{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T15:04:24Z","timestamp":1792508664780,"version":"4.5.0"},"reference-count":208,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,6,3]],"date-time":"2021-06-03T00:00:00Z","timestamp":1622678400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61960206010"],"award-info":[{"award-number":["61960206010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Pipelines play an important role in the national\/international transportation of natural gas, petroleum products, and other energy resources. Pipelines are set up in different environments and consequently suffer various damage challenges, such as environmental electrochemical reaction, welding defects, and external force damage, etc. Defects like metal loss, pitting, and cracks destroy the pipeline\u2019s integrity and cause serious safety issues. This should be prevented before it occurs to ensure the safe operation of the pipeline. In recent years, different non-destructive testing (NDT) methods have been developed for in-line pipeline inspection. These are magnetic flux leakage (MFL) testing, ultrasonic testing (UT), electromagnetic acoustic technology (EMAT), eddy current testing (EC). Single modality or different kinds of integrated NDT system named Pipeline Inspection Gauge (PIG) or un-piggable robotic inspection systems have been developed. Moreover, data management in conjunction with historic data for condition-based pipeline maintenance becomes important as well. In this study, various inspection methods in association with non-destructive testing are investigated. The state of the art of PIGs, un-piggable robots, as well as instrumental applications, are systematically compared. Furthermore, data models and management are utilized for defect quantification, classification, failure prediction and maintenance. Finally, the challenges, problems, and development trends of pipeline inspection as well as data management are derived and discussed.<\/jats:p>","DOI":"10.3390\/s21113862","type":"journal-article","created":{"date-parts":[[2021,6,3]],"date-time":"2021-06-03T21:03:32Z","timestamp":1622754212000},"page":"3862","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":230,"title":["Pipeline In-Line Inspection Method, Instrumentation and Data Management"],"prefix":"10.3390","volume":"21","author":[{"given":"Qiuping","family":"Ma","sequence":"first","affiliation":[{"name":"School of Automation, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7563-1523","authenticated-orcid":false,"given":"Guiyun","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Automation, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanli","family":"Zeng","sequence":"additional","affiliation":[{"name":"Shenyang Academy of Instrumentation Science, Shenyang 110043, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5084-0276","authenticated-orcid":false,"given":"Rui","family":"Li","sequence":"additional","affiliation":[{"name":"PipeChina Northern Company, Langfang 065000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huadong","family":"Song","sequence":"additional","affiliation":[{"name":"Shenyang Academy of Instrumentation Science, Shenyang 110043, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9584-8586","authenticated-orcid":false,"given":"Zhen","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9993-1013","authenticated-orcid":false,"given":"Bin","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Automation, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5596-7599","authenticated-orcid":false,"given":"Kun","family":"Zeng","sequence":"additional","affiliation":[{"name":"School of Automation, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"03119001","DOI":"10.1061\/(ASCE)PS.1949-1204.0000407","article-title":"A review of failure prediction models for oil and gas pipelines","volume":"11","author":"Zakikhani","year":"2020","journal-title":"J. Pipeline Syst. Eng. Pract."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"03120001","DOI":"10.1061\/(ASCE)CO.1943-7862.0001819","article-title":"Trenchless construction technologies for oil and gas pipelines: State-of-the-art review","volume":"146","author":"Lu","year":"2020","journal-title":"J. Constr. Eng. Manag."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.measurement.2017.07.058","article-title":"Discontinuity inspection in pipelines: A comparison review","volume":"111","author":"Coramik","year":"2017","journal-title":"Measurement"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.ijpvp.2016.11.007","article-title":"A review on pipeline corrosion, in-line inspection (ILI), and corrosion growth rate models","volume":"149","author":"Vanaei","year":"2017","journal-title":"Int. J. Press. Vessel. Pip."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"104735","DOI":"10.1016\/j.engfailanal.2020.104735","article-title":"Localized Corrosion and Mitigation Approach of Steel Materials Used in Oil and Gas Pipelines\u2014An overview","volume":"116","author":"Alamri","year":"2020","journal-title":"Eng. Fail. Anal."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1016\/j.compstruct.2017.06.044","article-title":"Failure pressure analysis of composite repair system for wall loss defect of metallic pipelines","volume":"176","author":"Budhe","year":"2017","journal-title":"Compos. Struct."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.jlp.2018.03.012","article-title":"Risk identification of third-party damage on oil and gas pipelines through the Bayesian network","volume":"54","author":"Guo","year":"2018","journal-title":"J. Loss Prev. Process Ind."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.ijpvp.2003.11.004","article-title":"The effect of dents in pipelines\u2014Guidance in the pipeline defect assessment manual","volume":"81","author":"Cosham","year":"2004","journal-title":"Int. J. Press. Vessel. Pip."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"98","DOI":"10.28999\/2514-541X-2020-4-2-98-107","article-title":"Causes of the field flowline weld joint rust-through damage","volume":"4","author":"Mambetov","year":"2020","journal-title":"Pipeline Sci. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.corsci.2011.08.030","article-title":"Evaluation of environment-assisted cracking susceptibility of a grade X100 pipeline steel","volume":"54","author":"Mustapha","year":"2012","journal-title":"Corros. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"990","DOI":"10.1016\/j.matdes.2015.09.123","article-title":"Material flow influence on the weld formation and mechanical performance in underwater friction taper plug welds for pipeline steel","volume":"88","author":"Yin","year":"2015","journal-title":"Mater. Des."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Feng, Q., Li, R., Nie, B., Liu, S., Zhao, L., and Zhang, H. (2017). Literature review: Theory and application of in-line inspection technologies for oil and gas pipeline girth weld defection. Sensors, 17.","DOI":"10.3390\/s17010050"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Wright, R.F., Lu, P., Devkota, J., Lu, F., Ziomek-Moroz, M., and Ohodnicki, P.R. (2019). Corrosion sensors for structural health monitoring of oil and natural gas infrastructure: A review. Sensors, 19.","DOI":"10.3390\/s19183964"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Vilkys, T., Rudzinskas, V., Prentkovskis, O., Tretjakovas, J., Vi\u0161niakov, N., and Maruschak, P. (2018). Evaluation of failure pressure for gas pipelines with combined defects. Metals, 8.","DOI":"10.3390\/met8050346"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Quej-Ake, L.M., Rivera-Olvera, J.N., Dom\u00ednguez-Aguilar, Y.d.R., Avelino-Jim\u00e9nez, I.A., Garibay-Febles, V., and Zapata-Pe\u00f1asco, I. (2020). Analysis of the Physicochemical, Mechanical, and Electrochemical Parameters and Their Impact on the Internal and External SCC of Carbon Steel Pipelines. Materials, 13.","DOI":"10.3390\/ma13245771"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1056","DOI":"10.1016\/j.corsci.2006.05.048","article-title":"Corrosion behaviour of steel in concrete in the presence of stray current","volume":"49","author":"Bertolini","year":"2007","journal-title":"Corros. