CN104143248A - Forest fire detection, prevention and control method based on unmanned aerial vehicle - Google Patents
Forest fire detection, prevention and control method based on unmanned aerial vehicle Download PDFInfo
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Abstract
The invention discloses a forest fire detection, prevention and control method based on an unmanned aerial vehicle. According to the forest fire detection, prevention and control method, the mode that visible-light images and thermal infrared images are combined is adopted, a forest fire can be judged by observing thermal image difference values of high-brightness points of the images, and fire extinguishing bags are released so as to extinguish fire head points in time or control fire behaviors primarily; accurate analysis is further conducted through a receiving station on the ground, abnormal areas missed during rough judgment conducted by the unmanned aerial vehicle can be found in time, and particularly monitoring can be achieved more effectively by forming a percentage distribution diagram of fire behavior possibility coefficients; efficiency and accuracy are high.
Description
Technical field
The invention belongs to security against fire technical field, be specifically related to a kind of forest fire detection and preventing control method based on unmanned plane.
Background technology
Forest fire is one of global important disaster of forestry, all can cause heavy losses and the environmental pollution on a large scale of forest resourceies every year.Traditional forest fire protection monitoring, mainly adopts Ren Gong lookout, monitoring remote video and satellite remote sensing mode.
Ren Gong lookout mode is in She Li lookout post, commanding elevation, and operator on duty takes turns at keeping watch for 24 hours, due to artificial carelessness and fault, can make many condition of a fire fail to find early, incurs loss through delay and puts out the fire the time, causes serious consequence.
Monitoring remote video mode is to build a large amount of video surveillance points in forest zone, and control point is equipped with video camera, by wired or wireless network, real-time pictures is sent to Surveillance center, by center personnel's implementing monitoring.Which does not need directly to accredit personnel to scene, forest zone, but is manually difficult to the early stage condition of a fire of identification on remote.Especially visible image capturing crane monitoring system, at night, does not almost have the illumination of detectable spectral range, is almost very dark on video image, is difficult to find and judge forest fires.Even if change thermal infrared video monitoring into,, easily there is monitoring dead point, thereby cause a hidden trouble in forest environment complexity.
Satellite remote sensing mode is by finding forest fires after the processing of remote sensing photo, but satellite can only be found the forest fires in larger region, cannot find in early days at fire; Also there is the problems such as remote sensing images lack of resolution, very flexible simultaneously.
In prior art, also the existing forest fire based on unmanned plane detects.The disclosed technology of CN102496234A patent be " when finding after the burning things which may cause a fire disaster point of forest; utilize infrared video camera on unmanned plane to be filmed; and communicated by letter via satellite and send to fire-fighting " center " in unmanned plane GPS position; whose discovery burning things which may cause a fire disaster point? how to find burning things which may cause a fire disaster point? can automatically identify, extract burning things which may cause a fire disaster point? in this patented technology, nothing describes in detail, cannot automatically identify conflagration area, spreading range and development trend, in this patent, disclosed technical application is very poor.The open function that also only limits to image acquisition, analysis and forecast in addition, in the time that people receive signal and find fire point to carry out prevention and control measure, the possible intensity of a fire spreads.
Summary of the invention
The problem existing based on above-mentioned prior art, the invention provides a kind of forest fire detection and preventing control method based on unmanned plane, efficiently finds suspicious burning things which may cause a fire disaster, automatically calculates fire alarm probability, frees the judgement of probability carry out preliminary prevention and control and alarm for fire.
