Inspection Gauge Research Articles

Design of bypass structure and dynamic motion simulation for ultra-large diameter pipeline inspection gauge

Aiming at the problem of controlling the operating velocity of a large-diameter heavy-duty pipeline inspection gauge (PIG), this paper designs the bypass structure to study the velocity change and flow field state when the Ø1219 mm PIG is operating in pipeline with different bypass rates. Fluent is applied to numerical simulation of the fluid-structure interaction flow field based on the dynamic mesh method. The results show that: the bypass rate of 2%–3% can satisfy the velocity of PIG in 3–5 m/s reasonable interval. The larger the bypass rate is, the larger the turbulence intensity is, and the gradual increase of the pressure difference suffered by the PIG. The operating velocity of the PIG can be regulated more accurately by corresponding to the bypass rate and the pressure difference front and rear. Comparing the experimental and simulation results, the error rate of the velocity decrease with bypass rate of 1%–3% is 12.8 %.

Dynamics Modeling and Analysis of Small-Diameter Pipeline Inspection Gauge during Passing Through Elbow

Abstract With small diameters, numerous elbows and complex internal environment, gathering and transportation pipelines are widely applied in the oil and gas pipeline network. To guarantee their safety, a pipeline inspection gauge (PIG) driven by the pressure differential is used. When the PIG collides with the elbows in the pipeline, it exhibits complex nonlinear dynamic behaviors and its reliability and stability may also be greatly affected. To study the vibration response characteristics passing through the elbow, the dynamic modeling of the small-diameter PIG is conducted first in this paper based on the ADAMS software. Then, the fluid-structure coupling is achieved by combining the dynamic model and the numerical calculation program of the fluid equation in Simulink. The simulation results indicate that the axial and swing acceleration amplitudes of the two sections increase with the increasing speed of the double-section detector, while the opposite trend is observed for the vertical acceleration amplitudes. By comparison, it is found that the acceleration response in the second section is generally greater than that in the first section. The results also show that the axial offset of the PIG at the elbow is inversely proportional to the speed and radius of the elbow, which is the main cause of the lift-off values of sensors.

Study on the dynamic evolution of friction and wear of polyurethane material for pipeline inspection gauge

The dynamic evolution in friction and wear can lead to interface failure and induce vibrations in pipeline inspection gauge. The friction behavior between polyurethane and X70 steel was evaluated with annular face contact under 0.042 to 0.07 MPa. The temperature increase was recorded using infrared cameras. Dynamic simulations of frictional heat and stress-strain were conducted using Abaqus software. The results indicate that in the initial stages, abrasive wear, stress (1.5 MPa), and frictional temperature rise (65 °C) of PU were observed in the inner-ring region at 0.056 MPa. The surface roughness (3.394 μm) of the PU became comparable to that of the steel ring (3.768 μm) due to abrasive wear. In the later stages, a higher frictional temperature (80 °C) and increased stress (3.8 MPa) were observed in the outer ring. Concurrently, Schallamach waves and ridge-like stripes indicative of stick-slip behavior emerged in the outer ring. The viscoelastic hysteresis effect is the fundamental cause of the dynamic evolution of the friction coefficient and wear. Frictional heat exacerbates the evolution of stick-slip behavior and increases fluctuations in the friction coefficient. The findings of this research can be utilized to analyze the causes of interface failure and vibration in pipeline inspection gauge.

Subsea pipeline inspection gauges fluctuating friction control under time-varying disturbance

To suppress friction fluctuations during the operation of a pipeline inspection gauge (PIG) and to avoid speed deviations, which may lead to poor detection accuracy and jamming, an adaptive backstepping controller with improved unscented Kalman filter (UKF) was proposed in this paper. Firstly, the friction model was derived, and based on this, the nonlinear dynamic model of PIG was established. Then, an adaptive backstepping controller was designed to estimate the dynamic parameters of the system and stabilize the operating velocity of the PIG by controlling the friction, and adaptive noise based UKF was applied to obtain more accurate feedback estimated signals to deal with the time-varying disturbances in the environment. An active control PIG prototype and a pipeline experimental platform was built, and experiments were conducted under various conditions. Under all conditions, compared to the uncontrolled system, the proposed control strategy can reduce the fluctuation range of friction values by more than 59%, reduce the velocity fluctuation range by more than 88%, and maintain the velocity control error within 4%. Compared to the other controllers, the proposed controller demonstrated better performance in terms of control precision and robustness, verifying the effectiveness and reliability of the proposed controller.

