CN110673628B - Inspection method for oil-gas pipeline of composite wing unmanned aerial vehicle - Google Patents
Inspection method for oil-gas pipeline of composite wing unmanned aerial vehicle Download PDFInfo
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Abstract
The invention discloses a composite wing unmanned aerial vehicle oil and gas pipeline inspection method, and belongs to the technical field of oil and gas pipeline inspection. Firstly, setting initial parameters and planning routes at a ground station, simultaneously mounting a hyperspectral camera, a visible light camera and an onboard image processor on a composite wing unmanned aerial vehicle platform, and performing whole-course autonomous inspection on an oil-gas pipeline; then the composite wing unmanned aerial vehicle flies along a flight route, the hyperspectral camera and the visible light camera simultaneously acquire image information above an oil-gas pipeline and the surrounding environment, and real-time processing is carried out through the onboard image processor. The unmanned aerial vehicle transmits images acquired by the hyperspectral camera and the visible light camera to the ground station in real time through a data link, and simultaneously transmits abnormal condition information detected by the onboard image processor to the ground station; the ground station immediately alarms ground personnel when finding abnormal conditions, reminds the ground personnel to pay attention, and takes corresponding measures in time. The invention improves the efficiency, the accuracy and the real-time performance of the whole routing inspection process.
Description
Technical Field
The invention belongs to the technical field of oil and gas pipeline inspection, and relates to a composite wing unmanned aerial vehicle oil and gas pipeline inspection method.
Background
Petroleum and natural gas are important energy sources in China, and guaranteeing the safe transportation of oil gas is an important task, and the oil gas transportation in China mainly adopts a pipeline transportation mode. By the end of 2015, the total mileage of oil and gas pipelines built nationwide reaches 12 kilometers, and 31 provinces of the country are covered. The terrain where oil and gas pipelines pass through is very complex, including mountainous regions, rivers and population gathering areas, so that the oil and gas pipelines are affected and damaged by harsh environments such as mountainous and river flows and sometimes are attacked by people.
The traditional oil and gas pipeline inspection mainly adopts a manual inspection mode: in the region with flat terrain, an inspector can carry an inspection vehicle to inspect; only manual walking is used in places where vehicles cannot reach: the region that people can not reach lacks effective means of patrolling and examining.
Along with unmanned aerial vehicle's development in recent years, unmanned aerial vehicle is applied to oil gas pipeline gradually and patrols and examines the field, and the operation is patrolled and examined to oil gas pipeline to the present majority adoption fixed wing or many rotor unmanned aerial vehicle carry camera. Fixed wing and many rotor unmanned aerial vehicle all have respective characteristics: the fixed wing unmanned aerial vehicle has the advantages of wide range of range, long endurance time, high requirement on take-off and landing sites, inflexible operation and the like. Many rotor unmanned aerial vehicle possess vertical take-off and landing, fixed point hover, receive advantages such as little, the mobility is strong in the place restriction of take-off and landing, but its navigation time is short, the task radius is little, cruise speed is slow.
Therefore, the composite wing unmanned aerial vehicle is most suitable for the characteristics of long inspection distance, complex terrain, no running and landing conditions and the like of an oil-gas pipeline. The compound wing unmanned aerial vehicle is also called a Vertical Take-Off and Landing (VTOL) fixed wing unmanned aerial vehicle, has the advantages of multi-rotor Vertical Take-Off and Landing, can Take Off and land without a runway, and has the advantages of wide range and long endurance time of the fixed wing.
At present, the method for collecting image information of a pipeline and the periphery of the pipeline by a high-definition camera mounted on an unmanned aerial vehicle mostly adopts the steps that the image information is stored in an SD card or is transmitted to a ground station through image transmission/data transmission equipment, and personnel in the ground station monitor or correct and splice images in the later period. The mode of monitoring by ground personnel is easy to omit, and the data volume for processing the images at the later stage is large and the real-time performance is poor; furthermore, the leakage of buried pipelines and natural gas pipelines cannot be monitored by means of image information acquired by a visible light camera.
The change of the chemical environment of the earth surface caused by the leakage of hydrocarbon substances such as oil gas can cause the change of spectral characteristics of soil, rocks, plants, water areas and the like, and the hyperspectral camera can be used for extracting the information of the characteristics, so that the leakage of the oil gas can be detected very accurately. For interference of natural environment around a pipeline and human factors, a visible light camera can be used for image acquisition, firstly, images are segmented, then, feature extraction and automatic classification are carried out, suspicious targets such as people, vehicles or mechanical equipment are mainly and intelligently identified, when a problem is found, an alarm is immediately sent out to remind ground personnel to carry out auxiliary confirmation on video image information sent back, so that abnormal conditions are guaranteed to be handled in time, and corresponding measures are taken in time.