The problem existing for solving above-mentioned prior art, the technical scheme that the present invention takes is: forest fire detection and preventing control method based on unmanned plane, it is characterized in that, comprise the following steps:
1) default weather data, visible images and the thermal infrared images of guarded region under normal circumstances in unmanned plane; The threshold value of default high-temperature region and thermal imagery difference;
2) by unmanned plane, guarded region is patrolled and taken visible images and thermal infrared images simultaneously, and by corresponding camera site and the shooting time of GPS positioning function real time record image, data are reached to ground receiving station by wireless transmission simultaneously;
3) to step 2) visible images and the thermal infrared images of the guarded region under normal circumstances that prestores with step 1) respectively of the visible images that obtains and thermal infrared images carry out respectively the mark of higher warm area and the calculating of thermal imagery difference, and contrast with predetermined threshold value;
4) when not breaking through predetermined threshold value, ignore the higher region of normal temperature, continue inspection; Breaking through predetermined threshold value, is improper region by this zone definitions, and receiving station gives the alarm earthward; Simultaneously, unmanned plane is located by GPS, throw in fire extinguishing bag to improper region, and taking this improper region as the center of circle, in overhead circumaviate, real-time multi-direction is monitored the dynamic change in this region and is sent to ground receiving station, until thermal imagery difference returns in predetermined threshold value, cancel alarm, continue inspection;
5) ground receiving station receiving step 2) transmit data, comprehensive fire gross data and empirical data are carried out comprehensive systematic analysis to visible images and thermal infrared images, form the percent profile figure of the each condition of a fire possibility of guarded region coefficient, and the GPS locator data that possibility coefficient is greater than to 70% region feeds back to unmanned plane by wireless transmission, carry out from high to low emphasis tour by unmanned plane from possibility coefficient value; Ground receiving station receiving step 4) transmit data, comprehensive fire gross data and empirical data are carried out comprehensive systematic analysis to visible images and thermal infrared images, be defined as catching fire a little, the calculating area that catches fire, arrange in time action, determine unmanned plane wrong report, sound all clear and feed back unmanned plane by wireless transmission and continue inspection.
Default threshold value obtain manner described in step 1): the thermal infrared images of guarded region under normal circumstances, in conjunction with default weather data, adjust brightness of image scope, be described threshold range.
The analysis of the visible images of ground receiving station described in step 4) to the daytime receiving also comprises smog analysis, be specially the image that separates each frame, under rgb color space, wherein R represents the red component of pixel, G represents the green component of pixel, B represents the blue component of pixel, I represents three-component average, as-20 < R-G < 0,-55 < G-B <-10, when 15 < B-R < 90 or 130 < I < 255, cyan smog, in the time of 230 < I < 255, it is white smoke, 128 < R=G=B < 192 are grey smog, different smog, in conjunction with thermal imagery difference, participates in the calculating of Fire Possibility coefficient in conjunction with empirical data.
The larger variation of existence compared with the average gray value of self before the current average gray in described grey smog region and a period of time, and the difference of this area grayscale value and whole detection zone average gray value exceedes setting threshold, this region directly judges that this region appearance is potential abnormal.
The analysis of the visible images in the evening that step 4) receives described ground receiving station also comprises flame analysis, be specially the image that separates each frame, under rgb color space, wherein R represents the red component of pixel, G represents the green component of pixel, and B represents the blue component of pixel, and relatively R signal and B signal is slight: if R signal exceedes B signal and the difference threshold value higher than setting, can judge that this region is partially red, for the probability of flame higher; Otherwise be considered as disturbing.
Described R signal obviously exceedes B signal, and with a period of time before self mean difference there is larger variation, this difference and whole detection zone mean difference exceed setting threshold simultaneously, this region directly judge this region occur potential extremely.
Catch fire described in the step 5) calculating of area, is by flying height data and image area, calculates acquisition by geometry.
When in step 5), possibility coefficient value is identical, unmanned plane is preferentially patrolled from the region near self.
Described wireless transmission is by the wireless communication networks of public radio communication network or self-organization or system via satellite.
