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Unsupervised ELM has improved to extract nonlinear features. A nonlinear dynamic process monitoring method named sparse representation preserving embedding based on ELM (SRPE-ELM) is proposed in this paper. First, the noise is removed by sparse representation and the sparse coefficient is applied to construct the adjacency graph. The adjacency graph with a data-adaptive neighborhood can extract dynamic manifold structure better than a specified neighborhood parameter. Secondly, a new objection function considered the sparse reconstruction and output weights is established to extract nonlinear dynamic manifold structure. Thirdly, the statistic SPE and T<jats:sup>2<\/jats:sup> based on SRPE-ELM are built to monitor the whole process. Finally, SRPE-ELM is applied in the IRIS data classification example, a numerical case and Tennessee Eastman benchmark process to verify the effectiveness of process monitoring. <\/jats:p>","DOI":"10.1177\/0142331219898937","type":"journal-article","created":{"date-parts":[[2020,3,17]],"date-time":"2020-03-17T07:25:36Z","timestamp":1584429936000},"page":"1895-1907","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":8,"title":["Sparse representation preserving embedding based on extreme learning machine for process monitoring"],"prefix":"10.1177","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5014-887X","authenticated-orcid":false,"given":"Hui","family":"Yongyong","sequence":"first","affiliation":[{"name":"College of Electrical and Information Engineering, Lanzhou University of Technology, China"},{"name":"Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, China"}]},{"given":"Zhao","family":"Xiaoqiang","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Lanzhou University of Technology, China"},{"name":"Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, China"},{"name":"National Experimental Teaching Center of Electrical and Control Engineering, Lanzhou University of Technology, China"}]}],"member":"179","published-online":{"date-parts":[[2020,3,17]]},"reference":[{"key":"bibr1-0142331219898937","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2016.09.007"},{"key":"bibr2-0142331219898937","doi-asserted-by":"publisher","DOI":"10.1162\/089976603321780317"},{"key":"bibr3-0142331219898937","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2015.05.012"},{"key":"bibr4-0142331219898937","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2013.07.029"},{"key":"bibr5-0142331219898937","doi-asserted-by":"publisher","DOI":"10.1109\/CONTROL.2014.6915178"},{"issue":"2","key":"bibr6-0142331219898937","first-page":"5","volume":"58","author":"Deng C","year":"2015","journal-title":"Science in China. 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