Forest fire monitoring and identification method based on atmospheric electric field instrument

Abstract

The invention relates to the field of forest fire monitoring, and discloses a forest fire monitoring identification method based on an atmospheric electric field instrument, which comprises a forest fire monitor for identifying forest fire, the forest fire monitor is provided with a thermal imager and an airflow monitor, the thermal imager is used for monitoring the temperature of a target object and generating a thermal image, and the airflow monitor is used for monitoring the temperature of the target object. The airflow monitor is used for monitoring the flowing speed of airflow around the forest fire monitor, when a forest fire occurs, as flame heats air, strong convective motion can be generated, the convective motion can change the flowing speed of the airflow around, and therefore monitoring of the change of the airflow speed can serve as an auxiliary index for judging whether the forest fire occurs or not. In combination with data of the thermal imager and the airflow monitor, whether forest fire exists or not can be judged more accurately.

Description

Technical Field

[0001] The invention relates to the field of forest fire monitoring, and in particular to a forest fire monitoring and identification method based on an atmospheric electric field instrument. Background Art

[0002] Forest fire is one of the common disasters in forest ecosystems. Once a forest fire occurs, it will not only have a serious impact on biodiversity, but also threaten human life and property. Therefore, it is crucial to monitor and respond to forest fires in a timely manner. At present, forest fire monitoring technology mainly relies on video surveillance and meteorological radar. Video surveillance uses high-definition cameras to monitor forests in real time, and uses image processing and pattern recognition technology to identify flames and smoke, so as to achieve the purpose of early warning and monitoring. This method has the characteristics of all-weather and strong real-time performance, and can provide rich terrain and personnel activity information, which is convenient for forest fire prevention. However, the coverage of video surveillance is relatively limited, and it is greatly affected by weather conditions such as cloud and fog obstruction and terrain, which may lead to monitoring blind spots or false alarms. Meteorological radar identifies fire conditions by detecting water vapor and particulate matter in the atmosphere. When a forest fire occurs, flames and smoke will generate specific radar echo signals. Forest fire monitoring can be achieved by analyzing and processing these signals, but the monitoring accuracy of meteorological radar is often affected by many factors, such as radar beam width, resolution, detection height and environmental factors, resulting in certain limitations in practical applications. Summary of the invention

[0003] The present invention provides a forest fire monitoring and identification method based on an atmospheric electric field instrument, which overcomes the shortcomings described in the background technology.

[0004] The technical solution adopted by the present invention to solve its technical problem is: A forest fire monitoring and identification method based on an atmospheric electric field instrument comprises a forest fire monitoring instrument for identifying forest fires, wherein the forest fire monitoring instrument is provided with a thermal imager and an airflow monitor, wherein the thermal imager is used to monitor the temperature of a target object and generate a thermal image, and the airflow monitor is used to monitor the airflow velocity around the forest fire monitoring instrument; Among them, the forest fire monitoring and identification method includes the following specific steps: S1: Use a thermal imager to monitor and capture the temperature of the target object, generate a video of the monitored temperature through thermal imaging, and merge the three color components of red, green and blue in the video into a single grayscale value to generate a grayscale image, so that the grayscale image only contains brightness information; S2: dividing the video image into 25 regional images of a rectangular array with a length of five and a width of five, representing the brightness information in the regional images by grayscale values ​​of 0 to 255, and recording the grayscale values ​​of the grayscale images in all the regional images; S3: In the brightness information of the images in all areas between 0 and 255, a gray value threshold is set, and whether it is a fire area is determined by the gray value threshold.

[0005] A preferred technical solution, in step S3, when determining whether it is a fire area based on the gray value threshold, the degree of fire is determined by the percentage of the area images determined to be the fire area to all the area images; When there is no fire area, it is safe; When the number of regional images of the fire area accounts for 1% to 5% of the number of all regional images, it is suspected to be on fire; When the number of regional images of the fire area accounts for more than 5% of the number of all regional images, a fire alarm is issued.

[0006] A preferred technical solution is that in step S1, while the temperature of the target object is monitored and captured by a thermal imager, the gas flow speed around the forest fire monitor is also monitored by an airflow monitor.

