection surface , the solar incident direction vector , the reflection direction vector , the component observation direction vector , the included angle between the component observation direction vector and the reflection direction vector is approximately 81.2°, which is greater than the half field of view angle. Therefore, the reflected light cannot enter the infrared thermal imaging detection component, and this temperature anomaly point is not caused by reflection.

[0070] S3. Identify the combustibles at the suspicious fire monitoring point, and analyze the combustion risk of the combustibles at the suspicious fire monitoring point based on the ignition point data and oxygen data of the combustibles;

[0071] In this embodiment, S3 includes the following specific steps:

[0072] Identify the combustibles at the suspicious fire monitoring point, obtain the ignition point of the combustibles, the minimum oxygen concentration threshold for combustion, the temperature of the current suspicious fire monitoring point, and the oxygen concentration of the current suspicious fire monitoring point, and analyze the combustion risk of the combustibles at the suspicious fire monitoring point. In specific implementation, the calculation of the combustion risk of the combustibles can select the following formula: , where is the combustion risk of the combustibles, is the oxygen concentration of the current suspicious fire monitoring point, is the minimum oxygen concentration threshold for combustion. When , the minimum oxygen concentration threshold for combustible combustion is not reached, the value of is taken as 0, is the temperature of the current suspicious fire monitoring point, and are used to adjust the non-linear effects of temperature and oxygen concentration. In this embodiment , the above formula improves the efficiency of evaluating the risk level by analyzing the contribution degree of oxygen concentration and the proximity between the temperature of the current suspicious fire monitoring point and the ignition point;

[0073] Exemplarily, the ignition point of coal at a certain coal loading and unloading terminal is 300°, the minimum oxygen concentration threshold for combustion is 12%, the oxygen concentration of the currently monitored suspicious fire monitoring point is 16%, and the temperature of the currently monitored suspicious fire monitoring point is 84°. Then the combustion risk of the combustibles at this suspicious fire monitoring point is ×0.28≈0.093.

[0074] S4. Analyze the possibility that the suspicious fire monitoring point is a flame based on the image data of the suspicious fire monitoring point;

[0075] In this embodiment, S4 includes the following specific steps:

[0076] Obtain the image of the suspicious fire monitoring point after grayscale processing, and extract the characteristic data of the suspicious flame area. The characteristic data of the suspicious flame area includes the flame area growth rate, circularity, and rectangularity;

[0077] In specific implementation, the calculation of the flame area growth rate can select the following formula: , where is the flame area growth rate at time t1, is the flame area growth rate at time t0, is the area of the flame region at time t1. After binarizing the image, the pixel points with a pixel value of 255 are screened out, and the flame area is the sum of the pixel points. is the area of the flame region at time t0. The above formula reflects the trend of the flame spreading rapidly to the surrounding according to the flame area growth rate;

[0078] The calculation of circularity can select the following formula: , where is the circularity, is the area of the flame region, is the perimeter of the flame region. The above formula calculates the degree of approximation of the flame region shape to a circle. The flame shape is not fixed, and the closer it is to a circle, the lower the possibility that it is a flame;

[0079] The calculation of rectangularity can select the following formula: , where is the rectangularity, is the area of the minimum bounding rectangle of the flame region area. The above formula calculates the degree of approximation of the flame region shape to the bounding rectangle. The flame contour has roughness, and the closer it is to the bounding rectangle, the lower the possibility that it is a flame;

[0080] Analyze the possibility that the suspicious fire monitoring point is a flame based on the flame area growth rate, circularity, and rectangularity. In specific implementation, the calculation of the possibility that the suspicious fire monitoring point is a flame can select the following formula: , where is the possibility that the suspicious fire monitoring point is a flame.

[0081] S5. Analyze whether a fire has occurred at the suspicious fire monitoring point based on the combustion risk of the combustible at the suspicious fire monitoring point and the possibility that the suspicious fire monitoring point is a flame.

