The Experts below are selected from a list of 2259 Experts worldwide ranked by ideXlab platform
Gang-bing Song - One of the best experts on this subject based on the ideXlab platform.
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a method of pipeline corrosion detection based on Hoop Strain monitoring technology
Structural Control & Health Monitoring, 2017Co-Authors: Liang Ren, Tao Jiang, Peng Zhang, Gang-bing SongAbstract:Summary A pipeline is often an important structure with very long service life. It is of great significance to monitor the corrosion level of a pipeline to ensure its safety operation. This paper aims to develop a new nondestructive method to detect the pipeline corrosion. It is assumed that the pipeline corrosion will result in a variation of the circumferential Strain. The nondestructive detection method is based on a novel fiber Bragg grating (FBG) Hoop-Strain sensor, which can accurately measure the circumferential Strain of a pipeline. In this paper, the theoretical study and numerical analysis based on finite element method are detailed in our initial work. Then, tests are conducted on three steel pipes to verify the effectiveness and accuracy of this method. The results demonstrate that the FBG Hoop-Strain sensor has good performance in the circumferential Strain measurement and is sensitive to the variation of the circumferential Strain caused by different corrosion level. The FBG Hoop-Strain sensor is considered to be a promising device in pipeline corrosion monitoring. Copyright © 2016 John Wiley & Sons, Ltd.
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Gas pipeline leakage detection based on PZT sensors
Smart Materials and Structures, 2017Co-Authors: Junxiao Zhu, Siu Chun Ho, Zi-guang Jia, Liang Ren, Gang-bing SongAbstract:In this paper, an innovative method for rapid detection and location determination of pipeline leakage utilizing lead zirconate titanate (PZT) sensors is proposed. The negative pressure wave (NPW) is a stress wave generated by leakage in the pipeline, and propagates along the pipeline from the leakage point to both ends. Thus the NPW is associated with Hoop Strain variation along the pipe wall. PZT sensors mounted on the pipeline were used to measure the Strain variation and allowed accurate (within 2% error) and repeatable location (within 4% variance) of five manually controlled leakage points. Experimental results have verified the effectiveness and the location accuracy for leakage in a 55 meter long model pipeline.
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experimental study of pipeline leak detection based on Hoop Strain measurement
Structural Control & Health Monitoring, 2015Co-Authors: Hong-nan Li, Siu Chun Ho, Gang-bing SongAbstract:Summary Pipelines are widely used for the transport of a large variety of fluids, such as natural gas, across long distances. While pipelines provide a convenient mode of transportation of fluids, their safe usage is one of the foremost concerns especially if their contents are harmful to the environment or if the hosting area is prone to third-party intrusions. Thus, rapid detection and localization of pipeline leakage is paramount to the minimization of damage brought to the environment and stakeholders in the event of an unexpected leakage. In this work, a novel Hoop Strain based negative pressure wave (NPW) approach was used to detect and localize pipeline leakages in a 180 ft PVC pipeline equipped with five manually controllable leakage points. Using the new approach, both the arrival time of the NPW and the energy attenuation profile of the NPW can be used to detect and localize leakages with higher accuracy and in a wider variety of situations. The time of arrival approach allowed accurate (within 7.33% error) and repeatable localization of the leakage points; however, using the energy attenuation of the NPW, leakages with low leakage rates (<5 lpm) can also be detected, albeit at the cost of inaccuracies at the inlet and outlet of the pipeline (8.3% error in the ends vs. 4.3% error in the body). Copyright © 2014 John Wiley & Sons, Ltd.
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Experimental study of leakage detection of natural gas pipeline using FBG based Strain sensor and least square support vector machine
Journal of Loss Prevention in the Process Industries, 2014Co-Authors: Qingmin Hou, Huizhe Cao, Liang Ren, Wenling Jiao, Gang-bing SongAbstract:Leakage is the most common cause of natural gas pipeline accidents. This work was devoted to natural gas pipeline leakage detection, which is based on detecting negative pressure wave signals caused by leakage. The FBG Strain sensor, which is based on monitoring the Hoop Strain of a pipeline to detect negative pressure wave signals, is fabricated and experimentally tested. Compared to conventional pressure sensors, FBG Strain sensors were shown to be less influenced by noise, and they have the advantage of being a nondestructive sensing method. This makes them ideal for sensing pressure transients, which could be analyzed to detect natural gas pipeline leakage. Toward this objective, a least square support vector machine (LS-SVM) classifier was developed as an automatic leakage detection technique. This technique proved to be effective at detecting leakage.
