{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:02:29Z","timestamp":1760230949091,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,16]],"date-time":"2022-08-16T00:00:00Z","timestamp":1660608000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["L211010","3212032","2022YJS155"],"award-info":[{"award-number":["L211010","3212032","2022YJS155"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds for the Central Universities","award":["L211010","3212032","2022YJS155"],"award-info":[{"award-number":["L211010","3212032","2022YJS155"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The transient pulses caused by local faults of rolling bearings are an important measurement information for fault diagnosis. However, extracting transient pulses from complex nonstationary vibration signals with a large amount of background noise is challenging, especially in the early stage. To improve the anti-noise ability and detect incipient faults, a novel signal de-noising method based on enhanced time-frequency manifold (ETFM) and kurtosis-wavelet dictionary is proposed. First, to mine the high-dimensional features, the C-C method and Cao\u2019s method are combined to determine the embedding dimension and delay time of phase space reconstruction. Second, the input parameters of the liner local tangent space arrangement (LLTSA) algorithm are determined by the grid search method based on Renyi entropy, and the dimension is reduced by manifold learning to obtain the ETFM with the highest time-frequency aggregation. Finally, a kurtosis-wavelet dictionary is constructed for selecting the best atom and eliminating the noise and reconstruct the defective signal. Actual simulations showed that the proposed method is more effective in noise suppression than traditional algorithms and that it can accurately reproduce the amplitude and phase information of the raw signal.<\/jats:p>","DOI":"10.3390\/s22166108","type":"journal-article","created":{"date-parts":[[2022,8,16]],"date-time":"2022-08-16T03:40:32Z","timestamp":1660621232000},"page":"6108","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A New De-Noising Method Based on Enhanced Time-Frequency Manifold and Kurtosis-Wavelet Dictionary for Rolling Bearing Fault Vibration Signal"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9387-8706","authenticated-orcid":false,"given":"Qingbin","family":"Tong","sequence":"first","affiliation":[{"name":"School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China"},{"name":"Beijing Rail Transit Electrical Engineering Technology Research Center, Beijing 100044, China"}]},{"given":"Ziyu","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China"}]},{"given":"Feiyu","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8568-4821","authenticated-orcid":false,"given":"Ziwei","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China"}]},{"given":"Qingzhu","family":"Wan","sequence":"additional","affiliation":[{"name":"School of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1016\/j.jsv.2007.02.029","article-title":"Cyclic spectral analysis of rolling-element bearing signals: Facts and fictions","volume":"304","author":"Antoni","year":"2007","journal-title":"J. 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