CN112377264A - Coal and gas outburst alarm method based on image recognition acceleration characteristics - Google Patents
Coal and gas outburst alarm method based on image recognition acceleration characteristics Download PDFInfo
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- CN112377264A CN112377264A CN202011446727.4A CN202011446727A CN112377264A CN 112377264 A CN112377264 A CN 112377264A CN 202011446727 A CN202011446727 A CN 202011446727A CN 112377264 A CN112377264 A CN 112377264A
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- 239000003245 coal Substances 0.000 title claims abstract description 87
- 230000001133 acceleration Effects 0.000 title claims abstract description 43
- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000005065 mining Methods 0.000 claims abstract description 10
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 claims description 74
- 238000012544 monitoring process Methods 0.000 claims description 34
- 230000005641 tunneling Effects 0.000 claims description 13
- 230000002159 abnormal effect Effects 0.000 claims description 9
- 238000009434 installation Methods 0.000 claims description 6
- 238000004891 communication Methods 0.000 claims description 5
- 238000001514 detection method Methods 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 claims description 2
- 238000004880 explosion Methods 0.000 abstract description 5
- 206010003497 Asphyxia Diseases 0.000 abstract description 3
- 230000009286 beneficial effect Effects 0.000 abstract 1
- 238000007726 management method Methods 0.000 description 12
- 238000004519 manufacturing process Methods 0.000 description 9
- 230000001960 triggered effect Effects 0.000 description 4
- 238000009412 basement excavation Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 239000011435 rock Substances 0.000 description 3
- 230000005856 abnormality Effects 0.000 description 2
- 239000003086 colorant Substances 0.000 description 2
- 238000003708 edge detection Methods 0.000 description 2
- 238000010191 image analysis Methods 0.000 description 2
- 238000003709 image segmentation Methods 0.000 description 2
- 238000010223 real-time analysis Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 239000002817 coal dust Substances 0.000 description 1
- 238000002485 combustion reaction Methods 0.000 description 1
- 230000005670 electromagnetic radiation Effects 0.000 description 1
- 238000013277 forecasting method Methods 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
- E21F17/18—Special adaptations of signalling or alarm devices
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Abstract
The invention discloses a coal and gas outburst alarm method based on image recognition acceleration characteristics. The alarming method fully considers various characteristics of coal and gas outburst of the coal mining working face, is simple to implement, can accurately judge the coal and gas outburst of the coal mining working face, effectively improves rescue efficiency, is beneficial to managers to take corresponding measures in time, can effectively avoid accidents such as gas explosion and the like caused by the coal and gas outburst, and avoids or reduces casualties caused by gas suffocation and gas explosion.
Description
Technical Field
The invention relates to a coal and gas outburst alarm method based on image recognition acceleration characteristics, and relates to the fields of image processing, communication and the like.
Background
Coal is the main energy source in China and accounts for about 70% of primary energy. The coal industry is a high-risk industry, and accidents such as gas, flood, fire, roof, coal dust and the like disturb the safety production of coal mines. In the coal mine accidents in China, the accidents are mostly serious gas accidents, and casualties caused by the gas accidents are the largest percentage of all coal mine accidents. Therefore, gas accident prevention and control is very important.
The gas accidents include gas explosion, coal and gas outburst, gas suffocation, gas combustion and other accidents. In order to avoid or reduce the occurrence of coal and gas outburst accidents, various coal or rock and gas outburst control methods are proposed, and play an important role in the safety production work of coal mines. However, the existing coal and gas outburst real-time monitoring and forecasting methods (including micro-shock, acoustic emission, electromagnetic radiation, infrared radiation and the like) have higher false alarm rate and missed report rate, and are difficult to meet the requirements of coal mine safety production.
Coal and gas outburst easily occurs on the underground coal mine excavation working face, if the coal and gas outburst in the area can be rapidly and accurately judged in the first time, accidents such as gas explosion and the like caused by the coal and gas outburst can be effectively avoided, and casualties caused by gas suffocation and gas explosion are avoided or reduced.
