CN112285119A - Oil-gas pipeline crack detection method based on unmanned locomotive cooperation - Google Patents
Oil-gas pipeline crack detection method based on unmanned locomotive cooperation Download PDFInfo
- Publication number
- CN112285119A CN112285119A CN202011186941.0A CN202011186941A CN112285119A CN 112285119 A CN112285119 A CN 112285119A CN 202011186941 A CN202011186941 A CN 202011186941A CN 112285119 A CN112285119 A CN 112285119A
- Authority
- CN
- China
- Prior art keywords
- aerial vehicle
- unmanned aerial
- unmanned
- oil
- gas pipeline
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 39
- 230000003137 locomotive effect Effects 0.000 title claims abstract description 17
- 238000000034 method Methods 0.000 claims abstract description 16
- 230000002159 abnormal effect Effects 0.000 claims abstract description 11
- 238000012216 screening Methods 0.000 claims abstract description 8
- 238000012545 processing Methods 0.000 claims abstract description 5
- 238000001931 thermography Methods 0.000 claims abstract description 4
- RZVHIXYEVGDQDX-UHFFFAOYSA-N 9,10-anthraquinone Chemical compound C1=CC=C2C(=O)C3=CC=CC=C3C(=O)C2=C1 RZVHIXYEVGDQDX-UHFFFAOYSA-N 0.000 claims description 18
- 238000004891 communication Methods 0.000 claims description 6
- 238000005516 engineering process Methods 0.000 claims description 3
- 239000003921 oil Substances 0.000 abstract description 22
- 239000010742 number 1 fuel oil Substances 0.000 abstract description 3
- 230000005540 biological transmission Effects 0.000 abstract 1
- 208000037656 Respiratory Sounds Diseases 0.000 description 3
- 230000007547 defect Effects 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000032683 aging Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000011248 coating agent Substances 0.000 description 1
- 238000000576 coating method Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000006378 damage Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N25/00—Investigating or analyzing materials by the use of thermal means
- G01N25/72—Investigating presence of flaws
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Pathology (AREA)
- Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Signal Processing (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Automation & Control Theory (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The invention discloses an oil-gas pipeline crack detection method based on unmanned locomotive cooperation, which comprises an unmanned locomotive; the unmanned aerial vehicle is loaded with the unmanned aerial vehicle and comprises the following steps; the method comprises the following steps: the unmanned vehicle-mounted unmanned aerial vehicle drives to a certain position according to a specified route, and the unmanned aerial vehicle takes off when a detection person sends a take-off instruction; step two: the unmanned aerial vehicle flies to a certain height to carry out large-scale shooting detection on the exposed oil and gas pipeline in the Xinjiang desert area; step three: processing the image shot by the unmanned aerial vehicle in the step two, and screening abnormal pictures through an algorithm; step four: according to the screening result, when an abnormal condition occurs, the unmanned aerial vehicle automatically hovers, sends out an alarm signal and then transmits the thermal imaging image and the GPS positioning information to the detection personnel; step five: and if no abnormity exists, the unmanned aerial vehicle continues to patrol. The crack detection device provided by the invention realizes crack detection of large-range oil and gas transmission pipelines in Xinjiang areas by utilizing efficient matching of the unmanned aerial vehicle and the unmanned aerial vehicle, and has the advantages of high speed and high efficiency.
Description
Technical Field
The invention relates to an oil-gas pipeline crack detection method based on unmanned locomotive cooperation, and belongs to the technical field of oil-gas pipeline detection.
Background
Pipeline transportation is often the best choice for oil and gas transportation because of its numerous advantages, but oil and gas pipeline is becoming ageing along with the increase of service time, and the pipeline fracture that the crackle caused becomes one of the leading failure cause of oil and gas pipeline, and its loss and destruction that causes is inestimable. At present, there are many methods for detecting and locating pipeline leakage, and although the leakage point can be found, the method is only for a local range. The long-distance oil and gas pipeline is usually corroded by two environments, namely an inner environment and an outer environment, in the operation process, the inner environment and the outer environment are controlled to a great extent in recent years, and therefore the pipeline detection mainly aims at coating defects and pipeline defects caused by outer corrosion. The oil and gas pipeline is transported in the Xinjiang area on the desert ground, the range is wide, and the large-range detection of the rupture condition of the oil and gas pipeline has certain difficulty.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an oil-gas pipeline crack detection method based on unmanned locomotive cooperation, which realizes large-range crack detection of an oil-gas pipeline paved on the ground by using the autonomous cooperation of an unmanned aerial vehicle and an unmanned vehicle, is convenient to know the condition of the oil-gas pipeline in time, repairs the cracks in time and finds out leakage points of the oil-gas pipeline in time.
