Pipeline Defects Research Articles

Design of A Free Floating Ultrasonic Inner Spherical Detector for Pressure Pipeline

Ultrasonic inspection of the corrosion and scaling in industrial pressure pipelines is necessary due to the adverse effects of defects on medium flow and heat transfer. In this paper, a free floating ultrasonic inner spherical detector has been designed to detect and locate defects in pipelines. The flange mechanical structure of ultrasonic inner detection intelligent ball meets the internal space requirements and external environmental requirements. They are connected of two parts flange type. A complete set of spherical shell structure design covering the functions of sealing and external pressure resistance is proposed and completed. One part is the inner sphere, and the other is the outer shell. Pipeline experiments show that the spherical detector can reach the exit smoothly through curved pipes, inclined pipes and vertical pipes without jamming and stable motion attitude, collects all kinds of information along the way, determines the existence of defects and achieves accurate positioning.

Inspection Robot for Submarine Pipeline Based on Machine Vision

In order to improve the intelligence of submarine pipeline inspection, reduce manpower and material resources, and improve inspection efficiency, an underwater pipeline inspection robot based on machine vision is proposed. This paper introduces the existing pipeline inspection methods and technologies, and analyzes the feasibility of pipeline inspection and inspection technologies based on image processing. On the basis of this subject, the corresponding circuit and embedded system are designed, and the related images are sampled, processed and analyzed, and the images are subjected to threshold segmentation, binarization, edge corrosion and other operations. Furthermore, the experimental site and underwater robot were built, and the pipeline defects were detected in real time by using the recognition method based on neural network.

THE USE OF GIS TECHNOLOGIES AND AEROSPACE SURVEY MATERIALS FOR THE ANALYSIS OF PIPE DEFECTS IN MAIN OIL PIPELINES AND THE SOURCES OF THEIR OCCURRENCE

The article is devoted to the problem of determining the position of pipe defects in the main pipeline, identified using in-line diagnostics (IDD) data and correlating them with possible sources. Data on defects can be obtained using IDD, spatial referencing is performed using GIS technologies (linear coordinate system tools), and the sources of defects (hazardous natural processes) are determined using Earth remote sensing tools.

Effect of location of crack in dent on burst pressure of pipeline with combined dent and crack defects

Burst pressure of pipelines with longitudinal cracks located at the centre of rectangular dents varies with defect size and recent reports indicate that it could be very high for shallow cracks inside shallow dents and for cracks inside restrained dents. However, it is not clear whether cracks located in the flank of dents would have the same impact on burst pressure of pipelines with dent-crack defects. In addition, studies show that the location of maximum strain in circular dents shifts away from the centre towards the flank when dented pipes are pressurised, but the implication on the propagation of longitudinal cracks located in various parts of a dent has not yet been widely investigated. In this paper, models of pipelines with longitudinal cracks inside rectangular dents were created using the Finite Element Methods software Abaqus to analyse crack propagation and predict the associated burst pressure. The in-built Extended Finite Element procedure in Abaqus was used to model crack propagation through the pipe. The models were calibrated and validated using previously published results of burst tests and tests of material properties. The effect of longitudinal cracks in both the flank and centre of the dents on the burst pressure was analysed by varying the crack length, the crack depth, the dent depth, the internal pressure during dent formation and the dent constraint condition. The results show that longitudinal cracks in the flank of rectangular dents are more severe for pipeline integrity than cracks located in the centre of dents. Crack depth and crack location inside the dents are the most influential parameters when assessing dent-crack defects in pipelines. Their effects on burst pressure are magnified by crack length, dent depth and denting pressure.

