Pipeline Maintenance Research Articles

Fatigue assessment of buried metal pipelines under traffic loads using video monitoring data

Traffic loads have an important impact on long-term performance of buried urban pipelines due to generation of cyclic stress and fatigue damage. As a key task for pipeline fatigue assessment, the investigation of traffic-induced pipe stress and fatigue load spectrums is always a big challenge. Focusing on the metal pipelines buried under urban intersection, an integrated framework is proposed for fatigue assessment of the pipelines under traffic loads using video monitoring data acquired by the widespread surveillance cameras in cities. The computer vision algorithms and a quarter vehicle model are first employed to identify traffic loads. Analytical pipe-soil models are then developed to calculate pipeline stress and establish the traffic-induced fatigue load spectrums of buried pipelines, based on which the Monte-Carlo simulations are finally conducted to evaluate cumulative fatigue damage and fatigue reliability. A case study on a DN500 steel pipeline buried under an urban intersection demonstrates and validates the fatigue assessment procedure. The results can provide a basis for decision support regarding maintenance and replacement of urban pipelines.

The prediction analysis of failure pressure of pipelines with axial double corrosion defects in cold regions based on the BP neural network

The conventional corrosion assessment codes show a certain conservatism in predicting the failure pressure of pipelines with double corrosion defects, which will lead to the failure of reasonable maintenance of pipelines. In addition, when the numerical simulation method is used to predict the failure pressure of the pipeline, the time cost is relatively large. To predict the failure pressure accurately and quickly, ABAQUS and MATLAB were used to analyze the failure pressure of pipelines with axial double corrosion defects in cold regions in this paper, and developed the BP (Back Propagation) neural network for predicting the failure pressure. The results show that the corrosion depth has the most obvious effect on the failure pressure, and the maximum failure pressure loss rate is 42.40%; corrosion length is second, 17.56%; and corrosion spacing is the smallest at 7.16%. Compared with the codes, the failure pressure value predicted by the BP neural network is the closest to the experimental data. The maximum error is 10% and the minimum error is 1%. It proves that it is reasonable to use the BP neural network to predict the failure pressure.

Simulation study on mechanical wear of the diamond grain cutting pipeline steel

With the exploitation of marine resources, the development of maintenance operation technology for subsea pipelines transporting oil and gas has become the focus worldwide. Diamond bead wire serves as important engineering equipment in subsea pipeline maintenance, and the study of the wear mechanism of diamond grains on the beads is key to improving the cutting efficiency and lifetime of diamond bead wire. In this work, a theoretical model of the mechanical wear rate of the diamond grain was established, and a simulation model of the diamond grain cutting X65 pipeline steel was developed by applying smoothed particle hydrodynamics method. By studying the effects of the cutting factors of the diamond grain on mechanical wear, the mechanisms of adhesive wear, abrasive wear, and fatigue wear were clarified. The results indicate that the diamond grain in line contact or large surface contact with X65 steel contributes more to wear rate reduction than point contact; The mechanical wear rate predominated by adhesive wear and abrasive wear of the diamond grain increases with the increase of cutting speed and depth. And when the cutting speed is 22–26 m/s and the depth is 20–30 μm, the growing trend of the mechanical wear rate turns gentle, which is more suitable to balance improving cutting efficiency and reducing mechanical wear.

Uncertainty in the Estimation of Partial Safety Factors for Different Steel-Grade Corroded Pipelines

This paper assesses the uncertainty of the partial safety factors for the design of corroded pipelines against burst failure due to the variability associated with the strength model selection. First, 10 calibrated burst pressure prediction models for corroded pipelines are adopted and duly categorised under low-, medium- and high-grade steel classes. The probabilistic characteristics of the pipe burst strength are studied using Monte Carlo simulation for the selected models. Model uncertainty factors are used to correct the burst pressure predictions by the design equations. Model strength factors are derived for models in each category that will provide coherent reliability. The first-order reliability method is employed to estimate the partial safety factors and their uncertainty as a function of operational time. Finally, the influence of the corrosion growth model on the evaluation of partial safety factors is assessed. The results obtained in this study can provide vital guidance regarding the design and maintenance of different steel-grade pipelines.