In order to achieve the purpose, the invention adopts the technical scheme that: an oil and gas pipeline crack detection method based on unmanned locomotive cooperation comprises an unmanned locomotive; the unmanned vehicle is loaded with an unmanned aerial vehicle, and the unmanned aerial vehicle comprises a rack, a power supply module and a flight control system; the power supply module and the flight control system are arranged on the rack; the flight control system is connected with a vision system, a power system and a communication system; the flight control system comprises an altimeter, a gyroscope, a magnetometer, an accelerometer, a positioning module and a flight control board; the altimeter, the gyroscope, the magnetometer, the accelerometer and the positioning module are respectively connected with a flight control panel taking the micro control unit as a core; the power system adopts a motor to control the power supply to move; the oil and gas pipeline crack detection method comprises the following steps;
the method comprises the following steps: the unmanned vehicle-mounted unmanned aerial vehicle drives to a certain position according to a specified route, and the unmanned aerial vehicle takes off when a detection person sends a take-off instruction;
step two: the unmanned aerial vehicle flies to a certain height to carry out large-scale shooting detection on the exposed oil and gas pipeline in the Xinjiang desert area;
step three: processing the image shot by the unmanned aerial vehicle in the step two, and screening abnormal pictures through an algorithm;
step four: according to the screening result, when an abnormal condition occurs, the unmanned aerial vehicle automatically hovers, sends out an alarm signal and then transmits the thermal imaging image and the GPS positioning information to the detection personnel;
step five: and if no abnormity exists, the unmanned aerial vehicle continues to patrol.
Further, be equipped with electric quantity self-detection device in the unmanned aerial vehicle, through setting for the early warning value, reach the early warning value when the electric quantity, unmanned aerial vehicle gets into the automatic mode of returning a voyage.
Furthermore, the unmanned vehicle is provided with a simple parking apron, and the unmanned vehicle automatically flies back to the simple parking apron and is automatically loaded back by the unmanned vehicle.
Furthermore, the unmanned aerial vehicle is provided with an infrared thermal imager, so that the exposed oil and gas pipelines in the desert area of Xinjiang can be shot and detected in a large range.
And further, in the third step, a color identification method and a thermal infrared imager are adopted to display different temperatures displayed on the picture, and an algorithm is further adopted to screen abnormal pictures.
Furthermore, in the fourth step, the unmanned aerial vehicle transmits the shot image back to the ground station by using the OFDM technology, and the thermal infrared imager is a vision system.
Further, the communication system comprises an NB-IOT module, and GPS positioning information is transmitted to the ground station by the NB-IOT module in time.
The invention has the beneficial effects that: utilize the high-efficient cooperation of unmanned aerial vehicle and unmanned car, realize detecting the crackle of oil gas conveying pipeline on a large scale in Xinjiang district, it is fast, efficient. Unmanned aerial vehicle is nimble convenient, to the inconvenient scheduling problem of long oil gas pipeline geographical position, this problem can be avoided to unmanned aerial vehicle, improves inspection efficiency greatly. Meanwhile, aiming at the large-scale area of the oil and gas pipeline in Xinjiang, a plurality of unmanned locomotives can be matched for starting, and the large-scale area can be used. Meanwhile, the unmanned aerial vehicle can automatically return to an unmanned vehicle in a designated place under the condition of insufficient electric quantity of automatic detection, and the unmanned vehicle can return to the designated place, so that the flight time of the unmanned aerial vehicle in the desert is reduced, and the working time is increased.
Drawings
Fig. 1 is a schematic view of the working process of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood, however, that the description herein of specific embodiments is only intended to illustrate the invention and not to limit the scope of the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, and the terms used herein in the specification of the present invention are for the purpose of describing particular embodiments only and are not intended to limit the present invention.
