scholarly journals Modeling and Calculation of Dent Based on Pipeline Bending Strain

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Qingshan Feng ◽  
Rui Li ◽  
Hong Zhang
Keyword(s):  
Inertial Measurement Unit ◽  
Oil And Gas ◽  
Measurement Unit ◽  
Mapping Data ◽  
Long Distance ◽  
Bending Strain ◽  
Strain Data ◽  
Integrity Management ◽  
Novel Method ◽  
The Mean

The bending strain of long-distance oil and gas pipelines can be calculated by the in-line inspection tool which used inertial measurement unit (IMU). The bending strain is used to evaluate the strain and displacement of the pipeline. During the bending strain inspection, the dent existing in the pipeline can affect the bending strain data as well. This paper presents a novel method to model and calculate the pipeline dent based on the bending strain. The technique takes inertial mapping data from in-line inspection and calculates depth of dent in the pipeline using Bayesian statistical theory and neural network. To verify accuracy of the proposed method, an in-line inspection tool is used to inspect pipeline to gather data. The calculation of dent shows the method is accurate for the dent, and the mean relative error is 2.44%. The new method provides not only strain of the pipeline dent but also the depth of dent. It is more benefit for integrity management of pipeline for the safety of the pipeline.

scholarly journals Pipeline Bending Strain Measurement and Compensation Technology Based on Wavelet Neural Network

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Rui Li ◽  
Maolin Cai ◽  
Yan Shi ◽  
Qingshan Feng ◽  
Shucong Liu ◽  
...  
Keyword(s):  
Neural Network ◽  
Oil And Gas ◽  
Original Method ◽  
Wavelet Neural Network ◽  
Measurement Unit ◽  
Gas Pipelines ◽  
Long Distance ◽  
Pipeline Inspection ◽  
Bending Strain ◽  
Oil And Gas Pipelines

The bending strain of long distance oil and gas pipelines may lead to instability of the pipeline and failure of materials, which seriously deteriorates the transportation security of oil and gas. To locate the position of the bending strain for maintenance, an Inertial Measurement Unit (IMU) is usually adopted in a Pipeline Inspection Gauge (PIG). The attitude data of the IMU is usually acquired to calculate the bending strain in the pipe. However, because of the vibrations in the pipeline and other system noises, the resulting bending strain calculations may be incorrect. To improve the measurement precision, a method, based on wavelet neural network, was proposed. To test the proposed method experimentally, a PIG with the proposed method is used to detect a straight pipeline. It can be obtained that the proposed method has a better repeatability and convergence than the original method. Furthermore, the new method is more accurate than the original method and the accuracy of bending strain is raised by about 23% compared to original method. This paper provides a novel method for precisely inspecting bending strain of long distance oil and gas pipelines and lays a foundation for improving the precision of inspection of bending strain of long distance oil and gas pipelines.

scholarly journals Development the method of pipeline bending strain measurement based on microelectromechanical systems inertial measurement unit

2020 ◽  
Vol 103 (2) ◽  
pp. 003685042092523
Author(s):  
Rui Li ◽  
Zhensheng Wang ◽  
Pengchao Chen
Keyword(s):  
Inertial Measurement Unit ◽  
Oil And Gas ◽  
Microelectromechanical Systems ◽  
Small Diameter ◽  
Measurement Unit ◽  
Additional Stress ◽  
Routine Practice ◽  
Inertial Measurement ◽  
Bending Strain ◽  
Key Factor

With the development of pipeline construction, the additional stress and strain becomes the key factor to induce the damage for oil and gas pipeline. The in-line inspection of pipeline bending strain which is based on high-end tactical-grade inertial measurement unit has become routine practice for the oil and gas pipelines over recent years. However, these accurate inertial measurement units are large size and high cost limit to use in small diameter pipelines of bending strain inspection. Microelectromechanical systems–based inertial navigation has been applied to mapping the centerline of the small size pipeline, and the accurate trajectory and attitude information become key factors to calculate the bending strain of pipelines. This article proposed a method not only to calculate the pipeline bending strain but also to improve the accuracy for the bending strain based on the wavelet analysis. Tests show that this method can be effectively used in the calculation and optimization of the bending strain, and it will increase the accuracy to within 19.1% of the actual bending strain.

