Knowledge representation method for spacecraft health status telemetry monitoring

Spacecraft health telemetry is an important basis of spacecraft health state monitoring and on-board fault diagnosis and analysis. However, it is often difficult to effectively monitor spacecraft telemetry due to its characteristics of great volume, complex variation patterns. By analyzing the patterns that influences the variation modes of spacecraft telemetry, the paper proposes a rule-based knowledge representation method. Using this method can catalog all telemetry data into classes, and all complicated knowledge can be expressed with a judgment of a single dynamically-shifting range. The proposed method reduces the complexity of telemetry monitoring, meanwhile provides a reliable evidence for spacecraft operation safety, fault detection and diagnosis.