Referring to fig. 1, an oil and gas pipeline crack detection method based on unmanned locomotive cooperation comprises an unmanned locomotive; the unmanned vehicle is loaded with an unmanned aerial vehicle, and the unmanned aerial vehicle comprises a rack, a power supply module and a flight control system; the power supply module and the flight control system are arranged on the rack; the flight control system is connected with a vision system, a power system and a communication system; the flight control system comprises an altimeter, a gyroscope, a magnetometer, an accelerometer, a positioning module and a flight control board; the altimeter, the gyroscope, the magnetometer, the accelerometer and the positioning module are respectively connected with a flight control panel taking the micro control unit as a core; the power system adopts a motor to control the power supply to move; the oil and gas pipeline crack detection method comprises the following steps;
the method comprises the following steps: the unmanned vehicle-mounted unmanned aerial vehicle drives to a certain position according to a specified route, and the unmanned aerial vehicle takes off when a detection person sends a take-off instruction;
step two: the unmanned aerial vehicle flies to a certain height to carry out large-scale shooting detection on the exposed oil and gas pipeline in the Xinjiang desert area;
step three: processing the image shot by the unmanned aerial vehicle in the step two, and screening abnormal pictures through an algorithm;
step four: according to the screening result, when an abnormal condition occurs, the unmanned aerial vehicle automatically hovers, sends out an alarm signal and then transmits the thermal imaging image and the GPS positioning information to the detection personnel;
step five: and if no abnormity exists, the unmanned aerial vehicle continues to patrol.
This embodiment is preferred, is equipped with electric quantity self-detection device in the unmanned aerial vehicle, through setting for the early warning value, reaches the early warning value when the electric quantity, and unmanned aerial vehicle gets into automatic mode of returning a voyage.
This embodiment is preferred, is equipped with simple and easy air park on the unmanned aerial vehicle, and unmanned aerial vehicle flies back to on the simple and easy air park of unmanned aerial vehicle by oneself, carries back by unmanned aerial vehicle is automatic.
The unmanned aerial vehicle is preferably provided with the thermal infrared imager, so that the exposed oil and gas pipelines in the desert area of Xinjiang can be shot and detected in a large range.
Preferably, in the third step, a color recognition method and a thermal infrared imager are adopted to display different temperature displays on the image, and an algorithm is further used to screen the abnormal image.
Preferably, in this embodiment, in step four, the unmanned aerial vehicle transmits the captured image back to the ground station by using the OFDM technology, and the thermal infrared imager is a vision system.
Preferably, the communication system comprises an NB-IOT module, through which the image is transmitted with GPS positioning information to the ground station in time.
The working principle of the invention is as follows: the autonomous cooperation of the unmanned aerial vehicle and the unmanned vehicle is utilized to carry out pipeline crack detection on large-range oil and gas conveying pipelines in Xinjiang areas. Unmanned aerial vehicle high altitude work utilizes high definition aerial photography to carry out the shooting to transport pipe in Xinjiang district on a large scale, is equipped with thermal infrared imager on the unmanned aerial vehicle, utilizes OFDM technique to pass the image of shooing back ground satellite station simultaneously. The image that shoots is through later stage image processing, and the search of the crackle condition on the discovery oil gas pipeline in time and oil gas pipeline leakage point. Meanwhile, the unmanned vehicle can move along with the unmanned vehicle, so that the unmanned vehicle can return to the unmanned vehicle in time due to insufficient electric quantity and is carried by the unmanned vehicle.
