Abstract: An abnormality determination model generating device generates an abnormality determination model for determining an abnormality of a facility performing a predetermined operation, and includes: a time-series signal clipping unit configured to clip K times from one or more time-series signals indicating an operation state of the facility during normal operation of the facility; and an abnormality determination model generating unit configured to generate the abnormality determination model from the time-series signals during the normal operation clipped out by the time-series signal clipping unit, wherein the abnormality determination model generating unit is configured to clip L items per one time of clipping from the time-series signals during the normal operation clipped by the time-series signal clipping unit and configures an L-dimensional vector including L variables.

Abstract: A trigger condition determination method for a time series signal determines a trigger condition for cutting out a monitored section being a target for abnormality diagnosis, from a monitored signal being a time series signal indicating a condition of a monitored facility in the abnormality diagnosis for the monitored facility, and includes: collecting signal groups including one or more monitored signals and a trigger candidate signal; cutting out the monitored section of the monitored signal; generating a learning model specifying a start time point of the cut-out monitored section, generating label data, and using one or more trigger candidate signals at each time point as an input and using the label data at each time point as an output, by using machine learning; and determining the trigger condition by using the learning model, for the monitored signal for which the abnormality diagnosis is performed.

Abstract: An abnormality determination apparatus: performs, during normal operation of the facility, K times of clipping from time-series signals indicating an operation state of the facility; sets M types as types of the time-series signals clipped by the time-series signal clipping unit, constructs an M-dimensional vector, and registers the constructed vector as a normal vector; sets an abnormality determination flag as a first type when a maximum value of correlation between variables is less than a predetermined value, sets an abnormality determination flag as a second type when the maximum value is the predetermined value or more, and performs, when the flag is of the second type, a principal component analysis on a registered normal vector group to calculate a transform coefficient of a principal component and registers each of the calculated transform coefficients as an abnormality determination model; and determines an abnormality of the facility.