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Before data reduction, KEPCA transforms input data into high-dimensional feature space based on a nonlinear kernel function and automatically determines the number of principal components (PCs) based on the computation of the inertia. The retained PCs express the maximum inertia entropy of data in the feature space. Then, we use the Parzen window estimator to compute the upper control limit (UCL) for inertia-based KEPCA instead of the Gaussian assumption. Our second contribution concerns a new combined index based on the monitoring indices T2 and SPE in order to simplify the detection task of the fault and prevent any confusion. The proposed approaches have been applied to process fault detection and diagnosis for the well-known benchmark Tennessee Eastman process (TE). Results were performing.<\/jats:p>","DOI":"10.1155\/2021\/5320241","type":"journal-article","created":{"date-parts":[[2021,7,14]],"date-time":"2021-07-14T19:50:09Z","timestamp":1626292209000},"page":"1-10","source":"Crossref","is-referenced-by-count":4,"title":["Fault Detection and Identification for Nonlinear Process Based on Inertia-Based KEPCA and a New Combined Monitoring Index"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7708-675X","authenticated-orcid":true,"given":"Loubna","family":"El Fattahi","sequence":"first","affiliation":[{"name":"Department of Physics, Faculty of Science, Moulay Ismail University, Meknes, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3883-6420","authenticated-orcid":true,"given":"El Hassan","family":"Sbai","sequence":"additional","affiliation":[{"name":"High School of Technology, Moulay Ismail University, Meknes, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1080\/00224065.2015.11918137"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1021\/ie901911p"},{"key":"3","article-title":"Recursive PCA for adaptive process monitoring","volume":"16","author":"W. 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