The method utilizes the efficient cooperation of the unmanned aerial vehicle and the unmanned aerial vehicle to realize the crack detection of the large-range oil and gas conveying pipeline in the Xinjiang area, and has high speed and high efficiency. Unmanned aerial vehicle is nimble convenient, to the inconvenient scheduling problem of long oil gas pipeline geographical position, this problem can be avoided to unmanned aerial vehicle, improves inspection efficiency greatly. Meanwhile, aiming at the large-scale area of the oil and gas pipeline in Xinjiang, a plurality of unmanned locomotives can be matched for starting, and the large-scale area can be used. Meanwhile, the unmanned aerial vehicle can automatically return to an unmanned vehicle in a designated place under the condition of insufficient electric quantity of automatic detection, and the unmanned vehicle can return to the designated place, so that the flight time of the unmanned aerial vehicle in the desert is reduced, and the working time is increased.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents or improvements made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (7)
1. An oil and gas pipeline crack detection method based on unmanned locomotive cooperation comprises an unmanned locomotive; the unmanned aerial vehicle is loaded with the unmanned aerial vehicle and is characterized in that the unmanned aerial vehicle comprises a rack, a power supply module and a flight control system; the power supply module and the flight control system are arranged on the rack; the flight control system is connected with a vision system, a power system and a communication system; the flight control system comprises an altimeter, a gyroscope, a magnetometer, an accelerometer, a positioning module and a flight control board; the altimeter, the gyroscope, the magnetometer, the accelerometer and the positioning module are respectively connected with a flight control panel taking the micro control unit as a core; the power system adopts a motor to control the power supply to move; the oil and gas pipeline crack detection method comprises the following steps;
the method comprises the following steps: the unmanned vehicle-mounted unmanned aerial vehicle drives to a certain position according to a specified route, and the unmanned aerial vehicle takes off when a detection person sends a take-off instruction;
step two: the unmanned aerial vehicle flies to a certain height to carry out large-scale shooting detection on the exposed oil and gas pipeline in the Xinjiang desert area;
step three: processing the image shot by the unmanned aerial vehicle in the step two, and screening abnormal pictures through an algorithm;
step four: according to the screening result, when an abnormal condition occurs, the unmanned aerial vehicle automatically hovers, sends out an alarm signal and then transmits the thermal imaging image and the GPS positioning information to the detection personnel;
step five: and if no abnormity exists, the unmanned aerial vehicle continues to patrol.
2. The method according to claim 1, wherein an electric quantity self-detection device is arranged in the unmanned aerial vehicle, and the unmanned aerial vehicle enters an automatic return mode when the electric quantity reaches an early warning value by setting the early warning value.
3. The method for detecting the oil and gas pipeline crack based on unmanned locomotive cooperation according to claim 1, wherein the unmanned vehicle is provided with a simple parking apron, and the unmanned vehicle automatically flies back to the simple parking apron and is automatically loaded back by the unmanned vehicle.
4. The unmanned locomotive cooperation-based oil and gas pipeline crack detection method as claimed in claim 1, wherein the unmanned aerial vehicle is provided with a thermal infrared imager so as to perform large-scale shooting detection on the exposed oil and gas pipeline in the desert area of Xinjiang.
5. The oil and gas pipeline crack detection method based on unmanned locomotive cooperation as claimed in claim 1, wherein in step three, a color recognition method and a thermal infrared imager are adopted to display different temperature displays on a picture and then an algorithm is used to screen abnormal pictures.
6. The unmanned aerial vehicle based on unmanned aerial vehicle cooperation of claim 1, wherein the unmanned aerial vehicle in the fourth step transmits the captured image back to the ground station by using OFDM technology, and the thermal infrared imager is a vision system.