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Bonab, M.M. (2019). Effects of different parameters on initiation and propagation of stress corrosion cracks in pipeline steels: A review. Metals, 9.","DOI":"10.3390\/met9050590"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1016\/j.engfracmech.2018.06.018","article-title":"Hydrogen induced cracking of pipeline and pressure vessel steels: A review","volume":"199","author":"Ghosh","year":"2018","journal-title":"Eng. Fract. Mech."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1108\/00035591111167695","article-title":"Stray current corrosion in buried pipeline","volume":"58","author":"Zhu","year":"2011","journal-title":"Anti-Corros. Methods Mater."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.ndteint.2012.07.008","article-title":"Corrosion detection of internal pipeline using NDT optical inspection system","volume":"52","author":"Safizadeh","year":"2012","journal-title":"NDT E Int."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1310","DOI":"10.1016\/j.conbuildmat.2011.01.011","article-title":"Combining multiple NDT methods to improve testing effectiveness","volume":"38","author":"Lim","year":"2013","journal-title":"Constr. Build. Mater."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1504\/IJMPT.2015.066863","article-title":"Comparison of NDT\u2013methods for automatic inspection of weld defects","volume":"50","author":"Broberg","year":"2015","journal-title":"Int. J. Mater. Prod. Technol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Camerini, C., Rebello, J.M.A., Braga, L., Santos, R., Chady, T., Psuj, G., and Pereira, G. (2018). In-line inspection tool with eddy current instrumentation for fatigue crack detection. Sensors, 18.","DOI":"10.3390\/s18072161"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.apenergy.2017.04.048","article-title":"Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review","volume":"198","author":"Tahan","year":"2017","journal-title":"Appl. Energy"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ge, L., Zhang, C., Tian, G., Xiao, X., Ahmed, J., Wei, G., Hu, Z., Xiang, J., and Robinson, M. (2021). Current Trends and Perspectives of detection and location for buried non-metallic pipelines. Chin. J. Mech. Eng., accepted for publication.","DOI":"10.1186\/s10033-021-00613-z"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"72","DOI":"10.12776\/ams.v23i1.879","article-title":"Influence of heat treatments on the microstructure of welded API X70 pipeline steel","volume":"23","author":"Digheche","year":"2017","journal-title":"Acta Metall. Slovaca"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"121994","DOI":"10.1016\/j.jclepro.2020.121994","article-title":"Carbon dioxide transport via pipelines: A systematic review","volume":"266","author":"Lu","year":"2020","journal-title":"J. Clean. Prod."},{"key":"ref_28","unstructured":"Orazem, M. (2014). Underground Pipeline Corrosion, Elsevier. No. 63."},{"key":"ref_29","unstructured":"Farrag, K., Marean, J., Stubee, E., Gauthier, S., and Oleksa, P. (2020, July 09). Pipeline Safety and Integrity Monitoring Technologies Assessment, Available online: https:\/\/ww2.energy.ca.gov\/2019publications\/CEC-500-2019-053\/CEC-500-2019-053.pdf."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1016\/j.sna.2006.08.010","article-title":"Residual magnetic field sensing for stress measurement","volume":"135","author":"Wilson","year":"2007","journal-title":"Sens. Actuators A Phys."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/j.robot.2015.09.012","article-title":"Application of robotics in onshore oil and gas industry\u2014A review Part I","volume":"75","author":"Shukla","year":"2016","journal-title":"Robot. Auton. Syst."},{"key":"ref_32","first-page":"357","article-title":"3D magnetic field sensing for magnetic flux leakage defect characterisation","volume":"48","author":"Wilson","year":"2006","journal-title":"Insight-Non-Destr. Test. Cond. Monit."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.ndteint.2006.08.002","article-title":"Experiment and simulation study of 3D magnetic field sensing for magnetic flux leakage defect characterisation","volume":"40","author":"Li","year":"2007","journal-title":"NDT E Int."},{"key":"ref_34","first-page":"1","article-title":"Highly Sensitive Planar Hall Magnetoresistive Sensor for Magnetic Flux Leakage Pipeline Inspection","volume":"54","author":"Pham","year":"2018","journal-title":"IEEE Trans. Magn."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.measurement.2017.02.051","article-title":"The axial crack testing model for long distance oil-gas pipeline based on magnetic flux leakage internal inspection method","volume":"103","author":"Liu","year":"2017","journal-title":"Measurement"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1109\/TII.2019.2926283","article-title":"Pipeline magnetic flux leakage image detection algorithm based on multiscale SSD network","volume":"16","author":"Yang","year":"2019","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Azad, A., and Kim, N. (2019). Design and optimization of an MFL coil sensor apparatus based on numerical survey. Sensors, 19.","DOI":"10.3390\/s19224869"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1016\/j.measurement.2019.02.077","article-title":"Estimation of the diameters, depths and separation distances of the closely-spaced pitting defects using combination of three axial MFL components","volume":"138","author":"Azizzadeh","year":"2019","journal-title":"Measurement"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.ndteint.2011.08.011","article-title":"An adaptive channel equalization algorithm for MFL signal","volume":"45","author":"Mukherjee","year":"2012","journal-title":"NDT E Int."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.ndteint.2007.08.001","article-title":"Automatic ultrasonic inspection for internal defect detection in composite materials","volume":"41","author":"Leo","year":"2008","journal-title":"NDT E Int."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Taheri, H., and Hassen, A.A. (2019). Nondestructive ultrasonic inspection of composite materials: A comparative advantage of phased array ultrasonic. Appl. Sci., 9.","DOI":"10.3390\/app9081628"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Mohammadkhani, R., Zanotti Fragonara, L., Padiyar, M.J., Petrunin, I., Raposo, J., Tsourdos, A., and Gray, I. (2020). Improving depth resolution of ultrasonic phased array imaging to inspect aerospace composite structures. Sensors, 20.","DOI":"10.3390\/s20020559"},{"key":"ref_43","first-page":"14","article-title":"Ultrasonic digital phased array dynamic focusing system","volume":"19","author":"Chen","year":"2000","journal-title":"Appl. Acoust."