Disclosure of Invention
When coal and gas outburst occurs on a mining working face, a large amount of coal rock gushes outwards at high speed and high acceleration, and is accumulated in most areas of the working face in large quantity, even gushes outwards through an air inlet roadway, an air return roadway and a tunneling roadway of the mining face, various electronic equipment and communication lines in the areas can be damaged, and meanwhile, the methane concentration is increased rapidly; the invention provides a coal and gas outburst alarm method based on image recognition acceleration characteristics according to the characteristics, and the main principle is that the movement and accumulation of a large amount of coal rocks with abnormal acceleration in a monitoring area are found through real-time analysis of video images collected by a camera, and the coal and gas outburst alarm is accurately realized by combining the numerical value change of a methane sensor. The specific method comprises the following steps:
1. installing a camera on an underground coal mine excavation working surface; detecting the collected video image data of each path in real time, detecting the working conditions of a camera and a communication line, and simultaneously monitoring the change of the numerical value of a methane sensor in a nearby area; when the abnormal change acceleration of the outline of a fixed object in a set area, the abnormal change acceleration of the area of the fixed object or the abnormal motion acceleration of a large number of objects in a video image of the camera is detected, determining that the data is abnormal; when the data abnormality is detected and the methane concentration in the nearby area is monitored to be rapidly increased or reach an alarm value, or the data abnormality and related equipment faults occur successively in a short time, a coal and gas outburst alarm and power-off locking signal is sent out, the power supply of all non-intrinsic safety electrical equipment in the underground coal mine is cut off, and the removal of the underground coal mine operating personnel is informed.
2. The method comprises the steps of installing cameras on a coal face hydraulic support or a coal mining machine, in a coal face air inlet roadway and a coal face air return roadway, and installing cameras in a tunneling roadway of a tunneling working face or on a tunneling machine and on one side or two sides of a tunneling roadway fork.
3. The installation position of the camera is close to the top of the roadway or the height of the camera is more than 2 meters; the camera focal length and exposure value are manually set, and the auto-focus and auto-white balance functions of the camera are turned off.
4. The exterior of a fixed object in the monitoring range of the camera is coated with a color which is obviously different from the roadway environment.
5. Segmenting the image using color features of the stationary object; extracting the contours displayed before and after the fixed object is shielded; and when the acceleration of the contour perimeter changing along with the time is counted and found to exceed a threshold value and continue for a period of time, and the methane concentration in the nearby area is monitored to be rapidly increased or reach an alarm value, a coal and gas outburst alarm and power-off locking signal is sent out.
6. Segmenting the image using color features of the stationary object; extracting the contours displayed before and after the fixed object is shielded; when the acceleration of the change of the contour area along with the time is counted and found to exceed a threshold value and continue for a period of time, and the methane concentration in the nearby area is monitored to be rapidly increased or reach an alarm value, a coal and gas outburst alarm and power-off locking signal is sent out.
7. And (3) performing speed identification on the moving object in the video image by using a speed identification algorithm, and sending out coal and gas outburst alarm and power-off locking signals when counting that the acceleration of the movement of the object exceeds a threshold value and lasts for a period of time and the concentration of methane in a nearby area is monitored to be rapidly increased or reach an alarm value.
8. The method comprises the following steps of utilizing a digital signal processor arranged in or outside a camera to complete analysis and alarm of video images at the front end of video acquisition, or directly using the camera with a moving acceleration detection function to monitor, and when the moving acceleration of an object is detected to exceed a threshold value and continue for a period of time, and simultaneously monitoring that the methane concentration in a nearby area is rapidly increased or reaches an alarm value, sending out coal and gas outburst alarm and power-off locking signals.
Drawings
Embodiments of the drawings will become apparent from the following description, given by way of example only of at least one preferred but non-limiting embodiment, described in connection with the accompanying drawings.
FIG. 1 is a schematic view of a coal face camera and methane sensor mounting location;
FIG. 2 is a schematic view of the installation positions of a camera and a methane sensor on a heading face;
FIG. 3 is a schematic system diagram of embodiment 1;
FIG. 4 is a schematic view of the workflow of video management and coal and gas outburst alarm in embodiment 1;
FIG. 5 is a schematic system diagram of embodiment 2;
FIG. 6 is a schematic view of the workflow of video management and coal and gas outburst alarm in embodiment 2;
FIG. 7 is a schematic view of a process for analyzing video images to detect the acceleration of the perimeter change of the contour of an object fixed in position;
FIG. 8 is a schematic view of a process for analyzing video images to detect acceleration of change in the profile area of an object fixed in position;
FIG. 9 is a schematic diagram of a process for analyzing and detecting the acceleration of an object;
Detailed Description
The installation position of the coal face camera is shown in fig. 1, and specifically comprises the following steps:
1. a camera (101) on a coal face hydraulic support or a coal mining machine.