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design and experimental study on fbg Hoop Strain sensor in pipeline monitoring
Optical Fiber Technology, 2014Co-Authors: Liang Ren, Zi-guang Jia, Gang-bing SongAbstract:Abstract Pipeline monitoring is an important task for the economic and safe operation of pipelines as well as for loss prevention and environmental protection. The circumferential Strain is of significance in pipeline integrity monitoring. In this paper, an indirect pipeline corrosion monitoring method based on the circumferential Strain measurement is firstly proposed, with main objectives at designing a circumferential Strain measuring device. Combined with unique advantages of optical fiber sensing, an FBG Hoop-Strain sensor was designed and encapsulated. Its enhanced sensitivity mechanism in the circumferential Strain measurement and manufacturing technique is detailed. The experimental study of the developed FBG Hoop-Strain sensor is conducted on a PVC model pipeline to investigate its characteristics, including reliability and some tentative dynamic tests. Results of model tests show that the FBG Hoop-Strain sensor demonstrates good performance in the circumferential Strain measurement, and can be considered as a practical device for pipeline health monitoring.
Zi-guang Jia - One of the best experts on this subject based on the ideXlab platform.
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experimental investigation of fiber bragg grating Hoop Strain sensor based method for sudden leakage monitoring of gas pipeline
Structural Health Monitoring-an International Journal, 2020Co-Authors: Tao Jiang, Liang Ren, Jiajian Wang, Zi-guang JiaAbstract:Pipeline, serving as one of the most important gas transportation methods, can cause serious consequences in the event of leakage, so leakage monitoring is particularly important. In our previous s...
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multipoint Hoop Strain measurement based pipeline leakage localization with an optimized support vector regression approach
Journal of Loss Prevention in The Process Industries, 2019Co-Authors: Zi-guang Jia, Bo Kong, Qingmin HouAbstract:Abstract Pipelines are used to carry fluids across long distances. Given the costly and hazardous nature of some of these fluids, timely and accurate inspection for damages is imperative to prevent harmful financial and environmental consequences. In the previous research, a fiber optic based Hoop Strain sensor is developed and reported to accomplish the goal of pipeline corrosion and leakage monitoring. The sensors form a foundation upon which advanced damaged detection algorithms can be carried out. In this paper, the application of distributed Hoop Strain sensing information combined with support vector regression (SVR) is demonstrated to pinpoint leakage position on a long-distance pressurized pipeline. The SVR parameters were further optimized by a genetic algorithm (GA) in order to improve accuracy. The resulting leakage detection system had a mean squared error as low as 0.076 when no noise was present. The effect of noise (approximated by Gaussian white noise) was studied in a simulation, showing an effective 5% error for a 55 km simulated pipeline. Results also showed that the use of more sensors corresponded to heightened robustness towards different noise levels.
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pipeline leakage localization based on distributed fbg Hoop Strain measurements and support vector machine
Optik, 2019Co-Authors: Zi-guang Jia, Zhenyu Wang, Wei SunAbstract:Abstract Across the globe, pipelines help to carry all kinds of fluids across vast distances. Our prior work in fiber Bragg grating (FBG) Hoop Strain sensors are among the most recently reported technologies aimed at accomplishing the goal of continuous pipeline monitoring. Multiple Hoop Strain signals can be extracted from distributed FBG Hoop Strain sensors set along the pipeline to reflect leakage process. In this paper, we demonstrate the use of multiple, distributed FBG Hoop Strain sensors in cooperation with a support vector regression (SVR) to localize a leakage point along a model pipeline. Series of terminal Hoop Strain variations are extracted as the input variables to achieve multi regression analysis as to localize the leakage point. The parameters of different kernel functions are optimized through five-fold cross validation to obtain the highest leakage localization accuracy. The result shows that when taking radial basis kernel function (RBF) with optimized C and γ values, the localization mean square error (MSE) reaches as low as 0.043. The anti-noise capability of the SVR model is evaluated through superimposing Gaussian white noise of different levels. From the simulation study, the average localization error is still acceptable (≈500 m) even in 5% noise situation. The influence of Hoop Strain sensing points as input variables is also investigated. The system with more Hoop Strain sensing points shows more stable capability for different level noises. The results demonstrate feasibility and robustness of the SVR approach using multi-Hoop Strain measurements for pipeline leakage localization.