Technologies and application of pipeline centerline and bending strain of In-line inspection based on inertial navigation

2017 ◽  
Vol 40 (5) ◽  
pp. 1554-1567 ◽  
Author(s):  
Rui Li ◽  
Maolin Cai ◽  
Yan Shi ◽  
Qingshan Feng ◽  
Pengchao Chen
Keyword(s):  
Oil And Gas ◽  
Original Position ◽  
Routine Practice ◽  
Long Distance ◽  
Mapping Unit ◽  
Bending Strain ◽  
Integrity Management ◽  
Inspection Data ◽  
Oil Company ◽  
Extra Stress

Inertial mapping unit (IMU) in-line inspection (ILI) has become routine practice for long-distance buried transport pipelines of oil and gas. It is capable of measuring the pipeline centerline position coordinates and locating the pipeline anomalies, features and fittings to help the oil company manage it. The IMU inspection data also can be used to compute the pipeline bending strain and assess the potential deviation from the original position where endures the extra stress. This paper introduces the main principle, measurement and data processing for IMU ILI. As a key point of calculation for centerline and bending strain, the identification and optimization of the signal are also discussed. At the end of this paper, the developments of IMU ILI are presented. The IMU ILI becomes an important and effective method for pipeline integrity management and safe operation of buried oil and gas pipelines.

scholarly journals A novel algorithm for pipeline displacement and bending strain of in-line inspection based on inertia measurement technology

2018 ◽  
Vol 10 (12) ◽  
pp. 168781401881675
Author(s):  
Shucong Liu ◽  
Dezhi Zheng ◽  
Tianhao Wang ◽  
Mengxi Dai ◽  
Rui Li ◽  
...  
Keyword(s):  
Strain Measurement ◽  
Inertial Measurement Unit ◽  
Spline Interpolation ◽  
Measurement Unit ◽  
Measurement Technology ◽  
Safe Operation ◽  
Inertial Measurement ◽  
Filtering Algorithm ◽  
Measuring Devices ◽  
Bending Strain

The in-line inspection tool with Inertial Measurement Unit tool is becoming a routine and important practice for many pipeline companies and is effective for whole-line bending strain measurement. However, the measurements of Inertial Measurement Unit tool are always affected by noises and errors, which are caused by inherent inaccuracies and deficiencies of the experimental techniques and measuring devices. For the calculations of the bending strain, the results are very sensitive to the noises and errors. A filtering algorithm based on cubic spline interpolation was proposed for Inertial Measurement Unit data processing to eliminate noises and errors for bending strain, and the effectiveness is validated through the pipeline field test. The results showed that the average pipeline displacement deviation declined 13.82% in the three tests, and the bending strain error reduced from 0.037% to 0.014%. The proposed method effectively improves the inspection accuracy and provides an effective method for pipeline displacement and strain inspection, which ensures the safe operation of the pipeline.

Study on the Assets Integrity Management System of Long Distance Oil and Gas Pipeline

2006 ◽  
Author(s):  
Weibin Wang ◽  
Wenqiang Tong ◽  
Zupei Yang ◽  
Muyang Ai ◽  
Hongsheng Cui ◽  
...  
Keyword(s):  
Management System ◽  
Oil And Gas ◽  
Gas Pipeline ◽  
Research Development ◽  
Practical Application ◽  
Long Distance ◽  
Steel Pipeline ◽  
System Risk ◽  
Integrity Management ◽  
And Function

The integrity management system of steel pipeline is an international popular pattern of assets management at present. It has important meaning and effect that establishing and consummating a set of assets integrity management (AIM) system with practical application value in all the integrity management system. By using the AIM system, risk can be identified and ranged timely; more detect and assess data may be gained; the maintenance and remedy cost can be saved and the monitoring become more convenient and quick. Thereby, the AIM system can contribute to dynamic and circular integrity management. According to the latest research development of integrity management in the international, this paper illustrate the assets integrity management in detail from the aspect of the application of assets integrity management, design way, workflow, and function introducing, which is based on the design module of assets integrity management.

scholarly journals Novel indoor positioning algorithm based on Lidar/inertial measurement unit integrated system

2021 ◽  
Vol 18 (2) ◽  
pp. 172988142199992
Author(s):  
Ping Jiang ◽  
Liang Chen ◽  
Hang Guo ◽  
Min Yu ◽  
Jian Xiong
Keyword(s):  
Mobile Robot ◽  
Kalman Filtering ◽  
Inertial Measurement Unit ◽  
Simultaneous Localization And Mapping ◽  
Measurement Unit ◽  
Accuracy Rate ◽  
Inertial Measurement ◽  
Mean Error ◽  
Localization And Mapping ◽  
The Mean