Mechanical behavior analysis of gas pipeline with defects under lateral landslide

Landslide is the main factor threatening the operation safety of long-distance gas pipeline, and the internal corrosion of pipeline will also seriously affect its reliability. Using LS-DYNA software, considering the interaction between pipeline and soil, a model of pipeline with defects crossing landslide is established based on the coupling of smoothed particle hydrodynamics and finite element method (SPH-FEM). The effect of the depth, number and spacing of pipeline defects and gas pressure on the mechanical behavior of pipeline is analyzed. The results show that the corrosion defects and gas pressure have little effect on the deformation of the pipeline. It is also found that when the gas pressure of the pipeline increases gradually from zero, the residual strength of the pipeline has a maximum value. Additionally, for the single corrosion defect, the maximum plastic deformation appears in the center of the corrosion defect, but for the double corrosion defect, it appears in junction of the corrosion defects. Furthermore, with the increase of landslide displacement, the plastic strain zone gradually extends along the circumference of the pipeline in these two kinds of defective pipelines. At the same time, the interaction between adjacent corrosion defects is found. The interaction is related to the defect spacing: within a certain range, the interaction increases with the increase of the defect spacing, the maximum equivalent stress appears at the junction of defects, and the stress concentration area expands along the circumferential direction. With the further increase of the spacing, the interaction disappears.

Assessment of the Local Mechano-Electrochemical Effect on Pipeline Defects by 2D and 3D Finite Element Models

Local corrosion at a defect on a pipeline was assessed using both 2-dimensional (2D) and 3-dimensional (3D) finite element models under mechano-electrochemical (M-E) interaction. While the M-E interaction increases corrosion activity at the defect, the assessment of M-E interaction would have different results using 2D and 3D models. Compared with the 3D model, the 2D model produces a greater local stress, a higher local plastic strain, a more negative corrosion potential and a higher anodic current density at the defect, and thus, a lower threshold internal pressure causing local yielding. The 3D model is more conservative for corrosion rate prediction of corroded pipelines. A new concept, rAZ (the ratio of the anodic zone length to defect length in the 2D model, or the ratio of the anodic zone area to the defect area in the 3D model), is proposed to define growth mode of the corrosion defect. There is a smaller rAZ produced in 2D model. At specific internal pressures, the 2D model predicts an ellipsoidal defect center area experiencing accelerated corrosion and potentially resulting in pipeline leaking.

Non-contact harmonic magnetic field detection for parallel steel pipeline localization and defects recognition

A novel detection method and targets signal extraction algorithm for parallel steel pipeline localization and defects recognition based on harmonic magnetic field are proposed. An orthogonal vector differential focusing array detector was designed, which radiates high-frequency (HF) and ultra-low-frequency (ULF) electromagnetic waves to pipeline based on the principle of Frequency Modulated Continuous Wave (FMCW), and records the signals in parallel using high-sensitivity Tunnel Magneto Resistance (TMR) array sensors. The joint signal pre-processing algorithm of Combination Morphological Pulse Elimination (CMPE) and Quantum Genetic Gaussian Potential Stochastic Resonance (QGGPSR) is proposed to improve signal quality by adaptively eliminating random pulse and noise. The time–frequency analysis algorithm Complementary Ensemble Local Mean Decomposition (CELMD) is used to decompose the pipeline defects signal in detail, and the appropriate components are selected and fused into a correlation array signal cluster. Finally, the targets signal are separated by Limited-memory BFGS Independent Component Analysis (L-BFGS-ICA) based on machine learning optimization to enhance their legibility. The magnetic dipole harmonic simulation model and the 20# steel parallel pipeline experimental platform are established, and compared with the passive detection method to verify the effectiveness and practicality of the proposed method. The results show that this method can accurately locate parallel pipelines and detect different kinds of defects in noisy environment, which is of great significance for the application of non-contact Non-Destructive Testing (NDT) in practical engineering.

Experimental Investigation of Pipeline In-Service Welding Process

Welding of pipeline in active operation (called in-service welding) is an advancedtechnique employed to repair pipelines to safe transmission of petroleum or gas. A thermalexperimental study is accomplished on welding process of gas pipeline in this work. Anexperimental setup had been designed, manufactured and instrumented to estimate the methodfor repairing locally pipelines defects (such as cracks and holes wall surface) under the influenceof internal pressure. Also the thermal history of welding process was investigated experimentallyto three cases which are : traditional welding process with no fluid flows inside the test pipe, anin-service welding process considering air as the flowing fluid inside test pipe, and an in-servicewelding process considering the liquefied petroleum gas (LPG) as flowing fluid inside test pipe.Results show that direct deposition of welding metal on a through hole under the influence ofinternal pressure succeeded for flow rate less than (12lpm) and failed for flow equal or higherthan (12lpm) in which a sleeve repair is considered. The calculations are followed by a separatethermal stress analysis based on the thermal history.