[0082] In this embodiment, S5 includes the following specific steps:

[0083] Obtain the fire occurrence risk based on the combustion risk of the combustible at the suspicious fire monitoring point and the possibility that the suspicious fire monitoring point is a flame. In specific implementation, the fire occurrence risk can select the following formula: , where is the fire occurrence risk, and the exponents and For adjusting the non - linear influence of the combustion risk of combustibles and the possibility that the suspicious fire monitoring point is a flame, in this embodiment ;

[0084] According to the comparison result between the fire occurrence risk and the preset fire occurrence risk threshold, analyze whether a fire has occurred at the suspicious fire monitoring point. In specific implementation, the fire occurrence risk threshold is obtained by calculating the average fire occurrence risk through the combustion risk of combustibles and the possibility that the suspicious fire monitoring point is a flame after identifying temperature anomalies from the thermal images collected from the historical fires in this area. If the fire occurrence risk is less than the preset fire occurrence risk threshold, it is judged that no fire has occurred, and the indicator light is constantly green. If the fire occurrence risk is greater than or equal to the preset fire occurrence risk threshold, it is judged that a fire has occurred, and the indicator light is constantly red.

[0085] In summary, the infrared thermal imaging fire detector used in this embodiment detects fires by analyzing the flames generated during the combustion process through video images. It adopts a vanadium oxide uncooled infrared focal plane imaging detection component, and based on video image analysis technology and artificial intelligence deep learning technology, it conducts early temperature and flame detection on the protected area. It has functions such as temperature monitoring, fire warning, fire detection, video monitoring, and event detection, and can realize video display, control, storage, playback, automatic processing of alarm information, alarm recording, automatic calculation and calibration of the fire point position, and false alarm area management. It is suitable for fire prevention automated remote monitoring and warning, and is applicable to key area sites such as forests, converter transformers, wharf conveyors, energy storage power stations, and dry coal sheds.

[0086] Please refer to Figure 3 , Figure 3 which is a schematic structural framework diagram of a flame recognition system for an infrared thermal imaging detector provided by the present invention.

[0087] A flame recognition system for an infrared thermal imaging detector provided by the present invention includes: a temperature anomaly positioning module, which is used to obtain the visualized thermal image generated by the infrared thermal imaging detection component, analyze the temperature anomaly according to the thermal image, and locate the temperature anomaly point;

[0088] A specular reflection analysis module, which is used to obtain the normal vector of the reflection surface according to the location and judgment time of the temperature anomaly point, obtain the incident angle and the reflection direction vector according to the position data of the sun, obtain the observation direction vector of the component according to the position data of the infrared thermal imaging detection component, and obtain the included angle between the observation direction vector of the component and the reflection direction vector;

[0089] A suspicious fire monitoring point analysis module, which is used to judge whether the temperature anomaly point is a specular reflection according to the comparison result between the included angle between the observation direction vector of the component and the reflection direction vector and the half - field - of - view angle of the component, and mark the temperature anomaly points that do not conform to specular reflection as suspicious fire monitoring points;

[0090] A combustion risk analysis module for identifying combustibles at suspicious fire monitoring points and analyzing the combustion risk of the combustibles at the suspicious fire monitoring points based on the ignition point data and oxygen data of the combustibles;

[0091] A flame possibility analysis module for analyzing the possibility that a suspicious fire monitoring point is a flame based on the image data of the suspicious fire monitoring point;

[0092] A fire identification module for analyzing whether a fire has occurred at a suspicious fire monitoring point based on the combustion risk of the combustibles at the suspicious fire monitoring point and the possibility that the suspicious fire monitoring point is a flame.

[0093] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, modules, and sub-modules described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0094] Please refer to Figure 4 , Figure 4 which is a schematic structural framework diagram of a computer device provided by the present invention.

[0095] An embodiment of the present invention further provides a computer device, including a memory and a processor. When a computer program stored in the memory is executed by the processor, the processor executes the steps of a method for flame recognition for an infrared thermal imaging detector as described above.

[0096] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program / instructions are stored. When the computer program / instructions are executed by a processor, the steps of a method for flame recognition for an infrared thermal imaging detector as described above are implemented.