ИСПЫТАНИЯ ПО ОПРЕДЕЛЕНИЮ ПАРАМЕТРОВ УПРАВЛЯЕМОСТИ ЛЁГКОГО КОЛЁСНОГО ВЕЗДЕХОДА АМФИБИИ С БОРТОВЫМ СПОСОБОМ ПОВОРОТА

This article presents some data obtained during tests of particularly light snowmobiles with an on-board turning method in order to identify indicators of their technical and operational properties, in particular controllability. The intermediate results of the work carried out by the team of researchers of the R.E. Alekseev NSTU are presented. The investigated snowmobile is supposed to form the basis of a model range of ground transportation and technological means. The developed line is positioned to ensure the individual mobility of technical personnel engaged in the maintenance of pipelines, power lines and communications, in addition to conducting search and rescue and patrol operations, including in the circumpolar regions of the North. The development, as well as the modernization of their structures, experimental substantiation of the calculation principles was chosen as a further direction of the project development.

КОНТРОЛЬ ПАРАМЕТРОВ СОСТОЯНИЯ КАТОДНОЙ ЗАЩИТЫ МАГИСТРАЛЬНЫХ ТРУБОПРОВОДОВ С ИСПОЛЬЗОВАНИЕМ БЕСПРОВОДНОГО ДОСТУПА

The article presents engineering solutions for creating a wireless system for data sampling of cathode protection for gas transmission pipelines. These aim at advancing level of automated monitoring of parameters of corrosion protection using existing methods and regulations on pipelines maintenance in force.

Maintenance and repair of water supply and drainage pipelines using modern equipment and based on forecast indicators

Maintenance and repair of water supply and drainage pipelines using modern equipment and based on forecast indicators

Research on integrity Management of long distance pipeline

Long-distance pipelines transport and distribute vast amounts of oil and natural gas around the world every day. It is considered the safest way to transport oil and gas because it rarely breaks down. The integrity management of long distance pipeline is very important for pipeline transportation. Based on the main content of integrity management of long distance pipeline and the basic requirements for operators, this paper puts forward the main responsibilities and management principles of integrity management of long distance pipeline. At last, according to the characteristics of Chinese long-distance pipeline, the integrity management of the whole pipeline is regulated, which is an important reference for the late safety maintenance of Chinese long-distance pipeline.

Концепция оптимизации обслуживания газопроводов

Концепция оптимизации обслуживания газопроводов

Supply resilience assessment of natural gas pipeline network systems

Resilience is one of the important components of system safety evaluation and optimization, the research of which for natural gas pipeline network system (NGPNS) is still in initial stage, especially for the resilience indexes and process description. To evaluate the resilience of NGPNS more synthetically and practically, considering different types of disturbances, an integrated framework is proposed for evaluating the supply resilience of NGPNS, involving the topology and operating conditions. The characteristics of both deterministic and probabilistic disturbances are analyzed. The innovations and corresponding methodology are that global resilience, temporal resilience and threshold resilience are proposed as the resilience evaluation indicators; the maximum flow method and shortest path method are integrated with operation and structural parameters to calculate the amounts and routes of gas supply, before and after disturbance; based on complex networks theory and graph theory, the traditional view point is changed from whole system to the affected area. The results can contribute to the guidance of NGPNS topological designing and the building of prewarning scheme, including spare gas sources and gas routes optimization, and the strategy of pipeline maintenance, also can help the rapid analysis of disturbance consequences and the enhancement of evaluating accuracy in NGPS resilience.

An inchworm-inspired soft robot with combined functions of omni-directional steering and obstacle surmounting

PurposeSoft rod-climbing robots have been known to have great potential in a wide variety of working conditions, including cable inspection and pipeline maintenance. However, one of the most notable issues preventing their popular adoption is their inability to effectively cross obstacles or transfer between rods. To overcome these difficulties, this paper aims to propose an inchworm-inspired soft robot with omni-directional steering.Design/methodology/approachTheoretical models are first established to analyze the telescopic deformation, bending, steering and climbing ability of the soft robot. The main modes of movement the soft robot is expected to encounter is then determined through controlled testing so to verify their effectiveness (those being rod climbing, steering and obstacle surmounting).FindingsThe soft robot demonstrated a capability to cross obstacles 1.3 times its own width and bend 120° omni-directionally, evidencing outstanding abilities in both omni-directional steering and obstacle surmounting. In addition, the soft robot also exhibited acceptable climbing performance in a variety of working conditions such as climbing along vertical rods, transferring between rods with differing diameters or friction surfaces and bearing a payload.Originality/valueThe soft robot proposed in this paper possesses abilities that are both exceptional and crucial for practical use, specifically with regard to its omni-directional steering and obstacle surmounting.