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fbg Hoop Strain sensor development and application for pipeline leakage monitoring
Advanced Sensor Systems and Applications VIII, 2018Co-Authors: Zi-guang JiaAbstract:Pipelines are used across multiple key industries and in a sense acts like a circulatory system for society by carrying vital fluids safely across large distances. A wide variety of tools have been developed to help monitor the health of pipelines. Among these tools, the fiber Bragg grating (FBG) Hoop Strain sensor has great potential to measure the Hoop Strain variation on a pressurized pipeline and thus help detect anomalies, such as leakages. In this work, the Hoop Strain sensor with enhanced sensitivity is developed and encapsulated for pipeline leakage monitoring. Its specially designed mechanism with pre-tension function is detailed. The other branch of this research is the application of Hoop Strain information for pipeline leakage detection and localization. Three Hoop Strain-based methods are proposed to localize pipeline leakages with higher accuracy and in wider variety of situations. Some simulation work and experimental study are conducted to verify these methods. The results demonstrate that the FBG Hoop Strain sensor shows great promise for pipeline leakage detection and localization.
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pipeline abnormal classification based on support vector machine using fbg Hoop Strain sensor
Optik, 2018Co-Authors: Zi-guang Jia, Liang Ren, Zhenyu WangAbstract:Abstract Pipelines function as blood vessels serving to bring life-necessities, their safe usage is one of the foremost concerns. In our previous work, fiber Bragg grating (FBG) Hoop Strain sensor with enhanced sensitivity was developed to measure the Hoop Strain variation on a pressurized pipeline. In this paper, combined with multi-class support vector machine (SVM) learning method, the Hoop Strain information is used to classify pipeline abnormal working conditions, including cases of external impact, normal leakage and small rate leakage. The parameters of different kernel functions are optimized through 5-fold cross validation to obtain the highest prediction accuracy. The result shows that when taking radial basis kernel function (RBF) with optimized C and γ values, the classification accuracy for abnormal condition reaches up to 95%. The error appears only in separating the small leakage cases from normal working conditions. This pipeline abnormal classification approach using FBG Hoop Strain sensor combined with multi-class SVM shows potential prospective in pipeline accident monitoring and safety evaluation.
Liang Ren - One of the best experts on this subject based on the ideXlab platform.
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experimental investigation of fiber bragg grating Hoop Strain sensor based method for sudden leakage monitoring of gas pipeline
Structural Health Monitoring-an International Journal, 2020Co-Authors: Tao Jiang, Liang Ren, Jiajian Wang, Zi-guang JiaAbstract:Pipeline, serving as one of the most important gas transportation methods, can cause serious consequences in the event of leakage, so leakage monitoring is particularly important. In our previous s...
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pipeline abnormal classification based on support vector machine using fbg Hoop Strain sensor
Optik, 2018Co-Authors: Zi-guang Jia, Liang Ren, Zhenyu WangAbstract:Abstract Pipelines function as blood vessels serving to bring life-necessities, their safe usage is one of the foremost concerns. In our previous work, fiber Bragg grating (FBG) Hoop Strain sensor with enhanced sensitivity was developed to measure the Hoop Strain variation on a pressurized pipeline. In this paper, combined with multi-class support vector machine (SVM) learning method, the Hoop Strain information is used to classify pipeline abnormal working conditions, including cases of external impact, normal leakage and small rate leakage. The parameters of different kernel functions are optimized through 5-fold cross validation to obtain the highest prediction accuracy. The result shows that when taking radial basis kernel function (RBF) with optimized C and γ values, the classification accuracy for abnormal condition reaches up to 95%. The error appears only in separating the small leakage cases from normal working conditions. This pipeline abnormal classification approach using FBG Hoop Strain sensor combined with multi-class SVM shows potential prospective in pipeline accident monitoring and safety evaluation.
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performance study of fbg Hoop Strain sensor for pipeline leak detection and localization
Journal of Aerospace Engineering, 2018Co-Authors: Zi-guang Jia, Liang Ren, Tao JiangAbstract:AbstractPipelines provide a convenient mode of transportation of fluids, and their safe usage is one of the foremost concerns. In our previous work, a Hoop Strain–based negative pressure wave (NPW)...
