▪ Monitoring needs to produce a small number of alerts that are relatively intuitive to interpret, and likely to be actionable by experts in flight operations ▪ Cauchy — Poisson model is robust enough to: — Apply to all types of safety events — rare or otherwise — Account for over-dispersion in the data as well as deal with spikes in the training period — Effectively filter out nuisance alarms and at the same time be sensitive enough to detect true outliers ▪ Reaction from the customer, CAST Working Group (WG), has been largely positive — Use control charts to monitor the effectiveness of their safety enhancements each quarter ▪ The control charts have been annotated with the Westinghouse Electric alerting rules so a change in the mean could be detected as well ▪ The methodology helped the WG to focus their attention on a limited set of airports with anomalies — Facilitating the understanding of the causal factors and operational procedures causing the anomaly.
Robust Parametric Empirical Bayes based anomaly detection for flight safety events
01.04.2013
787177 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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