Forest fire detection and preventing control method based on unmanned plane of the present invention, has following advantage than prior art:
1) mode that adopts visible images to be combined with thermal infrared images, the wherein advantage of thermal infrared system, the image of 7.5 to 13.5 microns of thermal infrared spectrums can be converted to visible images, due to exceed all objects that exceed absolute zero all backscatter go out infrared spectrum, temperature is higher, the infrared spectrum scattering is stronger, so, in the gray level image showing at thermal infrared imaging, the intensity of brightness of object on image is directly proportional to the temperature of object, therefore unmanned plane can judge risk of forest fire by the thermal imagery difference of watching the high point of brightness on image, throw in fire extinguishing bag, put out in time duration and degree of heating point or tentatively control the intensity of a fire,
2) thermal infrared imaging is not limited by daytime, and daytime and evening can judge risk of forest fire accurately, by the further control of ground receiving station;
3) by the further Accurate Analysis in ground receiving station, can find in time slightly to be sentenced the improper region of being omitted by unmanned plane, particularly, can more effective realization monitor by the percent profile figure that forms condition of a fire possibility coefficient;
4), in conjunction with factors such as weather, smog, colors, improved the precision of monitoring.
Brief description of the drawings
Fig. 1 is schematic flow sheet of the present invention.
Embodiment
Below in conjunction with embodiment, the present invention is described in detail.
Embodiment 1
Forest fire detection and a preventing control method based on unmanned plane, steps flow chart as shown in Figure 1:
1) default weather data, visible images and the thermal infrared images of guarded region under normal circumstances in unmanned plane; The threshold value of default thermal imagery difference; Threshold value obtain manner: the thermal infrared images of guarded region under normal circumstances, in conjunction with default weather data, adjust brightness of image scope, be described threshold range;
2) by unmanned plane, guarded region is patrolled and taken visible images and thermal infrared images simultaneously, and by corresponding camera site and the shooting time of GPS positioning function real time record image, data are reached to ground receiving station by cordless communication network simultaneously;
3) to step 2) visible images and the thermal infrared images of the guarded region under normal circumstances that prestores with step 1) respectively of the visible images that obtains and thermal infrared images carry out respectively the mark of higher warm area and the calculating of thermal imagery difference, and contrast with predetermined threshold value;
4) when not breaking through predetermined threshold value, ignore the higher region of normal temperature, continue inspection; Breaking through predetermined threshold value, is improper region by this zone definitions, and receiving station gives the alarm earthward; Simultaneously, unmanned plane is located by GPS, throw in fire extinguishing bag to improper region, and taking this improper region as the center of circle, in overhead circumaviate, real-time multi-direction is monitored the dynamic change in this region and is sent to ground receiving station, until thermal imagery difference returns in predetermined threshold value, cancel alarm, continue inspection;
5) ground receiving station receiving step 2) transmit data, comprehensive fire gross data and empirical data are carried out comprehensive systematic analysis to visible images and thermal infrared images, form the percent profile figure of the each condition of a fire possibility of guarded region coefficient, and the GPS locator data that possibility coefficient is greater than to 70% region feeds back to unmanned plane by cordless communication network, carry out from high to low emphasis tour by unmanned plane from possibility coefficient value; When possibility coefficient value is identical, unmanned plane is preferentially patrolled from the region near self; Ground receiving station receiving step 4) transmit data, comprehensive fire gross data and empirical data are carried out comprehensive systematic analysis to visible images and thermal infrared images, be defined as catching fire a little, by flying height data and image area, calculate by how much account forms the area that catches fire, arrange in time action, determine unmanned plane wrong report, sound all clear and feed back unmanned plane by cordless communication network and continue inspection.
