Method for event-based failure prediction and remaining useful life estimation
AssigneeHitachi, Ltd.
InventorsWalid SHALABY, Mahbubul ALAM, Dipanjan GHOSH, Ahmed FARAHAT, Chetan GUPTA
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Abstract
Example implementations involve systems and methods for predicting failures and remaining useful life (RUL) for equipment, which can involve, for data received from the equipment comprising fault events, conducting feature extraction on the data to generate sequences of event features based on the fault events; applying deep learning modeling to the sequences of event features to generate a model configured to predict the failures and the RUL for the equipment based on event features extracted from data of the equipment; and executing optimization on the model.
Claims18
A method for predicting failures and remaining useful life (RUL) for equipment, the method comprising:
- for data received from the equipment comprising fault events, conducting feature extraction on the data to generate sequences of event features based on the fault events;
- applying deep learning modeling to the sequences of event features to generate a model configured to predict the failures and the RUL for the equipment based on event features extracted from data of the equipment;
- and
- executing optimization on the model.
A non-transitory computer readable medium, storing instructions for predicting failures and remaining useful life (RUL) for equipment, the instructions comprising:
- for data received from the equipment comprising fault events, conducting feature extraction on the data to generate sequences of event features based on the fault events;
- applying deep learning modeling to the sequences of event features to generate a model configured to predict the failures and the RUL for the equipment based on event features extracted from data of the equipment;
- and
- executing optimization on the model.
An apparatus configured to predict failures and remaining useful life (RUL) for equipment, the apparatus comprising:
- a processor, configured to:
- for data received from the equipment comprising fault events, conduct feature extraction on the data to generate sequences of event features based on the fault events;
- apply deep learning modeling to the sequences of event features to generate a model configured to predict the failures and the RUL for the equipment based on event features extracted from data of the equipment;
- and
- execute optimization on the model.
Dependencies are inferred from the claim text.