Anomaly detection is an important field for the anticipation of aircraft maintenance operations, working as an enabler of diagnostic and prognostic functions. A method has been implemented to detect abnormal data in Aircraft Condition Monitoring System (ACMS) records. Rather than using already known and usual detection triggers which are partial detectors and insensitive to new flight and system conditions, this method automatically extracts abnormal data points without requiring any a priori information about the system and its conditions. To accomplish this objective, we propose to combine a segmentation based and density clustering approaches for detecting and filtering anomalies. This method was applied on A340 ACMS data recordings. The detection logics associated with the new anomalies can be used as new detection conditions to be potentially implemented onboard, further extending legacy detection capabilities.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Unsupervised anomaly detection for Aircraft Condition Monitoring System


    Beteiligte:


    Erscheinungsdatum :

    01.03.2015


    Format / Umfang :

    767934 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring

    Schwabacher, Mark / Oza, Nikunj / Matthews, Bryan | AIAA | 2007


    Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring

    Schwabacher, Mark / Oza, Nikunj / Matthews, Bryan | AIAA | 2009


    Unsupervised Scalable Multimodal Driving Anomaly Detection

    Qiu, Yuning / Misu, Teruhisa / Busso, Carlos | IEEE | 2023

    Freier Zugriff

    UNSUPERVISED ANOMALY DETECTION FOR AUTONOMOUS VEHICLES

    SINDHWANI VIKAS / SIDAHMED HAKIM / CHOROMANSKI KRZYSZTOF et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    AIRCRAFT CONDITION MONITORING SYSTEM

    HAUKOM MICHAEL JAMES | Europäisches Patentamt | 2023

    Freier Zugriff