Identification and Sizing of Neighboring Pits Using Three-Axis Magnetic Flux Leakage Technique

Abstract Neighboring corrosion pits are one of the most frequently found defects in gas pipelines. Because of the interaction with each other, these defects accelerate the corrosion growth rates in the wall of the pipelines. Hence, it is meaningful to discriminate multiple neighboring pits from single isolated pits by analyzing their characteristics. This article presents the results of a study on the use of a three-axis magnetic flux leakage (MFL) technique for the identification and sizing of neighboring corrosion pits. Various patterns of two neighboring pits are considered by modifying the separation distances between them. Finite element modeling as well as experimental measurements is used to investigate the spatial distributions of the three MFL components (axial, radial, and circumferential) generated by the neighboring pits. The results indicate that the axial as well as the radial MFL components of the neighboring pits merge to one signature the closer the two defects are, and thus, no width sizing of the individual pits is possible anymore. In contrast, both pits are still discernible in the circumferential MFL signatures. The described method can help to identify neighboring corrosion pits and thus improve the sizing accuracy of MFL measurements.

Experimental Study of the Behavior of Wrinkled Energy Pipelines Subjected to Cyclic Pressure Loading

AbstractThe development of a small wrinkle defect in a buried pipeline can be a challenging issue for pipeline operators to approach. Although extensive research has been conducted to evaluate the ...

Evolved fuzzy min-max neural network for new-labeled data classification

Pattern classification is a fundamental problem in many data-driven application domains. New-labeled data refers to the data with the labels that are new and different from source labels. How to learn the new-labeled data is a crucial research in the data classification. In this paper, an evolved fuzzy min-max neural network for new-labeled data classification (FMM-NLA) is proposed. In FMM-NLA, the network can be self-evolved. Unlike the traditional FMM methods, the trained network of FMM-NLA can be expanded when new-labeled data added. FMM-NLA is a continuing-learning method, which can realize the continuing training process without retraining all the data. In order to verify the superiority of the proposed method, benchmark data sets are used. The experimental results show that FMM-NLA is effective in handling new-labeled data. Moreover, the application result on the pipeline defect recognition in depth shows that FMM-NLA is effective in solving the new-labeled defect recognition problem.

Passive imaging of water pipelines using ambient turbulence noise

Ambient noise generated by flowing water turbulence is harnessed as a signal source for imaging key parameters and fault detection in water pipelines. This approach is important because it can aid in the estimation of wave speed or detection of water pipeline defects such as blockages and leakages. More importantly it overcomes the challenging problem of generating a signal source of sufficient power to provide the necessary signal-to-noise ratios for conventional water pipeline imaging and fault detection techniques. In this paper, the expressions of the auto- and cross-correlation functions of the ambient noise between sensors are derived using wave theory. It is shown that the time-domain Green’s functions can be extracted from the correlation functions. Experimental and numerical examples are provided for water pipelines to demonstrate that wave speed can be estimated from the time-domain Green’s functions. A method for extending the technique, by using straightforward but accurate approximations of the correlation functions, to detect the presence of defects in the profile of the water pipeline is also proposed.

Servo control and detection system of magnetic levitation pipeline based on FPI bus

The growth rate of China’s plastic pipe industry ranks first in the world. In 2018, China’s plastic pipe production broke through the 16 million ton mark. With the growth of China’s economy, the output of plastic pipe still has a large space for increase. However, the detection of pipeline defects has been relatively backward in China. Aiming at the problem of pipeline internal inspection, this paper proposes a magnetic suspension non-contact detection method, and designs a real-time feedback servo control system for the detection system. to improve the efficiency and quality of pipeline inspection, and expand the scope of pipeline inspection in industrial production.