Theoretical research of impact vibration of multi-section serial pipeline inspection gauge in large drop pipeline

When operating in large drop pipelines, pipeline inspection gauge may experience severe impact vibration at elbows, potentially leading to its failure. This paper focuses on serial pipeline inspection gauges with multiple sections in large drop pipelines, analyzes the force acting on the pipeline inspection gauge during the descent phase, and establishes a multi-body dynamics model of the gauge under pipe-soil coupling conditions. In addition, a correction formula is developed for the pressure changes in the medium at the front and rear of the pipeline inspection gauge. To solve the model, MSC/ADAMS and MATLAB/Simulink are used for the bi-directional fluid–structure-interaction joint simulation. Moreover, the results are compared with the pipeline inspection gauge motion model established by OLGA. The study investigates the dynamic responses, vibration superposition and laws of dynamic evolution at the upper and lower elbows of the large drop pipeline. The results show that the speed of the gauge increases suddenly during the descent in large drop sections and then stabilizes, with different effects of the fluid medium pressure difference at various stages. The vibration responses along the axial, horizontal radial, and vertical directions at the elbows vary, with the second section experiencing stronger vibrations due to superposition effects. Compared to fixed boundaries, the acceleration extremes of the gauge are lower under the constraints of pipe-soil model, indicating significant soil buffering and vibration damping effects.

Dynamics of a large-diameter and multi-section pipeline inspection gauge when crossing obstacles

The dynamic behavior generated by the collision between multi-section Pipeline Inspection Gauge (PIG) and obstacles inside the pipeline is highly complex. A double section PIG is connected through a double universal joint and is divided into front section and rear section. The transmission patterns of vibration and their effects between the two sections are not yet fully known. This study investigates the vibration response and transmission law of a large-diameter and multi-section PIG when crossing obstacles. By constructing a high fidelity, full size, full factor nonlinear multi-system dynamic model of double section Φ1219mm PIGs, the changes in vibration acceleration of the PIG under different operating speeds are simulated. A full-size traction experimental setup has been built. The simulation results are compared with traction experiment and field experiment. The findings indicate that the sudden change in axial acceleration caused by collision is mainly concentrated in the frequency range of 0–50 Hz.

Numerical investigation of disk bypass pipeline inspection gauge with hole in disk

Bypass Pipeline Inspection Gauges (PIGs) are widely employed as the most effective and economical devices for pipeline cleaning, maintenance, and inspection operations. The speed of these bypass PIGs significantly impacts the operational activities of pipelines. Very high or low PIG speeds may cause damage to the pipeline and the PIG itself. Therefore, it is important to control the speed of the PIG for better pigging operations. This study focuses on the influencing parameters and their impact on PIG speed. The approach of Computational Fluid Dynamics (CFD) has been utilized to model fully turbulent flow around a sample of a disk bypass PIG with a hole in the disk section for four different cases. PIG speed and pressure loss coefficient are measured to evaluate the effectiveness of the PIG. Meanwhile, two dimensionless groups are introduced based on the influencing design parameters for the movement of the disk bypass PIG, with and without a hole, to measure the optimal design parameters. The results show that a disk bypass PIG with a hole in the disk provides 5%-7% better results in terms of PIG speed and 6%-9% for the pressure loss coefficient around the PIG section. Among the four cases of a disk bypass PIG with a hole in the disk section, case-1 shows better pigging operation, with a dimensionless group value of 0.24. However, case-1 exhibits a 2.7%-22% reduction in PIG speed and a 12%-72% reduction in the pressure loss coefficient compared to other cases. Additionally, the lowest value of the presented dimensionless group indicates better pigging operation, and the optimal value of the dimensionless group is 0.24 for the design consideration of the PIG. This study holds directional significance for the design of the structural parameters of the PIG, which are useful for pipeline clean-up, inspection, and operational maintenance, and it provides reference value for related researches.