},{"key":"ref_44","first-page":"25","article-title":"Application of phased array ultrasonic sectorial scanning technique in girth weld inspection of submarine pipeline","volume":"42","author":"Chen","year":"2020","journal-title":"Nondestruct. Test."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.ultras.2018.12.004","article-title":"Experimental analysis of surface detection methods for two-medium imaging with a linear ultrasonic array","volume":"94","author":"Matuda","year":"2019","journal-title":"Ultrasonics"},{"key":"ref_46","first-page":"331","article-title":"Automatic defect classification in long-range ultrasonic rail inspection using a support vector machine-based smart system","volume":"46","author":"McNamara","year":"2004","journal-title":"Insight-Non-Destr. Test. Cond. Monit."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1903","DOI":"10.1177\/1475921718817169","article-title":"Open guided waves: Online platform for ultrasonic guided wave measurements","volume":"18","author":"Moll","year":"2019","journal-title":"Struct. Health Monit."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Olisa, S.C., Khan, M.A., and Starr, A. (2021). Review of Current Guided Wave Ultrasonic Testing (GWUT) Limitations and Future Directions. Sensors, 21.","DOI":"10.3390\/s21030811"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/S0041-624X(97)00038-3","article-title":"Defect detection in pipes using guided waves","volume":"36","author":"Lowe","year":"1998","journal-title":"Ultrasonics"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.ndteint.2018.06.003","article-title":"The choice of ultrasonic inspection method for the detection of corrosion at inaccessible locations","volume":"99","author":"Khalili","year":"2018","journal-title":"NDT E Int."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.jsv.2015.10.018","article-title":"Ultrasonic isolation of buried pipes","volume":"363","author":"Leinov","year":"2016","journal-title":"J. Sound Vib."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.compstruct.2018.06.100","article-title":"Damage identification for plate-like structures using ultrasonic guided wave based on improved MUSIC method","volume":"203","author":"Zuo","year":"2018","journal-title":"Compos. Struct."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"3396","DOI":"10.1177\/1045389X17721038","article-title":"Magnetic flux leakage-based local damage detection and quantification for steel wire rope non-destructive evaluation","volume":"29","author":"Kim","year":"2018","journal-title":"J. Intell. Mater. Syst. Struct."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1016\/j.ultras.2004.02.013","article-title":"The use of ultrasonic guided waves and wavelets analysis in pipe inspection","volume":"41","author":"Siqueira","year":"2004","journal-title":"Ultrasonics"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1109\/TUFFC.2003.1209557","article-title":"Omni-directional guided wave transducer arrays for the rapid inspection of large areas of plate structures","volume":"50","author":"Wilcox","year":"2003","journal-title":"IEEE Trans. Ultrason. Ferroelectr. Freq. Control"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.ultras.2014.11.003","article-title":"Fundamental understanding of wave generation and reception using d36 type piezoelectric transducers","volume":"57","author":"Zhou","year":"2015","journal-title":"Ultrasonics"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1329","DOI":"10.1177\/1045389X08096665","article-title":"Multi-mode damage detection methods with piezoelectric wafer active sensors","volume":"20","author":"Yu","year":"2009","journal-title":"J. Intell. Mater. Syst. Struct."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1016\/j.ndteint.2010.05.003","article-title":"Configuration optimization of magnetostrictive transducers for longitudinal guided wave inspection in seven-wire steel strands","volume":"43","author":"Liu","year":"2010","journal-title":"NDT E Int."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Hayashi, T., Kawashima, K., Sun, Z., and Rose, J.L. (2003, January 20\u201324). Guided Wave Propagation Mechanics across a Pipe Elbow. Proceedings of the ASME 2003 Pressure Vessels and Piping Conference, Cleveland, OH, USA.","DOI":"10.1115\/PVP2003-1851"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/j.ymssp.2019.04.013","article-title":"Time-domain spectral finite element method for analysis of torsional guided waves scattering and mode conversion by cracks in pipes","volume":"128","author":"Yeung","year":"2019","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1109\/TUFFC.2017.2683259","article-title":"Guided wave tomography of pipe bends","volume":"64","author":"Brath","year":"2017","journal-title":"IEEE Trans. Ultrason. Ferroelectr. Freq. Control"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"102149","DOI":"10.1016\/j.ndteint.2019.102149","article-title":"Variational mode decomposition linked wavelet method for EMAT denoise with large lift-off effect","volume":"107","author":"Si","year":"2019","journal-title":"NDT E Int."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.ndteint.2016.11.010","article-title":"Circumferential guided wave EMAT system for pipeline screening using shear horizontal ultrasound","volume":"86","author":"Clough","year":"2017","journal-title":"NDT E Int."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.ndteint.2008.08.003","article-title":"Influence of steel wrapping on magneto-inductive testing of the main cables of suspension bridges","volume":"42","author":"Christen","year":"2009","journal-title":"NDT E Int."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"7997","DOI":"10.1109\/JSEN.2020.2982680","article-title":"A Deep Learning-Based Ultrasonic Pattern Recognition Method for Inspecting Girth Weld Cracking of Gas Pipeline","volume":"20","author":"Yan","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1177\/1475921718805733","article-title":"Long-term stability of guided wave electromagnetic acoustic transducer systems","volume":"19","author":"Herdovics","year":"2020","journal-title":"Struct. Health Monit."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"2821","DOI":"10.1109\/20.951317","article-title":"Improved finite element method for EMAT analysis and design","volume":"37","author":"Shapoorabadi","year":"2001","journal-title":"IEEE Trans. Magn."},{"key":"ref_68","first-page":"821","article-title":"Development of single-channel and phased array electromagnetic acoustic transducers for austenitic weld testing","volume":"68","author":"Gao","year":"2010","journal-title":"Mater. Eval."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"095103","DOI":"10.1088\/0957-0233\/24\/9\/095103","article-title":"The design and calibration of particular geometry piezoelectric acoustic emission transducer for leak detection and localization","volume":"24","author":"Yalcinkaya","year":"2013","journal-title":"Meas. Sci. Technol."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1177\/1475921716689733","article-title":"Thickness reconstruction of nuclear power plant pipes with flow-accelerated corrosion damage using laser ultrasonic wavenumber imaging","volume":"17","author":"Truong","year":"2018","journal-title":"Struct. Health Monit."},{"key":"ref_71","first-page":"267","article-title":"Characterisation of steels with microdefects using a laser interferometry technique","volume":"49","author":"Zhitluhina","year":"2007","journal-title":"Insight-Non-Destr. Test. Cond. Monit."