Siemens Energy Global Gmbh & Co. Kg

Almir Avdovic

Thomas Hubauer

Mikhail Roshchin

Denis Krompaß

Felix Buggenthin

Bernt Andrassy

Giuseppe Fabio Ceschini

Sigurd Spieckermann

Mark Buckley

Davood Naderi

Richard Arnatt

Michael Werner

Zlatan Cota

A method and an apparatus for optimizing diagnostics of rotating equipment is provided. The apparatus includes a device for providing status information about status of the rotating equipment over a series of time windows whereby status can be derived from sensor features of at least one available sensor taking measurements during a predefinable time period, a device for using deep learning which combines provided historic sensor information with sequence of events data indicating warnings and/or alerts of the rotating equipment, whereby status information is supplemented with via deep learning predicted probabilities whether a warning and/or an alert has occurred within a time window, device for providing an amount of textual diagnostic knowledge cases, device for extracting semantic information on text features from the textual diagnostic knowledge cases, and device for combining status information and semantic information into a unified representation enabling optimization of the diagnostics.

Method and apparatus for optimizing diagnostics of rotating equipment

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Norrkoping, Sweden

Almir Avdovic