In the method and system for line patrol of the pipeline unmanned aerial vehicle, disclosed as CN 108470143 a, a double-vision camera (i.e., a visible light camera and an infrared camera) is adopted to perform lens switching according to the environment to obtain image information for patrol; then, the shot image information is intelligently identified, and the identified abnormal image is sent to a monitoring center. The method is suitable for the inspection of oil pipelines which are visible on the ground or have temperature difference, the leakage of the natural gas pipelines can not be monitored by a visible light or infrared camera, and most buried pipelines can not be monitored.
Disclosure of Invention
The invention provides a composite wing unmanned aerial vehicle oil-gas pipeline inspection method aiming at the defects of the current oil-gas pipeline inspection technical means, which adopts an inspection mode that a composite wing unmanned aerial vehicle is mounted with a hyperspectral camera, a visible light camera and an onboard image processor, not only can inspect the overground oil-gas pipeline, but also can inspect the buried pipeline, two cameras simultaneously acquire image information above the oil-gas pipeline and the surrounding environment, respectively process two images through the onboard image processor, and timely alarm the ground personnel about oil-gas leakage and abnormal conditions of the surrounding environment.
The inspection method of the composite wing unmanned aerial vehicle oil and gas pipeline comprises the following specific steps:
step one, setting initial parameters and planning a route by a ground station.
The parameters to be set on the ground station before flight include: parameters of a hyperspectral camera, parameters of a visible light camera, aerial survey parameters, a mapping scale, a course overlapping rate, a lateral overlapping rate and the like;
and the ground station reads the coordinate data of the oil-gas pipeline to generate a target line, and the flight line is automatically generated by combining the mission load and the turning radius.
The task load refers to performance index parameters of the airborne hyperspectral camera and the visible light camera and information related to the installation mode of the aircraft platform and the like.
Step two, simultaneously mounting a hyperspectral camera, a visible light camera and an onboard image processor on a composite wing unmanned aerial vehicle platform, and performing whole-course autonomous inspection on an oil and gas pipeline;
the whole-course autonomous inspection comprises the following steps: autonomous take-off, autonomous flight along flight paths, autonomous return and autonomous landing.
Thirdly, the composite wing unmanned aerial vehicle flies along a flight route, the hyperspectral camera and the visible light camera simultaneously acquire image information above an oil-gas pipeline and in the surrounding environment, and the hyperspectral camera image and the visible light camera image are respectively processed in real time through the onboard image processor;
checking whether the oil-gas pipeline has a leakage condition or not by processing the image of the hyperspectral camera;
the specific detection process is as follows:
firstly, preprocessing, radiation correction, data normalization processing and the like are carried out on collected original hyperspectral image data, then, according to the change of the surrounding environment caused by hydrocarbon substances leaked from oil gas, corresponding wave bands are extracted to highlight the change characteristics, the change characteristics are detected in the processed hyperspectral images, and then whether the hydrocarbon substances leak or not is judged.
And checking whether the surrounding environment of the oil and gas pipeline is abnormal or not through image processing of the visible light camera.
The specific detection process comprises the steps of detecting image change and identifying an abnormal target;
the image change detection judges whether the environment around the pipeline is changed or not by comparing the currently acquired image with the previously acquired image.
The abnormal target identification mainly identifies suspicious people, vehicles or mechanical equipment and the like; considering that airborne calculation and storage resources of the unmanned aerial vehicle are limited, a lightweight deep learning algorithm MobileNet V1-SSD is adopted to automatically detect suspicious targets such as people, vehicles or mechanical equipment, FCN semantic segmentation branches are added on the basis of the MobileNet V1-SSD, image pixels of original oil and gas pipelines are extracted, and fine pipeline damage analysis can be carried out.
The unmanned aerial vehicle transmits images acquired by the hyperspectral camera and the visible light camera to the ground station in real time through a data link, and transmits abnormal condition information detected by the onboard image processor to the ground station;
the abnormal condition information comprises whether the hydrocarbon substances leak or not; whether the environment around the pipeline has large change; whether a suspect person, vehicle, or mechanical device is present; whether the pipeline is damaged.