Wherein: the analysis of the visible images of ground receiving station described in step 4) to the daytime receiving also comprises smog analysis, be specially the image that separates each frame, under rgb color space, wherein R represents the red component of pixel, G represents the green component of pixel, B represents the blue component of pixel, I represents three-component average, as-20 < R-G < 0,-55 < G-B <-10, when 15 < B-R < 90 or 130 < I < 255, cyan smog, in the time of 230 < I < 255, it is white smoke, 128 < R=G=B < 192 are grey smog, different smog, in conjunction with thermal imagery difference, participates in the calculating of Fire Possibility coefficient in conjunction with empirical data.When the larger variation of existence compared with self average gray value before a period of time of the current average gray in described grey smog region, and the difference of this area grayscale value and whole detection zone average gray value exceedes setting threshold, this region directly judges that this region appearance is potential abnormal.
The analysis of the visible images in the evening that step 4) receives described ground receiving station also comprises flame analysis, be specially the image that separates each frame, under rgb color space, wherein R represents the red component of pixel, G represents the green component of pixel, and B represents the blue component of pixel, and relatively R signal and B signal is slight: if R signal exceedes B signal and the difference threshold value higher than setting, can judge that this region is partially red, for the probability of flame higher; Otherwise be considered as disturbing.When described R signal obviously exceedes B signal, and with a period of time before self mean difference there is larger variation, this difference and whole detection zone mean difference exceed setting threshold simultaneously, this region directly judge this region occur potential extremely.
Claims (9)
1. forest fire detection and the preventing control method based on unmanned plane, is characterized in that, comprises the following steps:
1) default weather data, visible images and the thermal infrared images of guarded region under normal circumstances in unmanned plane; The threshold value of default high-temperature region and thermal imagery difference;
2) by unmanned plane, guarded region is patrolled and taken visible images and thermal infrared images simultaneously, and by corresponding camera site and the shooting time of GPS positioning function real time record image, data are reached to ground receiving station by wireless transmission simultaneously;
3) to step 2) visible images and the thermal infrared images of the guarded region under normal circumstances that prestores with step 1) respectively of the visible images that obtains and thermal infrared images carry out respectively the mark of higher warm area and the calculating of thermal imagery difference, and contrast with predetermined threshold value;
4) when not breaking through predetermined threshold value, ignore the higher region of normal temperature, continue inspection; Breaking through predetermined threshold value, is improper region by this zone definitions, and receiving station gives the alarm earthward; Simultaneously, unmanned plane is located by GPS, throw in fire extinguishing bag to improper region, and taking this improper region as the center of circle, in overhead circumaviate, real-time multi-direction is monitored the dynamic change in this region and is sent to ground receiving station, until thermal imagery difference returns in predetermined threshold value, cancel alarm, continue inspection;
5) ground receiving station receiving step 2) transmit data, comprehensive fire gross data and empirical data are carried out comprehensive systematic analysis to visible images and thermal infrared images, form the percent profile figure of the each condition of a fire possibility of guarded region coefficient, and the GPS locator data that possibility coefficient is greater than to 70% region feeds back to unmanned plane by wireless transmission, carry out from high to low emphasis tour by unmanned plane from possibility coefficient value; Ground receiving station receiving step 4) transmit data, comprehensive fire gross data and empirical data are carried out comprehensive systematic analysis to visible images and thermal infrared images, be defined as catching fire a little, the calculating area that catches fire, arrange in time action, determine unmanned plane wrong report, sound all clear and feed back unmanned plane by wireless transmission and continue inspection.
2. forest fire detection and the preventing control method based on unmanned plane according to claim 1, it is characterized in that, default threshold value obtain manner described in step 1): the thermal infrared images of guarded region under normal circumstances, in conjunction with default weather data, adjust brightness of image scope, be described threshold range.
3. forest fire detection and the preventing control method based on unmanned plane according to claim 1, it is characterized in that, the analysis of the visible images of ground receiving station described in step 4) to the daytime receiving also comprises smog analysis, be specially the image that separates each frame, under rgb color space, wherein R represents the red component of pixel, G represents the green component of pixel, B represents the blue component of pixel, I represents three-component average, as-20 < R-G < 0,-55 < G-B <-10, when 15 < B-R < 90 or 130 < I < 255, cyan smog, in the time of 230 < I < 255, it is white smoke, 128 < R=G=B < 192 are grey smog, different smog, in conjunction with thermal imagery difference, participates in the calculating of Fire Possibility coefficient in conjunction with empirical data.