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Wang, W., Dalton, D., Hua, X., Wang, X., Chen, Z., and Song, G. (2017). Experimental study on vibration control of a submerged pipeline model by eddy current tuned mass damper. Appl. Sci., 7.","DOI":"10.3390\/app7100987"},{"key":"ref_73","first-page":"302","article-title":"Electromagnetic and eddy current NDT: A review","volume":"43","author":"Sophian","year":"2001","journal-title":"Insight"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1016\/j.compositesb.2018.12.021","article-title":"Contactless high-speed eddy current inspection of unidirectional carbon fiber reinforced polymer","volume":"168","author":"Machado","year":"2019","journal-title":"Compos. Part B Eng."},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Shull, P.J. (2002). Nondestructive Evaluation: Theory, Techniques, and Applications, CRC Press.","DOI":"10.1201\/9780203911068"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"2490","DOI":"10.1109\/JSEN.2018.2886816","article-title":"Multi-layer magnetic focusing sensor structure for pulsed remote field eddy current","volume":"19","author":"Yang","year":"2018","journal-title":"IEEE Sens. J."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.measurement.2018.09.054","article-title":"Dual sensing coils used for RFEC testing of joint casings in oil wells","volume":"133","author":"Shi","year":"2019","journal-title":"Measurement"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/S0963-8695(00)00026-8","article-title":"Remote field eddy current technique applied to non-magnetic steam generator tubes","volume":"34","author":"Fukutomi","year":"2001","journal-title":"NDT E Int."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.sna.2006.06.056","article-title":"Flexible eddy current sensor array for proximity sensing","volume":"135","author":"Chen","year":"2007","journal-title":"Sens. Actuators A Phys."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1016\/S0963-8695(03)00050-1","article-title":"Design of an eddy-current array probe for crack sizing in steam generator tubes","volume":"36","author":"Huang","year":"2003","journal-title":"NDT E Int."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.compositesb.2013.12.005","article-title":"Non-destructive testing of low-energy impact in CFRP laminates and interior defects in honeycomb sandwich using scanning pulsed eddy current","volume":"59","author":"He","year":"2014","journal-title":"Compos. Part B Eng."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/j.ndteint.2004.09.007","article-title":"Reduction of lift-off effects for pulsed eddy current NDT","volume":"38","author":"Tian","year":"2005","journal-title":"NDT E Int."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1016\/j.measurement.2019.04.091","article-title":"Design and optimisation of mutual inductance based pulsed eddy current probe","volume":"144","author":"Ona","year":"2019","journal-title":"Measurement"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.ndteint.2017.02.009","article-title":"Pulse-modulation eddy current probes for imaging of external corrosion in nonmagnetic pipes","volume":"88","author":"Li","year":"2017","journal-title":"NDT E Int."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"112030","DOI":"10.1016\/j.sna.2020.112030","article-title":"A novel magnetic force transmission eddy current array probe and its application for nondestructive testing of defects in pipeline structures","volume":"309","author":"Xie","year":"2020","journal-title":"Sens. Actuators A Phys."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"1589","DOI":"10.1109\/20.497556","article-title":"Efforts towards gaining a better understanding of the remote field eddy current phenomenon and expanding its applications","volume":"32","author":"Sun","year":"1996","journal-title":"IEEE Trans. Magn."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"2102","DOI":"10.1016\/j.matlet.2004.01.006","article-title":"Remote field eddy current testing for detection of stress corrosion cracks in gas transmission pipelines","volume":"58","author":"Kim","year":"2004","journal-title":"Mater. Lett."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1016\/j.ndteint.2011.05.004","article-title":"PEC thermography for imaging multiple cracks from rolling contact fatigue","volume":"44","author":"Wilson","year":"2011","journal-title":"NDT E Int."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.corsci.2013.09.001","article-title":"An investigation into eddy current pulsed thermography for detection of corrosion blister","volume":"78","author":"He","year":"2014","journal-title":"Corros. Sci."},{"key":"ref_90","doi-asserted-by":"crossref","unstructured":"Ciampa, F., Mahmoodi, P., Pinto, F., and Meo, M. (2018). Recent advances in active infrared thermography for non-destructive testing of aerospace components. Sensors, 18.","DOI":"10.3390\/s18020609"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1063\/1.2902698","article-title":"Mechanisms and models for crack detection with induction thermography","volume":"975","author":"Vrana","year":"2008","journal-title":"AIP Conf. Proc."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1080\/10589750701448225","article-title":"Thermo-inductive crack detection","volume":"22","author":"Tranta","year":"2007","journal-title":"Nondestruct. Test. Eval."},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Tian, G., Wilson, J., Cheng, L., Almond, D.P., Kostson, E., and Weekes, B. (2011). Pulsed Eddy Current Thermography and Applications. New Developments in Sensing Technology for Structural Health Monitoring, Springer.","DOI":"10.1007\/978-3-642-21099-0_10"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1109\/TMAG.2010.2091418","article-title":"A new method for evaluation of mechanical stress using the reciprocal amplitude of magnetic Barkhausen noise","volume":"47","author":"Mierczak","year":"2010","journal-title":"IEEE Trans. Magn."},{"key":"ref_95","first-page":"474","article-title":"Influence of lift off on Barkhausen noise parameters of construction steel","volume":"69","year":"2018","journal-title":"J. Electr. Eng."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1016\/j.jmmm.2019.04.082","article-title":"Repeatability and stability study of residual magnetic field for domain wall characterization","volume":"485","author":"Zeng","year":"2019","journal-title":"J. Magn. Magn. Mater."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.ndteint.2019.05.002","article-title":"Deep neural networks based approach for welded joint detection of oil pipelines in radiographic images with Double Wall Double Image exposure","volume":"105","author":"Suyama","year":"2019","journal-title":"NDT E Int."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.ndteint.2016.11.006","article-title":"Radiographic modelling for NDE of subsea pipelines","volume":"86","author":"Haith","year":"2017","journal-title":"NDT E Int."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.ijleo.2017.05.066","article-title":"An improved version of Otsu\u2019s method for segmentation of weld defects on X-radiography images","volume":"142","author":"Malarvel","year":"2017","journal-title":"Optik"},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.ndteint.2016.11.003","article-title":"Automated detection of welding defects in pipelines from radiographic images DWDI","volume":"86","author":"Boaretto","year":"2017","journal-title":"NDT E Int."