ISSN-L: 0798-1015 • eISSN: 2739-0071 (En línea)
Vol. 43 (Nº 07) Año 2022. Art. 3
Recibido/Received: 03/05/2022 • Aprobado/Approuved: 01/07/2022 • Publicado/Published: 15/07/2022
DOI: 10.48082/espacios-a22v43n07p03
BECERRA-ANGARITA, Oscar F. 1
ALVAREZ-PIZARRO, Yuli A. 2
Abstract
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.
Key words: fault diagnosis, Granger causality, system identification
Resumen
La supervisión de procesos industriales es un tema importante en la actualidad debido a la creciente necesidad de procesos más seguros para los operadores y efectivos para las empresas. Los lazos de control afectados por perturbaciones se agrupan con PCA, en función de su mayor variabilidad y las relaciones causales entre ellos se detectan mediante la causalidad de Granger. Un algoritmo de dibujo de gráficos permite indicar la fuente de la perturbación. El procedimiento se aplica a datos de un proceso químico simulado CSTR. El procedimiento propuesto indicaba correctamente las fuentes de perturbaciones.
Palabras clave: diagnóstico de fallas, causalidad de Granger, identificación del sistemas
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1. Docente investigador. Ingenieria electrónica . Universidad de Investigación y Desarrollo - UDI. Colombia. obecerra2@udi.edu.co
2. Docente. Ingenieria de telecomunicaciones. Universidad Santo Tomás. Colombia. yuli.alvarez01@ustabuca.edu.co
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