@misc{10481/88761,
year = {2022},
url = {https://hdl.handle.net/10481/88761},
abstract = {Nowadays, how to select the kernel function and their parameters for ensuring high-performance indicators in fault diagnosis applications remains as two open research issues. This paper provides a comprehensive literature survey of kernel-preprocessing methods in condition monitoring tasks, with emphasis on the procedures for selecting their parameters. Accordingly, twenty kernel optimization criteria and sixteen kernel functions are analyzed. A kernel evaluation framework is further provided for helping in the selection and adjustment of kernel functions. The proposal is validated via a KPCA-based monitoring scheme and two well-known benchmark processes.},
organization = {Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brazil (Finance Code 001 and CAPES-PRINT Process No. 88881.311758/2018-01)},
organization = {ARIA- National Program of Research and Innovation, Project No. 27, CITMA, Cuba},
organization = {Asociación Universitaria Iberoamericana de Postgrado (AUIP)},
organization = {Fundação Carlos Chagas Filho de Amparo a Pesquísa do Estado do Rio de Janeiro (FAPERJ), Brazil},
organization = {Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil},
organization = {Universidad Tecnológica de La Habana José Antonio Echeverría (CUJAE), Cuba},
publisher = {Elsevier},
title = {Criteria for optimizing kernel methods in fault monitoring process: A survey},
doi = {10.1016/j.isatra.2021.08.040},
author = {Llanes Santiago, Orestes and Bernal de Lázaro, José M. and Silva Neto, Antônio J. and Cruz Corona, Carlos Alberto},
}