Anomaly Detection Over an Ultrasonic Sensor in an Industrial Plant
- Esteban Jove 12
- José-Luis Casteleiro-Roca 1
- Jose Manuel González-Cava 2
- Héctor Quintián 1
- Héctor Alaiz-Moretón 3
- Bruno Baruque 4
- Méndez-Pérez, Juan Albino 2
- José Luis Calvo-Rolle 1
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1
Universidade da Coruña
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2
Universidad de La Laguna
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3
Universidad de León
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4
Universidad de Burgos
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- Hilde Pérez García (coord.)
- Lidia Sánchez González (coord.)
- Manuel Castejón Limas (coord.)
- Héctor Quintián Pardo (coord.)
- Emilio Corchado Rodríguez (coord.)
Publisher: Springer Suiza
ISBN: 978-3-030-29859-3, 978-3-030-29858-6
Year of publication: 2019
Pages: 492-503
Congress: Hybrid Artificial Intelligent Systems (14. 2019. León)
Type: Conference paper
Sustainable development goals
Abstract
The significant industrial developments in terms of digitalization and optimization, have focused the attention on anomaly detection techniques. This work presents a detailed study about the performance of different one-class intelligent techniques, used for detecting anomalies in the performance of an ultrasonic sensor. The initial dataset is obtained from a control level plant, and different percentage variations in the sensor measurements are generated. For each variation, the performance of three one-class classifiers are assessed, obtaining very good results.