},{"key":"ref_101","doi-asserted-by":"crossref","unstructured":"Hou, W., Zhang, D., Wei, Y., Guo, J., and Zhang, X. (2020). Review on computer aided weld defect detection from radiography images. Appl. Sci., 10.","DOI":"10.3390\/app10051878"},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1166\/asem.2014.1444","article-title":"Evaluation of pipelines in industrial radiography using image processing techniques","volume":"6","author":"Yazdani","year":"2014","journal-title":"Adv. Sci. Eng. Med."},{"key":"ref_103","doi-asserted-by":"crossref","unstructured":"Grosse, C.U., and Ohtsu, M. (2008). Acoustic Emission Testing, Springer Science & Business Media.","DOI":"10.1007\/978-3-540-69972-9"},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"107254","DOI":"10.1016\/j.ymssp.2020.107254","article-title":"Crack detection and localization in a fluid pipeline based on acoustic emission signals","volume":"150","author":"Quy","year":"2021","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1784\/204764218824811570","article-title":"On the application of AE technology in continuous monitoring of pipelines of power units operating at high temperatures","volume":"8","author":"Paton","year":"2018","journal-title":"Int. J. Cond. Monit."},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.engfracmech.2018.04.027","article-title":"Acoustic emission signal processing framework to identify fracture in aluminum alloys","volume":"210","author":"Wisner","year":"2019","journal-title":"Eng. Fract. Mech."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1016\/j.engfracmech.2018.03.010","article-title":"Artificial intelligence-based machine learning considering flow and temperature of the pipeline for leak early detection using acoustic emission","volume":"210","author":"Ahn","year":"2019","journal-title":"Eng. Fract. Mech."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"508","DOI":"10.1016\/j.robot.2015.09.013","article-title":"Application of robotics in offshore oil and gas industry\u2014A review Part II","volume":"75","author":"Shukla","year":"2016","journal-title":"Robot. Auton. Syst."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"107206","DOI":"10.1016\/j.oceaneng.2020.107206","article-title":"Modeling of the in-pipe inspection robot: A comprehensive review","volume":"203","author":"Yakub","year":"2020","journal-title":"Ocean Eng."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"032021","DOI":"10.1088\/1757-899X\/382\/3\/032021","article-title":"Comparative Analysis of In-line Inspection Equipments and Technologies","volume":"382","author":"Song","year":"2018","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"103933","DOI":"10.1016\/j.jngse.2021.103933","article-title":"An innovative approach towards defect detection and localization in gas pipelines using integrated in-line inspection methods","volume":"90","author":"Sampath","year":"2021","journal-title":"J. Nat. Gas Sci. Eng."},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1016\/j.engfailanal.2018.05.010","article-title":"A review on pipeline integrity management utilizing in-line inspection data","volume":"92","author":"Xie","year":"2018","journal-title":"Eng. Fail. Anal."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"111844","DOI":"10.1016\/j.sna.2020.111844","article-title":"High sensitivity flexible double square winding eddy current array for surface micro-defects inspection","volume":"309","author":"Ma","year":"2020","journal-title":"Sens. Actuators A Phys."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1061\/(ASCE)0887-3828(2006)20:2(126)","article-title":"Condition rating model for underground infrastructure sustainable water mains","volume":"20","author":"Zayed","year":"2006","journal-title":"J. Perform. Constr. Facil."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"16","DOI":"10.31471\/2311-1399-2020-1(13)-16-25","article-title":"Technologies of cleaning and in-line inspection of gas mains","volume":"7","author":"Banakhevych","year":"2020","journal-title":"J. Hydrocarb. Power Eng."},{"key":"ref_116","unstructured":"Stawicki, O., Ahlbrink, R., and Schroeer, K. (2009, January 18). Shallow Internal Corrosion sensor technology for heavy pipe wall inspection. Proceedings of the PPSA Seminar, Aberdeen, UK. Available online: http:\/\/www.ppsa-online.com\/papers\/09-Aberdeen\/2009-05-Stawicki.pdf."},{"key":"ref_117","unstructured":"Keuter, J. (2014, January 19). In-Line Inspection of Pipes Using Corrosion Resistant Alloys (CRA). Proceedings of the PPSA Seminar, Aberdeen, UK."},{"key":"ref_118","unstructured":"Barbian, A., and Beller, M. (2012, January 16\u201320). In-line inspection of high pressure transmission pipelines: State-of-the-art and future trends. Proceedings of the 18th World Conference on Nondestructive Testing, Durban, South Africa."},{"key":"ref_119","unstructured":"Krieg, W., Beuker, T., Klann, M., Damaschke, J., and Lindner, H. (2007, January 16\u201317). A novel EMAT crack detection and coating disbondment (RoCD2) ILI technology. Proceedings of the 2nd Pipeline Technology Conference, Hannover, Germany."},{"key":"ref_120","unstructured":"(2019, April 09). I2I Pipelines. Available online: http:\/\/www.i2ipipelines.com\/."},{"key":"ref_121","unstructured":"Denenberg, S.A., Yanko, S., Neil, J.G., Todd, M.D., Andrew, P.W., Don, S., and Brian, M. (2014). Method and Apparatus for Measurement of Material Condition. (Application No. GB2534808A), UK Patent."},{"key":"ref_122","unstructured":"Harris, C. (2012, January 14). Assessing mechanical damage using multiple data sets in inline inspection. Proceedings of the Pigging Products and Services Association (PPSA) Seminar Papers, Aberdeen, UK."},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"31036","DOI":"10.3390\/s151229845","article-title":"Theory and application of magnetic flux leakage pipeline detection","volume":"12","author":"Shi","year":"2015","journal-title":"Sensors"},{"key":"ref_124","doi-asserted-by":"crossref","unstructured":"Xiaoting, G., Yunpeng, S., Huadong, S., Chunfeng, X., Haibo, Z., and Yunan, W. (2019, January 1\u20133). Design and application of magnetoelectric composite heterogeneous field multi-function sensor. Proceedings of the 2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI), Changsha, China.","DOI":"10.1109\/ICEMI46757.2019.9101724"},{"key":"ref_125","doi-asserted-by":"crossref","unstructured":"Lindner, H. (2015). Deepwater, High-Pressure and Multidiameter Pipelines\u2014A Challenging in-Line Inspection Project. Oil and Gas Pipelines, John Wiley & Sons, Inc.","DOI":"10.1002\/9781119019213.ch52"},{"key":"ref_126","unstructured":"Beuker, T., Brockhaus, S., Ahlbrink, R., and McGee, M. (2009, January 5\u20139). Addressing challenging environments\u2013Advanced In-line inspection solutions for gas pipelines. Proceedings of the 24th World Gas Conference, Buenos Aires, Argentina."},{"key":"ref_127","unstructured":"(2018, March 01). ROSEN. Available online: https:\/\/www.rosen-group.com\/."},{"key":"ref_128","first-page":"26","article-title":"How to ensure integrity in non-piggable pipelines","volume":"228","author":"Philips","year":"2001","journal-title":"Pipeline Gas J."},{"key":"ref_129","unstructured":"Mirzoev, S., Mashurov, S., and Sibila, J. (2015, January 8\u201310). A Comprehensive Approach to Integrity of Non-Piggable Pipeline Based on Combined DCVG\/CIPS\/MTM Survey. Proceedings of the Pipeline Technology Conference, Berlin, Germany."