Methods for anomaly and operational state detection of a technical system

Abstract

The invention relates to a computer-implemented method for creating a model for detecting an anomaly or an operating state or a change in an operating state in a technical system (1), comprising the following steps: - Providing (S1) time series of operational variables, each indicating a temporal progression of an operational variable, as training data; - Performing (S2) a piecewise linear approximation on the time series of the operating variables to obtain segments of concatenated linear functions for each of the operating variables, obtaining change points (T) as time points between the segments of all operating variables, and summarizing the change points (T) of all operating variables to define state segments between two temporally successive state segments that define time intervals of the time series of the operating variables; - Determining (S3) characteristics of the time-dependent behavior of the operating variables for each of the state segments in order to form a state vector for each (S4); - Training (S6) a classification model based on the state vectors; - Implement (S7) the classification model in a control unit of the technical system (1).

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