{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T15:05:30Z","timestamp":1778857530291,"version":"3.51.4"},"reference-count":23,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2024,4,13]],"date-time":"2024-04-13T00:00:00Z","timestamp":1712966400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2022YFF0608704"],"award-info":[{"award-number":["2022YFF0608704"]}]},{"name":"National Key Research and Development Program of China","award":["51575518"],"award-info":[{"award-number":["51575518"]}]},{"name":"National Natural Science Foundation of China","award":["2022YFF0608704"],"award-info":[{"award-number":["2022YFF0608704"]}]},{"name":"National Natural Science Foundation of China","award":["51575518"],"award-info":[{"award-number":["51575518"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Synchrosqueezed transform (SST) is a time\u2013frequency analysis method that can improve energy aggregation and reconstruct signals, which has been applied in the fields of medical treatment, fault diagnosis, and seismic wave processing. However, when dealing with time-varying signals, SST suffers from poor time\u2013frequency resolution and is unable to deal with long signals. In order to accurately extract the characteristic frequency of variable speed rolling bearing faults, this paper proposes a synchrosqueezed transform method based on fast kurtogram and demodulation and piecewise aggregate approximation (PAA). The method firstly filters and demodulates the original signal using fast kurtogram and Hilbert transform to reduce the influence of background noise and improve the time\u2013frequency resolution. Then, it compresses the signal by using piecewise aggregate approximation, so that the SST can deal with long signals and, thus, extract the fault characteristic frequency. The experimental data verification results indicate that the method can effectively identify the fault characteristic frequency of variable-speed rolling bearings.<\/jats:p>","DOI":"10.3390\/s24082502","type":"journal-article","created":{"date-parts":[[2024,4,15]],"date-time":"2024-04-15T08:08:12Z","timestamp":1713168492000},"page":"2502","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Synchrosqueezed Transform Method Based on Fast Kurtogram and Demodulation and Piecewise Aggregate Approximation for Bearing Fault Diagnosis"],"prefix":"10.3390","volume":"24","author":[{"given":"Yanlu","family":"Chen","sequence":"first","affiliation":[{"name":"College of Railway Transportation, Hunan University of Technology, Zhuzhou 412007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3562-9178","authenticated-orcid":false,"given":"Lei","family":"Hu","sequence":"additional","affiliation":[{"name":"Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan 411201, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0258-528X","authenticated-orcid":false,"given":"Niaoqing","family":"Hu","sequence":"additional","affiliation":[{"name":"Laboratory of Science and Technology on Integrated Logistics Support, National University of Defense Technology, Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiyu","family":"Zeng","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":[[2024,4,13]]},"reference":[{"key":"ref_1","first-page":"289","article-title":"Short-time Fourier transform","volume":"Volume 32","author":"Lim","year":"1987","journal-title":"Advanced Topics in Signal Processing"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.patrec.2010.09.021","article-title":"Estimation of the orientation of textured patterns via wavelet analysis","volume":"32","author":"Lefebvre","year":"2011","journal-title":"Pattern Recogn. 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