{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T08:37:44Z","timestamp":1772527064309,"version":"3.50.1"},"reference-count":25,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T00:00:00Z","timestamp":1707782400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["12202103"],"award-info":[{"award-number":["12202103"]}]},{"name":"National Natural Science Foundation of China","award":["2021B1515120090"],"award-info":[{"award-number":["2021B1515120090"]}]},{"name":"National Natural Science Foundation of China","award":["2022A1515011324"],"award-info":[{"award-number":["2022A1515011324"]}]},{"name":"Guangdong Basic and Applied Basic Research Foundation","award":["12202103"],"award-info":[{"award-number":["12202103"]}]},{"name":"Guangdong Basic and Applied Basic Research Foundation","award":["2021B1515120090"],"award-info":[{"award-number":["2021B1515120090"]}]},{"name":"Guangdong Basic and Applied Basic Research Foundation","award":["2022A1515011324"],"award-info":[{"award-number":["2022A1515011324"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this study, a quantitative detection method of pipeline cracks based on a one-dimensional convolutional neural network (1D-CNN) was developed using the time-domain signal of ultrasonic guided waves and the crack size of the pipeline as the input and output, respectively. Pipeline ultrasonic guided wave detection signals under different crack defect conditions were obtained via numerical simulations and experiments, and these signals were input as features into a multi-layer perceptron and one-dimensional convolutional neural network (1D-CNN) for training. The results revealed that the 1D-CNN performed better in the quantitative analysis of pipeline crack defects, with an error of less than 2% in the simulated and experimental data, and it could effectively evaluate the size of crack defects from the echo signals under different frequency excitations. Thus, by combining the ultrasonic guided wave detection technology and CNN, a quantitative analysis of pipeline crack defects can be effectively realized.<\/jats:p>","DOI":"10.3390\/s24041204","type":"journal-article","created":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T04:09:21Z","timestamp":1707797361000},"page":"1204","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Quantitative Detection of Pipeline Cracks Based on Ultrasonic Guided Waves and Convolutional Neural Network"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-7477-7589","authenticated-orcid":false,"given":"Yuchi","family":"Shen","sequence":"first","affiliation":[{"name":"Department of Civil Engineering, Qinghai University, Xining 810016, China"}]},{"given":"Jing","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Dongguan University of Technology, Dongguan 523808, China"}]},{"given":"Junfeng","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Mechanics and Construction Engineering, Jinan University, Guangzhou 510632, China"}]},{"given":"Weiwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Dongguan University of Technology, Dongguan 523808, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5615-2503","authenticated-orcid":false,"given":"Xiaolin","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, Qinghai University, Xining 810016, China"}]},{"given":"Hongwei","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Dongguan University of Technology, Dongguan 523808, China"},{"name":"Guangdong Provincial Key Laboratory of Intelligent Disaster Prevention and Emergency Technologies for Urban Lifeline Engineering, Dongguan 523808, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7633","DOI":"10.1016\/j.egypro.2013.06.709","article-title":"A New Cost Estimate Methodology for Onshore Pipeline Transport of CO2 in China","volume":"37","author":"Bai","year":"2013","journal-title":"Energy Procedia"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.jlp.2016.10.014","article-title":"An acoustic emission based multilevel approach to buried gas pipeline leakage localization","volume":"44","author":"Xu","year":"2016","journal-title":"J. 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