Uplifting the study of the inline inspection technique on the buckling pipelines in pipeline integrity management strategy

This work reports the development of inline inspection (ILI) methodology to enhance the pigging activity for the dented pipeline, facilitate the pigging process to prevent Pipeline Inspection Gauge (PIG) from getting stuck and improve the safety passage for buckled pipelines. The recent report unveils the condition of the UNPIGGABLE pipelines, which reduce the inner diameter of pipelines to 257.51 mm, equivalent to 27.58 % of the initial diameter and restricts the pigging activity. In this report, the pull-through test coupled with the collapsibility test was conducted. The success of the test above allows the ILI equipment based on the magnetic flux leakage (MFL) technique to record the internal and external wall loss inwardly and geometric defect on diameter of the pipelines. The prepared artificial dented pipeline was made before it underwent several tests. Based on the pull-through test, the maximum force of 27000 N is more significant than the pipeline operating pressure to enable the MFL tool to pass through the pipelines despite exhibiting the geometry anomaly. Compressing the opposite magnetic yoke of the collapsibility test is critical, showing that the ILI MFL tool reaches its maximum compression of 242 mm. The value is lower than the minimum internal diameter of 257 mm. The ILI results show that the highest metal loss was achieved at 73 % at 15504 m at the bottom of the inspected pipelines. At the same time, the dented area reduces to more than 6 % of the pipelines’ nominal outer diameter and imposes the pipe’s integrity status to red. The distinctive result of the research can be used to model the future unprecedented pigging process when buckles appear in pipelines

A Pipeline Inspection Gauge Positioning Method Based on Distributed Fiber Optic Vibration Sensing

A Pipeline Inspection Gauge Positioning Method Based on Distributed Fiber Optic Vibration Sensing

Research on pipeline inspection gauges localization based on residual denoising autoencoder

To improve pipeline transportation efficiency, long-distance pipelines need to be cleaned regularly. Pipeline inspection gauges (PIGs) are widely used in pigging operations. The traditional PIG localization method generally has a large error and cannot achieve continuous tracking. To solve the problem of PIG real-time tracking and localization, this paper proposes a method of PIG localization for oil pipelines based on a denoising autoencoder(DAE). The attention deconvolution residual block (ADR) is introduced in the decoder part of the DAE, so that this model can learn and use global information to selectively emphasize key features, suppress useless features, and improve the noise removal performance of the model. After denoising, the negative pressure wave(NPW) signal is normalized, the time delay is extracted, and the PIG is located using the NPW localization formula. Experiments show that this method can effectively achieve real-time PIG localization. Compared with the EMD and DAE positioning methods, the relative positioning accuracy is increased by 3.5 times and 8.4 times, respectively.

Analysis via 3D FEM of the Passing Capacity of Pipeline Inspection Gauges in Bends with Different Curvatures

Pipeline inspection gauges easily become wedged in offshore and onshore small-diameter pipelines (where the outer diameter, D, of the pipe is less than 150 mm), particularly at the bends. To reveal the relationship between PIG capacity and bend curvature radius, a quantitative study on the passing capacity of PIG was conducted in this paper from three key perspectives of performance: safe application, sealing, and driving. The results demonstrate that the pipeline inspection gauge exhibits better passing capacity as the curvature radius of the bend increases. To improve the poorest passing capacity, in the case of R = 3D, different numbers of grooves are opened in the cup. The results demonstrate that the cup with 24 square grooves has a substantial impact on optimizing the passing capacity of the pipeline inspection gauge. This enhancement results in improvements in safe application performance (40.8%), sealing performance (12.22%), and driving performance (17%). This research aims to expand our understanding of blockages in small-diameter pipelines and provide a basis for optimizing the structure of the pipeline inspection gauge for small-diameter pipelines.

Research and prediction of pipeline inspection gauges velocity based on simulation and neural network

Pipeline transportation is a highly efficient transportation mode, and pipeline inspection gauge (PIG) is a widely used pipeline cleaning, detection and maintenance device. The PIG's ability to fulfill its intended purpose hinges heavily on its motion velocity. And it is vital to predict and control the velocity of PIG to ensure optimal functioning. This paper establishes several models with different rotary valve orifice numbers, orifice diameters, valve openings, and sealing disc compression amounts. The effects of the factors on PIG force state and velocity are analyzed by finite element method (FEM). With these simulation outcomes, the paper establishes velocity prediction models based on polynomial fitting, support vector machine (SVM) and neural network methods. In addition, by combining neural networks with genetic algorithms, the PIG size is optimized. The results demonstrate that compared with polynomial fitting and SVM, neural networks are more convenient and accurate and have a broader application prospect.

