{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T03:57:22Z","timestamp":1768795042849,"version":"3.49.0"},"reference-count":30,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,9]],"date-time":"2020-09-09T00:00:00Z","timestamp":1599609600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["61201131"],"award-info":[{"award-number":["61201131"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Development and industrial application of ultra-high temperature and high pressure wireline logging system from Science and technology project of CNOOC","award":["CNOOC-KJ ZDHXJSGG YF 2019-02"],"award-info":[{"award-number":["CNOOC-KJ ZDHXJSGG YF 2019-02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>An ultrasonic sensors system is commonly used to measure the wall thickness of buried pipelines in the transportation of oil and gas. The key of the system is to precisely measure time-of-flight difference (TOFD) produced by the reflection of ultrasonic on the inner and outer surfaces of the pipelines. In this paper, based on deep learning, a novel method termed Wave-Transform Network is proposed to tackle the issues. The network consists of two parts: part 1 is designed to separate the potential overlapping ultrasonic echo signals generated from two surfaces, and part 2 is utilized to divide the sample points of each signal into two types corresponding to before and after the arrival time of ultrasonic echo, which can determine the time-of-flight (TOF) of each signal and calculate the thickness of pipelines. Numerical simulation and actual experiments are carried out, and the results show satisfactory performances.<\/jats:p>","DOI":"10.3390\/s20185140","type":"journal-article","created":{"date-parts":[[2020,9,9]],"date-time":"2020-09-09T09:01:09Z","timestamp":1599642069000},"page":"5140","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["A Study on Determining Time-Of-Flight Difference of Overlapping Ultrasonic Signal: Wave-Transform Network"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0415-087X","authenticated-orcid":false,"given":"Zhipeng","family":"Li","sequence":"first","affiliation":[{"name":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3584-6693","authenticated-orcid":false,"given":"Tong","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1218-9475","authenticated-orcid":false,"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuyang","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenqiu","family":"Yao","sequence":"additional","affiliation":[{"name":"Glasgow College, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanjun","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yibing","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,9]]},"reference":[{"key":"ref_1","unstructured":"(2014, December 19). Principle of Well Logging. Available online: https:\/\/wehitoil.com\/well-logging-part-i\/."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Garc\u00eda-Mart\u00edn, J., G\u00f3mez-Gil, J., and V\u00e1zquez-S\u00e1nchez, E. (2011). Non-Destructive Techniques Based on Eddy Current Testing. Sensors, 11.","DOI":"10.3390\/s110302525"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/0022-3913(73)90193-5","article-title":"Radiographic testing of metal castings for use in dental implants","volume":"30","author":"Smith","year":"1973","journal-title":"J. Prosthet. Dent."},{"key":"ref_4","first-page":"373","article-title":"Diagnosis of Fluid Leaks in Pipelines Using Dynamic PCA \u204e\u204eThis research was supported by the National Council of Science and Technology (CONACYT), with project number 3595, and the Tecnol\u00f3gico Nacional de M\u00e9xico (TecNM). The supports are gratefully acknowledged","volume":"51","author":"Puig","year":"2018","journal-title":"IFAC-PapersOnLine"},{"key":"ref_5","unstructured":"Thierry, S., Klieber, C., Lemarenko, M., Brill, T.M., and Constable, K. (2017, January 17\u201321). Ultrasonic Cement Logging: Expanding the Operating Envelope and Efficiency. Proceedings of the Spwla Logging Symposium, Oklahoma City, OK, USA."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1080\/09349840601128747","article-title":"Ultrasonic Analysis of the Degree of Cure and Cohesive Properties of the Adhesive in a Bond Joint","volume":"18","author":"Maeva","year":"2007","journal-title":"Res. Nondestruct. Eval."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"110413","DOI":"10.1016\/j.engstruct.2020.110413","article-title":"Ultrasonic inline inspection of a cement-based drinking water pipeline","volume":"210","author":"Geelen","year":"2020","journal-title":"Eng. Struct."},{"key":"ref_8","unstructured":"Barshinger, J., Pellegrino, B., and Nugent, M. (2016, January 14). Permanently Installed Monitoring System for Accurate Wall Thickness and Corrosion Rate Measurement. Proceedings of the CORROSION 2016, Vancouver, BC, Canada."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3346","DOI":"10.1121\/1.410647","article-title":"Separation of overlapping reflections for ultrasonic NDE applications","volume":"96","author":"Patton","year":"1994","journal-title":"Acoust. Soc. Am. J."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2324","DOI":"10.1109\/TUFFC.2010.1693","article-title":"Separation of overlapping linear frequency modulated (LFM) signals using the fractional fourier transform","volume":"57","author":"Cowell","year":"2010","journal-title":"IEEE Trans. Ultrason. Ferroelectr. Freq. Control"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1587\/transfun.E97.A.393","article-title":"Optimal Transform Order of Fractional Fourier Transform for Decomposition of Overlapping Ultrasonic Signals","volume":"97","author":"Lu","year":"2014","journal-title":"IEICE Trans. Fundam. Electron. Commun. Comput. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Lu, Y., Kasaeifard, A., Oruklu, E., and Saniie, J. (2010, January 11\u201314). Performance evaluation of fractional Fourier transform(FrFT) for time-frequency analysis of ultrasonic signals in NDE applications. Proceedings of the 2010 IEEE International Ultrasonics Symposium, San Diego, CA, USA.","DOI":"10.1109\/ULTSYM.2010.5935838"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2819","DOI":"10.4028\/www.scientific.net\/AMR.734-737.2819","article-title":"Research on Direct Wave Separation of PD Ultrasonic Signal Based on ICA","volume":"734\u2013737","author":"Hou","year":"2013","journal-title":"Adv. Mater. Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"978","DOI":"10.1038\/nature04485","article-title":"Efficient auditory coding","volume":"439","author":"Smith","year":"2006","journal-title":"Nature"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1996","DOI":"10.1109\/TUFFC.2010.1647","article-title":"A matching pursuit method for approximating overlapping ultrasonic echoes","volume":"57","author":"Mor","year":"2010","journal-title":"IEEE Trans. Ultrason. Ferroelectr. Freq. Control"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1109\/58.920713","article-title":"Model-based estimation of ultrasonic echoes. Part I: Analysis and algorithms","volume":"48","author":"Demirli","year":"2001","journal-title":"IEEE Trans. Ultrason. Ferroelectr. Freq. Control"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1109\/TIM.2006.870123","article-title":"A Measurement Method Based on Kalman Filtering for Ultrasonic Time-of-Flight Estimation","volume":"55","author":"Angrisani","year":"2006","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.measurement.2016.08.013","article-title":"Estimating ultrasonic time-of-flight through echo signal envelope and modified Gauss Newton method","volume":"94","author":"Lu","year":"2016","journal-title":"Measurement"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Zhang, W., Li, Z., Gao, X., Li, Y., and Shi, Y. (2020). Arrival-Time Detection in Wind-Speed Measurement: Wavelet Transform and Bayesian Information Criteria. Sensors, 20.","DOI":"10.3390\/s20010269"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"974","DOI":"10.1109\/TIM.2019.2908704","article-title":"Improved Time-of-Flight Estimation Method for Acoustic Tomography System","volume":"69","author":"Bao","year":"2020","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1785\/0120120347","article-title":"An Automatic Kurtosis-Based P- and S-Phase Picker Designed for Local Seismic Networks","volume":"104","author":"Baillard","year":"2014","journal-title":"Bull. Ssmological Soc. Am."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3035","DOI":"10.1007\/s00521-016-2333-5","article-title":"Signal detection based on empirical mode decomposition and Teager\u2013Kaiser energy operator and its application to P and S wave arrival time detection in seismic signal analysis","volume":"28","author":"Kirbas","year":"2016","journal-title":"Neural Comput. Appl."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1109\/JSTSP.2019.2908700","article-title":"Deep Learning for Audio Signal Processing","volume":"13","author":"Purwins","year":"2019","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Weninger, F., Hershey, J.R., Roux, J.L., and Schuller, B. (2014, January 3\u20135). Discriminatively trained recurrent neural networks for single-channel speech separation. Proceedings of the 2014 IEEE Global Conference on Signal & Information Processing, Atlanta, GA, USA.","DOI":"10.1109\/GlobalSIP.2014.7032183"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Grais, E.M., Sen, M.U., and Erdogan, H. (2014, January 4\u20139). Deep neural networks for single channel source separation. Proceedings of the 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, Italy.","DOI":"10.1109\/ICASSP.2014.6854299"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1773","DOI":"10.1109\/TASLP.2017.2716443","article-title":"Two-Stage Single-Channel Audio Source Separation Using Deep Neural Networks","volume":"25","author":"Grais","year":"2017","journal-title":"IEEE\/ACM Trans. Audio Speech Lang. Process."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.1109\/TAC.2004.831175","article-title":"A framework for stabilization of nonlinear sampled-data systems based on their approximate discrete-time models","volume":"49","author":"Nesic","year":"2004","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., and Brox, T. (2015). U-Net: Convolutional Networks for Biomedical Image Segmentation. International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2481","DOI":"10.1109\/TPAMI.2016.2644615","article-title":"SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation","volume":"39","author":"Badrinarayanan","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.conengprac.2018.09.006","article-title":"Online leak diagnosis in pipelines using an EKF-based and steady-state mixed approach","volume":"81","author":"Puig","year":"2018","journal-title":"Control Eng. Pract."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/18\/5140\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:08:24Z","timestamp":1760177304000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/18\/5140"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,9]]},"references-count":30,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2020,9]]}},"alternative-id":["s20185140"],"URL":"https:\/\/doi.org\/10.3390\/s20185140","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,9]]}}}