A Proposal of Robust Condition Monitoring Scheme for Industrial Systems

Authors

  • Adrian Rodríguez-Ramos Universidad Tecnológica de La Habana José Antonio Echeverría
  • Francisco Javier Ortiz Universidad Politécnica Salesiana
  • Orestes Llanes-Santiago Universidad Tecnológica de La Habana José Antonio Echeverría

DOI:

https://doi.org/10.13053/cys-27-1-4534

Keywords:

Robust condition monitoring, pythagorean fuzzy sets, missing information, noise

Abstract

The Industry 4.0 paradigm aims to obtain high levels of productivity and efficiency, more competitive final products and compliance with the demanding regulations related to industrial safety. To achieve these objectives, the industrial systems must be equipped with condition monitoring systems for early detection, isolation, and location of faults. The paper presents a proposal for a condition monitoring system characterized by its robustness in presence of noise and missing variables in the measurements. The proposal combines the use of simple and effective imputation algorithms with a fuzzy classification kernel algorithm based on the use of the non-standard Pythagorean fuzzy sets. The proposed scheme was validated using the known DAMADICS test problem with excellent results.

Author Biographies

Adrian Rodríguez-Ramos, Universidad Tecnológica de La Habana José Antonio Echeverría

Departamento de Automatica y Computación

Francisco Javier Ortiz, Universidad Politécnica Salesiana

Programa de Maestría en Electronica y Automatización

Orestes Llanes-Santiago, Universidad Tecnológica de La Habana José Antonio Echeverría

Departamento de Automatica y Computación

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Published

2023-03-30

Issue

Vol. 27 No. 1 (2023): 27(1) 2023

Section

Articles of the Thematic Section

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