Interference Wear Behaviors of the Pipeline Inspection Gauge Sealing Cups: Experimental Research and Numerical Modeling

Interference Wear Behaviors of the Pipeline Inspection Gauge Sealing Cups: Experimental Research and Numerical Modeling

A novel parallel constrained extended Kalman filter for improving navigation algorithm – case study: gas pipeline

In many real navigation problems, moving objects may have some state or measurement constraints along their way. Using these constraints in conventional Extended Kalman Filter (EKF) equations results large matrices which are computationally time-consuming. In this paper, a new Constrained Navigation Filter (CNF) is proposed as a parallel to reduce the computational burden of the conventional EKF algorithm while increasing the positioning accuracy. So a methodology has been developed for Strap-down Inertial Navigation System (SINS) based on MEMS IMU applied on Pipeline Inspection Gauge (PIG) to sense data at constant sampling rate of 108 km of the pipeline. The results verified that using such a hybrid approach has improved positional accuracy 8.97% in comparison with that of the latest methods like EKF/ Pipe Line Junctions (PLJ). Also, the proposed method is 2.277 times better than EKF/PLJ in the algorithm runtime.

Experiments and modeling of fluctuating frictional force of pipeline inspection gauges

At present, pipeline inspection gauge (PIG) is the main means to ensure the reliability of oil and gas transportation pipelines. Due to the unstable friction between the PIG and the pipeline, the failure and blockage of the PIG often occurs. In this paper, the theoretical modeling and experimental measurement of fluctuating friction on PIG are studied. Firstly, considering the coupling relationship between cylindrical shell and conical shell, the contact radial force model between PIG and pipeline is derived. Based on which, the nonlinear frictional model of PIG is proposed, and the parameters are measured by several experiments. Then an experimental platform is developed to measure the fluctuating friction force of PIG in actual operation, and verify the accuracy of the proposed model. The motion characteristic analysis and dynamics research are carried out, and the PIG creeping phenomenon caused by fluctuating friction is explained. Finally, based on the proposed nonlinear friction model, the influence of parameters is analyzed. The conclusions based on the proposed model and the experiments results can provide technical supports for practical engineering application.

Research on identification of multiple target signals based on φ-OTDR

Phase sensitive optical time domain reflectometer (φ-OTDR) is widely employed in pipeline safety early warning, perimeter security, Pipeline inspection gauge (PIG) positioning and tracking, etc. Generally, equipment is applied in outdoor environments. There is a high probability that multiple intrusion signals exist simultaneously at a common position. Therefore, it is significant to unmix and identify each signal. In this paper, a multi-target signal recognition method based on φ-OTDR is proposed. The basic principles of φ-OTDR system and fixed point algorithm based on negative entropy maximization (FASTICA) are briefly introduced. The blind source separation and recognition of the mixed signals of hammer and motor are carried out, which proves the effectiveness of the method. In order to further quantitatively evaluate the effect of separation, the feature extraction of hammer signal and motor signal is carried out from two aspects respectively from time and frequency domain. The feature vector describing signal characteristics in terms of both time and frequency domain is proposed and used as the evaluation criterion of the separation performance. The experimental results show that the separated signal basically conforms to the feature vector, and the time domain feature is the most stable, with a maximum error of only 3.08%.

Multi-channel frequency difference noise analysis and cancellation method for the balanced field electromagnetic pipeline inspection gauge.

The balanced field electromagnetic technique as an effective in-line inspection method for cracks in long-distance oil and gas pipelines uses the pipeline inspection gauge (PIG) as the detection tool. PIG is characterized by the employment of a large number of sensors, but as each channel uses its crystal oscillator as a signal source, it inevitably generates frequency difference noise, which affects crack detection. A method of eliminating the frequency difference noise by using same-frequency excitation is proposed to solve the problem. Combining the principle of electromagnetic field propagation with the detection signal processing process, the formation process and characteristics of the frequency difference noise are theoretically analyzed, and the specific impact of frequency difference noise on crack detection is analyzed. The method of unified clock excitation for all channels is adopted, and a same-frequency excitation system is developed. The correctness of the theoretical analysis and the validity of the proposed method are verified by platform experiments and pulling tests. The results show that the effect of the frequency difference on noise follows the whole detection process, and the smaller the frequency difference, the longer the noise period. The frequency difference noise distorts the crack signal and is of comparable magnitude to the crack signal, which tends to drown out the crack signal. The same-frequency excitation method can eliminate frequency difference noise at the source and has a high signal-to-noise ratio. The method can provide a reference for multi-channel frequency difference noise cancellation in other AC detection technologies.

