Resumen de Anomaly Detection Over an Ultrasonic Sensor in an Industrial Plant
Esteban Jove Pérez, José-Luis Casteleiro-Roca, José Manuel González Cava, Héctor Quintián Pardo, Héctor Alaiz Moretón, Bruno Baruque Zanón, Juan Albino Méndez Pérez, José Luis Calvo Rolle
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.