[0007] A preferred technical solution is to connect the airflow monitor to the network terminal, obtain the temperature and wind speed information of the monitoring site in real time through the network connection, record the airflow velocity of the monitoring site in real time, and take the highest value of the airflow velocity in 0.5h, and use the highest value to determine the airflow velocity threshold of the monitoring site; Among them, when the gas flow velocity monitored by the airflow monitor exceeds the airflow velocity threshold of the monitoring location, the time of exceeding the airflow velocity threshold of the monitoring location is used to determine whether it is abnormal airflow flow. When the airflow velocity threshold of the monitoring location is exceeded for 1 minute, abnormal airflow flow is determined and the fire is confirmed at the same time.

[0008] Compared with the prior art, this technical solution has the following advantages: The smoke and particulate matter released by forest fires can act as carriers of charged particles. When these charged particles move in the atmosphere, they interact with other charged particles or electric fields in the atmosphere, thereby affecting the distribution and intensity of the atmospheric electric field. More specifically, smoke and particulate matter increase the charge concentration in the atmosphere, resulting in an increase in the electric field strength. Monitoring the gas flow velocity around the forest fire monitor through an airflow monitor can assist in determining whether a forest fire exists. When a forest fire occurs, the flames heat the air and produce strong convection motion, which changes the surrounding airflow velocity. Therefore, monitoring changes in airflow velocity can be used as an auxiliary indicator for determining whether a forest fire has occurred. Combining the data from thermal imagers and airflow monitors, it is possible to more accurately determine whether a forest fire exists. For example, when a thermal imager detects a high temperature area but the airflow monitor does not detect a significant change in airflow, it may indicate that the high temperature area is not caused by a forest fire, but by other factors such as solar radiation, geothermal heat, etc. This can reduce misjudgments caused by false alarms from a single sensor. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0010] Figure 1 Logic diagram of forest fire monitoring identification method.

[0011] Figure 2 This is a schematic diagram of a forest fire monitoring instrument.

[0012] Figure 3 for Figure 2 Schematic side view of .

[0013] Figure 4 A schematic diagram of a fixed component.

[0014] Figure 5 Schematic diagram of the tightening disk.

[0015] Figure 6 Schematic diagram of the tightening belt.

[0016] In the picture: Forest fire monitoring instrument 1; Thermal imager 2; Airflow monitor 3; Fixed shell 4, slot 41; Fixed component 5, tightening disk 51, inner disk 511, outer disk 512, torsion spring 513, tightening belt 52, belt body 521, swing rod 1 522, swing rod 2 523, connecting rod 524, connecting button 525, spring 526, motor 53; Electric field meter6. DETAILED DESCRIPTION Embodiment 1

[0017] like Figure 1 As shown, the present invention proposes a forest fire monitoring and identification method based on an atmospheric electric field instrument, comprising a forest fire monitoring instrument 1 for identifying forest fires, wherein the forest fire monitoring instrument 1 is provided with a thermal imager 2 and an airflow monitor 3, wherein the thermal imager 2 is used to monitor the temperature of a target object and generate a thermal image, and the airflow monitor 3 is used to monitor the airflow velocity around the forest fire monitoring instrument 1; Among them, the forest fire monitoring and identification method includes the following specific steps: S1: using the thermal imager 2 to monitor and capture the temperature of the target object, and generating a video of the monitored temperature through thermal imaging, and merging the three color components of red, green and blue in the video into a single grayscale value to generate a grayscale image, so that the grayscale image only contains brightness information; S2: dividing the video image into 25 regional images of a rectangular array with a length of five and a width of five, representing the brightness information in the regional images by grayscale values ​​of 0 to 255, and recording the grayscale values ​​of the grayscale images in all the regional images; S3: In the brightness information of the images in all areas between 0 and 255, a gray value threshold is set, and whether it is a fire area is determined by the gray value threshold.

[0018] A preferred technical solution, in step S3, when determining whether it is a fire area based on the gray value threshold, the degree of fire is determined by the percentage of the area images determined to be the fire area to all the area images; When there is no fire area, it is safe; When the number of regional images of the fire area accounts for 1% to 5% of the number of all regional images, it is suspected to be on fire; When the number of regional images of the fire area accounts for more than 5% of the number of all regional images, a fire alarm is issued.

