General Electric Company
Industrial asset temporal anomaly detection with fault variable ranking

Abstract:

A method of temporal anomaly detection includes accessing sensor data readings obtained at a monitored industrial asset, performing a data cleanup operation on at least a portion of the accessed sensor data readings, transforming at least the cleaned-up portion of the accessed sensor data readings to time series feature space sensor data, applying a multi-kernel-based projection algorithm to the time series feature space sensor data, computing a respective anomaly score and a respective ranking for one or more variables of the sensor data readings, and providing at least the computed respective anomaly score or the respective ranking for at least one of the one or more variables to a user. Ranking the anomaly score includes comparing each anomaly score to a threshold and then assigning a ranking to scores with a magnitude greater than the threshold based on its magnitude. A system and a non-transitory computer-readable medium are also disclosed.