Fuzzy Anomaly Detection in Monitoring Sensor Data - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2010

Fuzzy Anomaly Detection in Monitoring Sensor Data

Abstract

Today, many industrial companies must face challenges raised by maintenance. In particular, the anomaly detection problem is probably one of the most investigated. In this paper we address anomaly detection in new train data by comparing them to a source of normal train behavior knowledge, expressed as sequential patterns. To this end, fuzzy logic allows our approach to be both finer and easier to interpret for experts. In order to show the quality of our approach, experiments have been conducted on real and simulated anomalies.
Fichier principal
Vignette du fichier
FIEEE2010.pdf (222.54 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

lirmm-00503132 , version 1 (25-03-2019)

Identifiers

Cite

Julien Rabatel, Sandra Bringay, Pascal Poncelet. Fuzzy Anomaly Detection in Monitoring Sensor Data. FUZZ-IEEE, Jul 2010, Barcelone, Spain. ⟨10.1109/FUZZY.2010.5584253⟩. ⟨lirmm-00503132⟩
113 View
135 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More