| dc.creator | Becerra Angarita, Oscar F. Becerra Angarita | |
| dc.creator | Álvarez Pizarro, Yuli A. | |
| dc.date | 2022-08-16 | |
| dc.date.accessioned | 2022-10-28T12:08:32Z | |
| dc.date.available | 2022-10-28T12:08:32Z | |
| dc.identifier | http://saber.ucv.ve/ojs/index.php/rev_esp/article/view/24260 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/4956159 | |
| dc.description | Industrial process supervision is an important subject nowdays due to the increased requirement for safer processes for operators and effective for companies. Control loops affected by disturbs, are grouped with PCA, based on their increased variability and the causal relationships between them are detected via Granger causality. A graph drawing algorithm allows indicating the source of the disturbance. The procedure is applied to data from a simulated chemical process CSTR. The proposed procedeture correctly indicated the sources of disturbances. | es-ES |
| dc.language | spa | |
| dc.publisher | Editorial Espacios | es-ES |
| dc.relation | http://saber.ucv.ve/ojs/index.php/rev_esp/article/view/24260/144814490570 | |
| dc.source | Revista Espacios; Vol. 43 Núm. 7 (2022); 30-48 | es-ES |
| dc.source | 2739-0071 | |
| dc.source | 0798-1015 | |
| dc.title | Granger causality procedeture to diagnosis and failture in industrial systems: Procedimiento de causalidad de Granger para diagnóstico y localización de fallas en sistemas industriales | es-ES |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
| dc.type | Artículos revisado por pares | es-ES |
