Using a digital twin to facilitate environment-specific prognostic-surveillance operations for engineering assets in the field
Abstract:
During operation, the system receives time-series signals from sensors in the asset while the asset is operating. Next, the system obtains real-time environmental parameters for an environment in which the asset is operating. The system then selects an environment-specific inferential model for the asset based on the real-time environmental parameters, wherein the environment-specific inferential model was trained on a golden system while the golden system was operating in an environment that matches the real-time environmental parameters. Next, the system uses the environment-specific inferential model to generate estimated values for the received time-series signals based on correlations among the received time-series signals, and performs a pairwise-differencing operation between actual values and the estimated values for the received time-series signals to produce residuals. Finally, the system determines from the residuals whether the asset is operating correctly.
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