Research on mechanical behaviors of submarine pipeline inspection gauges in the elbow: FSI simulation and mathematic modeling

Pigs applied for submarine pipeline inspection and cleaning operations frequently suffer from blockage risk when passing through the elbow. It is meaningful to understand the frictional contact characteristics of the pig when it runs through the elbow, which helps improve the traveling ability of the pig. In this paper, a basic assumption that the trajectory of the mandrel geometric center coincides with the pipeline central axis is put forward according to the 3D Fluid-Structure Interaction (FSI) simulation results, and then a dynamic analytical model that predicts the driving force and describes the mechanical behaviors of cup pig in the straight pipeline and the elbow is respectively derived using a novel algorithm combined with the modified Burgers-Frenkel (MB-F) model. The established analytical model was calculated by means of MATLAB programming. Take a specific working condition as an example, and a quantitative assessment method was proposed. Based on the calculation results of the analytical model, the frictional contact characteristic of the pig in the elbow was studied, and the traveling performance and security of the pigging operation were further evaluated.

Smart Cup for In-Situ 3D Measurement of Wall-Mounted Debris via 2D Sensing Grid in Production Pipelines

The accumulation of separated out impurities from pipeline transported medium onto the pipe wall is a major cause of downtime maintenance of oil and gas production systems. To regularly scrub off wall-mounted debris and probe the severity, pipeline inspection gauges (PIG) are the state-of-the-art tools developed for the task, using the pressure differential across the device as the driving force, and tag-along sensing equipment for wall defects measurement. Currently, the PIG propulsion and sensing tasks are realized by separate compartments, limited to large diameter operations. In this work, a soft solution for medium to small diameter pipelines has been demonstrated. The smart cup with integrated sensing grid is proposed to achieve integrated wall-mounted debris dimensional measurement, without the need of additional sensors. To achieve the goal, this work starts from the mathematical modelling of the geometric problem, to new fabrication procedures, experimental setup, and finally finishes with validation results. Initial results have shown that using the proposed smart cup, the wall-mounted debris can be detected, with modelling error maxed at 5.1%, and deformation detection accuracy between 1.18% and 1.92% with respect to the outer diameter.

A Simultaneous Pipe-Attribute and PIG-Pose Estimation (SPPE) Using 3-D Point Cloud in Compressible Gas Pipelines.

An accurate estimation of pipe attributes, pose of pipeline inspection gauge (PIG), and downstream pipeline topology is essential for successful in-line inspection (ILI) of underground compressible gas pipelines. Taking a 3D point cloud of light detection and ranging (LiDAR) or time-of-flight (ToF) camera as the input, in this paper, we present the simultaneous pipe-attribute and PIG-pose estimation (SPPE) approach that estimates the optimal pipe-attribute and PIG-pose parameters to transform a 3D point cloud onto the inner pipe wall surface: major- and minor-axis lengths, roll, pitch, and yaw angles, and 2D deviation from the center of the pipe. Since the 3D point cloud has all spatial information of the inner pipe wall measurements, this estimation problem can be modeled by an optimal transformation matrix estimation problem from a PIG sensor frame to the global pipe frame. The basic idea of our SPPE approach is to decompose this transformation into two sub-transformations: The first transformation is formulated as a non-linear optimization problem whose solution is iteratively updated by the Levenberg-Marquardt algorithm (LMA). The second transformation utilizes the gravity vector to calculate the ovality angle between the geometric and navigation pipe frames. The extensive simulation results from our PIG simulator based on the robot operating system (ROS) platform demonstrate that the proposed SPPE can estimate the pipe attributes and PIG pose with excellent accuracy and is also applicable to real-time and post-processing non-destructive testing (NDT) applications thanks to its high computational efficiency.