Research on Intelligent Anomaly Detection Algorithm of Launch Vehicle Telemetry Data

In the field of launch vehicles, high launch density, heavy work intensity and large data volume have brought the traditional automatic anomaly detection with incomplete coverage, and complex design of criterion, which influencing performance evaluation of launch vehicle. In order to fully mine the data variation law implied in the massive telemetry data, the intelligent anomaly detection algorithm is proposed and designed as a beneficial supplement to the traditional anomaly detection algorithm, and improve the anomaly detection coverage and efficiency. With the telemetry data generated by the liquid launch vehicle taken as the research object, and the intelligent anomaly detection algorithm is compared with the traditional algorithm. It is shown that the algorithm proposed adapts to the anomaly detection scenarios with frequency anomaly and frame loss, which may be difficult for traditional algorithms to design anomaly detection criteria, and the average anomaly detection performance is improved by nearly 30% and the variance is reduced by 85%, providing a reference for improving anomaly detection system and applying intelligent anomaly detection algorithms in aerospace.