[0019] Among them, in step S1, the generated video can be subjected to noise reduction processing by value filtering to improve the smoothness of the video and increase the recognition accuracy; The core idea of ​​median filtering is to use the relationship between pixel values ​​to remove noise. For median filtering, its basic principle is to replace the value of a point in a digital image or digital sequence with the median of the values ​​of each point in a neighborhood of the point, so that the surrounding pixel values ​​are close to the true value, thereby eliminating isolated noise points. Mean filtering is a typical linear filtering algorithm, which replaces the original pixel value with the average value of all pixels in the template. However, while removing noise, mean filtering will also destroy the details of the image and make the image blurred.

[0020] Furthermore, since forest fires release a large amount of heat, smoke and particulate matter, these substances will change the physical and chemical properties of the atmosphere. Specifically, the heat released by forest fires will heat the atmosphere, causing the air to rise and form convection, further affecting the vertical movement of the atmosphere. This vertical movement can affect the distribution and intensity of the atmospheric electric field. Therefore, in step S1, while the temperature of the target object is monitored and captured by the thermal imager 2, the gas flow velocity around the forest fire monitor 1 is also monitored by the airflow monitor 3; By monitoring the gas flow velocity around the forest fire monitor 1 through the airflow monitor 3, it can assist in determining whether there is a forest fire. When a forest fire occurs, the flames heat the air and produce strong convection motion, which changes the surrounding airflow velocity. Therefore, monitoring changes in airflow velocity can be used as an auxiliary indicator to determine whether a forest fire has occurred. Combining the data from the thermal imager 2 and the airflow monitor 3, it can be more accurately determined whether there is a forest fire. For example, when the thermal imager detects a high temperature area but the airflow monitor does not detect significant airflow changes, it may indicate that the high temperature area is not caused by a forest fire, but by other factors such as solar radiation, geothermal heat, etc. This can reduce misjudgments caused by false alarms from a single sensor; The greater the intensity of the forest fire, the more heat is released and the stronger the convection movement is. Therefore, by monitoring the changes in airflow speed, the intensity of the forest fire can be indirectly assessed. The faster the airflow speed, the greater the intensity of the forest fire and the more urgent response measures need to be taken. The convection movement generated by the forest fire will push smoke and particulate matter to spread in a specific direction. By monitoring the direction and intensity of the airflow speed, the spread direction of the forest fire can be predicted, providing important decision-making basis for firefighters.

[0021] Furthermore, the airflow monitor 3 is connected to the network terminal, and the temperature and wind speed information of the monitoring site are obtained in real time through the network connection, the airflow velocity of the monitoring site is recorded in real time, and the highest value of the airflow velocity in 0.5h is taken, and the threshold value of the airflow velocity of the monitoring site is determined by the highest value; Among them, when the gas flow velocity monitored by the airflow monitor 3 exceeds the monitoring airflow velocity threshold, the time of exceeding the monitoring airflow velocity threshold is used to determine whether it is abnormal airflow flow. When it exceeds the monitoring airflow velocity threshold for 1 minute, abnormal airflow flow is determined and the fire is confirmed at the same time.

[0022] Although weather radar can detect water vapor and particulate matter in the atmosphere to identify fire conditions, its monitoring accuracy is affected by many factors, such as the width of the radar beam, resolution, detection height, and environmental factors. By setting a wind speed threshold through an airflow monitor and combining it with real-time wind speed data, it is possible to more accurately determine whether a forest fire has occurred and reduce false alarms and missed reports. Especially in the early stages of a forest fire, the flames and smoke may not be obvious enough, but the changes in airflow speed may be more significant, so the airflow monitor can provide an earlier warning. Real-time recording of the airflow velocity at the monitoring site and taking the highest value in 0.5h as the threshold can more objectively reflect the airflow characteristics of the monitoring site. When the gas flow velocity detected by the airflow monitor exceeds this threshold, combined with the time it exceeds the threshold, it can be judged whether it is an abnormal airflow flow, which can more accurately determine whether a forest fire has occurred. This method is more timely and accurate, and helps firefighters take timely measures to extinguish the fire.

