METHOD AND APPARATUS FOR OPTIMIZING DIAGNOSTICS OF ROTATING EQUIPMENT

The present invention relates generally to a method and an apparatus for optimizing diagnostics of rotating equipment, in particular a gas turbine. The apparatus comprises: a) Means (11) for providing status information about status of the rotating equipment over a series of time windows whereby status can be derived from sensor features (10) of at least one available sensor taking measurements during a predefinable time period, b) means (20) for using deep learning which combines provided historic sensor information with sequence of events data indicating warnings and/or alerts of the rotating equipment, c) whereby status information is supplemented with via deep learning predicted probabilities whether a warning and/or an alert has occurred within a time window, d) means (24) for providing an amount of textual diagnostic knowledge cases, e) means (17) for extracting semantic information on text features from the textual diagnostic knowledge cases, and f) means (19) for combining status information and semantic information into a unified representation enabling optimization of the diagnostics.