},{"key":"ref_130","unstructured":"Fletcher, R., and Chandrasekaran, M. (October, January 29). SmartBall\u2122: A new approach in pipeline leak detection. Proceedings of the International Pipeline Conference, Calgary, AB, Canada."},{"key":"ref_131","unstructured":"Ariaratnam, S.T., and Chandrasekaran, M. (2020, June 29). Development of a Free-Swimming Acoustic Tool for Liquid Pipeline Leak Detection Including Evaluation for Natural Gas Pipeline Applications, Available online: https:\/\/rosap.ntl.bts.gov\/view\/dot\/34534."},{"key":"ref_132","doi-asserted-by":"crossref","unstructured":"Papavinasam, S. (2013). Corrosion Control in the Oil and Gas Industry, Gulf Professional Publishing.","DOI":"10.1016\/B978-0-12-397022-0.00002-9"},{"key":"ref_133","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TRO.2004.838000","article-title":"Differential-drive in-pipe robot for moving inside urban gas pipelines","volume":"21","author":"Roh","year":"2005","journal-title":"IEEE Trans. Robot."},{"key":"ref_134","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1163\/1568553054255646","article-title":"Development of a steerable, wheel-type, in-pipe robot and its path planning","volume":"19","author":"Oya","year":"2005","journal-title":"Adv. Robot."},{"key":"ref_135","doi-asserted-by":"crossref","unstructured":"Yukawa, T., Suzuki, M., Satoh, Y., and Okano, H. (2006, January 8\u201311). Design of magnetic wheels in pipe inspection robot. Proceedings of the 2006 IEEE International Conference on Systems, Man and Cybernetics, Taipei, Taiwan.","DOI":"10.1109\/ICSMC.2006.384388"},{"key":"ref_136","unstructured":"NACE (2007). Performing Close-Interval Potential Surveys and DC Surface Potential Gradient Surveys on Buried or Submerged Metallic Pipelines, NACE Standards (NACE International). NACE SP0207."},{"key":"ref_137","first-page":"14","article-title":"A Practical Comparison of Above Ground Techniques for Coating Defect Delineation","volume":"6","author":"Borek","year":"1988","journal-title":"Ind. Corros."},{"key":"ref_138","doi-asserted-by":"crossref","first-page":"2081","DOI":"10.1016\/j.proeng.2014.12.451","article-title":"Design of a new in-pipe inspection robot","volume":"97","author":"Nayak","year":"2014","journal-title":"Procedia Eng."},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1163\/156855311X614554","article-title":"Stiffness design of springs for a screw drive in-pipe robot to pass through curved pipes and vertical straight pipes","volume":"26","author":"Kakogawa","year":"2012","journal-title":"Adv. Robot."},{"key":"ref_140","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.autcon.2015.10.006","article-title":"Multi-tier method using infrared photography and GPR to detect and locate water leaks","volume":"61","author":"Atef","year":"2016","journal-title":"Autom. Constr."},{"key":"ref_141","doi-asserted-by":"crossref","first-page":"15912","DOI":"10.3390\/s131215912","article-title":"GPR-based water leak models in water distribution systems","volume":"13","author":"Cabrera","year":"2013","journal-title":"Sensors"},{"key":"ref_142","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.measurement.2012.05.032","article-title":"State of the art review of inspection technologies for condition assessment of water pipes","volume":"46","author":"Liu","year":"2013","journal-title":"Measurement"},{"key":"ref_143","unstructured":"Beller, M., Sabido, C., and Steinvoorte, T. (2015, January 8\u201310). Inspection of Challenging Pipelines. Proceedings of the Pipeline Technology Conference, Berlin, Germany."},{"key":"ref_144","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.tust.2011.10.011","article-title":"Condition assessment of the buried utility service infrastructure","volume":"28","author":"Hao","year":"2012","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"2654","DOI":"10.1109\/TMTT.2012.2198235","article-title":"Buried object characterization using ultra-wideband ground penetrating radar","volume":"60","author":"Li","year":"2012","journal-title":"IEEE Trans. Microw. Theory Tech."},{"key":"ref_146","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1109\/TAES.2006.1642579","article-title":"Performance of an adaptive feature-based processor for a wideband ground penetrating radar system","volume":"42","author":"Torrione","year":"2006","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_147","first-page":"5","article-title":"Infrared vision for the nondestructive assessment of panel paintings","volume":"31","author":"Castanedo","year":"2010","journal-title":"CINDE J."},{"key":"ref_148","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.ndteint.2015.09.003","article-title":"Evaluation of historical bridges through recreation of GPR models with the FDTD algorithm","volume":"77","author":"Solla","year":"2016","journal-title":"NDT E Int."},{"key":"ref_149","doi-asserted-by":"crossref","first-page":"1943","DOI":"10.1016\/j.proeng.2014.12.348","article-title":"Investigation of surface texture using image processing techniques","volume":"97","author":"Srivani","year":"2014","journal-title":"Procedia Eng."},{"key":"ref_150","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1016\/j.tust.2007.06.001","article-title":"Underground asset location and condition assessment technologies","volume":"22","author":"Costello","year":"2007","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_151","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.ndteint.2010.11.006","article-title":"Generating and detecting torsional guided waves using magnetostrictive sensors of crossed coils","volume":"44","author":"Kim","year":"2011","journal-title":"NDT E Int."},{"key":"ref_152","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1080\/00207549208942892","article-title":"An application of machine vision in the automated inspection of engineering surfaces","volume":"30","author":"Baul","year":"1992","journal-title":"Int. J. Prod. Res."},{"key":"ref_153","doi-asserted-by":"crossref","first-page":"031004","DOI":"10.1115\/1.4006093","article-title":"Machine tool condition monitoring based on an adaptive Gaussian mixture model","volume":"134","author":"Yu","year":"2012","journal-title":"J. Manuf. Sci. Eng."},{"key":"ref_154","doi-asserted-by":"crossref","unstructured":"Raghavan, A. (2007). Guided-Wave Structural Health Monitoring. [Ph.D. Thesis, University of Michigan].","DOI":"10.1177\/0583102406075428"},{"key":"ref_155","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1109\/TII.2018.2828811","article-title":"An estimation method of defect size from MFL image using visual transformation convolutional neural network","volume":"15","author":"Lu","year":"2018","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_156","doi-asserted-by":"crossref","unstructured":"Czimmermann, T., Ciuti, G., Milazzo, M., Chiurazzi, M., Roccella, S., Oddo, C.M., and Dario, P. (2020). Visual-Based Defect Detection and Classification Approaches for Industrial Applications\u2014A SURVEY. Sensors, 20.","DOI":"10.3390\/s20051459"},{"key":"ref_157","doi-asserted-by":"crossref","unstructured":"Moomen, A., Ali, A., and Ramahi, O.M. (2016). Reducing sweeping frequencies in microwave NDT employing machine learning feature selection. Sensors, 16.","DOI":"10.3390\/s16040559"},{"key":"ref_158","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.ultras.2013.07.018","article-title":"Ultrasonic sensor based defect detection and characterisation of ceramics","volume":"54","author":"Kesharaju","year":"2014","journal-title":"Ultrasonics"},{"key":"ref_159","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.ndteint.2009.10.003","article-title":"Classification of pulsed eddy current GMR data on aircraft structures","volume":"43","author":"Kim","year":"2010","journal-title":"NDT E Int."