[0023] By obtaining real-time wind speed information at the monitoring site through network terminals, the layout of the forest fire monitoring system can be optimized. In areas with fast wind speeds and strong convective movements, the number or density of monitoring equipment can be increased to improve monitoring coverage and accuracy. At the same time, adjusting the operating strategy of the monitoring system according to real-time wind speed data can save resources and energy and improve monitoring efficiency.

[0024] When monitoring forest fires, the forest fire monitor 1 needs to be fixed to avoid falling off due to airflow, animals and other objective factors, or abnormal monitoring or failure caused by the cheapness. The forest fire monitor 1 of the present invention also achieves a fixing effect through a fixing component 5 arranged on its back, such as Figure 2-Figure 6 As shown, the fixing assembly 5 includes a tightening disc 51, a tightening belt 52, and a motor 53. The tightening disc 51 is mounted on the output shaft of the motor 53, and the tightening belt 52 is wound around the tightening disc 51. The fixing assembly 5 is fixed to the back of the forest fire monitoring device 1 through a fixing shell 4, and the fixing shell 4 is covered on the tightening disc 51 and the tightening belt 52. The tightening disk 51 includes an inner disk 511, an outer disk 512, and a torsion spring 513. The outer disk 512 is sleeved outside the inner disk 511, and the torsion spring 513 is arranged between the inner disk 511 and the outer disk 512. When the inner disk 511 or the outer disk 512 rotates, force transmission is realized through the torsion spring 513, and energy storage, i.e., soft connection, is realized through the torsion spring 513, which is used to tighten the tightening belt 52. When the forest fire monitor 1 is fixed, after the tightening belt 52 is wrapped around the fixed object, the end of the tightening belt 52 is inserted into the slot 41 arranged on the side of the fixing shell 4 to be fixed; like Figure 6 As shown, the tightening belt 52 includes a belt body 521 and a rocker rod 1 522 symmetrically arranged on the left and right sides of the belt body 521. The ends of the two rocker rods 1 522 are connected to a rocker rod 2 523 through a rotating shaft. The rocker rod 2 523 is provided with a connecting rod 524 on the side facing the belt body 521. The connecting rod 524 is respectively connected to the rocker rod 1 522 and the belt body 521 through springs 526. Three springs 526 are provided, and the three springs 526 are connected by a connecting button 525. When the rocker rod 2 523 swings outward, it is deformed and unfolded by pulling the spring 526.

[0025] Since the swing rod 1 522 and the swing rod 2 523 will be tightened downward under force, when the forest fire monitor 1 is fixed by pulling the tightening belt 52 and tightening the tightening belt 52 using the torsion spring 513, the end of the swing rod 2 523 can be inserted into the tree trunk by squeezing the swing rod 2 523 downward to fix it. Embodiment 2

[0026] like Figure 2 , Figure 3As shown, the forest fire detector 1 in the present invention is also provided with an electric field meter 6, which is used to detect the charge concentration in the air. Since the smoke and particulate matter released by the forest fire can serve as carriers of charged particles, these charged particles will interact with other charged particles or electric fields in the atmosphere when moving in the atmosphere, thereby affecting the distribution and intensity of the atmospheric electric field. More specifically, the smoke and particulate matter will increase the charge concentration in the atmosphere, resulting in an increase in the electric field intensity. Based on this content, the present invention proposes another method for monitoring forest fires, and the steps are as follows: S1: When there is no forest fire, install the forest fire detector 1 to monitor the charge concentration in the air through the electric field meter 6, and record the monitoring data, record the monitoring data, record the highest threshold of the charge concentration in the air monitored in the last hour, and conduct continuous rolling monitoring; S2: When the monitored charge concentration exceeds the highest recorded threshold in a short period of time, the system triggers the alarm mechanism to remind relevant personnel to pay attention and take countermeasures.

