Detección de anomalías basada en técnicas inteligentes de una planta de obtención de material bicomponente empleado en la fabricación de palas de aerogenerador

  1. Esteban Jove Pérez 1
  2. José-Luis Casteleiro-Roca 1
  3. Héctor Quintián Pardo 1
  4. Juan Albino Méndez Pérez 2
  5. José Luis Calvo Rolle 1
  1. 1 Univesidade da Coruña,
  2. 2 Universidad de La Laguna
    info

    Universidad de La Laguna

    San Cristobal de La Laguna, España

    ROR https://ror.org/01r9z8p25

Journal:
Revista iberoamericana de automática e informática industrial ( RIAI )

ISSN: 1697-7920

Year of publication: 2020

Volume: 17

Issue: 1

Pages: 84-93

Type: Article

DOI: 10.4995/RIAI.2019.11055 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

Abstract

Technological advances, especially in the industrial field, have led to the development and optimization of the activities that takes place on it. To achieve this goal, an early detection of any kind of anomaly is very important. This can contribute to energy and economic savings and an environmental impact reduction. In a context where the reduction of pollution gasses emission is promoted, the use of alternative energies, specially the wind energy, plays a key role. The wind generator blades are usually manufactured from bicomponent material, obtained from the mixture of two dierent primary components. The present research assesses dierent one-class intelligent techniques to perform anomaly detection on a bicomponent mixing system used on the wind generator manufacturing. To perform the anomaly detection, the intelligent models were obtained from real dataset recorded during the right operation of a bicomponent mixing plant. The classifiers for each technique were validated using artificial outliers, achieving very good results.

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