7. The method of claim 1, wherein the communication system comprises an NB-IOT module through which the image is transmitted in time with GPS location information to a ground station.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011186941.0A CN112285119A (en) | 2020-10-30 | 2020-10-30 | Oil-gas pipeline crack detection method based on unmanned locomotive cooperation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011186941.0A CN112285119A (en) | 2020-10-30 | 2020-10-30 | Oil-gas pipeline crack detection method based on unmanned locomotive cooperation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112285119A true CN112285119A (en) | 2021-01-29 |
Family
ID=74352604
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011186941.0A Pending CN112285119A (en) | 2020-10-30 | 2020-10-30 | Oil-gas pipeline crack detection method based on unmanned locomotive cooperation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112285119A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113124991A (en) * | 2021-04-20 | 2021-07-16 | 青岛派科森光电技术股份有限公司 | Distributed optical fiber vibration monitoring and vehicle and unmanned aerial vehicle linkage system and method |
| CN113271357A (en) * | 2021-05-17 | 2021-08-17 | 南京邮电大学 | Ground-air cooperative networking system and control method |
| CN113759972A (en) * | 2021-09-10 | 2021-12-07 | 廊坊中油朗威工程项目管理有限公司 | Oil-gas pipeline safety inspection system and method |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104279425A (en) * | 2014-09-05 | 2015-01-14 | 河南汉威电子股份有限公司 | Pipeline-leakage detecting system and method on basis of infrared imaging and unmanned aircraft |
| CN106155086A (en) * | 2016-08-09 | 2016-11-23 | 长安大学 | A kind of Road Detection unmanned plane and automatic cruising method thereof |
| CN106774221A (en) * | 2017-01-22 | 2017-05-31 | 江苏中科院智能科学技术应用研究院 | A kind of unmanned plane cooperates patrol system and method with unmanned vehicle |
-
2020
- 2020-10-30 CN CN202011186941.0A patent/CN112285119A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104279425A (en) * | 2014-09-05 | 2015-01-14 | 河南汉威电子股份有限公司 | Pipeline-leakage detecting system and method on basis of infrared imaging and unmanned aircraft |
| CN106155086A (en) * | 2016-08-09 | 2016-11-23 | 长安大学 | A kind of Road Detection unmanned plane and automatic cruising method thereof |
| CN106774221A (en) * | 2017-01-22 | 2017-05-31 | 江苏中科院智能科学技术应用研究院 | A kind of unmanned plane cooperates patrol system and method with unmanned vehicle |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113124991A (en) * | 2021-04-20 | 2021-07-16 | 青岛派科森光电技术股份有限公司 | Distributed optical fiber vibration monitoring and vehicle and unmanned aerial vehicle linkage system and method |
| CN113271357A (en) * | 2021-05-17 | 2021-08-17 | 南京邮电大学 | Ground-air cooperative networking system and control method |
| CN113759972A (en) * | 2021-09-10 | 2021-12-07 | 廊坊中油朗威工程项目管理有限公司 | Oil-gas pipeline safety inspection system and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112285119A (en) | Oil-gas pipeline crack detection method based on unmanned locomotive cooperation | |
| CA3025554C (en) | System, method and computer program product for automatic inspection of a train | |
| CN102654940B (en) | Processing method of traffic information acquisition system based on unmanned aerial vehicle and | |
| CN104616003B (en) | Foreign matter identification system on power line | |
| CN104948915A (en) | Pipeline leakage detection system achieved based on infrasound and unmanned aerial vehicle technology | |
| US20130318214A1 (en) | Data transfer system and method thereof | |
| JP2006082775A (en) | Unmanned flying object controlling system and method | |
| CN207345845U (en) | A kind of railway line security hidden danger cruising inspection system | |
| CN114115287B (en) | Unmanned vehicle-unmanned aerial vehicle air-ground collaborative patrol and guide system | |
| CN107069549A (en) | Rotor wing unmanned aerial vehicle power-line patrolling system | |
| CN108765620A (en) | A kind of networking electric power network circuit automatic detecting method | |
| CN110763804A (en) | Atmospheric pollution source tracing system and method based on unmanned aerial vehicle | |
| CN107194368A (en) | A kind of unmanned plane Crude Oil at Sea leakage is searched and emergency processing method | |
| CN110825099B (en) | Inspection unmanned aerial vehicle control method and device for smart road | |
| CN112859917A (en) | Flight control system capable of intelligently setting safety points of air route | |
| CN111694369B (en) | Night patrol control system for police unmanned aerial vehicle | |
| KR20150105659A (en) | Unmanned aerial vehicle based structure safety inspection system using multi-sensor | |
| Wang et al. | A flying robotic system for power line corridor inspection | |
| CN112489348A (en) | Coal yard temperature intelligent detection and early warning method based on unmanned aerial vehicle | |
| CN115884092A (en) | Unmanned aerial vehicle self-organizing network system for mountain oil and gas pipeline | |
| CN108303991A (en) | Unmanned plane obstruction warning system | |
| CN207364667U (en) | A kind of unmanned plane pipeline inspection system | |
| CN220506524U (en) | Unmanned aerial vehicle intelligent cruises at oil gas pipeline leak detection system | |
| CN113485414A (en) | Fault processing system and method for computer monitoring device of substation | |
| CN210107071U (en) | Unmanned aerial vehicle oil pipe system of patrolling and examining |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210129 |