Research on Weld Defect Identification with X-ray Based on Convolutional Neural Network

In the process of X-ray weld defect detection, a deep learning network structure based on the principle of simulated visual perception is constructed. The size and number of layers of convolutional neural network template, and the influence of different activation functions, are analyzed with an improved method proposed, which may avoid the characteristic steps for the extraction of defect images, and can be used to directly determine the presence of any defect. Experiments on 200 images show that the proposed method for SDR images has an identification rate of more than 98%, which is better than other methods, and has highly practically in pipeline defect detection.

Research and evaluation of the measurement uncertainty with the pipeline robot

The pipeline robot used to detect and maintain the pipeline is a novel technical means, which changes the single traditional mode of excavation sampling inspection of pipeline. This detection technology not only improved the accuracy of pipeline detection but also is easy to analyze the causes of pipeline defects for pipeline engineering management maintenance staff. It is possible to carry out a review of defect and develop pipeline maintenance solutions. Using this method can eliminate the security hidden danger before repairing or replacing section. Thus, the use of a pipeline can save a lot of maintenance costs and reduce pipeline maintenance cost, which can also ensure the safety of people’s life and property. In addition, this method can also reduce the toxic gas or liquid leakage to protect environmental pollution. Therefore, the research of a pipeline detection robot has an important scientific significance and social value. In this paper, our group has a base of the long-term research with the geometric measurement technology, so the measurement uncertainty of the common pipeline robot is studied. The measurement uncertainty of error about positioning is defined as U=0.59mm+9×10−2L, k=2 (L unit is m), and the uncertainty evaluation of angle errors measured, including the forward and backward pitching angle, left-right tilt angle, is U=0.10°+4.6×10−3 θ(θ unit is °).

Shedding Damage Detection of Metal Underwater Pipeline External Anticorrosive Coating by Ultrasonic Imaging Based on HOG + SVM

Underwater pipelines are the channels for oil transportation in the sea. In the course of pipeline operation, leakage accidents occur from time to time for natural and man-made reasons which result in economic losses and environmental pollution. To avoid economic losses and environmental pollution, damage detection of underwater pipelines must be carried out. In this paper, based on the histogram of oriented gradient (HOG) and support vector machine (SVM), a non-contact ultrasonic imaging method is proposed to detect the shedding damage of the metal underwater pipeline external anti-corrosion layer. Firstly, the principle of acoustic scattering characteristics for detecting the metal underwater pipelines is introduced. Following this, a HOG+SVM image-extracting algorithm is used to extract the pipeline area from the underwater ultrasonic image. According to the difference of mean gray value in the horizontal direction of the pipeline project area, the shedding damage parts are identified. Subsequently, taking the metal underwater pipelines with three layers of polyethylene outer anti-corrosive coatings as the detection object, an Autonomous Surface Vehicle (ASV) for underwater pipelines defect detection is developed to verify the detection effect of the method. Finally, the underwater ultrasonic image which used to detect the metal underwater pipeline shedding damage is obtained by acoustic sensor. The results show that the shedding damage can be detected by the proposed method. With the increase of shedding damage width, the effect of pipeline defect location detection is better.

