Anomaly Detection in Airliner Centrifugal Compressor Using Sensor Data during the Climb Phase

Abstract

In recent years, aircraft have been able to quickly acquire vast and diverse sensor data, leading to the expansion of predictive maintenance applications. Centrifugal compressors are crucial to aircraft air conditioning systems, which has a high need for anomaly detection due to the impact of failures. However, due to non-stationary behavior, there is a challenge in anomaly detection of the air conditioning system. In this study, we propose a method of detecting anomalies by comparison of actual and predicted behavior of centrifugal compressors for non-stationary time-series data. Multiple failure cases confirmed that bearing deterioration results in changes in behavior.