},{"key":"ref_160","doi-asserted-by":"crossref","first-page":"095002","DOI":"10.1088\/1361-6420\/aaca8f","article-title":"A transdimensional Bayesian approach to ultrasonic travel-time tomography for non-destructive testing","volume":"34","author":"Tant","year":"2018","journal-title":"Inverse Probl."},{"key":"ref_161","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.ndteint.2014.07.003","article-title":"Study on defect classification in multi-layer structures based on Fisher linear discriminate analysis by using pulsed eddy current technique","volume":"67","author":"Chen","year":"2014","journal-title":"NDT E Int."},{"key":"ref_162","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1016\/j.prostr.2019.05.089","article-title":"Application of wavelet analysis and machine learning on vibration data from gas pipelines for structural health monitoring","volume":"14","author":"Zajam","year":"2019","journal-title":"Procedia Struct. Integr."},{"key":"ref_163","doi-asserted-by":"crossref","first-page":"16917","DOI":"10.1007\/s00500-020-04985-7","article-title":"A complete online-SVM pipeline for case-based reasoning system: A study on pipe defect detection system","volume":"24","author":"Le","year":"2020","journal-title":"Soft Comput."},{"key":"ref_164","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.asoc.2016.10.040","article-title":"Detection and sizing of metal-loss defects in oil and gas pipelines using pattern-adapted wavelets and machine learning","volume":"52","author":"Layouni","year":"2017","journal-title":"Appl. Soft Comput."},{"key":"ref_165","doi-asserted-by":"crossref","first-page":"3073","DOI":"10.1109\/TMAG.2009.2020160","article-title":"Machine learning techniques for the analysis of magnetic flux leakage images in pipeline inspection","volume":"45","author":"Reilly","year":"2009","journal-title":"IEEE Trans. Magn."},{"key":"ref_166","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.ultras.2016.07.014","article-title":"A novel Bayesian approach to acoustic emission data analysis","volume":"72","author":"Agletdinov","year":"2016","journal-title":"Ultrasonics"},{"key":"ref_167","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1109\/TIM.2019.2963555","article-title":"Automated visual defect detection for flat steel surface: A survey","volume":"69","author":"Luo","year":"2020","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_168","doi-asserted-by":"crossref","first-page":"155103","DOI":"10.1063\/5.0020404","article-title":"Deep learning approaches for thermographic imaging","volume":"128","author":"Lehner","year":"2020","journal-title":"J. Appl. Phys."},{"key":"ref_169","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.neucom.2020.07.093","article-title":"DeftectNet: Joint loss structured deep adversarial network for thermography defect detecting system","volume":"417","author":"Ruan","year":"2020","journal-title":"Neurocomputing"},{"key":"ref_170","doi-asserted-by":"crossref","first-page":"472","DOI":"10.1109\/TIP.2020.3036770","article-title":"A Lightweight Spatial and Temporal Multi-Feature Fusion Network for Defect Detection","volume":"30","author":"Hu","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"ref_171","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1007\/s42524-020-0121-5","article-title":"A review of condition-based maintenance: Its prognostic and operational aspects","volume":"7","author":"Li","year":"2020","journal-title":"Front. Eng. Manag."},{"key":"ref_172","doi-asserted-by":"crossref","first-page":"103721","DOI":"10.1016\/j.engappai.2020.103721","article-title":"A state of the art review on condition assessment models developed for sewer pipelines","volume":"93","author":"Hawari","year":"2020","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_173","first-page":"012024","article-title":"A review on oil and gas pipelines corrosion growth rate modelling incorporating artificial intelligence approach","volume":"Volume 476","author":"Nasser","year":"2020","journal-title":"Proceedings of the IOP Conference Series: Earth and Environmental Science, Proceedings of the 2nd International Conference on Civil & Environmental Engineering"},{"key":"ref_174","doi-asserted-by":"crossref","first-page":"04020028","DOI":"10.1061\/(ASCE)WR.1943-5452.0001205","article-title":"Linear model and regularization for transient wave\u2013based pipeline-condition assessment","volume":"146","author":"Wang","year":"2020","journal-title":"J. Water Resour. Plan. Manag."},{"key":"ref_175","doi-asserted-by":"crossref","first-page":"104224","DOI":"10.1016\/j.ijpvp.2020.104224","article-title":"External corrosion pitting depth prediction using Bayesian spectral analysis on bare oil and gas pipelines","volume":"188","author":"Balekelayi","year":"2020","journal-title":"Int. J. Press. Vessel. Pip."},{"key":"ref_176","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1515\/corrrev-2018-0022","article-title":"A brief review on the erosion-corrosion behavior of engineering materials","volume":"36","author":"Kuruvila","year":"2018","journal-title":"Corros. Rev."},{"key":"ref_177","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.engfailanal.2017.08.008","article-title":"Statistical model and structural reliability analysis for onshore gas transmission pipelines","volume":"82","author":"Pesinis","year":"2017","journal-title":"Eng. Fail. Anal."},{"key":"ref_178","doi-asserted-by":"crossref","first-page":"04018097","DOI":"10.1061\/(ASCE)WR.1943-5452.0001034","article-title":"Reliability analysis of water distribution systems using physical probabilistic pipe failure method","volume":"145","author":"Mazumder","year":"2019","journal-title":"J. Water Resour. Plan. Manag."},{"key":"ref_179","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.corsci.2012.09.005","article-title":"Reliability assessment of buried pipelines based on different corrosion rate models","volume":"66","author":"Valor","year":"2013","journal-title":"Corros. Sci."},{"key":"ref_180","first-page":"1","article-title":"A review of data-driven oil and gas pipeline pitting corrosion growth models applicable for prognostic and health management","volume":"9","author":"Heidary","year":"2018","journal-title":"Int. J. Progn. Health Manag."},{"key":"ref_181","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.strusafe.2016.09.004","article-title":"Probabilistic physical modelling of corroded cast iron pipes for lifetime prediction","volume":"64","author":"Ji","year":"2017","journal-title":"Struct. Saf."},{"key":"ref_182","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.neucom.2016.12.038","article-title":"A survey of deep neural network architectures and their applications","volume":"234","author":"Liu","year":"2017","journal-title":"Neurocomputing"},{"key":"ref_183","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.autcon.2014.05.003","article-title":"Artificial neural network models for predicting condition of offshore oil and gas pipelines","volume":"45","author":"Senouci","year":"2014","journal-title":"Autom. Constr."