[0097] An embodiment of the present invention further provides a computer program product, including a computer program / instructions. When the computer program / instructions are executed by a processor, the steps of a method for flame recognition for an infrared thermal imaging detector as described above are implemented.

[0098] In several embodiments provided by the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical, or other forms.

[0099] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example, and moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0100] In addition, each functional unit in various embodiments of the present invention may be integrated into a processing unit, may exist physically alone for each unit, or two or more units may be integrated into one unit.

[0101] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0102] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A flame recognition method for an infrared thermal imaging detector, characterized in that, Including: S1. Obtain the visualized thermal image generated by the infrared thermal imaging detection component, analyze the temperature anomaly according to the thermal image, and locate the temperature anomaly point; S2. Obtain the normal vector of the reflection surface according to the location and judgment time of the temperature anomaly point, obtain the incident angle and the reflection direction vector according to the position data of the sun, obtain the observation direction vector of the component according to the position data of the infrared thermal imaging detection component, and judge whether the temperature anomaly point is a reflection according to the comparison result between the included angle of the component observation direction vector and the reflection direction vector and the half field of view angle of the component, and mark the temperature anomaly point that does not conform to the reflection as a suspicious fire monitoring point; The S2 includes the following specific steps: S21. Obtain the location and judgment time of the temperature anomaly point, identify the reflection surface corresponding to the temperature anomaly point, obtain the reflectivity, azimuth angle and tilt angle of the reflection surface, and obtain the normal vector of the reflection surface according to the azimuth angle and tilt angle of the reflection surface; S22. Obtain the position data of the sun, the position data of the sun includes the solar altitude angle and the solar azimuth angle, obtain the solar incident direction vector according to the solar altitude angle and the solar azimuth angle, and obtain the incident angle and the reflection direction vector according to the normal vector of the reflection surface and the solar incident direction vector; S23. Obtain the position data of the infrared thermal imaging detection component, the position data of the infrared thermal imaging detection component includes the azimuth angle, pitch angle and field of view angle of the component, and obtain the observation direction vector of the component according to the azimuth angle and pitch angle of the component; S24. Obtain the included angle between the component observation direction vector and the reflection direction vector, and judge whether the reflected light can enter the infrared thermal imaging detection component according to the comparison result between the included angle and the half field of view angle of the component. If the included angle is less than or equal to the half field of view angle of the component, it is judged that the reflected light can enter the infrared thermal imaging detection component, and perform the operation of step S25. If the included angle is greater than the half field of view angle of the component, it is judged that the reflected light cannot enter the infrared thermal imaging detection component, and perform the operation of step S3; S25. Obtain the reflection intensity according to the incident angle and the reflectivity of the reflection surface, and obtain the theoretical temperature rise according to the reflection intensity; S26. Judge whether the temperature anomaly point is a reflection according to the comparison between the theoretical temperature rise and the actual temperature rise of the temperature anomaly point. If the theoretical temperature rise is greater than or equal to the actual temperature rise, it is judged that the temperature anomaly point is a reflection point. If the theoretical temperature rise is less than the actual temperature rise, it is judged that the temperature anomaly point does not conform to the reflection, and mark the temperature anomaly point that does not conform to the reflection as a suspicious fire monitoring point; S3. Identify the combustibles at the suspicious fire monitoring point, and analyze the combustion risk of the combustibles at the suspicious fire monitoring point according to the ignition point data and oxygen data of the combustibles; S4. Analyze the possibility that the suspicious fire monitoring point is a flame according to the image data of the suspicious fire monitoring point; S5. Analyze whether a fire has occurred at the suspicious fire monitoring point according to the combustion risk of the combustibles at the suspicious fire monitoring point and the possibility that the suspicious fire monitoring point is a flame.