2. A camera (102) in the coal face return airway.
3. And a camera (103) in the air intake tunnel of the coal face.
4. A coal face upper corner methane sensor (104).
5. A coal face methane sensor (105).
6. Coal face air intake tunnel methane sensor (106).
7. A coal face return airway methane sensor (107).
The installation position of the tunneling working face camera is shown in fig. 2, and specifically comprises the following steps:
1. and (5) tunneling in a roadway (201).
2. And (202) tunneling in the roadway at the side of the air outlet of the roadway fork.
3. And (203) tunneling in the roadway at the side of the fork air inlet of the roadway.
4. A heading face methane sensor (204).
5. And a methane sensor (205) for the return air flow of the excavation tunnel.
Embodiment 1:
the system shown in fig. 3 mainly comprises:
1. and the video identification server (301) is responsible for processing the video images of all the cameras and sending out alarm and power-off locking signals by analyzing data change and fault information.
2. A monitoring host (302); the monitoring system has the acousto-optic alarm function, production management personnel can check field video images, data changes of sensors and equipment faults through the monitoring host, alarm and power-off locking signals can be manually sent out, all non-intrinsic safety electrical equipment power supplies in the underground coal mine are cut off, and scheduling instructions are sent out to inform underground operation personnel to remove the underground coal mine. And may retrieve historical monitoring data from the storage server.
3. A storage server (303); the system is responsible for collecting and storing camera signals, sensor signals and equipment fault signals and providing inquiry and calling services for users.
4. A network switch (304); and the system is responsible for the management and data exchange of all equipment accessed to the mining Ethernet.
5. A downhole switch (305); the system is responsible for access and data exchange of substations, has an explosion-proof shell and meets the underground explosion-proof requirement of the coal mine.
6. A substation (306); the explosion-proof camera is responsible for the access and data exchange of the camera and the sensor, has an explosion-proof shell and meets the underground explosion-proof requirement of the coal mine.
7. A camera (307); the digital network camera is provided with an explosion-proof shell which meets the explosion-proof requirement of the coal mine.
8. A methane sensor (308); the methane sensor is a full-range or high-low concentrated methane sensor and has an automatic alarm function.
The working process of video management and coal and gas outburst alarm is shown in figure 4:
(401) the video camera collects video images, digitalizes and compresses the video images, and transmits compressed video signals to the substation through a network cable.
(402) transmitting the video signal and the methane sensor signal to a downhole switch via a substation.
(403) the underground switch transmits the signals to an aboveground network switch, and the network switch distributes the video signals and the methane sensor signals to a storage server, a monitoring terminal and a video identification server.
(404) the video recognition server analyzes and detects the video image and the working condition of the equipment in real time, and sends out alarm and power-off locking signals when the alarm condition is met.
(405) the monitoring host displays the site video, the methane sensor data and the equipment working condition in real time, receives the alarm signal of the video identification server, and automatically gives an audible and visual alarm when the alarm condition is met; production management personnel can check the on-site real-time video, the methane sensor data, the alarm condition and the equipment condition, and when hardware for video and data acquisition is damaged, the historical on-site video and sensor data are called. The production management personnel can manually send out alarm and power-off locking signals, cut off the power supply of all non-intrinsic safety electrical equipment in the underground coal mine, and send a scheduling instruction to inform the withdrawing of the underground coal mine operating personnel.
Embodiment 2:
the system shown in fig. 5 mainly includes:
1. a storage server (501); the system is responsible for collecting and storing video signals, alarm signals, methane sensor signals and equipment working conditions and providing query and calling services for users.
2. A monitoring host (502); the monitoring system has the acousto-optic alarm function, production management personnel can check the field video image, the alarm condition, the methane sensor data and the equipment condition through the monitoring host, can manually send out alarm and power-off locking signals, cut off the power supply of all non-intrinsic safety electrical equipment in the underground coal mine, and send a scheduling instruction to inform the underground coal mine operating personnel to be removed. And may retrieve historical monitoring data from the storage server.