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pipeline leak localization based on fbg Hoop Strain sensors combined with bp neural network
Applied Sciences, 2018Co-Authors: Zi-guang Jia, Liang Ren, Wei SunAbstract:Pipelines function as blood vessels serving to bring life-necessities, so their safe usage is one of the foremost concerns. In our previous work, a fiber Bragg grating (FBG) Hoop Strain sensor with enhanced sensitivity was developed to measure the pressure drop induced by pipeline leakage. Some Hoop Strain information during the leakage transient process can be extracted from the amount of FBG Hoop Strain sensors set along the pipeline. In this paper, an integrated approach of a back-propagation (BP) neural network and Hoop Strain measurement is first proposed to locate the leak points of the pipeline. Five Hoop Strain variations are employed as input neurons to achieve pattern recognition so as to predict the leakage point. The RMS error can be as low as 1.01% when choosing appropriate hidden layer neurons. Furthermore, the influence of noise on the network’s performance is investigated through superimposing Gaussian noise with a different level. The results demonstrate the feasibility and robustness of the neural network for pipeline leakage localization.
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Pipeline corrosion and leakage monitoring based on the distributed optical fiber sensing technology
Measurement: Journal of the International Measurement Confederation, 2018Co-Authors: Liang Ren, Chao Lin Yuan, Zi-guang Jia, Dong-sheng Li, Tao Jiang, Hong-nan LiAbstract:Pipeline is an important structure to transport oil and gas through long distances. However, pipeline also suffers from many threats especially corrosion and leakage. Therefore, it is necessary to conduct pipeline safety monitoring. With the advantage of high precision in distributed Strain measurement, the optical frequency domain reflectometry (OFDR) technique is more suitable for pipeline monitoring. In this paper, a new application of the OFDR technique is introduced to monitor both corrosion and leakage. In order to verify this method, simulation tests of corrosion and leakage were conducted. In the corrosion test, several optical fiber sensors were bonded to the pipe surface with the same interval, forming a sensor array. Based on the sensor array, a Hoop Strain nephogram was created to show the corrosion level and corrosion location. In the leakage test, the results indicated that pipeline leakage can be detected by the distributed optical fiber sensor (DOFS). All the test results demonstrate that it is possible to monitor pipeline corrosion and leakage based on the Hoop Strain theory and the DOFS.
Junjie Zeng - One of the best experts on this subject based on the ideXlab platform.
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stress Strain behavior of polyethylene terephthalate fiber reinforced polymer confined normal high and ultra high strength concrete
Journal of building engineering, 2020Co-Authors: Junjie Zeng, Wanyang Gao, Scott T Smith, Yongchang GuoAbstract:Abstract Polyethylene terephthalate (PET) fiber-reinforced polymer (FRP) composites, which are made from recycled PET products and exhibit large rupture Strain (LRS), have gained more and more attention in recent years on account of their environmentally friendly origin. One promising application of such fibers is in the confinement of concrete. Research is, however, limited and particularly for the stress-Strain behavior of PET FRP-confined concrete. In light of such a knowledge gap, this paper presents an experimental investigation on the stress-Strain behavior of PET FRP-confined normal-, high- and ultra high-strength concrete cylinders. It is found that the stress-Strain behavior of the confined high-strength (as well as ultra high-strength) concrete specimens exhibits a Strain hardening-softening-hardening behavior, while the confined normal-strength concrete specimens generally exhibit a monotonic ascending behavior. In addition, all concrete grades confined with the PET fibers exhibit a typical axial Strain-Hoop Strain curve with an inflection point. A new design-oriented stress-Strain model is then proposed based on a comprehensive review of experimental data for PET FRP-confined normal-, high- and ultra high-strength concrete. Comparisons between experimental results and predictions show that the proposed model provides satisfactory predictions for PET FRP-confined concrete.
