Abstract: A method including generating synthetic labelled training data based on a set of labelled sensor data associated with one or more industrial automation devices; and training, based at least on the synthetic labelled training data, one or more machine learning models for fault classification associated with the one or more industrial automation devices.

Abstract: A system and a method for obtaining an estimated output power of an electric motor is configured to obtain the estimated output power by performing an output power estimation on the basis of data measured by condition monitoring sensors, the data including vibration measurement data and magnetic flux density measurement data.

Abstract: A system and method for estimating a power output of an electric motor with at least one magnetic field sensor includes providing magnetic field signal data, providing magnetic field frequency data based on the magnetic field signal data, determining a fundamental harmonic frequency of the supply frequency and at least one further frequency, determining a ratio between an amplitude of the at least one further harmonic frequency and an amplitude of the fundamental harmonic frequency, providing reference ratio data describing a relation of a ratio between an amplitude of the at least one further harmonic frequency and an amplitude of the fundamental harmonic frequency and a power output of the electric motor, and estimating the power output of the electric motor based on the reference ratio data and the determined ratio.