4. forest fire detection and the preventing control method based on unmanned plane according to claim 3, it is characterized in that, the larger variation of existence compared with the average gray value of self before the current average gray in described grey smog region and a period of time, and the difference of this area grayscale value and whole detection zone average gray value exceedes setting threshold, this region directly judges that this region appearance is potential abnormal.
5. forest fire detection and the preventing control method based on unmanned plane according to claim 1, it is characterized in that, the analysis of the visible images in the evening that step 4) receives described ground receiving station also comprises flame analysis, be specially the image that separates each frame, under rgb color space, wherein R represents the red component of pixel, G represents the green component of pixel, B represents the blue component of pixel, relatively R signal and B signal is slight: if R signal exceedes B signal and the difference threshold value higher than setting, can judge that this region is partially red, for the probability of flame higher; Otherwise be considered as disturbing.
6. forest fire detection and the preventing control method based on unmanned plane according to claim 5, it is characterized in that, described R signal obviously exceedes B signal, and there is larger variation with the mean difference of self before a period of time, this difference and whole detection zone mean difference exceed setting threshold simultaneously, and this region directly judges that this region appearance is potential abnormal.
7. forest fire detection and the preventing control method based on unmanned plane according to claim 1, is characterized in that, the calculating of the area that catches fire described in step 5) is by flying height data and image area, calculates acquisition by geometry.
8. forest fire detection and the preventing control method based on unmanned plane according to claim 1, is characterized in that, when in step 5), possibility coefficient value is identical, unmanned plane is preferentially patrolled from the region near self.
9. according to forest fire detection and preventing control method based on unmanned plane described in claim 1-8 any one, it is characterized in that, described wireless transmission is by the wireless communication networks of public radio communication network or self-organization or system via satellite.
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| CN104616419A (en) * | 2015-01-18 | 2015-05-13 | 南京森林警察学院 | Sky, ground and air integrated remaining fire monitoring method for forest fire |
| CN104614322A (en) * | 2015-02-02 | 2015-05-13 | 北京航空航天大学 | Detection method for radio-frequency fuel oil harm |
| CN105205970A (en) * | 2015-04-02 | 2015-12-30 | 无锡桑尼安科技有限公司 | Fire alarm system based on aerial photography |
| CN104834920A (en) * | 2015-05-25 | 2015-08-12 | 成都通甲优博科技有限责任公司 | Intelligent forest fire recognition method and device based on multispectral image of unmanned plane |
| CN105243627A (en) * | 2015-09-06 | 2016-01-13 | 天维尔信息科技股份有限公司 | Fire-fighting monitoring system based on unmanned aerial vehicle |
| CN106168683B (en) * | 2015-09-09 | 2020-01-24 | 河南联纵消防科技有限公司 | Rapid and accurate positioning method for fire source |
| CN106168683A (en) * | 2015-09-09 | 2016-11-30 | 河南联纵消防科技有限公司 | A kind of burning things which may cause a fire disaster fast accurate localization method |
