1. Introduction
Pipelines are the main logistics for oil and gas over long distances. In China alone, by the end of 2021, there were over 150,000 km of oil and gas pipelines, according to [
1]. A pipeline leak may result in significant economic or human loss. Inner defects are the most common causes of failures, such as corrosion, deformation, crack, dent, deposit, and metal loss. Therefore, regular maintenance of the pipeline is an essential task.
Generally, natural gas pipelines are classified into gathering and transmission pipelines. Gathering pipelines are small-sized pipelines that transport raw gas from production wells to processing stations. Transmission pipelines are large-diameter pipelines for the transmission of purified commercial gas. Gathering pipelines are more susceptible to corrosion, leading to leakage because raw gas comes with high-percentage impurities, such as H2S, CO2, and water, compared to purified gas. Regular internal inspections of the gathering pipelines are necessary.
The most reasonable and effective way to detect long and buried pipelines is through the use of pipeline detection robots equipped with internal or in-line inspection (ILI) techniques [
2,
3]. Consequently, research on in-pipe inspection robots has significantly enhanced over the years [
3,
4]. Typical in-pipe robots are divided into wheel-driven robots, tractor/track-driven robots and fluid-powered robots, according to different driving mechanisms in conventional locomotion [
5,
6,
7]. For example, the pipeline inspection gauge (PIG) [
8] is a type of passive robot equipped with magnetic flux leakage (MFL) [
9], ultrasonic testing (UT) [
10], eddy currents (ECs) [
11], and electromagnetic acoustic transducers (EMATs). However, the significant drawbacks are the significantly higher operating cost and indirect observation of defects. In particular, non-direct observation of the defect is very unfriendly to end-users. Visual inspection in the ILI involves the use of closed-circuit television (CCTV) [
12] for pipeline inspection. The visual inspection system is usually a mobile platform with proper cameras and lights. The camera is used to capture high-resolution videos or photos of the damaged inner pipeline surface. In the visual inspection of the inner pipeline, online inspection is usually manually done by means of a multi-core cable, while the offline inspection is executed by a powered mobile robot. Obviously, the former is often impractical in long and in-service pipelines due to the lack of reliable wireless communication and power supply [
13]. Although the latter records images while the robot is passing through the pipeline and then analyzes the images outside the pipeline, the latter is also limited by the mobile platform itself and is not adapted to long pipelines. The wheeled pipe robot mounted on the camera is representative, which has a large overall structure and requires significant energy. As a result, the inspection ability of long or curved pipelines is highly dependent on a high-power supply.
Fortunately, the principle of gathering pipelines, which involves moving gas from high-pressure to low-pressure regions, offers the possibility of long-distance movement for non-power-driven motion platforms. Meanwhile, the pig receiver and launcher, commonly used in pigging processes, provide easy access to the in-line robot. In this work, we developed a prototype of the natural gas-driven pipeline endoscopic robot (GDPER) for long-distance natural gas gathering pipelines with an internal diameter of 154 mm, which has no electric motors and can move through vertical pipelines, elbows, and branches, and has a scaled body and pressure-resistant structure to operate at pressures up to 6 MPa. During the movement of the GDPER prototype in the axial direction of the pipe, the camera constantly captures HD-quality videos of the inner wall at a rate of 30 frames per second (fps) throughout the length of the pipeline. The integrated distance recording combined with the saved MP4 format video files can be further processed to locate defect spots.
In this paper, we introduced the design and structure of the GDPER in
Section 2; the pipeline passing capacity of the prototype of GDPER is analyzed by the ADAMS simulation software environment in
Section 3. Finally, we describe the preliminary test results and the performance discussion.
2. Design of the Prototype of GDPER
2.1. General Solution for GDPER
A modular design was chosen for the robot, which was designed to pass through gas-gathering pipelines with an internal diameter of 154 mm. The robot is propelled by the flowing gas at a speed equivalent to the fluid velocity. It can be composed of several units, each with a specialized function, linked by universal joints. In this design, the prototype consists only of the traction speed regulation unit, the distance measuring unit, and the camera unit. Individually designed units were mounted along the core of the axis, linked by universal joints. The traction and speed regulation unit is composed of a resin bowl and a speed control module that provides the robot with forward driving force through the natural gas in the pipeline under the action of the pressure difference between the front and rear of the unit. The distance measuring unit carries three odometers to measure travel length. The camera unit has a camera and a set of ring LED lights to record high-definition images of the inner wall of the pipeline and is located at the tail of the robot. A lithium battery is placed in each unit to supply a constant 12 V to the sensor. The structure composition of GDPER is given in
Figure 1. The details of each unit are described below.
2.2. Traction and Speed Regulation Unit
The natural gas in the gathering pipeline carries a significant amount of energy and flows at a certain speed. Thus, a specially designed traction structure can enable the robot to complete long-distance and long-term motion within the pipeline, utilizing the gas flow.
The traction and speed regulation control unit is divided into three sections. The front section is a double-layer bowl with flow rate adjustment holes made of polyurethane rubber material. The double bowl not only drives the entire unit forward but also provides sufficient support. The middle section is a cone-shaped flow control valve cover that can move back and forth to adjust the area of the flow control hole. The rear section is the motor compartment, equipped with a screw motor, three pairs of adaptive support wheels, and a sealing cover. These three sections are connected by three double-ended threaded smooth shafts. The cone-shaped flow control valve cover is driven by a screw motor that moves back and forth on the smooth shaft. Changing the area of the flow adjustment orifice changes the differential pressure before and after the bowl. As a result, the robot can travel under the fluid pressure difference drive, and the travel speed range is also adjustable.
