Abstract: A data processing system for generating predictive maintenance models is disclosed, including one or more processors, a memory, and a plurality of instructions stored in the memory. The instructions are executable to receive a historical dataset relating to each of a plurality of systems, including maintenance data and operational data. The instructions are further executable to display one or more algorithm templates and one or more data features calculated from the operational data, in a graphical user interface. The instructions are further executable to receive a selection of an algorithm template, a data feature, and a value of a parameter associated with the algorithm template, and to train and evaluate the selected algorithm template on the selected data feature according to the received value. The instructions are further executable to display a result of a metric of the evaluation, and generate a predictive maintenance model using the selected algorithm template.

Abstract: A device includes one or more processors configured to access sensor data generated during a time window by one or more sensors onboard an aircraft. The one or more processors are configured to determine, based on the sensor data, a lateral acceleration dataset indicating frequency and magnitude of lateral buffet of the aircraft detected during the time window. The one or more processors are configured to determine, based on the sensor data, a vertical acceleration dataset indicating frequency and magnitude of vertical buffet of the aircraft detected during the time window. The one or more processors are configured to determine a buffet metric based on the lateral acceleration dataset and the vertical acceleration dataset. The one or more processors are configured to determine a buffet indicator based, at least in part, on the buffet metric. The one or more processors are configured to provide the buffet indicator to a display.