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First, the vibrational signals of bearings are subjected to adaptive filtering to eliminate background noise. Second, frequency-domain transformation is performed, and a coarse-grained approach is used to continuously segment the spectrum. Within each segment, amplitude-enhancement operations are executed, transforming the data into a CGLF graph that enhances fault characteristics. This graph is then fed into a Swin Transformer-based pattern-recognition network. Third and finally, a high-precision fault diagnosis model is constructed using fully connected layers and Softmax, enabling the diagnosis of bearing faults. The fault recognition accuracy reaches 98.30% and 98.50% with public datasets and laboratory data, respectively, thereby validating the feasibility and effectiveness of the proposed method. This research offers an efficient and feasible fault diagnosis approach for rolling bearings.<\/jats:p>","DOI":"10.3390\/s24113540","type":"journal-article","created":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T03:46:49Z","timestamp":1717127209000},"page":"3540","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Bearing-Fault-Feature Enhancement and Diagnosis Based on Coarse-Grained Lattice Features"],"prefix":"10.3390","volume":"24","author":[{"given":"Xiaoyu","family":"Li","sequence":"first","affiliation":[{"name":"Naval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang 524088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9928-5242","authenticated-orcid":false,"given":"Baozhu","family":"Jia","sequence":"additional","affiliation":[{"name":"Naval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang 524088, China"},{"name":"Technical Research Center for Ship Intelligence and Safety Engineering of Guangdong Province, Zhanjiang 524088, China"},{"name":"Guangdong Provincial Key Laboratory of Intelligent Equipment for South China Sea Marine Ranching, Guangdong Ocean University, Zhanjiang 524088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiqiang","family":"Liao","sequence":"additional","affiliation":[{"name":"Naval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang 524088, China"},{"name":"Technical Research Center for Ship Intelligence and Safety Engineering of Guangdong Province, Zhanjiang 524088, China"},{"name":"Guangdong Provincial Key Laboratory of Intelligent Equipment for South China Sea Marine Ranching, Guangdong Ocean University, Zhanjiang 524088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[{"name":"Naval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang 524088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ren, B., Yang, M., Chai, N., Li, Y., and Xu, D. 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