As an important research field of mobile robot, simultaneous localization and mapping technology is the core technology to realize intelligent autonomous mobile robot. Aiming at the problems of low positioning accuracy of Lidar (light detection and ranging) simultaneous localization and mapping with nonlinear and non-Gaussian noise characteristics, this article presents a mobile robot simultaneous localization and mapping method that combines Lidar and inertial measurement unit to set up a multi-sensor integrated system and uses a rank Kalman filtering to estimate the robot motion trajectory through inertial measurement unit and Lidar observations. Rank Kalman filtering is similar to the Gaussian deterministic point sampling filtering algorithm in structure, but it does not need to meet the assumptions of Gaussian distribution. It completely calculates the sampling points and the sampling points weights based on the correlation principle of rank statistics. It is suitable for nonlinear and non-Gaussian systems. With multiple experimental tests of small-scale arc trajectories, we can see that compared with the alone Lidar simultaneous localization and mapping algorithm, the new algorithm reduces the mean error of the indoor mobile robot in the X direction from 0.0928 m to 0.0451 m, with an improved accuracy rate of 46.39%, and the mean error in the Y direction from 0.0772 m to 0.0405 m, which improves the accuracy rate of 48.40%. Compared with the extended Kalman filter fusion algorithm, the new algorithm reduces the mean error of the indoor mobile robot in the X direction from 0.0597 m to 0.0451 m, with an improved accuracy rate of 24.46%, and the mean error in the Y direction from 0.0537 m to 0.0405 m, which improves the accuracy rate of 24.58%. Finally, we also tested on a large-scale rectangular trajectory, compared with the extended Kalman filter algorithm, rank Kalman filtering improves the accuracy of 23.84% and 25.26% in the X and Y directions, respectively, it is verified that the accuracy of the algorithm proposed in this article has been improved.

Recommended Procedures for Evaluation and Synthesis of Pipelines Subject to Multiple IMU Tool Surveys

2020 ◽  
Author(s):  
James D. Hart ◽  
Nasir Zulfiqar ◽  
Ed McClarty
Keyword(s):  
Inertial Measurement Unit ◽  
Three Dimensional ◽  
Ground Movement ◽  
Measurement Unit ◽  
Profile Data ◽  
Inertial Measurement ◽  
Bending Strain ◽  
Primary Focus ◽  
High Degree ◽  
Strapdown Inertial Measurement Unit

Abstract This paper summarizes recommended procedures for evaluation and synthesis of geometry data from pipelines subjected to repeat in-line inspections (ILI) using strapdown Inertial Measurement Unit (IMU) tools. The paper provides an overview of IMU tool instrumentation (gyroscopes, accelerometers and odometers), a brief summary of IMU tool data processing and discusses IMU tool sensitivity and accuracy specifications. The paper also provides a review of the approaches that are used to identify ground movement signatures in IMU data profiles. Based on a single IMU survey, it can be difficult to determine with certainty if a given bending strain feature was induced during construction of the pipeline (e.g., by conforming the pipeline profile to an uneven trench profile) or was the result of post-construction movement of the pipeline (e.g., due to geohazards along the alignment such as landslides, karst, etc.). Because such a large percentage of vendor identified bending strain anomalies in IMU surveys are the result of construction, comparison of pipeline geometry changes between two (or more) inertial inspections is normally a more reliable method of identifying areas of actual post-construction movement of the pipeline. This is because a high degree of repeatability is observed in overlays of the pipeline geometry data signatures obtained from different IMU surveys at construction-induced bending features whereas the geometry signals associated with real pipeline movement frequently exhibit change patterns in out-of-straightness, pitch and heading and curvature/bending strain profiles that correspond to increasing pipe curvature and deformation. The primary focus of this paper is to summarize recommended data deliverables and plots of three-dimensional pipeline geometry profile data from different IMU tool surveys at vendor-identified bending strain anomalies including multi-panel overlay plot packages as well as survey-to-survey difference or change profiles that greatly assist in distinguishing if the feature is the result of construction or due to post-construction movement and to aid in the evaluation of pipeline deformation states.

scholarly journals IMU-Aided High-Frequency Lidar Odometry for Autonomous Driving

2019 ◽  
Vol 9 (7) ◽  
pp. 1506 ◽  
Author(s):  
Hanzhang Xue ◽  
Hao Fu ◽  
Bin Dai
Keyword(s):  
High Frequency ◽  
Inertial Measurement Unit ◽  
Autonomous Driving ◽  
Initial Guess ◽  
Measurement Unit ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Diverse Environment ◽  
Novel Method ◽  
Localization Information

For autonomous driving, it is important to obtain precise and high-frequency localization information. This paper proposes a novel method in which the Inertial Measurement Unit (IMU), wheel encoder, and lidar odometry are utilized together to estimate the ego-motion of an unmanned ground vehicle. The IMU is fused with the wheel encoder to obtain the motion prior, and it is involved in three levels of the lidar odometry: Firstly, we use the IMU information to rectify the intra-frame distortion of the lidar scan, which is caused by the vehicle’s own movement; secondly, the IMU provides a better initial guess for the lidar odometry; and thirdly, the IMU is fused with the lidar odometry in an Extended Kalman filter framework. In addition, an efficient method for hand–eye calibration between the IMU and the lidar is proposed. To evaluate the performance of our method, extensive experiments are performed and our system can output stable, accurate, and high-frequency localization results in diverse environment without any prior information.

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