A Scoping Review of Pipeline Maintenance Methodologies Based on Industry 4.0

The fourth industrial revolution was a milestone at the industrial level. It forced most industries to evolve technically and for their collaborators to prepare and advance together with technology; the oil industry was no exception. It develops its activities in dangerous and dynamic environments and needs to protect its human resources, equipment, and infrastructure. This article presents a scoping review, based on the PRISMA guidelines, of pipeline maintenance methodologies based on Industry 4.0. From the first collection of 123 articles from prestigious databases such as SpringerLink, MDPI, Scopus, IEEEXplore and ACM, a final sample of 31 articles was obtained. Here, technologies that enhance preventive and predictive maintenance systems are discussed. The results show that predictive maintenance compared to preventive maintenance has a percentage difference in upkeep time optimization of 38% in the last five years. This difference was corroborated with a Student’s t-test for independent samples, with a significance of 0.023. Likewise, the most used technologies were analyzed, with artificial intelligence standing out with 45.16%.

Risk Indentification on Superheater Pipeline Boiler of 600 MW Power Plants Using a Risk Based Inspection (RBI) Method

Steam power plants are the most efficient type of power generation and can make a significant contribution to the demand for electricity resources. Steam power plants, in general, utilize energy derived from seawater to be process into steam in boilers so that often many pipe failures have occurred due to thinning due to corrosion caused by inappropriate water quality in small units and difficult to detect continuously. In general, inspection planning related to pipe thinning in steam power plants shows a minimal trend compared to inspections in the oil & gas industry. Moreover, it has no basic policy as to how inspection intervals and piping methods will be carry out. In this study, it carried out with the aim of conducting a risk assessment of boiler pipe failure so that it can provide a more optimal overview of the inspection plan. Analysis using Risk Based Inspection (RBI) will be used as a research reference to create the most effective and efficient inspection system as to minimize the impact and expenses cost in pipeline maintenance. After RBI assessment, the inspection plan for superheater pipeline on boiler line will be held every 2 years.

An enhanced positioning technique for underground pipeline robot based on inertial Sensor/Wheel odometer

For traditional underground pipeline robot based on the inertial sensor/wheel odometer, the outliers of the data collected by the positioning system, the attitude error of the inertial sensor and the velocity measurement error of the wheel odometer are crucial factors affecting positioning accuracy of the pipeline robot, and have a significant influence on underground pipeline maintenance and pipeline mapping. To solve the above three error factors, an enhanced positioning method for the underground pipeline robot based on the inertial sensor / wheel odometer is proposed in this paper. Firstly, basic principles including robot attitude calculation based on inertial sensors, robot velocity calculation based on wheel odometer, position calculation of pipeline robot and outliers elimination based on extrapolation fitting method are introduced; secondly, the velocity information and attitude angle of the pipeline robot is corrected by prior-backtracking method; thirdly, the round-trip positioning data optimization method based on adaptive weight is designed to improve the accuracy of the whole pipeline robot positioning system; finally, three pipelines with different lengths are introduced to verify the effectiveness and reliability of the proposed method. The experimental results show that the error of position information is no more than 0.18%, 0.07% and 0.11% of survey length, respectively.

Method to simulate transient pressure behaviors in subsea natural gas pipelines with a moving smart isolation device

The pipeline maintenance technology using smart isolation devices is an effective mean to prevent potential accidents occurred in subsea natural gas pipelines. The devices need to move with the flowing fluid and finally stop at a desired location inside the pipe, to achieve successful communication with the external link. The sudden change of the moving velocity of the device may cause severe transient pressures, which is one of the determining factors of the moving process of the device and its final stopping location inside pipe. This paper proposes a method using a coupled dynamic mesh technique to simulate the transient pressure behaviors in natural gas pipelines with a moving device. The implicit and explicit coupled method has been developed to achieve the simulation of the moving interfaces and improve the ability of incorporating complex influence factors. Verifications have been conducted using the results from the experimental method, and the reasonable agreement between the results from these two methods validates that the proposed method can be used to simulate the transient pressure behaviors in gas pipelines with a moving device. The proposed simulation method coupling with the moving state of the device has been developed and applied to a practical case to predict the moving process and thus the final stopping location of the device.

