During the flight tests of the new prototypes, a specialized department of the company collects and monitors the data stored by the sensors and instrumentation on the aircraft. Once analyzed, this data is provided to the design engineers who thoroughly verify the helicopter's behavior in flight. During flight testing, adverse situations, like a momentary loss of data connection or other minor sensor malfunctions can occur. These inconveniences lead to the return of anomalous spikes that are very difficult to identify in the huge amount of data collected for each flight.
To distinguish and eliminate these anomalies, we have developed automatic anomalous spike identification algorithms that can handle the huge stream of data generated. With the help of a dashboard, the company's specialized operators can check the anomalous detections reported by the algorithm and decide whether to eliminate them because they are the result of a sensor error or to forward them to the designers for further investigation of the aircraft.