The data link includes airborne end and ground end: the airborne end is mounted on the composite wing unmanned aerial vehicle; the ground end is connected with a ground station to realize communication between the air and the ground.
And step five, the ground station immediately alarms ground personnel when finding the abnormal condition, and reminds the ground personnel to pay attention so as to take corresponding measures in time.
The invention has the advantages that:
(1) a composite wing unmanned aerial vehicle oil and gas pipeline inspection method is a vertical take-off and landing fixed wing unmanned aerial vehicle, and has the functions of multi-rotor vertical take-off and landing, and the advantages of wide range and long endurance time of fixed wings.
(2) The method for inspecting the oil-gas pipeline of the composite wing unmanned aerial vehicle is simple in whole automatic inspection operation, the workload of ground personnel is effectively reduced, and the safety of the whole inspection process is greatly improved.
(3) A method for inspecting an oil-gas pipeline of a composite wing unmanned aerial vehicle can detect leakage of a natural gas pipeline and a buried oil-gas pipeline through a hyperspectral camera, and the detection of oil-gas leakage is more accurate.
(4) According to the method for inspecting the oil-gas pipeline of the composite wing unmanned aerial vehicle, the workload of ground monitoring personnel can be reduced through airborne intelligent image processing software, careless omission caused by inattention is avoided, and the accuracy of target identification is greatly improved.
(5) A real-time image processing is carried out through an onboard image processor, an alarm is given immediately when an abnormal condition is found, and the real-time performance of a routing inspection task is improved.
Drawings
FIG. 1 is a flow chart of a method for inspecting an oil and gas pipeline of a composite wing unmanned aerial vehicle according to the present invention;
FIG. 2 is a schematic diagram of an abnormal object recognition model according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
The invention discloses a method for inspecting an oil-gas pipeline of a composite wing unmanned aerial vehicle, which comprises the steps of planning an inspection task when the composite wing unmanned aerial vehicle flies forward, automatically inspecting the whole process of the composite wing unmanned aerial vehicle, processing acquired images in real time, finding out pipeline leakage or other abnormal conditions, and giving an alarm in time.
As shown in fig. 1, the specific steps are as follows:
step one, setting initial parameters and planning a route by a ground station.
The ground station is provided with unmanned aerial vehicle ground station software, and has the functions of remote control and remote measurement, flight instruments, state alarm, data recording, electronic maps, routing inspection planning and the like.
The parameters to be set on the ground station before flight include: parameters of a hyperspectral camera, parameters of a visible light camera, aerial survey parameters, a mapping scale, a course overlapping rate, a lateral overlapping rate and the like; and then the ground station reads the coordinate data file of the oil-gas pipeline, the ground station software automatically generates a target line, and the flight path is automatically generated by combining the task load and the turning radius.
The task load refers to performance index parameters of the airborne hyperspectral camera and the visible light camera, and related information such as an installation mode of an airplane platform.
Secondly, mounting a hyperspectral camera by adopting a composite wing unmanned aerial vehicle platform, and carrying out whole-course autonomous inspection on the oil-gas pipeline by adopting a visible light camera and an onboard image processor;
the whole-course autonomous inspection comprises the following steps: taking off autonomously and flying autonomously along a flight route; the image information is collected in the flying process, and simultaneously the collected image information is transmitted to the ground station in real time through the data chain, so that ground personnel can monitor the image information, and the ground personnel can also send instructions to the flight control system and the onboard image processor through the data chain on the ground station. And finishing the polling task, autonomous return and autonomous landing.
Compared with the unmanned aerial vehicle platform mounting infrared camera and the visible light camera in the prior art, the unmanned aerial vehicle platform mounting infrared camera and the visible light camera have the following advantages: the composite wing unmanned aerial vehicle is embodied on an aircraft platform, has the function of multi-rotor vertical take-off and landing, and has the advantages of wide range and long endurance time of a fixed wing; moreover, the existing infrared camera and visible light camera can only inspect oil pipelines which are visible on the ground or have temperature difference, the leakage of natural gas pipelines can not be monitored by using the visible light or infrared camera, most buried pipelines can not be monitored, the hyperspectral camera is used, and the leakage characteristics of hydrocarbon substances of the oil pipelines and the natural gas pipelines can be accurately inspected no matter the oil pipelines or the natural gas pipelines are inspected, no matter the visible pipelines or the buried fixed pipelines are buried on the ground.