[0027] In step S2, in order to determine the accuracy of the maximum threshold value of the charge concentration, during monitoring, every 5 minutes is used as a recording interval. In a single recording interval, the average value of the charge concentration in the air continuously monitored by the electric field meter 6 in the recording interval is taken, and the charge concentration average value is used to determine whether the charge concentration in the interval exceeds the maximum threshold value of the charge concentration in the air detected in the last 1 hour described in step S1; When the charge concentration threshold in a single recording interval is higher than 15% of the highest charge concentration threshold in the last hour, an alarm is triggered; A forest fire is determined when the charge concentration threshold within a single recording interval is 30% higher than the highest charge concentration threshold in the last hour.

[0028] It should be explained that the method of determining the forest fire situation by monitoring the increase or decrease of the charge concentration contained in the air by the electric field meter 6 in this embodiment can be used in combination with the forest fire detection method described in the first embodiment; That is, the thermal imager 2 determines that among the twenty-five area images, the number of highlighted area images caused by grayscale values ​​exceeding the preset threshold value accounts for 1% to 5% of the total number of area images, indicating a suspected fire. At the same time, the electric field meter 6 detects that the charge concentration threshold in a single recording interval is higher than 15% of the highest charge concentration threshold in the last hour. While an alarm is issued, the fire is confirmed through secondary detection achieved by the cooperation of the thermal imager 2 and the electric field meter 6.

[0029] The above-mentioned method of monitoring forest fires is a result confirmation method through double condition weighting. Forest fires are determined by screening weight conditions. That is, forest fires can be determined without satisfying the relative threshold exceeded in a single condition to issue an alarm. Therefore, it has the effect of faster response and more accurate monitoring.

[0030] The above description is only a preferred embodiment of the present invention, and therefore cannot be used to limit the scope of the present invention. That is, equivalent changes and modifications made according to the patent scope of the present invention and the contents of the specification should still fall within the scope of the present invention.

Claims

1. A forest fire monitoring and identification method based on an atmospheric electric field instrument, characterized in that: The invention comprises a forest fire monitor (1) for identifying forest fires, wherein the forest fire monitor (1) is provided with a thermal imager (2) and an airflow monitor (3), wherein the thermal imager (2) is used to monitor the temperature of a target object and generate a thermal image, and the airflow monitor (3) is used to monitor the airflow velocity around the forest fire monitor (1); Among them, the forest fire monitoring and identification method includes the following specific steps: S1: Using a thermal imager (2) to monitor and capture the temperature of the target object, and generating a video of the monitored temperature through thermal imaging, and merging the three color components of red, green, and blue in the video into a single grayscale value to generate a grayscale image, so that the grayscale image only contains brightness information; S2: dividing the video image into 25 regional images of a rectangular array with a length of five and a width of five, representing the brightness information in the regional images by grayscale values ​​of 0 to 255, and recording the grayscale values ​​of the grayscale images in all the regional images; S3: setting a gray value threshold in the brightness information of the images in all areas between 0 and 255, and judging whether it is a fire area by the gray value threshold; While the temperature of the target object is monitored and captured by the thermal imager (2), the gas flow velocity around the forest fire monitoring device (1) is also monitored by the airflow monitor (3); The airflow monitor (3) is connected to the network terminal, and the temperature and wind speed information of the monitoring site are obtained in real time through the network connection, and the airflow velocity of the monitoring site is recorded in real time, and the highest value of the airflow velocity in 0.5h is taken, and the threshold value of the airflow velocity of the monitoring site is determined by the highest value; When the gas flow velocity monitored by the airflow monitor (3) exceeds the airflow velocity threshold of the monitoring location, the time taken to exceed the airflow velocity threshold of the monitoring location is used to determine whether it is abnormal airflow. When the airflow velocity threshold of the monitoring location is exceeded for 1 minute, abnormal airflow is determined and a fire is confirmed at the same time.

2. The forest fire monitoring and identification method based on the atmospheric electric field instrument according to claim 1 is characterized in that: In step S3, when determining whether it is a fire area based on the gray value threshold, the degree of fire is determined by the percentage of the area images determined to be the fire area to all the area images; When there is no fire area, it is safe; When the number of regional images of the fire area accounts for 1% to 5% of the number of all regional images, it is suspected to be on fire; When the number of regional images of the fire area accounts for more than 5% of the number of all regional images, a fire alarm is issued.

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