| CN106558181B (en) * | 2015-09-28 | 2019-07-30 | 东莞前沿技术研究院 | Fire monitoring method and apparatus |
| CN106558181A (en) * | 2015-09-28 | 2017-04-05 | 东莞前沿技术研究院 | Fire monitoring method and apparatus |
| CN105759826A (en) * | 2015-11-03 | 2016-07-13 | 天津艾思科尔科技有限公司 | Aircraft with intelligent fire-fighting detection apparatus |
| CN105270629A (en) * | 2015-11-06 | 2016-01-27 | 中国航空工业经济技术研究院 | System of forest fire fighting unmanned aircraft system |
| CN105322464A (en) * | 2015-11-28 | 2016-02-10 | 国网河南省电力公司郑州供电公司 | Foreign matter eliminating method for overhead line |
| CN105322464B (en) * | 2015-11-28 | 2018-06-19 | 国网河南省电力公司郑州供电公司 | Overhead transmission line foreign matter removing method |
| CN106887108A (en) * | 2015-12-16 | 2017-06-23 | 天维尔信息科技股份有限公司 | Early warning interlock method and system based on thermal imaging |
| CN105758993A (en) * | 2016-02-22 | 2016-07-13 | 陈勇 | Remote detection system and detection method of smoke on the basis of autonomous navigation unmanned aerial vehicle |
| CN105678946A (en) * | 2016-02-22 | 2016-06-15 | 吴正明 | Fire remote detection system and method based on unmanned plane |
| CN105758993B (en) * | 2016-02-22 | 2017-09-15 | 淮阴师范学院 | Smog Long Range Detecting and Ranging and its detection method based on independent navigation unmanned plane |
| CN105678289A (en) * | 2016-03-07 | 2016-06-15 | 谭圆圆 | Control method and device of unmanned aerial vehicle |
| CN105913604A (en) * | 2016-05-18 | 2016-08-31 | 中国计量大学 | Fire occurrence determining method and device based on unmanned aerial vehicle |
| CN106054928A (en) * | 2016-05-18 | 2016-10-26 | 中国计量大学 | All-region fire generation determination method based on unmanned plane network |
| CN106054928B (en) * | 2016-05-18 | 2019-02-19 | 中国计量大学 | A kind of full region fire generation measuring method based on unmanned plane network |
| CN106204786A (en) * | 2016-07-15 | 2016-12-07 | 山东智洋电气股份有限公司 | Operating condition of transformer station equipment one key inspection method |
| CN106210675A (en) * | 2016-09-22 | 2016-12-07 | 云南电网有限责任公司电力科学研究院 | Method, device and system for monitoring forest fire of power transmission line |
| CN106448016B (en) * | 2016-09-30 | 2018-08-17 | 国网湖南省电力公司 | A kind of cruise method of the transmission line forest fire monitoring device based on low power dissipation design |
| CN106448016A (en) * | 2016-09-30 | 2017-02-22 | 国网湖南省电力公司 | Low-power design based cruising method of forest fire monitoring device of power transmission line |
| CN106716281A (en) * | 2016-10-24 | 2017-05-24 | 深圳市大疆创新科技有限公司 | Controlling method, controlling device and unmanned aerial vehicle |
| CN106716281B (en) * | 2016-10-24 | 2020-11-06 | 深圳市大疆创新科技有限公司 | Control method, control device and unmanned aerial vehicle |
| CN108205861A (en) * | 2016-12-16 | 2018-06-26 | 中电科（德阳广汉）特种飞机***工程有限公司 | A kind of forest fire protection control system and method |
| CN106710128A (en) * | 2017-01-23 | 2017-05-24 | 无锡觅睿恪科技有限公司 | Fire alarm early-warning unmanned aerial vehicle |
| CN107218970A (en) * | 2017-05-24 | 2017-09-29 | 中国矿业大学 | Unmanned aerial vehicle for monitoring distribution and combustion situation of coal field fire area and method thereof |
| CN107316012A (en) * | 2017-06-14 | 2017-11-03 | 华南理工大学 | The fire detection and tracking of small-sized depopulated helicopter |
| CN107316012B (en) * | 2017-06-14 | 2020-12-22 | 华南理工大学 | Fire detection and tracking method of small unmanned helicopter |