Technique for operational diagnosis of pipelines of energy systems and complexes

THE PURPOSE. To consider the problems of reliability of pipeline systems of housing and communal services. To analyze existing methods for assessing the technical condition of pipelines. To develop an improved technique that allows you to search for various types of defects in pipelines. To develop a device for inertial excitation of low-frequency diagnostic vibration vibrations. To develop software in the LabVIEW environment for collecting, storing and processing signals from a sensitive sensor (piezoelectric sensor) installed on a pipeline. To conduct a series of experimental studies to te st the proposed methodology. METHODS. The method of inertial excitation of vibrations was used to excite vibrations in the wall of the investigated pipeline. To search for the natural frequencies of vibrations of the pipeline under study, mathematical mode ling methods were used, implemented in the ANSYS software package. During the experiments, the fast Fourier transform method was used to process the signals coming from the piezoelectric sensor. RESULTS. The article presents a technique for assessing the t echnical condition of pipelines, as well as a device for inertial excitation of vibrations. The article presents the results of experimental studies on a fiberglass pipeline, the results showed that when an oscillatory wave passes through the wall of a defect-free pipeline, its amplitude changes insignificantly. If there is a defect in the wall of the investigated pipeline, the vibration amplitude will be much weaker due to the dissipation of vibrational energy in the place of the defect. Thereby, it is pos sible to determine not only the presence of a defect, but also its size by the degree of attenuation of the signal amplitude CONCLUSION. The proposed technique is the basis for the creation of a new measuring and diagnostic complex for vibration control of pipelines.

Compressive-sensing based super-resolution detection for leakage and uniform blockage in water pipelines

Reflectometry techniques for water pipeline defect detection suffer from low resolution problems since only low frequency waves can travel long distances in pipeline systems. In this paper, a method for estimating the super-resolved impulse response (IR) of the system from reflectometry measurements is established using a gridless compressive sensing (CS) framework. The proposed method provides super-resolution results by reconstructing the sparse IR consisting of a series of delta (δ) functions, whose time delays and amplitudes are estimated by solving the dual problem of CS optimization. The unique reconstruction of IR is guaranteed by a minimum separation between adjacent δ functions, which closely relates to IR sparsity. This minimum separation requirement is validated theoretically, using the restricted isometry property, and numerically. It is proven that the IR of two discrete defects spaced less than a quarter of the minimum observation wavelength can be uniquely reconstructed with super-resolution. Systematic simulations and laboratory experiments show that the proposed method precisely recovers the IR of uniform blockages and leakages in water pipelines when the minimum separation is satisfied. With super-resolution IR, closely spaced blockage edges and leakages can be well distinguished and precisely localized. The size of both blockages and leakage holes can also be estimated with millimeter level accuracy.

Research on frequency domain synthetic aperture focusing pipeline guided wave imaging based on phase migration

In order to overcome the limitations of traditional ultrasonic imaging methods, which cannot directly give the imaging results of defects in a pipeline and have low imaging quality, a frequency domain synthetic aperture focusing pipeline imaging method based on phase migration is proposed. The measured data were reconstructed by frequency domain synthetic aperture focusing, and the results were compared with those of time-domain synthetic aperture focusing imaging. The results show that the frequency domain synthetic aperture imaging method is more accurate for the location and quantification of defects in a pipeline, the influence of noise waves on the imaging transverse resolution is reduced, and the imaging resolution is increased by nearly 30%. It was found that the quantitative errors of axial double defects are 5.2% and 17.9%, and that of circumferential defects is 7.5%. These results show that the frequency domain synthetic aperture focusing pipeline imaging algorithm based on phase migration can achieve the accurate determination of multiple defects in pipelines.

Harmonic Detection System and Identification Algorithm for Steel Pipeline Defects

Aiming at the problem of defects detection of steel pipeline, a harmonic detection system was developed based on electromagnetic principle, and the target signal identification algorithm was studied. The Advanced RISC Machine (ARM) Cortex-M3 was adopted to design digital adjustable harmonic excitation source, and its effective output power can up to 70 W. The Field Programmable Gate Arrays (FPGA) and ARM Cortex-M4 were introduced to design 15 channels high speed data collector, which parallel local-storage rate of each channel can reach 4.7 kHz. The electromagnetic focusing excitation array and Tunnel Magneto Resistance (TMR) sensors array were constructed to improve the spatial resolution of the detection system. Meanwhile, the system also integrated GPS positioning and LCD real-time display functions. Furthermore, the algorithm combining Empirical Mode Decomposition (EMD) and variable-scale Stochastic Resonance (SR) was proposed to process signal and enhance the targets. The effectiveness of the instrument and algorithm are well verified in both simulation and experiment. The results show that this method has higher integration and better detection effect, which provides a novel method for non-contact detection of metal material defects and is suitable for engineering applications.