The traction force is what drives the robot to move along the pipeline and is a critical specification for its performance. It is usually limited by the conditions of the pipeline, such as dust, bends, and weld heads. The robot itself is modeled as a lumped element with self-weight and corresponding friction forces, as shown in
Figure 2.
and
represent the friction forces against the pipeline inner wall of the bowl and the support wheel, respectively.
and
are the radial forces against the pipeline inner wall of the bowl and the support wheel, respectively, while
G represents the gravity of the robot itself.
,
, and
represent the flow of gas into, through, and out of the flow rate adjustment hole, respectively.
Thus, the traction force of the robot unit that should move along the pipeline can be expressed as
where
and
are the pressures at the back end and the front end of the unit, Pa. The effective force area of the bowl is
S, m
, the total weight of the robot is
m kg, and the acceleration of the robot motion is
a m/s
.
It is assumed that and are constant and m is also constant. The traction force of the robot obtained by the pressure difference overcomes the friction and makes the robot travel along the pipeline. If the traction force obtained by the robot through the pressure difference is greater than the friction force, the robot will travel through the pipeline. The velocity of the robot’s movement depends on the effective force area S of the bowl, i.e., . This can be achieved by adjusting the opening of the cone-shaped flow control valve cover. It is important to ensure constant movement of the robot through the pipeline for capturing high-quality images.
2.3. Distance Measuring Unit
In order to accurately detect internal defects through image recognition after the robot inspection, it is necessary to record the robot’s position throughout its deployment. Therefore, an odometer is used to calculate the robot’s speed and distance traveled, as well as to track the location of defects. To reduce data errors from a single odometer, three odometer (mileage) wheels are designed on the distance measuring unit, spaced 120 degrees apart from each other. Fusing data from the three sensors may increase positioning accuracy.
The odometer wheel (supported by the support arm) can make contact with the inner wall of the pipeline, travel along the pipeline using the spring preload, and rotate through rolling friction with the pipeline. An encoder is installed on the odometer wheel to record the number of rotations of the odometer wheel. If the total number of pulses output from the encoder for one cycle of the odometer wheel is
, then the robot’s travel distance
D can be calculated as
where
is the number of pulses for one circle of the encoder, and
r is the radius of the odometer wheel.
and
represent the number of teeth on the master gear and the slave gear, respectively. In order to prevent inaccurate recording caused by radial forces on the encoder’s rotating shaft, a transmission structure with meshing gears was designed. The structure of the odometer wheel module in the distance measuring unit is shown in
Figure 3.
2.4. Camera Unit
The image captured by the camera of the inner wall of the pipeline is the most visual representation of defects in the pipeline. Despite the rapid advancements in image processing methods, software-based visual assessment of the interior surfaces in a pipeline still heavily rely on the quality of the raw camera images. A key factor in obtaining high-quality endoscopic images is to ensure adequate illumination [
6]. However, the internal environment of the pipeline usually has an illumination level of 0 Lux. Additionally, acquiring high-quality images at a maximum speed of 3 m/s should be taken into consideration. To ensure high-quality videos, a full HD high-speed wide-angle digital camera with an LED ring is considered for optimal illumination.
Figure 4 illustrates the structure of the camera unit.
The camera and LED light ring were mounted along the axis-core in the center-round hole and the outer ring lamp groove, respectively. The camera and LED light ring each use one piece of protective glass instead of sharing one to avoid reflected light into the camera, resulting in image whitening and affecting image quality. The system will provide full HD wide-angle MP4 video files with a resolution of at 30 , including time and length stamps. The video recognition software will also provide a report that contains images with clock positions and locations of defects.
5. Experiment of Prototype of Pipeline Endoscope Robot
Based on the simulation analysis, the prototype robot was developed after optimizing the structure. The actual view of the prototype is illustrated in
Figure 14. In this section, a simple traction experiment is designed to verify: (1) the passability and over-obstacle capability of the distance measuring unit and the camera unit of the pipeline endoscopy robot individually and jointly in the straight and curved pipelines; and (2) the availability of the image data and the mileage data.
The experimental pipeline consists of multiple sections of pipeline, including two straight sections and one bend, with a total length of 24 m, as shown in
Figure 15. The in-pipeline robot is considered to have completed an experiment by traversing from one end of the pipeline to the other end. The experimental results demonstrate that the robot can smoothly pass through both the straight and curved parts of the experimental pipeline, and successfully cross the welded joints connecting the pipeline sections. The experimental setup is illustrated in
Figure 16, while the image stored on the SD card at the end of the experiment is shown in
Figure 17, which clearly reveals any defects present.
Figure 18 displays the mileage and speed data recorded during the robot’s traversal of the pipeline. The robot positioning accuracy can be verified by comparing it with the actual pipeline length.
In addition, initial testing of the passability of the gas-driven robot on an actual gathering pipeline was completed using the pig receiver and launcher at the gas gathering station. The length of the pipeline, i.e., the distance between the pig receiver and launcher, is approximately 5.75 km. The pressures at the inlet and outlet are 2.3 and 2.2 MPa, respectively. The total running time is about 28 min.
Figure 19 shows that both the traction unit and the prototype can pass through the target pipeline smoothly under gas drive. However, because the pipeline was not cleaned before the test, a large amount of oily dirt was still present in the pipeline, as can be seen in
Figure 19c for the traction unit after passing through the pipeline compared to the other two units before the test. This caused the distance measurement sensors to fail. This suggests that, in order to ensure the accuracy of the data, multiple pipeline pigging operations must also be completed in accordance with the relevant specifications for internal inspection activities before the visual examination.