| CN107481465A (en) * | 2017-08-21 | 2017-12-15 | 昆明理工大学 | A kind of aerial unmanned plane infrared monitoring method for early warning of forest adaptive cruise |
| CN107977018A (en) * | 2017-12-12 | 2018-05-01 | 吉林大学 | Crop straw burning monitoring method based on binocular stereo vision and unmanned plane |
| CN109471450A (en) * | 2018-03-10 | 2019-03-15 | 刘惠敏 | Drone flying height adjusting method |
| CN108986386A (en) * | 2018-07-28 | 2018-12-11 | 闫旭 | The fireproof monitoring system deployed to ensure effective monitoring and control of illegal activities based on cloud |
| CN109360370A (en) * | 2018-11-30 | 2019-02-19 | 广州高新兴机器人有限公司 | A method of it is detected based on robot pyrotechnics |
| CN111053988A (en) * | 2019-12-27 | 2020-04-24 | 扬州大学 | Intelligent forest fire prevention system based on unmanned aerial vehicle |
| CN111307291A (en) * | 2020-03-02 | 2020-06-19 | 武汉大学 | Surface temperature anomaly detection and positioning method, device and system based on unmanned aerial vehicle |
| CN111341060A (en) * | 2020-03-24 | 2020-06-26 | 西南民族大学 | Forest fire prevention system based on unmanned aerial vehicle discernment location |
| CN111564017A (en) * | 2020-06-04 | 2020-08-21 | 侯雨硕 | Intelligent early warning device for forest fire |
| CN111951508A (en) * | 2020-07-03 | 2020-11-17 | 北京中安安博文化科技有限公司 | Fire classification method, device, medium and electronic equipment |
| CN112232245A (en) * | 2020-10-22 | 2021-01-15 | 无锡臻永科技有限公司 | Four-wing aircraft field exploration system and method |
| CN112915421B (en) * | 2021-01-21 | 2022-05-03 | 湖南林科达农林技术服务有限公司 | Unmanned aerial vehicle-based forest fire retardant spraying method and unmanned aerial vehicle |
| CN112915421A (en) * | 2021-01-21 | 2021-06-08 | 湖南林科达农林技术服务有限公司 | Unmanned aerial vehicle-based forest fire retardant spraying method and unmanned aerial vehicle |
| CN112989941A (en) * | 2021-02-07 | 2021-06-18 | 浙江宇联信息发展有限公司 | Map-based video information transmission system |
| CN112989941B (en) * | 2021-02-07 | 2022-07-01 | 浙江宇联信息发展有限公司 | Map-based video information transmission system |
| CN113554845A (en) * | 2021-06-25 | 2021-10-26 | 东莞市鑫泰仪器仪表有限公司 | Be used for forest fire prevention thermal imaging device |
| CN113450531A (en) * | 2021-06-28 | 2021-09-28 | 中电科特种飞机***工程有限公司 | Forest fire prevention detection system |
| CN114152347A (en) * | 2021-09-30 | 2022-03-08 | 国网黑龙江省电力有限公司电力科学研究院 | Transformer substation power equipment fault positioning and fire research and judgment comprehensive detection method |
| CN113870515A (en) * | 2021-10-19 | 2021-12-31 | 国家电网有限公司 | Fire early warning system for high-voltage power field monitoring |
| CN113870515B (en) * | 2021-10-19 | 2023-05-26 | 国家电网有限公司 | Fire disaster early warning system for high-voltage power on-site monitoring |
| CN114002751A (en) * | 2021-10-26 | 2022-02-01 | 国网北京市电力公司 | Abnormal position identification method, system and device |
| CN114002751B (en) * | 2021-10-26 | 2023-11-03 | 国网北京市电力公司 | Abnormal position identification method, system and device |
| CN116382348A (en) * | 2023-05-11 | 2023-07-04 | 中国电建集团山东电力建设第一工程有限公司 | Unmanned aerial vehicle inspection method and system for power distribution equipment |
| CN116382348B (en) * | 2023-05-11 | 2023-10-20 | 中国电建集团山东电力建设第一工程有限公司 | Unmanned aerial vehicle inspection method and system for power distribution equipment |
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