DIAGNOSTICS, PROGNOSTICS, AND HEALTH MANAGEMENT FOR VEHICLES USING KINEMATIC CLUSTERS, BEHAVIORAL SENSOR DATA, AND MAINTENANCE IMPACT DATA

摘要

Machine learning based methods for vehicle maintenance are disclosed. In one aspect, there is a method that includes uploading a flight dataset. The flight dataset includes timestamped vectors of kinematic and behavioral sensor data elements acquired by on-board sensors. The method further includes assigning each timestamped vector of the flight dataset to a kinematic cluster. The method further includes identifying behavioral sensor data that is anomalous for the assigned kinematic cluster of the timestamped vector. The method further includes generating an alert criticality score for each combination of kinematic cluster and behavioral sensor with anomalous sensor data.