Abstract:On-orbit anomaly diagnosis of satellites and payloads is an essential support for the efficient and safe operations of satellites. Intelligent and efficient methods of satellite anomaly detection are one of the focuses of research in satellite ground systems. Under the background of the satellite missions of China’s Strategic Priority Program on Space Science, this study proposes an intelligent anomaly detection method of satellite engineering parameters based on the data characteristics and data anomaly forms of the space-science satellites and the gradient boosting decision tree (GBDT). The engineering data of the Quantum Science Experimental Satellite “Micius” are employed for application verification and analysis. Compared with the original “threshold + regular expression” anomaly detection method, the proposed method has an average accuracy of over 98%, with an increase of about two percentage points. False negatives and false positives can be effectively reduced, and the detection speed is increased by about six times.