Control system of the autonomous underwater helicopter for pipeline inspection

For decades, in order to fully transport energy and rationally redistribute resources, humans have laid a large number of underwater pipelines in rivers, lakes and oceans to transport resources. However, due to corrosion, load, natural vibration, and crustal movement, underwater pipelines will undergo fatigue fracture, causing resource leakage, environmental pollution and economic losses. In recent years, the problem of maintenance of underwater pipelines has become one of the most difficult problems that need to be solved. And the internal inspection of the pipeline is the key problem. In this paper, we successfully realize this through algorithm and experiments. Here we show a circular dish-shaped underwater helicopter (AUH) that used to realize the depth-fixed line tracking control in the underwater pipeline. This work proposed a priority control system which combines depth control and line tracking control well and an underwater image processing algorithm flow to identify the line well.

MODERN METHODS OF REPAIR OF PIPELINES

At the stages of maintenance and repair of pipeline systems, there is a need to use flameless cutting in existing pipelines, in particular: when it is necessary to connect intake chambers and start cleaning pistons, and during pipeline repair with a complete replacement of the pipe body without stopping the transportation of the product. Also, fireless cutting is effectively used to connect branch pipelines during the development of pipeline systems. One of the progressive directions of improving the maintenance and repair of pipelines is the development of cutting methods that would ensure high efficiency and environmental friendliness of the work. However, their successful application is impossible without a theoretical and experimental study of the process of welding the branch pipe to the operating pipeline.

Research on the Improving Performance of Foam Concrete Applied to the Filling of Natural Gas Pipeline Cross-River Tunnel.

The shield tunnel is a common solution for natural gas pipelines crossing rivers. Consequently, the development of natural gas tunnel filling materials with excellent performance is crucial to the safe operation and maintenance of pipelines. The foam concrete offers a reasonable solution. Nevertheless, since its inherent compressive strength decreases almost proportionally with the decrease in density, obstacles remain concerning obtaining the high density and relatively low strength required for natural gas tunnel filling. Here, a synergistic optimization strategy was proposed involving the orthogonal test, univariate control, and comprehensive balance method. It involves modifying the type and proportion of cementitious matrix, in particular by incorporating fly ash and PVA fibers in the mix design, and synergetic determining the best mix ratio from the aspects of compressive strength, stability, and dry density. The obtained foam concrete has a compressive strength of 4.29 MPa (FC4) and a dry density of 1060.59 kg/m3 (A11), which meets the requirements of pipeline pressure and pipeline anti-floating. This study is applied to the Yangtze River shield crossing project of the Sino-Russian Eastern Gas Pipeline, and ANSYS was used to simulate the stress and deformation of the foam concrete. This work provides an efficient foam concrete optimization mix scheme, and supports the application of foam concrete in the filling of the long-distance cross-river natural gas tunnels.

Cross-domain feature selection and diagnosis of oil and gas pipeline defects based on transfer learning

Developing intelligent pipeline defect diagnosis technology is of great significance to ensure the efficiency and safety of pipeline transportation. However, a challenge in real-world tasks is the inadaptability and instability of these technologies for processing data from different distributions. Therefore, this paper proposes an intelligent transfer defect diagnosis framework that combines a hybrid feature selection method and transfer learning (TL) technology. The hybrid feature selection method consists of two cross-domain filtering feature selection methods and feature subset evaluation. A Monte Carlo simulation wrapper is used to obtain the best transfer feature subset. The obtained optimal feature subset is fed to the feature adaptation-based classification method for defect diagnosis. We used two different datasets as the target domain and source domain and simulated two transfer scenarios to verify the framework. Experimental results demonstrate that the proposed diagnosis framework achieves high accuracy and effectiveness in pipeline defect diagnosis cross-domain transfer tasks. This will facilitate pipeline maintenance engineers in solving the problem of pipeline defect diagnosis and reasonably arranging pipeline maintenance.

Tensile Strain Capacity Prediction Model of an X80 Pipeline with Improper Transitioning and Undermatched Girth Weld.

As an important component of strain-based design, the tensile strain capacity (TSC) concept has been extensively used for pipelines that experience expectable plastic strain for both installation and service. However, some stress-based designed pipelines have experienced unforeseen plastic strain in the past decade that resulted in failure. It seems that the tensile strain capacity has gradually become an important requirement for geohazard risk management and pipeline maintenance of stress-based design pipelines. The tensile strain capacity of an X80 pipeline is investigated. The assessment in this work was based on the fracture initiation–control-based limit state. This limit state corresponds to the onset of stable tearing and generally provides a reasonably conservative estimate. Besides that, factors such as wall thickness, material’s strain hardening capacity, toughness, weld strength mismatch, HAZ (heat-affected zone) softening, pipe wall thickness, high–low misalignment, and internal pressure were also investigated to construct a prediction model of the X80 vintage pipeline.