The onboard image processor has the functions of image preprocessing, image segmentation, image enhancement and restoration, target detection and identification, target positioning and the like, and has the characteristics of low power consumption, low weight, small volume and strong computing power.
The onboard image processor is equipped with onboard intelligent image processing software.
Thirdly, the composite wing unmanned aerial vehicle flies along a flight route, the hyperspectral camera and the visible light camera simultaneously acquire image information of the upper part along the oil-gas pipeline and the surrounding environment, and the hyperspectral camera image and the visible light camera image are respectively processed in real time through the onboard image processor;
checking whether the oil-gas pipeline has a leakage condition or not by processing the image of the hyperspectral camera; and checking whether the surrounding environment of the oil and gas pipeline is abnormal or not through image processing of the visible light camera.
The image information includes video information and picture information.
The real-time processing process of two kinds of image information comprises the following steps: firstly, a hyperspectral image target detection process:
firstly, preprocessing is carried out on collected original hyperspectral image data, and the preprocessing comprises data formatting, useless data removing, conversion from brightness to reflectivity and the like. Meanwhile, radiation correction needs to be carried out on the hyperspectral image, and data is adjusted before target detection, including data normalization processing and the like. Then, according to the change of the surrounding environment caused by hydrocarbon substances leaked from oil gas, extracting corresponding wave bands to highlight the changed characteristics, for example, the spectral absorption characteristics of the hydrocarbon substances in the soil are mainly concentrated near 1.72 mu m and 2.3 mu m, and detecting the two wave bands in the processed hyperspectral image to further judge whether the hydrocarbon substances leak.
Processing flow of visible light image: detecting image change and identifying abnormal targets;
the image change detection judges whether the environment around the pipeline is changed or not by comparing the currently acquired image with the previously acquired image.
Abnormal object recognition mainly recognizes suspicious objects such as people, vehicles, or mechanical devices. In consideration of the limitation of airborne computing resources and storage resources of the unmanned aerial vehicle, the method adopts a lightweight deep learning algorithm MobileNet V1-SSD to automatically detect suspicious targets such as people, vehicles and mechanical equipment, adds an FCN semantic segmentation branch on the basis of the MobileNet V1-SSD, extracts image pixels of original oil and gas pipelines, and can perform fine pipeline damage analysis.
An abnormal object recognition model is schematically shown in fig. 2.
The MobileNet V1-SSD is a lightweight target detection model, and is mainly characterized by high detection speed, and compared with a general SSD, the detection model is different from a basic network part of a MobileNet V1-SSD in that a MobileNet structure is adopted. The depth separable convolutions (depthwise separable convolutions) used by MobileNet are essentially a sparsified representation with less redundant information, which greatly reduces the size and computational load of the model.
The depth separable convolution is a relatively computationally expensive to conventional convolution:
wherein the input size of the lamination layer is DK×DK× M, output size DF×DF×N。
The FCN semantic segmentation model carries out pixel-level classification on the image, and can solve the problem of semantic-level image segmentation. The branch is added to separate the pipeline from the background in the picture, so that the interference of the background image is reduced, and the damage analysis can be carried out on the pipeline. Unlike classical classification networks, the FCN semantic segmentation model accepts input images of any size, and upsamples the feature map of the last convolutional layer using the anti-convolutional layer to restore it to the same size as the input image, thereby generating a prediction for each pixel while preserving spatial information in the original input image.
The unmanned aerial vehicle transmits images acquired by the hyperspectral camera and the visible light camera to the ground station in real time through a data link, and simultaneously transmits information of abnormal conditions detected by the onboard image processor to the ground station;
the abnormal condition information comprises whether the hydrocarbon substances leak or not; whether the environment around the pipeline has large change; whether suspicious persons, vehicles or mechanical equipment are present, whether the pipeline is damaged, and the like.
The data link includes airborne end and ground end: the airborne end is mounted on the composite wing unmanned aerial vehicle; the ground end is connected with a ground station to realize communication between the air and the ground. The functions of image transmission, data transmission and remote control instruction transmission of the onboard end and the ground end are realized in a radio communication mode, and the transmission distance of the remote control instruction transmission can cover the radius of the inspection operation.
And step five, the ground station immediately alarms ground personnel when finding the abnormal condition, and reminds the ground personnel to pay attention so as to take corresponding measures in time.
