{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T05:54:29Z","timestamp":1740808469398,"version":"3.38.0"},"reference-count":31,"publisher":"SAGE Publications","issue":"12","license":[{"start":{"date-parts":[[2020,3,24]],"date-time":"2020-03-24T00:00:00Z","timestamp":1585008000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100013139","name":"humanities and social science fund of ministry of education of china","doi-asserted-by":"publisher","award":["18YJC630255"],"award-info":[{"award-number":["18YJC630255"]}],"id":[{"id":"10.13039\/501100013139","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"national natural science foundation of china","doi-asserted-by":"publisher","award":["51675450"],"award-info":[{"award-number":["51675450"]}],"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":[[2020,8]]},"abstract":"<jats:p> For the characteristics of nonlinear and multi-phase in the batch process, a self-adaptive multi-phase batch process fault diagnosis method is proposed in this paper. Firstly, kernel entropy component analysis (KECA) method is used to achieve multi-phase partition adaptively, which makes the process data mapped into the high-dimensional feature space and then constructs the core entropy and the angular structure similarity. Then a multi-phase KECA failure monitoring model is developed by using the angular structure similarity as the statistic, which is based on the partitioned phases and the effective failure features by the KECA feature extraction method. A multi-phase batch process fault diagnosis method, which applies the multi-class support vector machines (MSVM) and fireworks algorithm (FWA), is proposed to recognize each sub-phase fault diagnosis automatically. The effectiveness and advantages of the proposed multi-phase fault diagnosis method are illustrated with a case study on a fed-batch penicillin fermentation process. <\/jats:p>","DOI":"10.1177\/0142331220910885","type":"journal-article","created":{"date-parts":[[2020,3,24]],"date-time":"2020-03-24T09:02:13Z","timestamp":1585040533000},"page":"2324-2337","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["Phase partition and identification based on kernel entropy component analysis and multi-class support vector machines-fireworks algorithm for multi-phase batch process fault diagnosis"],"prefix":"10.1177","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0905-9303","authenticated-orcid":false,"given":"Min","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Southwest Jiaotong University, China"},{"name":"Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, China"}]},{"given":"Ruiqi","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Southwest Jiaotong University, China"}]},{"given":"Zhenyu","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Southwest Jiaotong University, China"}]},{"given":"Wenming","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Southwest Jiaotong University, China"},{"name":"Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, China"}]}],"member":"179","published-online":{"date-parts":[[2020,3,24]]},"reference":[{"key":"bibr1-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2007.4424483"},{"key":"bibr2-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.cherd.2012.01.004"},{"key":"bibr3-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2013.09.012"},{"key":"bibr4-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1021\/ie302069q"},{"key":"bibr5-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.asej.2014.10.009"},{"key":"bibr6-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1177\/0142331217750222"},{"issue":"7","key":"bibr7-0142331220910885","first-page":"972","volume":"68","author":"Hamideh R","year":"2018","journal-title":"Applied Soft Computing"},{"key":"bibr8-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2009.100"},{"key":"bibr9-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.conengprac.2018.07.012"},{"key":"bibr10-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1177\/0142331217690579"},{"key":"bibr11-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1080\/00207540500066937"},{"key":"bibr12-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2012.01.013"},{"key":"bibr13-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1021\/acs.iecr.6b01257"},{"key":"bibr14-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1002\/aic.10024"},{"key":"bibr15-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.ces.2018.05.055"},{"key":"bibr16-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1007\/s11771-013-1568-x"},{"key":"bibr17-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1007\/s00449-011-0649-1"},{"key":"bibr18-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2016.04.005"},{"key":"bibr19-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2016.08.013"},{"volume-title":"Fireworks Algorithm-Based Maximum Power Point Tracking for Uniform Irradiation as Well as Under Partial Shading Condition. Artificial Intelligence and Evolutionary Computations in Engineering Systems","year":"2016","author":"Sangeetha K","key":"bibr20-0142331220910885"},{"key":"bibr21-0142331220910885","first-page":"633","volume-title":"Conference on Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference","author":"Sch\u00f6lkopf B","year":"2006"},{"key":"bibr22-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2018.10.011"},{"key":"bibr23-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-13495-1_44"},{"issue":"5","key":"bibr24-0142331220910885","first-page":"1022","volume-title":"Transactions of the Institute of Measurement and Control","volume":"42","author":"Tang XC","year":"2019"},{"key":"bibr25-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2017.04.061"},{"key":"bibr26-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2015.02.007"},{"issue":"9","key":"bibr27-0142331220910885","first-page":"44","volume":"69","author":"Yongyong H","year":"2018","journal-title":"Journal of Process Control"},{"key":"bibr28-0142331220910885","doi-asserted-by":"publisher","DOI":"10.3724\/SP.J.1004.2010.00366"},{"key":"bibr29-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-014-1655-4"},{"key":"bibr30-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2016.12.013"},{"key":"bibr31-0142331220910885","doi-asserted-by":"publisher","DOI":"10.1109\/IPEMC.2016.7512529"}],"container-title":["Transactions of the Institute of Measurement and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0142331220910885","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/0142331220910885","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0142331220910885","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,28]],"date-time":"2025-02-28T20:43:22Z","timestamp":1740775402000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/0142331220910885"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,24]]},"references-count":31,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2020,8]]}},"alternative-id":["10.1177\/0142331220910885"],"URL":"https:\/\/doi.org\/10.1177\/0142331220910885","relation":{},"ISSN":["0142-3312","1477-0369"],"issn-type":[{"type":"print","value":"0142-3312"},{"type":"electronic","value":"1477-0369"}],"subject":[],"published":{"date-parts":[[2020,3,24]]}}}