},{"key":"ref_184","doi-asserted-by":"crossref","first-page":"103716","DOI":"10.1016\/j.jngse.2020.103716","article-title":"A new hybrid algorithm model for prediction of internal corrosion rate of multiphase pipeline","volume":"85","author":"Peng","year":"2021","journal-title":"J. Nat. Gas Sci. Eng."},{"key":"ref_185","doi-asserted-by":"crossref","first-page":"818","DOI":"10.1016\/j.psep.2021.01.008","article-title":"Advanced intelligence frameworks for predicting maximum pitting corrosion depth in oil and gas pipelines","volume":"147","author":"Seghier","year":"2021","journal-title":"Process Saf. Environ. Prot."},{"key":"ref_186","doi-asserted-by":"crossref","first-page":"102047","DOI":"10.1016\/j.strusafe.2020.102047","article-title":"Failure risk analysis of pipelines using data-driven machine learning algorithms","volume":"89","author":"Mazumder","year":"2021","journal-title":"Struct. Saf."},{"key":"ref_187","doi-asserted-by":"crossref","first-page":"104397","DOI":"10.1016\/j.engfailanal.2020.104397","article-title":"Corrosion defect modelling of aged pipelines with a feed-forward multi-layer neural network for leak and burst failure estimation","volume":"110","author":"Ossai","year":"2020","journal-title":"Eng. Fail. Anal."},{"key":"ref_188","doi-asserted-by":"crossref","unstructured":"Vankov, Y., Rumyantsev, A., Ziganshin, S., Politova, T., Minyazev, R., and Zagretdinov, A. (2020). Assessment of the condition of pipelines using convolutional neural networks. Energies, 13.","DOI":"10.3390\/en13030618"},{"key":"ref_189","doi-asserted-by":"crossref","unstructured":"Mahmoodzadeh, Z., Wu, K.Y., Droguett, E.L., and Mosleh, A. (2020). Condition-Based Maintenance with Reinforcement Learning for Dry Gas Pipeline Subject to Internal Corrosion. Sensors, 20.","DOI":"10.3390\/s20195708"},{"key":"ref_190","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1002\/ese3.522","article-title":"An ANN-based failure pressure prediction method for buried high-strength pipes with stray current corrosion defect","volume":"8","author":"Liu","year":"2020","journal-title":"Energy Sci. Eng."},{"key":"ref_191","first-page":"597","article-title":"Remote monitoring and control of LQR-PI controller parameters for an oil pipeline transport system","volume":"233","author":"Priyanka","year":"2019","journal-title":"Proc. Inst. Mech. Eng. I J. Syst. Control. Eng."},{"key":"ref_192","doi-asserted-by":"crossref","unstructured":"Shen, L., Li, J., Wu, Y., Tang, Z., and Wang, Y. (2019, January 21\u201324). Optimization of artificial bee colony algorithm based load balancing in smart grid cloud. Proceedings of the 2019 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), Chengdu, China.","DOI":"10.1109\/ISGT-Asia.2019.8881232"},{"key":"ref_193","doi-asserted-by":"crossref","unstructured":"Mayilvaganan, M., and Sabitha, M. (2013, January 26\u201328). A cloud-based architecture for Big-Data analytics in smart grid: A proposal. Proceedings of the 2013 IEEE International Conference on Computational Intelligence and Computing Research, Madurai, India.","DOI":"10.1109\/ICCIC.2013.6724168"},{"key":"ref_194","doi-asserted-by":"crossref","first-page":"2452","DOI":"10.1109\/TMTT.2017.2786696","article-title":"Chipless RFID sensor tag for metal crack detection and characterization","volume":"66","author":"Marindra","year":"2018","journal-title":"IEEE Trans. Microw. Theory Tech."},{"key":"ref_195","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1016\/j.measurement.2016.06.041","article-title":"Identification and characterisation of steel corrosion using passive high frequency RFID sensors","volume":"92","author":"Zhang","year":"2016","journal-title":"Measurement"},{"key":"ref_196","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.procs.2012.06.021","article-title":"Ultrasonic non-destructive testing (NDT) using wireless sensor networks","volume":"10","author":"Hassanein","year":"2012","journal-title":"Procedia Comput. Sci."},{"key":"ref_197","unstructured":"Meier, J., Tsalicoglou, I., and Mennicke, R. (2017, January 13\u201317). The future of NDT with wireless sensors, AI and IoT. Proceedings of the Proceedings 15th Asia Pacific Conference for Non-Destructive Testing, Singapore."},{"key":"ref_198","doi-asserted-by":"crossref","first-page":"2566","DOI":"10.1109\/TII.2020.2997836","article-title":"Multiphysics structured eddy current and thermography defects diagnostics system in moving mode","volume":"17","author":"Li","year":"2020","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_199","doi-asserted-by":"crossref","first-page":"20190608","DOI":"10.1098\/rsta.2019.0608","article-title":"Physic perspective fusion of electromagnetic acoustic transducer and pulsed eddy current testing in non-destructive testing system","volume":"378","author":"Guo","year":"2020","journal-title":"Philos. Trans. R. Soc. A"},{"key":"ref_200","unstructured":"Abney, L.J. (2007). Systems and Methods for Determining the Location of a Pig in a Pipeline. (US7222549B2), U.S. Patent."},{"key":"ref_201","doi-asserted-by":"crossref","first-page":"106130","DOI":"10.1016\/j.ultras.2020.106130","article-title":"Probing the limits of full-field linear local defect resonance identification for deep defect detection","volume":"105","author":"Segers","year":"2020","journal-title":"Ultrasonics"},{"key":"ref_202","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1109\/JIOT.2017.2664072","article-title":"Structural health monitoring framework based on Internet of Things: A survey","volume":"4","author":"Tokognon","year":"2017","journal-title":"IEEE Internet Things J."},{"key":"ref_203","first-page":"77","article-title":"Review analysis on cloud computing based smart grid technology in the oil pipeline sensor network system","volume":"6","author":"Priyanka","year":"2021","journal-title":"Pet. Res."},{"key":"ref_204","doi-asserted-by":"crossref","unstructured":"Zhang, J., Tian, G.Y., Marindra, A.M., Sunny, A.I., and Zhao, A.B. (2017). A review of passive RFID tag antenna-based sensors and systems for structural health monitoring applications. Sensors, 17.","DOI":"10.3390\/s17020265"},{"key":"ref_205","doi-asserted-by":"crossref","unstructured":"Wolter, B., Gabi, Y., and Conrad, C. (2019). Nondestructive testing with 3MA\u2014An overview of principles and applications. Appl. Sci., 9.","DOI":"10.3390\/app9061068"},{"key":"ref_206","unstructured":"Dobmann, G., Altpeter, I., Wolter, B., and Kern, R. (2008). Industrial Applications of 3MA\u2013Micromagnetic Multiparameter Microstructure and Stress Analysis. Electromagnetic Nondestructive Evaluation (XI), IOS Press. Chapter 31."},{"key":"ref_207","doi-asserted-by":"crossref","first-page":"423","DOI":"10.12989\/sss.2010.6.5_6.423","article-title":"Flexible smart sensor framework for autonomous structural health monitoring","volume":"6","author":"Rice","year":"2010","journal-title":"Smart Struct. Syst."},{"key":"ref_208","doi-asserted-by":"crossref","first-page":"2589","DOI":"10.1016\/j.renene.2019.08.092","article-title":"A survey on smart grid technologies and applications","volume":"146","author":"Dileep","year":"2020","journal-title":"Renew. Energy"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/11\/3862\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:10:31Z","timestamp":1760163031000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/11\/3862"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,3]]},"references-count":208,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["s21113862"],"URL":"https:\/\/doi.org\/10.3390\/s21113862","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,3]]}}}