{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T17:28:48Z","timestamp":1770139728019,"version":"3.49.0"},"reference-count":38,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2024,12,17]],"date-time":"2024-12-17T00:00:00Z","timestamp":1734393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2021YFF0501101"],"award-info":[{"award-number":["2021YFF0501101"]}]},{"name":"National Key R&amp;D Program of China","award":["52272347"],"award-info":[{"award-number":["52272347"]}]},{"name":"National Key R&amp;D Program of China","award":["2024JJ7132"],"award-info":[{"award-number":["2024JJ7132"]}]},{"name":"National Key R&amp;D Program of China","award":["22A0391"],"award-info":[{"award-number":["22A0391"]}]},{"name":"National Natural Science Foundation of China","award":["2021YFF0501101"],"award-info":[{"award-number":["2021YFF0501101"]}]},{"name":"National Natural Science Foundation of China","award":["52272347"],"award-info":[{"award-number":["52272347"]}]},{"name":"National Natural Science Foundation of China","award":["2024JJ7132"],"award-info":[{"award-number":["2024JJ7132"]}]},{"name":"National Natural Science Foundation of China","award":["22A0391"],"award-info":[{"award-number":["22A0391"]}]},{"name":"National Science Fund of Hu-nan","award":["2021YFF0501101"],"award-info":[{"award-number":["2021YFF0501101"]}]},{"name":"National Science Fund of Hu-nan","award":["52272347"],"award-info":[{"award-number":["52272347"]}]},{"name":"National Science Fund of Hu-nan","award":["2024JJ7132"],"award-info":[{"award-number":["2024JJ7132"]}]},{"name":"National Science Fund of Hu-nan","award":["22A0391"],"award-info":[{"award-number":["22A0391"]}]},{"name":"Scientific Research Project of Hunan Provincial Department of Education","award":["2021YFF0501101"],"award-info":[{"award-number":["2021YFF0501101"]}]},{"name":"Scientific Research Project of Hunan Provincial Department of Education","award":["52272347"],"award-info":[{"award-number":["52272347"]}]},{"name":"Scientific Research Project of Hunan Provincial Department of Education","award":["2024JJ7132"],"award-info":[{"award-number":["2024JJ7132"]}]},{"name":"Scientific Research Project of Hunan Provincial Department of Education","award":["22A0391"],"award-info":[{"award-number":["22A0391"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Rail corrugation intensifies wheel\u2013rail vibrations, often leading to damage in vehicle\u2013track system components within affected sections. This paper proposes a novel method for identifying rail corrugation, which combines Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), permutation entropy (PE), and Smoothed Pseudo Wigner\u2013Ville Distribution (SPWVD). Initially, vertical acceleration data from the axle box are decomposed using CEEMDAN to extract intrinsic mode functions (IMFs) with distinct frequencies. PE is used to evaluate the randomness of each IMF component, discarding those with high permutation entropy values. Subsequently, correlation analysis is performed on the retained IMFs to identify the component most strongly correlated with the original signal. The selected component is subjected to SPWVD time\u2013frequency analysis to identify the location and wavelength of the corrugation occurrence. Filtering is applied to the IMF based on the frequency concentration observed in the time\u2013frequency analysis results. Then, frequency\u2013domain integration is performed to estimate the rail\u2019s corrugation depth. Finally, the algorithm is validated and analyzed using both simulated data and measured data. Validation results show that this approach reliably identifies the wavelength and depth characteristics of rail corrugation. Additionally, the time\u2013frequency analysis results reveal variations in the severity of corrugation damage at different locations.<\/jats:p>","DOI":"10.3390\/s24248058","type":"journal-article","created":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T03:40:56Z","timestamp":1734493256000},"page":"8058","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Identification Method for Railway Rail Corrugation Utilizing CEEMDAN-PE-SPWVD"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1694-0975","authenticated-orcid":false,"given":"Jianhua","family":"Liu","sequence":"first","affiliation":[{"name":"College of Railway Transportation, Hunan University of Technology, Zhuzhou 412007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kexin","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Railway Transportation, Hunan University of Technology, Zhuzhou 412007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongmei","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Railway Transportation, Hunan University of Technology, Zhuzhou 412007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,17]]},"reference":[{"key":"ref_1","first-page":"14","article-title":"Application of fuzzy fault tree analysis for evaluation of railway safety risks: An evaluation of root causes for passenger train derailment","volume":"223","author":"Jafarian","year":"2009","journal-title":"Proc. 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