Specifically, when the hyperspectral camera identifies that leaked oil gas exists near the pipeline, the hyperspectral camera immediately gives an alarm to ground personnel, when the visible light camera identifies that abnormal changes or suspicious targets exist near the pipeline, the visible light camera also immediately gives an alarm to the ground personnel, the type, the position, the picture and the video information of the suspicious targets are transmitted to a ground station, and the ground personnel can further confirm the suspicious targets through the picture and the video information.
Line leaks or abnormal conditions include: pipeline leakage (especially leakage at pipeline joints), pipeline breakage, surface anticorrosive coating damage, pipeline displacement, earthwork collapse near the pipeline, bulk material stacking, livestock shed building, other building construction, crop planting, building or tree collapse, pipeline breaking, suspicious personnel, soil moving operation of vehicles near the pipeline, mechanical construction, perforation and oil stealing and the like.
Claims (4)
1. The composite wing unmanned aerial vehicle oil and gas pipeline inspection method is characterized by comprising the following specific steps:
the method comprises the following steps that firstly, initial parameters are set and a route is planned by a ground station;
step two, simultaneously mounting a hyperspectral camera, a visible light camera and an onboard image processor on a composite wing unmanned aerial vehicle platform, and performing whole-course autonomous inspection on an oil and gas pipeline;
thirdly, the composite wing unmanned aerial vehicle flies along a flight route, the hyperspectral camera and the visible light camera simultaneously acquire image information above an oil-gas pipeline and in the surrounding environment, and the hyperspectral camera image and the visible light camera image are respectively processed in real time through the onboard image processor;
checking whether the oil-gas pipeline has a leakage condition or not by processing the image of the hyperspectral camera;
the specific detection process is as follows:
firstly, preprocessing collected original hyperspectral image data, performing radiation correction and data normalization processing, then extracting corresponding wave bands to highlight the characteristics of the change according to the change of the surrounding environment caused by hydrocarbon substances leaked from oil gas, detecting the change characteristics in the processed hyperspectral image, and further judging whether the hydrocarbon substances leak or not;
checking whether the surrounding environment of the oil and gas pipeline is abnormal or not through image processing of the visible light camera;
the specific detection process comprises the steps of detecting image change and identifying an abnormal target;
the image change detection judges whether the surrounding environment of the pipeline changes by comparing the currently acquired image with the previously acquired image;
identifying abnormal objects primarily identifies suspicious persons, vehicles or mechanical equipment; considering that airborne calculation and storage resources of the unmanned aerial vehicle are limited, a lightweight deep learning algorithm MobileNet V1-SSD is adopted to automatically detect suspicious targets of people, vehicles or mechanical equipment, FCN semantic segmentation branches are added on the basis of MobileNet V1-SSD, image pixels of an original oil and gas pipeline are extracted, and fine pipeline damage analysis can be carried out;
the unmanned aerial vehicle transmits images acquired by the hyperspectral camera and the visible light camera to the ground station in real time through a data link, and transmits abnormal condition information detected by the onboard image processor to the ground station;
the data link includes airborne end and ground end: the airborne end is mounted on the composite wing unmanned aerial vehicle; the ground end is connected with a ground station to realize communication between the air and the ground;
and step five, the ground station immediately alarms ground personnel when finding the abnormal condition, and reminds the ground personnel to pay attention so as to take corresponding measures in time.
2. The inspection method for oil and gas pipelines of composite wing drones as claimed in claim 1, wherein the initial parameters set by the ground station in the first step include: parameters of a hyperspectral camera, parameters of a visible light camera, aerial survey parameters, a mapping scale, a course overlapping rate and a lateral overlapping rate;
the ground station reads the coordinate data of the oil-gas pipeline to generate a target line, and a flight line is automatically generated by combining the task load and the turning radius;
the task load refers to performance index parameters of an airborne hyperspectral camera and a visible light camera and an installation mode of the airborne hyperspectral camera and the visible light camera and an airplane platform.
3. The composite wing unmanned aerial vehicle oil and gas pipeline inspection method according to claim 1, wherein the whole-course autonomous inspection in the step two comprises: autonomous take-off, autonomous flight along flight paths, autonomous return and autonomous landing.
4. The inspection method for oil and gas pipelines of composite wing unmanned aerial vehicles according to claim 1, wherein the abnormal condition information in the fourth step includes whether hydrocarbon material leaks; whether the environment around the pipeline has large change; whether a suspect person, vehicle, or mechanical device is present; whether the pipeline is damaged.
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