AUTOMATIC FAULT CLASSIFICATION FOR MODEL-BASED PROCESS MONITORING

摘要

A computer implemented method, system and program product for automatic fault classification. A set of abnormal data can be automatically grouped based on sensor contribution to a prediction error. A principal component analysis (PCA) model of normal behavior can then be applied to a set of newly generated data, in response to automatically grouping the set of abnormal data based on the sensor contribution to the prediction error. Data points can then be identified, which are indicative of abnormal behavior. Such an identification step can occur in response to applying the principal component analysis mode of normal behavior to the set of newly generated data in order to cluster and classify the data points in order to automatically classify one or more faults thereof. The data points are automatically clustered, in order to identify a set of similar events, in response to identifying the data points indicative of abnormal behavior.