3. Monitoring a backup machine (503); when the monitoring host machine fails, the monitoring standby machine works.
4. A network switch (504); and the system is responsible for the management and data exchange of all equipment accessed to the mining Ethernet.
5. A downhole switch (505); the system is responsible for access and data exchange of substations, has an explosion-proof shell and meets the underground explosion-proof requirement of the coal mine.
6. A substation (506); the explosion-proof camera is responsible for the access and data exchange of the camera and the sensor, has an explosion-proof shell and meets the underground explosion-proof requirement of the coal mine.
7. A video recognition alarm device (507); the main processor selects a DSP chip, digitalizes and compresses the analog video signal collected by the camera, transmits the compressed video signal to the substation through a network cable, analyzes and identifies the video image, identifies the image change and the object movement in the set area, and automatically outputs an alarm signal when the image change and the object movement reach the set alarm index. The video identification alarm device and the camera (508) are installed in an explosion-proof shell which meets the explosion-proof requirement of the coal mine.
8. A camera (508); an analog camera is adopted to output standard analog video signals, and the standard analog video signals and a video identification alarm device (507) are installed in an explosion-proof shell which meets the explosion-proof requirement of a coal mine together.
9. A methane sensor (509); the methane sensor is a full-range or high-low concentrated methane sensor and has an automatic alarm function.
Embodiment 2 the working process of video management and coal and gas outburst alarm is shown in fig. 6:
(601) the video camera collects video data, transmits video analog signals to the video identification alarm device, digitizes and compresses the video by the video identification alarm device, and transmits the compressed video signals and mobile alarm signals to the substation.
(602) the video recognition alarm device analyzes and recognizes the video image, can recognize the image change and the object movement in the set area, and automatically outputs an alarm signal to the substation when the image change and the object movement reach the set alarm indexes.
And 3, (603) each substation sends the acquired various signals to an underground switch through the mining Ethernet ring network.
(604) the network switch receives the data forwarded by the downhole switch and distributes the video signals, the sensor signals and the alarm signals to the storage server, the monitoring host and the standby host.
(605) the storage server stores the video signal, the sensor signal and the alarm signal.
(606) the monitoring host displays the site video, the sensor data, the alarm condition and the equipment working condition in real time, and when the alarm condition is met, the monitoring host automatically gives an audible and visual alarm; production management personnel can check the real-time video, the alarm condition and the equipment working condition on site, and when hardware for video and data acquisition is damaged, historical site video and data are called. The production management personnel can manually send out coal and gas outburst alarm and power-off locking signals, cut off all non-intrinsic safety electrical equipment power supplies in the underground coal mine, and send out scheduling instructions to inform the operators in the underground coal mine to be removed.
The video image analysis process for detecting the change acceleration of the perimeter of the contour of the object with the fixed original position is shown in fig. 7:
(701) setting a monitoring area A in a video monitoring range, and calling setting area data each time an identification server is started.
(702) restoring the standard compressed video stream to image frames.
The currently acquired video images are:
F＝{f(x，y)，x∈M，y∈N，MN}
f is the gray value set of the points in the video image, the image resolution is M multiplied by N, (x, y) is the coordinate of any point in the video image, F (x, y)
Is the gray value of the point (x, y) in the video image.
(703) converting the RGB color space image into an HSV color space, determining the hue, saturation and brightness ranges of the colors of the fixed object in the HSV color space, and performing image segmentation according to the hue, saturation and brightness ranges.
(704) performing edge detection based on Canny operator to extract a series of contours.
(705) real-time analysis is carried out on the change acceleration of the perimeter of the fixed object contour identified by the image, and the early warning state is entered when the change acceleration of the perimeter of the contour exceeds a threshold value L (706).
The operation formula is as follows:
v1Representing the speed of change of the perimeter of the profile of a stationary object, v1(t1) And v1(t1-b1) Are each t1Time and t1-b1The speed of change of the perimeter of the contour, a, recognized at the time1Acceleration of contour perimeter change, b1Is less than t1Positive number of (c).