2. The flame recognition method for an infrared thermal imaging detector according to claim 1, characterized in that, The S1 includes the following specific steps: Obtain the visualized thermal image generated by the infrared thermal imaging detection component, perform grayscale processing on the thermal image, calculate the average grayscale of the set area, compare the average grayscale of the set area with the pixel threshold converted by the set temperature threshold through the mapping relationship. When the average grayscale of the set area is less than the grayscale threshold, it is judged that the temperature of the set area is normal. When the average grayscale of the set area is greater than or equal to the grayscale threshold, it is judged that the temperature of the set area is abnormal, and obtain the positioning of the temperature abnormal point.

3. The flame recognition method for an infrared thermal imaging detector according to claim 2, characterized in that The S3 includes the following specific steps: Identify the combustibles at the suspicious fire monitoring point, obtain the ignition point of the combustibles, the lowest oxygen concentration threshold for combustion, the temperature of the current suspicious fire monitoring point, and the oxygen concentration of the current suspicious fire monitoring point, and analyze the combustion risk of the combustibles at the suspicious fire monitoring point.

4. A flame recognition method for an infrared thermal imaging detector according to claim 3, characterized in that, The S4 includes the following specific steps: Obtain the image after grayscale processing of the suspicious fire monitoring point, extract the characteristic data of the suspicious flame area. The characteristic data of the suspicious flame area includes the flame area growth rate, circularity, and rectangularity, and analyze the possibility of the suspicious fire monitoring point being a flame according to the flame area growth rate, circularity, and rectangularity.

5. A method for flame recognition for an infrared thermal imaging detector according to claim 4, characterized in that, The S5 includes the following specific steps: Obtain the fire occurrence risk according to the combustion risk of the combustibles at the suspicious fire monitoring point and the possibility of the suspicious fire monitoring point being a flame. Analyze whether a fire occurs at the suspicious fire monitoring point according to the comparison result between the fire occurrence risk and the preset fire occurrence risk threshold. If the fire occurrence risk is less than the preset fire occurrence risk threshold, it is judged that no fire has occurred. If the fire occurrence risk is greater than or equal to the preset fire occurrence risk threshold, it is judged that a fire has occurred.

6. A flame recognition system for an infrared thermal imaging detector, which is used to implement the method for flame recognition for an infrared thermal imaging detector according to any one of claims 1-5, and is characterized in that, Include: A temperature anomaly positioning module, which is used to obtain the visualized thermal image generated by the infrared thermal imaging detection component, analyze the temperature anomaly according to the thermal image, and locate the temperature anomaly point; A reflection analysis module, which is used to obtain the normal vector of the reflection surface according to the positioning of the temperature anomaly point and the judgment time, obtain the incident angle and the reflection direction vector according to the position data of the sun, obtain the component observation direction vector according to the position data of the infrared thermal imaging detection component, and obtain the included angle between the component observation direction vector and the reflection direction vector; A suspicious fire monitoring point analysis module, which is used to judge whether the temperature anomaly point is a reflection according to the comparison result between the included angle between the component observation direction vector and the reflection direction vector and the half field of view angle of the component, and mark the temperature anomaly point that does not conform to the reflection as a suspicious fire monitoring point; A combustion risk analysis module, which is used to identify the combustibles at the suspicious fire monitoring point and analyze the combustion risk of the combustibles at the suspicious fire monitoring point according to the ignition point data and oxygen data of the combustibles; A flame possibility analysis module, which is used to analyze the possibility of the suspicious fire monitoring point being a flame according to the image data of the suspicious fire monitoring point; A fire identification module, which is used to analyze whether a fire occurs at the suspicious fire monitoring point according to the combustion risk of the combustibles at the suspicious fire monitoring point and the possibility of the suspicious fire monitoring point being a flame.

7. A computer device, characterized in that, It includes a memory and a processor. A computer program is stored in the memory. When the computer program is executed by the processor, the processor is caused to execute the steps of a flame recognition method for an infrared thermal imaging detector as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements a flame recognition method for an infrared thermal imaging detector as described in any one of claims 1-5.

9. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer is caused to execute a flame recognition method for an infrared thermal imaging detector as described in any one of claims 1-5.

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