Fault Warning of Satellite Momentum Wheels with a Lightweight Transformer Improved by FastDTW

The momentum wheel assumes a dominant role as an inertial actuator for satellite attitude control systems. Due to the effects of structural aging and external interference, the momentum wheel may experience the gradual emergence of irreversible faults. These fault features will become apparent in the telemetry signal transmitted by the momentum wheel. This paper introduces ADTWformer, a lightweight model for long-term prediction of time series, to analyze the time evolution trend and multi-dimensional data coupling mechanism of satellite momentum wheel faults. Moreover, the incorporation of the approximate Markov blanket with the maximum information coefficient presents a novel methodology for performing correlation analysis, providing significant perspectives from a data-centric standpoint. Ultimately, the creation of an adaptive alarm mechanism allows for the successful attainment of the momentum wheel fault warning by detecting the changes in the health status curves. The analysis methodology outlined in this article has exhibited positive results in identifying instances of satellite momentum wheel failure in two scenarios, thereby showcasing considerable promise for large-scale applications.