(707) In the early warning state, if no video data stream output is detected, an alarm is triggered (712);
(708) in an early warning state, judging whether the change acceleration of the perimeter of the outline is continuously larger than a threshold value, if so, adding 1(710) to a counter, otherwise, clearing the counter and returning (709);
(711) if the counter exceeds 10, indicating that the fixed object in the monitored area is monitored to be continuously shielded, triggering an alarm (712);
the video image analysis process for detecting the acceleration of the change of the contour area of the object with the fixed home position is shown in fig. 8 (part of the expression formula can refer to the description of fig. 7 above):
(801) setting a monitoring area A in a video monitoring range, and calling set area data each time an identification server is started.
(802) restoring the standard compressed video stream to image frames.
(803) converting the RGB color space image into an HSV color space, determining the hue, saturation and brightness ranges of the colors of the fixed object in the HSV color space, and performing image segmentation according to the hue, saturation and brightness ranges.
(804) extracting a series of contours by performing edge detection based on Canny operator.
And 5, (805) analyzing the change acceleration of the outline area of the fixed object identified by the image in real time, and entering an early warning state if the change acceleration of the outline area exceeds a threshold value L (806).
The operation formula is as follows:
v2Representing the speed of change of the profile area of a stationary object, v2(t2) And v2(t2-b2) Are each t2Time and t2-b2The speed of change of the contour area identified at the time, a2Acceleration as a change in profile area, b2Is less than t2Positive number of (c).
(807) In the early warning state, if no video data stream output is detected, an alarm is triggered (812);
(808) in an early warning state, judging whether the change acceleration of the outline area is continuously larger than a threshold value, if so, adding 1(810) to a counter, otherwise, clearing the counter and returning (809);
(811) if the counter exceeds 10, indicating that the fixed object in the monitored area is monitored to be continuously shielded, triggering an alarm (812);
the detection flow of detecting the motion acceleration of the object by analyzing the video image is shown in fig. 9 (part of the expression formula can refer to the description of fig. 7 above):
(901) setting a monitoring area A in a video monitoring range, and calling set area data each time an identification server is started.
(902) restoring the standard compressed video stream to image frames.
(903) identifying movement of objects within the monitored area using an optical flow algorithm.
(904) analyzing the motion acceleration of the object identified by the image in real time, and entering an early warning state (905) if the motion acceleration exceeds a threshold value L.
The operation formula is as follows:
v3Representing the speed of movement, v, of an object in the monitored area3(t3) And v3(t3-b3) Are each t3Time and t3-b3Speed of movement of the object identified at the moment of time, a3Acceleration of motion of the object, b3Is less than t3Positive number of (c).
(906) In the early warning state, if no video data stream output is detected, an alarm is triggered (911);
(907) in the early warning state, judging whether the motion acceleration of the object is continuously larger than a threshold value, if so, adding 1(909) to a counter, otherwise, clearing the counter and returning (908);
(910) if the counter exceeds 10, indicating that continuous high acceleration movement of the object in the monitored area is monitored, an alarm is triggered (911).
Claims (9)
1. A coal and gas outburst alarm method based on image recognition acceleration features is characterized in that: installing a camera at the position of a coal mine underground monitoring point; detecting the collected video image data of each path and the working conditions of a camera and a communication line in real time, and monitoring the change of the methane sensor value of the nearby area; analyzing whether abnormal features exist in the video image, wherein the abnormal features comprise the acceleration of the change of the outline of a fixed object in a set region, the acceleration of the change of the area of the fixed object, the motion and the volume of an object in a monitoring region or the acceleration of a moving object; when the abnormal characteristics are detected and the methane concentration in the nearby area is rapidly increased or reaches an alarm value, or the abnormal characteristics and related equipment faults occur successively in a short time, sending out coal and gas outburst alarm and power-off locking signals, cutting off the power supply of all non-intrinsic safety electrical equipment in the underground coal mine, and informing the removal of underground coal mine operators.
2. The alarm method according to claim 1, characterized in that: the installation positions of the cameras comprise a coal face hydraulic support or a coal mining machine, a coal face air inlet roadway, a coal face air return roadway, a tunneling roadway of a tunneling working face or a tunneling machine and one side or two sides of a tunneling roadway fork.
3. The alarm method according to claim 1, characterized in that: the installation position of the camera is close to the top of the roadway or the height of the camera is more than 2 meters; the camera adopts manual setting of camera focal length and exposure value, and has no automatic focusing and automatic white balance functions.
