Experiments on test stand sensor data show successful detection of a known anomaly in the test data.

A novel technique has been developed for anomaly detection of rocket engine test stand (RETS) data. The objective was to develop a system that post-processes a csv file containing the sensor readings and activities (time-series) from a rocket engine test, and detects any anomalies that might have occurred during the test. The output consists of the names of the sensors that show anomalous behavior, and the start and end time of each anomaly.