ABNORMALITY DETECTING METHOD AND ABNORMALITY DETECTING SYSTEM

摘要

(1) A compact set of learning data about normal cases is created using the similarities among data as key factors, (2) new data is added to the learning data according to the similarities and occurrence/nonoccurrence of an abnormality, (3) the alarm occurrence section of a facility is deleted from the learning data, (4) a model of the learning data updated at appropriate times made by the subspace method, and an abnormality candidate is detected on the basis of the distance between each piece of the observation data and a subspace, (5) analyses of event information are combined and an abnormality is detected from the abnormality candidates, and (6) the  deviance of the observation data is determined on the basis of the distribution of frequencies of use of the learning data, and the abnormal element (sensor signal) indicated by the observation data is identified.