{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T01:17:39Z","timestamp":1786065459131,"version":"3.56.0"},"reference-count":24,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2019,9,30]],"date-time":"2019-09-30T00:00:00Z","timestamp":1569801600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Fund major project of Yunnan Provincial","award":["201601PE00008, 2017FA028"],"award-info":[{"award-number":["201601PE00008, 2017FA028"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51465022"],"award-info":[{"award-number":["51465022"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51675251"],"award-info":[{"award-number":["51675251"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Transactions of the Institute of Measurement and Control"],"published-print":{"date-parts":[[2020,2]]},"abstract":"<jats:p>Variational mode decomposition (VMD) is an adaptive signal processing method proposed recently. It has gradually been widely used due to its good performance. According to the problem that the parameters of VMD need to be determined in advance, a simple and feasible method of determining the influence parameters based on the principle of kurtosis maximum is put forward. A novel intrinsic mode function (IMF) selection method based on resonance frequency is proposed in order to select the IMF that contains the abundant fault feature information. Firstly, the parameters of VMD are optimized by the principle of kurtosis maximum, the optimal penalty parameter and mode number of VMD are set, and the original fault signal is processed by the optimized VMD to obtain the established IMF components. Then, the sensitive IMF(s) with the fault information is selected by resonance frequency. Finally, the selected IMF(s) is analyzed by the envelope demodulation analysis to extract the fault characteristic frequency to judge the fault type of the rolling bearing. It is shown that the method can extract the weak characteristics of the early fault signal of the rolling bearing, and it can realize the judgment of the bearing fault accurately through the analysis of simulated signal and the actual data of bearing.<\/jats:p>","DOI":"10.1177\/0142331219875348","type":"journal-article","created":{"date-parts":[[2019,9,30]],"date-time":"2019-09-30T22:50:44Z","timestamp":1569883844000},"page":"518-527","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":55,"title":["Application of optimized variational mode decomposition based on kurtosis and resonance frequency in bearing fault feature extraction"],"prefix":"10.1177","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9895-689X","authenticated-orcid":false,"given":"Hua","family":"Li","sequence":"first","affiliation":[{"name":"Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Liu","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xing","family":"Wu","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing","family":"Chen","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2019,9,30]]},"reference":[{"key":"bibr1-0142331219875348","doi-asserted-by":"publisher","DOI":"10.1177\/0142331215592064"},{"key":"bibr2-0142331219875348","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2013.2288675"},{"key":"bibr3-0142331219875348","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2011.06.023"},{"key":"bibr4-0142331219875348","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2016.06.035"},{"issue":"5","key":"bibr5-0142331219875348","first-page":"1","volume":"60","author":"Helske J","year":"2017","journal-title":"International Journal of Public Health"},{"key":"bibr6-0142331219875348","doi-asserted-by":"publisher","DOI":"10.1098\/rspa.1998.0193"},{"key":"bibr7-0142331219875348","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2009.2013885"},{"key":"bibr8-0142331219875348","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2018.08.056"},{"key":"bibr9-0142331219875348","first-page":"320","volume-title":"The 9th International Conference on Modelling, Identification and Control (ICMIC 2017)","author":"Li H","year":"2017"},{"key":"bibr10-0142331219875348","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2016.02.011"},{"key":"bibr11-0142331219875348","doi-asserted-by":"publisher","DOI":"10.1177\/0954406212441886"},{"key":"bibr12-0142331219875348","first-page":"1","volume-title":"International Conference on Industrial and Information Systems","author":"Mohanty S","year":"2015"},{"key":"bibr13-0142331219875348","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2017.12.012"},{"key":"bibr14-0142331219875348","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2006.1660686"},{"key":"bibr15-0142331219875348","unstructured":"Rilling G, Flandrin P, Goncalves P (2003) On empirical mode decomposition and its algorithms. In: IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing, Vol. 3, NSIP-03, Grado (I). 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