The Boeing Company
Data-Driven Methodology for Automatic Detection of Data Drift

Abstract:

A system and method for drift detection is disclosed. The method may comprise training and testing an autoencoder, and using the trained and tested autoencoder to automatically detect data drift. The training may include initializing the autoencoder and training the autoencoder based on a first set of sensor data. The testing of the autoencoder with a second set of sensor data may comprise: for an empirical distribution of the reconstruction errors of the second set of sensor data, determining a value of a reconstruction error at the percentile threshold; determining that data drift is not present when the reconstruction error of the second set of sensor data is less than a threshold; and calculating a deviation output for at least one of the one or more sensors. Using the trained and tested autoencoder to automatically detect data drift in sensor data.