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pet frp concrete high strength steel hybrid solid columns with Strain hardening and ductile performance cyclic axial compressive behavior
Composites Part B-engineering, 2020Co-Authors: Yuyi Ye, Junfan Lv, Yi Ouyang, Junjie Zeng, Cheng JiangAbstract:Abstract This paper presents the results of an experimental program on the behavior of fiber-reinforced polymer (FRP)-concrete-high strength steel solid columns (FCSSCs), with an outer polyethylene terephthalate (PET) FRP tube and an inner circular high-strength steel (HSS) tube, under cyclic axial compression. A PET FRP tube has a much larger rupture Strain and a larger FRP Hoop Strain efficiency, leading to an excellent ductility of PET FRP-confined concrete. The HSS tube, which has a good deformation compatibility with the PET FRP-confined concrete in FCSSCs, provides a much larger longitudinal load carrying capacity and a larger confinement to the core concrete compared with a normal strength steel tube. The experimental results demonstrated that the axial load carrying capacity of an FCSSC is much larger than the summation of the axial load resistance of the hollow steel tube and that of the concrete-filled FRP tube; the buckling of the HSS tube is also prevented so that its post-yield material strength is effectively utilized. It is found that cyclic load-Strain envelope curves lie closely to the corresponding monotonic load-Strain curves, and repeated loading cycles increase the plastic Strain while decrease the reloading new stress. The existing stress-Strain model fails to provide an accurate prediction on the cyclic axial behavior of concrete under combined PET FRP-steel confinement.
Tao Jiang - One of the best experts on this subject based on the ideXlab platform.
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experimental investigation of fiber bragg grating Hoop Strain sensor based method for sudden leakage monitoring of gas pipeline
Structural Health Monitoring-an International Journal, 2020Co-Authors: Tao Jiang, Liang Ren, Jiajian Wang, Zi-guang JiaAbstract:Pipeline, serving as one of the most important gas transportation methods, can cause serious consequences in the event of leakage, so leakage monitoring is particularly important. In our previous s...
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performance study of fbg Hoop Strain sensor for pipeline leak detection and localization
Journal of Aerospace Engineering, 2018Co-Authors: Zi-guang Jia, Liang Ren, Tao JiangAbstract:AbstractPipelines provide a convenient mode of transportation of fluids, and their safe usage is one of the foremost concerns. In our previous work, a Hoop Strain–based negative pressure wave (NPW)...
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Pipeline corrosion and leakage monitoring based on the distributed optical fiber sensing technology
Measurement: Journal of the International Measurement Confederation, 2018Co-Authors: Liang Ren, Chao Lin Yuan, Zi-guang Jia, Dong-sheng Li, Tao Jiang, Hong-nan LiAbstract:Pipeline is an important structure to transport oil and gas through long distances. However, pipeline also suffers from many threats especially corrosion and leakage. Therefore, it is necessary to conduct pipeline safety monitoring. With the advantage of high precision in distributed Strain measurement, the optical frequency domain reflectometry (OFDR) technique is more suitable for pipeline monitoring. In this paper, a new application of the OFDR technique is introduced to monitor both corrosion and leakage. In order to verify this method, simulation tests of corrosion and leakage were conducted. In the corrosion test, several optical fiber sensors were bonded to the pipe surface with the same interval, forming a sensor array. Based on the sensor array, a Hoop Strain nephogram was created to show the corrosion level and corrosion location. In the leakage test, the results indicated that pipeline leakage can be detected by the distributed optical fiber sensor (DOFS). All the test results demonstrate that it is possible to monitor pipeline corrosion and leakage based on the Hoop Strain theory and the DOFS.
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a method of pipeline corrosion detection based on Hoop Strain monitoring technology
Structural Control & Health Monitoring, 2017Co-Authors: Liang Ren, Tao Jiang, Peng Zhang, Gang-bing SongAbstract:Summary A pipeline is often an important structure with very long service life. It is of great significance to monitor the corrosion level of a pipeline to ensure its safety operation. This paper aims to develop a new nondestructive method to detect the pipeline corrosion. It is assumed that the pipeline corrosion will result in a variation of the circumferential Strain. The nondestructive detection method is based on a novel fiber Bragg grating (FBG) Hoop-Strain sensor, which can accurately measure the circumferential Strain of a pipeline. In this paper, the theoretical study and numerical analysis based on finite element method are detailed in our initial work. Then, tests are conducted on three steel pipes to verify the effectiveness and accuracy of this method. The results demonstrate that the FBG Hoop-Strain sensor has good performance in the circumferential Strain measurement and is sensitive to the variation of the circumferential Strain caused by different corrosion level. The FBG Hoop-Strain sensor is considered to be a promising device in pipeline corrosion monitoring. Copyright © 2016 John Wiley & Sons, Ltd.