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Firstly, a fusion with Kernel Principal Component Analysis (KPCA) and time\u2010domain parameters is performed to carry out the feature extraction and dimensionality reduction for fault data. Then, an improved Grey Wolf Optimization (GWO) algorithm is applied to enhance its global search capability while speeding up the convergence, for the purpose of further optimizing the parameters of SVM. Finally, the experimental results are obtained to suggest that the proposed method performs better in optimization than the other intelligent diagnosis algorithms based on SVM, which improves the accuracy of fault diagnosis effectively.<\/jats:p>","DOI":"10.1155\/2021\/1956394","type":"journal-article","created":{"date-parts":[[2021,9,11]],"date-time":"2021-09-11T01:35:08Z","timestamp":1631324108000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Sensor Fault Diagnosis Method Based on <i>\u03b1<\/i>\u2010Grey Wolf Optimization\u2010Support Vector Machine"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7313-4307","authenticated-orcid":false,"given":"Xuezhen","family":"Cheng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3444-3665","authenticated-orcid":false,"given":"Dafei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0346-0454","authenticated-orcid":false,"given":"Chuannuo","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5570-9952","authenticated-orcid":false,"given":"Jiming","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,9,10]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.3037463"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/tie.2020.2984427"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/jsen.2020.2980868"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.3390\/s20030745"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sna.2020.111990"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/tie.2019.2907500"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/tie.2020.2992977"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cherd.2019.09.026"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2020.107284"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2020.110443"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.10.039"},{"key":"e_1_2_9_12_2","first-page":"66","article-title":"Research on fault diagnosis method of axle box bearing of emu based on improved shapelets algorithm","volume":"42","author":"Song Z. 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