4. The alarm method according to claim 1, characterized in that: the exterior of a fixed object in the monitoring range of the camera is coated with a color which is obviously different from the roadway environment.
5. The alarm method according to claim 1, characterized in that: the specific alarm method comprises the following steps:
(1) under the conditions that the camera works normally and the video communication is normal, when the acceleration of the profile change of a fixed object in a video image is detected to exceed a threshold value, and the methane concentration in a nearby area is rapidly increased or an alarm value is reached, a coal and gas outburst alarm and power-off locking signal is sent out;
(2) when the acceleration of the area change of a fixed object in a video image is detected to exceed a threshold value, and the methane concentration in a nearby area is rapidly increased or reaches an alarm value, a coal and gas outburst alarm and power-off locking signal is sent out;
(3) when the motion and the volume of the object in the video image and the acceleration of the moving object exceed the threshold value and the methane concentration in the nearby area is rapidly increased or reaches an alarm value, a coal and gas outburst alarm and power-off locking signal is sent out.
6. The alarm method according to claim 5, characterized in that: in the step (1), the color characteristics of the fixed object are used for segmenting the image; extracting the contour perimeter before and after a fixed object in a monitoring area is shielded; and when the acceleration of the contour perimeter changing along with the time is counted and found to exceed a threshold value and continue for a period of time, and the methane concentration in the nearby area is monitored to be rapidly increased or reach an alarm value, a coal and gas outburst alarm and power-off locking signal is sent out.
7. The alarm method according to claim 5, characterized in that: in the step (2), the color characteristics of the fixed object are used for segmenting the image; extracting the outline area before and after a fixed object in a monitoring area is shielded; when the acceleration of the change of the contour area along with the time is counted and found to exceed a threshold value and continue for a period of time, and the methane concentration in the nearby area is monitored to be rapidly increased or reach an alarm value, a coal and gas outburst alarm and power-off locking signal is sent out.
8. The alarm method according to claim 5, characterized in that: and (3) performing speed identification on the moving object in the video image by using a speed identification algorithm, and sending out coal and gas outburst alarm and power-off locking signals when the acceleration of the movement of the object is counted and found to exceed a threshold value and continue for a period of time and the methane concentration in the nearby area is monitored to be rapidly increased or reach an alarm value.
9. The alarm method according to claim 1, characterized in that: the method comprises the following steps of utilizing a digital signal processor arranged in or outside a camera to complete analysis and alarm of video images at the front end of video acquisition, or directly using the camera with a moving acceleration detection function to monitor, and when the moving acceleration of an object is detected to exceed a threshold value and continue for a period of time, and simultaneously monitoring that the methane concentration in a nearby area is rapidly increased or reaches an alarm value, sending out coal and gas outburst alarm and power-off locking signals.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114109509A (en) * | 2021-12-15 | 2022-03-01 | 中国矿业大学(北京) | Coal mine dynamic disaster monitoring and alarming method and monitoring and alarming system |
| CN114165288A (en) * | 2021-12-15 | 2022-03-11 | 中国矿业大学(北京) | Coal mine dynamic disaster monitoring and alarming method based on image recognition depth characteristics |
| CN115506848A (en) * | 2022-09-21 | 2022-12-23 | 中国矿业大学(北京) | Coal mine dynamic disaster sensing alarm method based on visible light image |
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2020
- 2020-12-09 CN CN202011446727.4A patent/CN112377264A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114109509A (en) * | 2021-12-15 | 2022-03-01 | 中国矿业大学(北京) | Coal mine dynamic disaster monitoring and alarming method and monitoring and alarming system |
| CN114165288A (en) * | 2021-12-15 | 2022-03-11 | 中国矿业大学(北京) | Coal mine dynamic disaster monitoring and alarming method based on image recognition depth characteristics |
| CN114165288B (en) * | 2021-12-15 | 2023-02-17 | 中国矿业大学(北京) | Coal mine dynamic disaster monitoring and alarming method based on image recognition depth characteristics |
| CN115506848A (en) * | 2022-09-21 | 2022-12-23 | 中国矿业大学(北京) | Coal mine dynamic disaster sensing alarm method based on visible light image |
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